TNAU – TNSLUB Project
Introduction
1. INTRODUCTION
Natural resources include an array of exhaustible and renewable resources.
Natural resources comprising land, water, forests and fisheries constitute the
basic support systems of life on earth. Among the range of natural resources,
land and water are the prime and basic resources for human survival, agriculture
and industrial development. According to a recent available official figure, out of
324 million hectares of total cultivated land area, as much as 175 million hectare
is subjected to environmental degradation. The rate of degradation is also said to
be very high. Every year 2.5 million hectare i.e., about one per cent of India’s
land area turns into wasteland. About 90 million hectare of the 175 million
hectare of degraded land, are almost completely unproductive. Land degradation
of this order has serious ecological and economic implications. Apart from the 50
per cent of the land area that is degraded in the above ways, about 27 per cent
are degraded by flood and salinity and alkalinity. It is estimated that our national
soil loss is about 6000 million tonnes annually, 18.5 per cent of the total soil loss
at the global level. This is very serious considering the fact that India has only 2.4
per cent of the total land area of the World. With this soil we lose about six million
tonnes of nutrients, which is greater than the quantity of fertilizers applied to our
soil every year.
1.1 Environment and Natural Resources
The environment is both a biological and physical source of all natural resources.
Some natural resources are renewable while others are non renewable. The
major environmental problems we face today are externality, degradation of
renewable resources and depletion of non-renewable resources. Since all kind of
production activities involve pollution in one form or another, externality is likely
to be with us in some form or another. No production activity is hundred per cent
perfect in terms of technology and hence some pollution will always be
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generated. Most economic activities involve transformation of resources and this
transformation processes generate pollution at different stages and often the
environment is used as a repository for waste products. When waste deposited in
the environment exceed the assimilative capacity, degradation of environmental
resources take place. Degradation of the environment affects quality of
resources, production system, public health, physical assets, plant and animal
system and scenic beauty.
The environmental costs occur in the forms of larger expenditure on health care,
provision of protected water supply and maintenance of assets, enhancement in
the use of resources to achieve a given level of output over time in order to
compensate for the decline in the quality of resources, abatement and defensive
expenditures incurred by consumers and enforcement authorities. As the impact
on the natural resource system is expected to increase with the expanding
population and industrial activities, seeking a higher standard of living becomes
the absolute need of the day. Hence what is required at this stage is a package
of policy measures to identify and monitor externalities, to identify their economic,
ecological and sociological effects and to internalize their effects within levels,
which are not only safe for survival but also appropriate to the quality of life.
1.2.
Industrial Development, Agriculture and Externality
Textile dyeing industry is one of the important industries in our country that
consumes substantial volume of water and chemicals. Many dyeing factories do
not have adequate provision for treating the effluents and hence it is discharged
into the river without any proper treatment thus making the river water unusable.
This also pollutes the sub-soil and ground water table. Though industrial growth
plays an important role in the economic development of the developing countries
it is apparent that the pollution effects of various industrial units in India had been
alarming. Even in early eighties, there were instances that the poly fibre factories
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in Dharwad district of Karnataka had polluted the Thungabhadra river resulting in
health disorders, drinking water quality deterioration, crop and milk yield decline
in buffaloes and mass mortality of fish (Anonymous, 1985).
Krupanidhi and
Bhushan (1988) in their study indicated the effects of distillery effluents in
Udaipur where the dug wells located 200 – 300 meters away from the polluting
units were found to be affected, which resulted in unsuitability of water for
drinking and irrigation.
As far as western Tamil Nadu is concerned the rivers Amaravathy, Noyyal,
Cauvery and Bhavani are polluted by the discharge of effluent water from the
nearby industries of various kinds. Rivers are important in these regions as they
are the lifeline of agricultural development and economic growth.
They also
provide recreational facilities - fishing, boating etc. and support a large variety of
fauna and flora and they are part of the natural scenic heritage. Industrial
development, improvements in living standards and changes in agricultural
practices, especially since the 1960s, have resulted in an increased demand for
good quality water. However, such developments have resulted in the production
of increased amounts of sewage, industrial wastewater, agricultural discharges
and run-off. Due to continuous drought during the past five years, the run off
water in the rivers is very minimum. So the effluents penetrated into the soil and
caused ground water pollution. The quality of both soil and ground water has
deteriorated and directly impacted the agricultural production system.
1.3. Textile Dyeing Industry and Externality of Effluents on Land and Water
A Historical Perspective
The textile dyeing industries in the western Tamil Nadu comprising the districts of
Coimbatore, Erode and Karur occupy a major role in developing the local
economy as well as polluting the land and ground water sources extensively. For
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Introduction
instance there are about 720 bleaching and dyeing industries located in and
around Tirupur. The cluster of industries located in Tirupur alone release around
100 million litres of effluent per day, which is discharged into the river Noyyal
after treatment, partial-treatment or without proper treatment. Similarly, in Karur
the liquid waste water is discharged into the river Amaravathy and in Erode and
Bhavani Taluks, the effluent is let off into the river Cauvery. But due to the recent
enforcement of rules and stringent action initiated by Tamil Nadu Pollution
Control Board, almost all the industries have constructed either Effluent
Treatment Plant (ETP) or have become a member of the Common Effluent
Treatment Plant (CETP).
Many industries, of late have installed Reverse
Osmosis (RO) plants to neutralize and recycle the effluents. However, some of
the industries with medium capacity are not having the adequate treatment plant
capacity because of high initial investment cost.
Some of the earlier studies conducted during different points of time have also
highlighted the ill-effects of the industrial effluents. One such study conducted by
Prabhakaran and Lakshmanan (1995) reported that waste water discharged from
textile industries affected the river basins of Noyyal, Bhavani and Amaravathi and
tributaries of river Cauvery rendering the downstream unusable for drinking,
bathing, irrigation and fish culture. Prabhakaran (1995) revealed that the effluent
of textile industries had affected the ground water quality through infiltration by
way of increased EC, SAR and RSC. The influence of such untreated effluents
on underground water was also reported by Muthusamy et al., (1987) and Gupta
and Jain (1992). The observation made by Paul (1995) also showed that the
discharging of chemicals in Tiruppur turned the ground water as well as the
surface water unsuitable for irrigation and domestic applications. All the above
studies have clearly pointed out the external effects of the industrial wastewater
on the local environment.
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Introduction
1.4. Effects of Effluents on Human and Animal Health
The effluents released from the dyeing factories are variously coloured (dark
blue, black, red, green, etc.), aesthetically unpleasant, invariably turbid, not
conducive for aquatic organisms and unfit for drinking and other domestic
purposes leading to serious human health hazards like itching, cracks, cough,
fever, wheezing, etc., and in animals, weight loss, poor milk yield and reduced
reproduction rate. The ecological consequences of the effluents are associated
with the degradation of the quality of the surface water body that receives the
effluents, sedimentation of soil, poor ground water quality and air pollution.
1.5. Industrial Pollution, Crop Growth and Yield
The crops cultivated in the area that is located nearer to the area where
wastewater stagnates have led to poor yield due to soil salinity and sodicity. Crop
establishment and productivity are greatly affected and none of the food crops
grow in these affected locations.
Besides, the hygienic condition is also
disturbed. This inhibits the germination rate, plant height and the overall crop
stand significantly.
It is understood that in many instances, the effluents
drastically reduced establishment of crop, vigor index in the seedlings of crops
like paddy, finger millet, cowpea, soybean and maize. As indicated elsewhere,
the textile dyeing industry consumes huge amount of freshwater and
consequently generates an equally large quantity of wastewater. The disposal of
sludge generated at large level from CETP is not a simple task. Large quantities
of sludge are also generated depending on the suspended solids in the
wastewater, the type and dosage of the coagulants and the degree to which the
solids are concentrated. This sludge contains salts and toxic metals and organic
impurities causing pollution to the ground water and land resources. Hence the
workers and the nearby population are at significant health risk. In addition, the
volume of accumulated sludge is increasing day by day. Hence the safe and
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sound disposal of sludge is essential to mitigate the problem.
The sludge
contains spent dyestuff and coagulants. It is slightly alkaline and having various
dyes and other organics.
Some of the recent reports have also highlighted the substantial degradation of
cropland, water and production agriculture in and around the areas, where
dyeing factories are located. Besides natural resources degradation, there were
occurrences of people suffering from health disorders and other morbidity related
incidences. However it is a matter of fact that the dyeing industries have created
opportunities for the people and labourers to get additional manpower
employment, increased wage earnings and enhanced family income.
There
were also reports of migration of farm labourer towards dyeing industries in order
to get a better standard of living and modern way of life.
Hence it is clear that
the dyeing industries have created both positive and negative externalities. It is a
matter of pride that the dyeing industries have contributed significantly in the
GDP growth of the country and add considerable amount of foreign exchange but
at the same time created resource degradation, health disorders, migration etc.
So it is of utmost importance to examine the long term sustainability of resources,
carrying capacity, ecology, environment as well as human welfare, while
addressing the issues of economic development.
Considering the foregoing
issues in mind, a study was undertaken with the following specific objectives.
1.6. Objectives
a. to analyze the external effects of industrial development on the quality
of land, water resources, crop land, crop output, employment, income,
migration, health and other related socio-economic attributes.
b. to study the environmental implications of dyeing factories on the
agricultural eco-systems and
c. to study the attitude of the stakeholders in conserving the valuable
land and water resources and to suggest workable policy
prescriptions for internalizing the externalities.
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Introduction
2. METHODOLOGY
The methodology for this study was finalized in consonance with the objectives,
sampling design, data collection and tools of analysis. This section thus deals
with the criteria for the selection of study area, sampling design for determining
the responses under question, collection of data, analytical tools etc.
2.1. Selection of Study Area
For the present study, only three districts namely Coimbatore, Karur and Erode
were purposively selected since the deterioration of land and ground water
qualities and its impact on cropland, irrigation and drinking water, crop
production, human and animal health, labour employment, farm income etc.,
were significantly pronounced only in these districts due to the high intensity of
dyeing and bleaching units. Besides, the time as well as the financial constraints
also restricted the extent of study area limited only to these three districts.
Tiruppur taluk in Coimbatore district, Karur taluk in Karur district and Bhavani and
Erode taluks in Erode district were selected based on the extent of external
effects on land and water. Four villages, two affected and two unaffected were
selected from each taluk. Based on the discussions held with the Government
departments like TNPCB, Revenue department, Agricultural department, experts
of textile and dyeing factory associations, the sample villages were classified as
affected and un-affected.
The critical parameters which influence crop growth
like pH, EC, TDS, TSS, chloride and sulphate concentrations were also
considered while selecting the study villages. Since the impact of land and
ground water degradation was not uniform in terms of intensity across zones,
three locations were considered for this study. The unaffected study villages
selected were located near by the affected study villages to ensure otherwise
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Introduction
similarity in agro-climatic conditions.
In the second stage, two different
categories of the respondents namely, (i) farm households and (ii) industrial
workers were selected from each of the selected villages to represent all the
categories.
From each taluk, four villages were purposively selected; two
villages to represent the affected category and the remaining two to compare the
impact with the unaffected category. Thus, altogether 16 villages were chosen
purposively. From each village 40 respondents were contacted for collecting the
data. Thus, the total sample size comprised of 640 respondents. The sample
households were subjected to detailed enquiries.
The category of industrial
workers selected for the study included employees of the local organisations,
petty shop owners as well as the workers in the nearby dyeing, bleaching and
knitting units. The details of the taluks, blocks and the sample villages identified
for the study are reported in
Table 2.1.
Table 2.1 Sample Districts, Taluks and Villages selected for the study
District
Taluk
Villages
Affected
Coimbatore
Karur
Erode
Erode
Tiruppur
Karur
Erode
Bhavani
Unaffected
Veerapandi
Muthanampalayam
Nallur
Velampalayam
Panchamadevi
Somur
Sanapparetti
Pallapalayam
Periasemur
Gangapuram
S.P.Agraharam
Soorianpalayam
Bhavani
Jambai
Andikulam
Ooratchikottai
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Introduction
2.2. Data
The data collection for the current investigation, unlike socio-economic research
was done with greater flexibilities and caution and logistic approaches and nonconventional means of information gathering was resorted to for collecting the
oral history, the dynamics of land and ground water use, management, effluent
treatment methods adopted, etc. It was noticed during data collection that the
degradation of land and ground water quality has consequently resulted in
reduction of the cultivated area, poor soil and water quality, crop productivity,
reduction in farm labour employment, farm income etc.
Data were collected both from primary and secondary sources for the study. The
primary data collected for the study pertained to the year 2004-06. In the first
stage, the socio-physical environment of the study area was understood. Details
on the temporal distribution of physical, climatological, institutional, demographic,
socio-economic, cultural and historical components were collected from the
village records maintained by the grass root level functionaries of the
Government departments.
2.3. Method of Enquiry
The micro economic behaviour of the village inhabitants depending on land and
ground water and the trend in income pattern, impact on water bodies, and the
indirect effects like equity, environmental sustainability and change in quality of
water and soil were studied. The impact of land and ground water quality
degradation on the crop production, environment, the averting and defensive
expenditures incurred, the respondents’ Willingness to Pay (WTP) for
replenishing the original status of their cropland or averting the influence were
derived through econometric analysis for micro level planning.
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The study also explored linkages between crop productions.
The farm level
losses were viewed primarily due to the degradation of land and ground water
quality, changes in agricultural production systems, labour employment, etc. The
study mainly focused its attention to analyze the changes in land and water
quality, share of income from farming and changes in income and employment
due to reduction in the cropland area over years. The study also attempted to
quantify how the earnings of the respondents varied as a result of the
degradation of land and ground water quality.
2.3.1. Externalities on Land
The effluents let out by the industries have created external effects on land
namely, land quality deterioration, decline in crop land value, poor crop yield,
abandoning of farm lands, etc., in spite of expenditure incurred by the sample
respondents on averting and defensive inputs. The impacts on agricultural land
were assessed based on enquiry with respondents regarding declining cropland
area, labour employment, cropping pattern and expenditure incurred on
defensive and averting inputs and secondary information collected from
development departments.
2.3.2.
Externalities on Water
The discharge of improperly treated effluents had changed the water quality
significantly. The change in water quality led to poor land quality and resulted in
loss of crop yields, loss of manpower employment in agriculture, etc. The water
quality was assessed through the quality parameters such as taste, colour, odour
and turbidity. The water quality index was constructed on a three-point scale of
one for poor water quality, two for average water quality and three for good water
quality for each of the quality parameters namely, taste, colour, odour and
turbidity. The combined effect of all these qualitative attributes formed the said
index.
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2.3.3. Averting and Defensive Expenditure
The averting and defensive expenditures for land included the additional input
costs on seed materials, organic fertilizers, tank silt and green manures, soil
amendments like gypsum, etc.
As such, farmers did not incur any expenditure
towards the treatment of water used for irrigation purposes, while the
respondents spent substantial amount on averting and defensive inputs for good
quality drinking water, which included fetching good quality water from the nearby
non polluted or less polluted areas. The opportunity cost of spending time to get
drinking water was also considered and quantified.
2.3.4. Externalities on Human Health
The externalities caused by the changes in the qualities of surface and subsurface water included the common health disorders namely; fever, jaundice,
dysentery, headache, allergies and to some extent skin rashes, etc.
The
expenditure incurred on human health included the cost of treatment namely,
physician cost, cost of medicine and also the opportunity cost of time spent for
taking treatment in health clinics.
2.3.5. Externalities on Animal Health
Reduction in animal population, poor health status of animals, reduction in milk
yield, reduced calving rate were the external effects observed on animals due to
the degradation of land and water quality parameters. Expenditure on cost of
treatment and loss in value of milk were also recorded to study the impact on
livestock.
2.3.6. Externalities on Socio-Economic Characteristics
Non availability of adequate period of farm employment, poor crop stand and
declining livestock income and reduction in farm and non-farm income, land
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selling, diversion of farm lands for non agricultural activities and labour mobility
towards non farm sector were the consequences of pollution externalities
observed in the study villages.
2.4. Impact Assessment Techniques
Impact assessment techniques viz., loss in productivity, agricultural and
aggregate damage functions, analysis for averting and defensive expenditures
on cropland and drinking water, hedonic pricing techniques for valuation of
croplands, and Contingent Valuation Techniques (CVT) to study the willingness
to pay of the individuals for improved environmental status were employed for
analyzing the data. The details of the models used for the analysis of the data
for studying the various attributes are presented below.
2.4.1. Damage Function
The damage function links pollution to yield. There are two types of damage
functions observed in agriculture viz., agricultural damage functions and
aggregate value damage functions. (For details refer Cropper and Oaters, 1992).
For the present study, value damage functions were developed and employed.
While the agricultural damage function was limited to agricultural damages alone,
the aggregate damage function considered loss in productivity of cropland and
labour, crop output, livestock production, change in quality of water, damage on
human and animal health, etc. The damage function used for the study was of
the following form.
YDDMGE
= f {AVERTECP, LQI, WQI, PCLDI}
AGDMGE
= f {AEXHH, AEXDW, WQI, PCLDI}
Where,
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YDDMGE
- Yield Damage (Rs./ha)
AGDMGE
- Aggregate Damage (Rs./household)
PCLDI
- Proximity of Crop Land to Dyeing / bleaching Industries
AVERTECP
- Averting Input Expenditure for Crop (Rs./ha)
LQI
- Land Quality Index*
WQI
- Water Quality Index*
AEXHH
- Averting Expenditure on Human Health (Rs./household)
AEXDW
- Averting Input Expenditure for Drinking Water (Rs./ha)
*Poor-1; Average-2; Good-3
It was expected that the averting expenditure for land inputs, the quality of land
and water would have a direct impact on the crop yield. It was also believed that
averting expenditures on land and drinking water might have negative influence
on aggregate damage.
Similarly, the averting expenditures on animal and
human health would have negative association with household aggregate
damage. It was also assumed that the proximity of croplands to the dyeing or
bleaching units would influence agricultural as well as the aggregate damages
significantly. Hence, it was also considered as a variable for functional analysis.
Agricultural and aggregate value damages were computed as the differences in
the value of each affected farm over the value of the each item before the
occurrences of such damages. The agricultural and aggregate damage functions
were estimated employing log-log regression model.
2.4.2.
Hedonic Model
A hedonic model was chosen to study the influence of land and ground water
quality and their effect on cropland in deciding the final value of croplands.
Miranowski (1984), Bartick (1987) and Palmquist (1989) in their studies had
demonstrated the application of hedonic techniques to value croplands, cropland
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Introduction
sales and land improvements, respectively.
Literature on hedonic pricing
methods also suggested that quality attributes of land, area under fallow,
distance between farm and the adjacent pollution source, crop productivity and
household characteristics would influence the value of agricultural land
significantly. The model used was of the following form.
VCLN
= f {LQI, WQI, PCLDI, CINSY, SCATFA}
VCLN
- Value of Crop Land (Rs./ha)
LQI
- Land Quality Index (scale*)
WQI
- Water Quality Index (scale*)
PCLDI
- Proximity of Cropland to Dyeing and Bleaching Industries
(distance in kilometers)
CINSY
- Cropping Intensity
SCATFA
- Share of Cropped Area to Total Farmland Area
Where,
(percentage)
*Poor-1; Average-2; Good-3
Several qualitative characteristics determine the value of land. Land and water
quality indices were considered in the model. Besides, the proximity of cropland
to the dyeing units, cropping intensity, percentage of cropped area to total
farmland area were expected to exert significant influence on value of land.
It was expected that LQI, WQI would have positive impact on land value and
there was no a priori assumption about the behavior of variable PCLDI. After
experimenting with various functional forms, the double log form of the
regression model was specified.
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2.4.3. Models on Averting or Defensive Expenditure
Averting
and
defensive
expenditures
were
incurred
to counteract the
consequences of pollution externalities. The mitigating expenditure involved
before the occurrences of pollution, investment made on inputs for reduction of
harmful effects after the occurrence of pollution and the expenditure incurred by
the respondents to protect their lands, animals, water resources from the health
hazards were included under this category. With and without concept was not
followed since the externality effects of land and water quality degradation was
found to occur throughout the village.
For instance, the cost involved in using additional quantity of seeds, organic
manures, application of soil amendments like gypsum, coir pith were considered
to be the land based averting expenditure due to the degradation of croplands
consequent to the degradation of the quality of land and ground water by the
discharge of untreated effluents. As stated earlier, the farmers in general did not
undertake any treatment for irrigation water.
Expenditure incurred in getting
protected water from the nearby areas was considered under averting
expenditure for drinking water.
The actual expenditure incurred towards human health included the cost of the
physician, the cost of the medicine and the opportunity cost of time spent in
taking treatment. It was assumed that the expenditures were perfect substitutes
for estimating the ill effects of the dyeing factory effluents on human health.
The determinants of actual averting and defensive expenditures for croplands
were estimated for the farm respondents of all the villages considered for the
study and for drinking water, the determinants of averting and defensive
expenditures were calculated for the affected categories of the respondents. The
determinants of averting and defensive expenditure were studied by using the
following Model.
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Y1 = f {FSIZE, EDN, SCATFA, PCLDI, LQI, QOMA, AWARE, WQI}
Y 2 = f {HI, EDN, HHSIZE, WQI, AWARE}
Where,
Y1 =
Actual per hectare expenditure on averting actions for croplands
(Rs. /ha)
Y 2=
Actual household expenditures on averting actions for drinking
water (Rs. /household)
HI
- Household Income (in Rs.)
FSIZE
- Farm Size (in ha)
EDN
- Education (scale*)
SCAFTA
- Share of Cropped Area to Total Farmland Area (per
centage)
QOMA
- Quantity of Organic Manure Applied (t/ha)
WQI
- Water Quality Index (scale**)
LOI
- Land Quality Index (scale**)
AWARE
- Awareness of Environmental Externality (scale***)
HHSIZE
- Size of the Family (numbers)
PCLDI
- Proximity of Cropland to Dyeing unit (in km)
________________________________________________
*
**
***
Illiterate-0; Primary-1; Secondary-2; Graduates-3.
Poor-1; Average-2; Good-3
Poor-1; Medium-2; High-3.
The model for the actual per hectare expenditure on averting actions of cropland
as well as for drinking water was constructed for the sample respondents. The
household income, age and educational level were expected to have a positive
influence on averting actions of cropland.
It was also hypothesized that
education would also influence the averting actions of the respondents positively.
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The proximity of the cropland to the dyeing unit was also considered because it
was thought that it would influence averting actions significantly.
2.4.4.
Contingent Valuation Technique (CVT)
The CVT determines consumer’s preferences by constructing hypothetical
markets. CVT arrives at the Willingness to Pay (WTP) to continue receiving
benefits. An attempt was made to examine the economic valuation of the land
and water quality using CVT.
Willingness to Pay was used to assess the value
of changes in the quantity and quality of agricultural land, irrigation and drinking
water in the study area. The survey schedule was designed in such a way that it
did encapsulate the knowledge and the attribute of the respondents towards the
land and water quality degradation, their perception and interest in correcting
actions. Information was also elicited to study the dependence of the households
on agriculture for employment, income, etc., problems faced by them in the
collection of water, measures if any taken by the users when shortage was
realized and their WTP for protecting irrigation water.
In order to get responses for the WTP, the following hypothetical situation was
created.
The households were asked what was their major requirement to
improve their agricultural activities.
Their response was good quality irrigation
water and also they wanted either to deepen their well or to draw water from the
unaffected locations.
The households were asked to assume that local
institutions sponsor a part of the expected expenditure that would be incurred.
The capital cost was taken to be rupees one lakh. For meeting the rest of the
expenses, each household’s WTP towards its capital in monetary terms and their
mode of payment was sought. (Note: The capital cost were fixed based on the
information obtained during the survey from the farmers, experts and field level
functionaries, income, living standards of the village inhabitants, etc).
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The WTP of the households towards the capital cost for the deepening or
drawing good quality water from the nearby sources was added after annualizing
the capital investment, taking a life annualized capital cost time of 15 years for
the capital investment at 12 per cent rate of interest. Similarly, using the wage
rate per day as prevalent in the study areas during the time of survey, the labour
time or days, the villagers who were willing to contribute towards the capital cost
in their region were converted in to monetary values. Hence WTP for good
quality water and ecological functions was the sum total of WTP for annualized
capital and the mode of payment.
The explanatory variables used for analyzing maximum WTP were; age of the
respondent, household composition, educational level, per capita agricultural
land, per capita standard cattle unit, interest in improving agricultural activities,
perception of quality of degradation of land and water, distance of dyeing units
from the farm, etc.
WTP
= f {AGE, HHSIZE, HHEDN, HHINCOME, PCAL, PCSCU,
IIAGA, PLGWD, PCLDI}
WTP
- Willingness to Pay (Rs. / household)
AGE
- Chronological Age of the Respondent (in years)
HHSIZE
- Size of the Household (in number)
HHEDN
- Household Head’s Education (scale)*
HHINCOME
- Household Income (Rs. /annum)
PCAL
- Per Capita Agricultural Land (in hectare)
PCSCU
IIAGA
- Per Capita Standard Cattle units (number)
- Interest in Improving Agricultural Activities (scale)**
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PLGWD
Introduction
- Perception of Land and Ground Water Degradation
(scale)***
PCLDI
*
**
***
- Proximity of Cropland to Dyeing units (in km)
Illiterate-0; Primary-1; Secondary-2; Graduate-3
Not interested-1, Somewhat-2, Fairly-3, Verymuch-4
Not at all-0; Somewhat-1; Very much-2
2.4.4.1 Expected Relationship
The economic theories and existing literature on CVT suggest that WTP for
improved environmental quality is directly related to the age of the respondent. It
was also expected that with an increase in the number of members in the
household, dependency on input for agricultural land would also increase.
Higher the perception of degradation as well as the interest in improving the
agricultural activities, the more was expected about the WTP.
It was also
expected that a person with higher education would be more concerned with the
protection of the environment. The nature of the relationship also depended on
other factors like income of the household, etc. Similarly, distance between the
farm and the dyeing units were yet another variable expected to affect WTP
significantly. Another important variable having direct link with the degradation of
the quality of water was the livestock number, which was taken as per capita
standard cattle units, which was assumed to have a positive coefficient
particularly for the farm households. It was also expected that the per capita
agricultural land would be correlated positively with WTP.
Similarly, it was
assumed that the proximity of the cropland to the dyeing unit would capture the
effect of distance on WTP. A person residing nearer to the dyeing unit was
expected to pay more for the improvement of agricultural activities due to the
maximum realization of benefits.
19
TNAU – TNSLUB Project
Introduction
2.4.5. Impact of effluent on the quality of groundwater and soil
characteristics
In order to assess the changes in the quality of groundwater and the physico –
chemical properties of soils, both water samples and soil samples were collected
from selected villages of Tiruppur, Karur, Bhavani and Erode taluks and analyzed
for various physico chemical properties.
2.4.5.1. Collection of water samples
Groundwater samples were collected from the earmarked wells as per the
standard procedure. Containers were rinsed 3 or 4 times with the water sample
before the sample were drawn. Collected water samples were stored in the
refrigerator at 4ºC for further analysis. To avoid changes from chemical and
biological activities minimum time were given between the time of collection and
laboratory evaluation. The collected water samples were subjected to various
physico- chemical characteristics as per the methods prescribed in Table.2.2.
2.4.5.2. Collection of soil samples
The soil samples were collected from the sample villages of four taluks as per the
standard methods described below.
The land was selected at random and the surface litters were removed at the
sampling spots. Then the auger was used to take the sample upto a depth of 15
cm and samples were drawn. At least 10 to 15 samples were collected from
each sampling unit, mixed thoroughly and from the composite samples,
representative samples were taken for further processing. The sample collected
from the field was dried in shade by spreading on a clean sheet of paper after
breaking the large lumps. Then the soil material was sieved through a 2mm
20
TNAU – TNSLUB Project
Introduction
sieve. The material passing through the sieve was collected and stored in a clean
container with proper labeling for laboratory analysis.
Table 2.2. Standard methods followed for the analysis of water samples
Estimation
Remarks
References
pH
1:2.5 organic waste: distilled Falcon et al. (1987)
water using pH meter
EC (dS/m)
1:2.5 organic waste: distilled Falcon et al. (1987)
water
using
conductivity
bridge.
Chloride (mg l-1)
Mohr’s method
Sulphate (mg l-1)
Turbidimetric method using Jackson (1973)
spectrophotometer at 420 nm
Calcium (mg l-1)
Versenate titration method
Jackson (1973)
Magnesium (mg l-1)
Versenate titration method
Jackson (1973)
BOD (mg l-1)
Standard procedure
APHA (1989)
COD (mg l-1)
Standard procedure
APHA (1989)
Jackson (1973)
Heavy metals (mg l- AAS
1
)
Lindsay
(1973)
and
Norwell
The processed soil samples were subjected to various physico- chemical
characteristics as per the methods prescribed in the following Table 2.3.
Table 2.3. Standard methods followed for the analysis of Soil samples
Estimation
pH
Remarks
1: 2.5 organic waste: distilled
water using pH meter
21
References
Falcon et al. (1987)
TNAU – TNSLUB Project
Introduction
water using pH meter
EC (dS/m)
1: 2.5 organic waste: distilled
water using conductivity
bridge.
Falcon et al. (1987)
Preparation of di acid
extract
H2SO4 : HClO4 @5:2
Biswas et al. (1977)
Preparation of triacid
extract
HNO3 : H2SO4 : HClO4 @
9:2:1
Piper et al. (1966)
Available Nitrogen
(kg/ha)
Alkaline permanganate
method
Subbiah and Asija
(1956)
Available Phosphorus
(kg/ha)
Colorimetric method
Olsen et al. (1954)
Available Potassium
(kg/ha)
Neutral normal ammonium
acetate extract
Stanford and English
(1949)
Heavy metals
AAS
Lindsay and Norwell
(1973)
4. MAJOR FINDINGS OF THE STUDY
The data collected from the sample respondents of the study villages were
analyzed using the statistical tools explained in section 2 of this report and the
results are presented in consonance with the specific objectives of the study.
22
TNAU – TNSLUB Project
Introduction
In this section, results are discussed separately for the sample taluks namely,
Tiruppur, Karur, Erode and Bhavani.
4.1. Tiruppur
4.1.1. Demographic Details
The family size of the respondents is presented in the Table 4.1. The overall
family size of the respondents in the affected village was 3.87 whereas in
unaffected category it was 3.73. The overall family size of the study villages of
Tiruppur taluk was 3.80.
Table 4.1. Family Size
(Numbers)
Sl. No.
Category
Average Size
1.
Affected
3.87
2.
Unaffected
3.73
Overall
3.80
4.1.2. Distribution of Respondents Based on Education
Knowledge about educational status of the respondents is indispensable to
decide the awareness and the attitude of people about their surroundings. From
Table 4.2, it is clear that about 75 per cent were literates in the affected villages
while in the unaffected villages it was only 69 per cent. Out of the 75 per cent,
about 23 per cent had completed at least their secondary education. But, in the
unaffected area out of 69 per cent of the literate population over 23 per cent had
completed their secondary education.
The vast employment opportunities
available in the industrial sector might have been the main reason for not
continuing education after secondary level. It could be noted that 15 to 17 per
cent of the respondents had college level education in commerce and fashion
technology for getting employment in the dyeing, bleaching and knitting
23
TNAU – TNSLUB Project
Introduction
industries. With the exception of primary education and illiterates all other
categories had similar levels of coverage in the affected and unaffected localities.
Table 4.2. Educational Status
Sl.
No.
Particulars
Affected Area
Unaffected Area
Number
Percentage
Number
Percentage
1.
Illiterates
57
24.57
70
31.25
2.
Primary
52
22.41
34
15.18
3.
Secondary
53
22.84
53
23.66
4.
Higher secondary
23
9.91
22
9.82
5.
Graduates
47
20.27
45
20.09
6.
Literates
175
75.43
154
68.75
Total
232
100.00
224
100.00
4.1.3. Land Holding Details
The land area possessed by sample respondents and the area under cultivation
are presented in Table 4.3. The land area comprises of wet, dry and garden
lands. It is obvious from the table that there was no wetland. The area owned
was 1.72 and 1.80 hectares in the affected and unaffected areas. Whereas, the
average area under cultivation was 1.03 ha in the affected areas and 1.15 ha in
the unaffected areas.
affected category was
The average garden land owned by a household in the
1.33 ha whereas it was 1.65 ha in the unaffected
category. The area under dry land accounted for 22.59 per cent and 8.60 per
cent of total area owned in the study villages. The percentage of area under
cultivation accounted for only 8.04 and 2.35 per cent of the total area cultivated in
the affected and unaffected areas.
24
TNAU – TNSLUB Project
Introduction
Table 4.3. Land Holding Details
(Average
ha)
Particulars
Affected Villages
Unaffected Villages
Area Owned
Area
Cultivated
Area
Owned
Area
Cultivated
Garden
land
1.33
(77.41)
0.95
(91.96)
1.65
(91.40)
1.12
(97.65)
Dry land
0.39
(22.59)
0.08
(8.04)
0.16
(8.60)
0.03
(2.35)
Total
1.72
(100.00)
1.03
(100.00)
1.80
(100.00)
1.15
(100.00)
Figures in parentheses indicate percentage to total
4.1.4. Details of Irrigation
Formerly, the river Noyyal, open wells and bore wells were the chief sources of
irrigation in the study villages. Now, as the river Noyyal is polluted, the farmers
depend on only wells for irrigation. The details of the irrigation wells are presented
in Table 4.4. The total number of open wells in the affected area was 59 while it
was 64 in the unaffected area. The average depth of the wells in the affected area
was 54.32mts. The number of wells abandoned was nine (15.25 per cent) in the
affected category where as it was only five (7.81 per cent) in the unaffected
category. This was due to the non-availability of good quality water in shallow
depths and improper maintenance. The quality of water was affected due to the
dyeing factory effluent in and around the study villages. The number of bore wells
in the affected area was 15 where as it was only seven in the unaffected areas. It
was reported that the dyeing factory owners had dug bore wells to a depth of
around 300 mts. This had led to depletion of the ground water table also. So,
some farmers had dug deeper bore wells (up to 250 mts) in order to sustain their
25
TNAU – TNSLUB Project
Introduction
agricultural activities. They were of the view that water at greater depths would be
of better quality with less pollutants.
Table 4.4. Details of Irrigation Wells
Sl.
No.
Particulars
Affected
Area
Unaffected
Area
1.
Total number of wells in the sample farms
59
64
2.
Average depth of open well (in mts.)
54
23
3.
Percentage of wells with good quality water
throughout the year
1.69
40.63
4.
Percentage of wells with water only during
rainy season
83.05
51.56
5.
Number of bore wells in the sample farms
15
7
6.
Average depth of bore wells (mts.)
221
149
-
19.23
Medium
27.27
80.77
Poor
72.73
-
7.
*
Water quality (Per centage)
Good
*As perceived by the respondents
4.1.5. Area Irrigated by Different Sources of Irrigation
The details on sources of irrigation are reported in Table 4.5. In both the affected
and non- affected villages there was no area under canal irrigation.
Area
irrigated by open wells in the unaffected area was about 47 per cent, whereas it
was only 12.04 per cent in the affected area. About four per cent of the farmers
in the affected area transported water by lorries to maintain their existing coconut
gardens whereas in the unaffected villages it was only 0.27 per cent. About 58
per cent of the area was under rain fed cultivation in the affected area, which was
about 23 per cent higher than that of the unaffected villages.
26
TNAU – TNSLUB Project
Introduction
Table 4.5. Sources of Irrigation
Sl.
Sources of Irrigation
Affected
No.
Unaffected (%)
(%)
1.
Open well
12.04
46.24
2.
Bore well
21.28
3.28
3.
Open well + Bore well
5.18
15.06
4.
Well + Purchased water
3.70
-
5.
Purchased water
-
0.27
6.
Rain fed
57.79
35.15
Fig.13 Sources of Irrigation – Tiruppur Taluk
S ource s o f Irriga tio n
70.00
57.79
60.00
50.00
46.24
40.00
35.15
30.00
21.28
20.00
15.06
12.04
10.00
3.28
5.18
3.70
0.00
0.00 0.27
0.00
Open well
-10.00
Bore well
Open well +
Bore well
Well +
Purchased
water
Purchased
water
Rain fed
Affected (%)
Sourc es of I rrigation
4.1.6.
Unaffected (%)
Area and Productivity of Different Crops: A Detailed Analysis
The area and productivity of the crops grown in the study area are reported in
Table 4.6.
Though the area under coconut in both affected and unaffected
villages was about 35 per cent, the productivity in the affected area was only
4,531 nuts whereas in the unaffected area it was about 12,605 nuts. This huge
27
TNAU – TNSLUB Project
Introduction
difference was due to the deterioration of land and water quality. The same trend
was observed in other crops too. The difference in yield ranged between (-) 8.23
and (-) 65 per cent. It was revealed by farmers that during the past years crops
like tobacco, turmeric, sugarcane, paddy, cotton, coconut, vegetables and
banana were cultivated.
However, vegetables and cash crops are not at all
present in the current crop plan. The poor quality soil and water has driven the
farmers to cultivate only rain fed cholam (fodder cholam) and farmers were
maintaining their existing coconut gardens with great difficulty.
Table 4.6. Area and Productivity of Crops
Sl.
No
1.
Crops
Affected
Villages
Area
Yield
(%)
(t/ha)
Unaffected
Villages
Area
Yield
(%)
(t/ha)
60.38
6.80
51.58
34.07
4.81
4531
0.99
0.73
Difference
Yield
Percentag
e
7.41
0.61
(-)8.23
35.29
2.19
12605
1.82
8074
0.83
(-)64.05
(-)45.60
86.45
2.19
96.21
9.76
(-)10.14
4.
Fodder
Cholam
Coconut*
Grain
Cholam
Banana
5.
Vegetables
-
-
6.57
65.65
-
-
6.
Groundnut
-
-
1.64
2.47
-
-
7.
Turmeric
-
-
0.54
3.50
-
-
2.
3.
* Yield in nuts/ha
4.1.7 Proximity of Cultivated Lands to Dyeing Industries
The distance between the respondent’s farm holdings and the dyeing industries
was less than a kilometre (0.78 km). Out of 60 respondents interviewed, 59 were
of the opinion that dyeing was their main activity in the villages (Table 4.7).
About
area and
34 respondents opined that knitting was also carried out in their
30 respondents in Nallur village expressed that bleaching was
28
TNAU – TNSLUB Project
Introduction
the main activity in their locality. The period of operation of factories ranged
from 10 months to
12 months.
Table 4.7. Location of Dyeing Industries
Sl.No
Particulars
1.
Proximity
2.
Average months in operation / year
Affected Villages
0.78
10-12
4.1.8. Farmers’ Opinion about Decline in Agricultural Activities
The farmers’ perceptions about the decline in agricultural activities are reported
in Table 4.8. Out of the 60 respondents interviewed, about 68 per cent were of
the view that the failure was due to water scarcity, 60 per cent opined that it was
due to labour scarcity and 78 per cent expressed that it was due to poor water
quality. Inadequate water supply, decline in water table, reduction in agricultural
income, poor crop stand were the other reasons for the failure of agricultural
activities.
Table 4.8. Opinion of Sample Farmers on Decline in Agricultural Activities
(Per cent)
Sl.No
Reasons for decline in agricultural
Affected Category
activity
1.
Poor water quality
78.33
2.
Water scarcity
68.33
3.
Labour scarcity
60.00
4.
Poor crop stand
36.67
5.
Decline in agricultural income
30.00
6.
Decline in water table
18.33
Fig.14 Opinion of Sample Farmers on Decline in Agricultural Activities –
Tiruppur Taluk
29
TNAU – TNSLUB Project
Introduction
Opinion of S a mple Fa rme rs on D e cline in Agricultura l Activitie s
100.00
80.00
78.33
68.33
60.00
60.00
36.67
40.00
30.00
18.33
20.00
0.00
Poor water
quality
Water
scarcity
Labour
scarcity
Poor crop
stand
Decline in
agricultural
income
Decline in
water table
Affe cte d ca te gory
4.1.9. Change in the Value of Agricultural Lands
It is obvious from Table 4.9 that in the unaffected villages, the value of
agricultural land had increased gradually. In the affected villages, because of the
increasing levels of textile industry activities during the last few decade, the
demand for land increased and most of the farmers sold their crop lands for
house sites and industrial activities. Due to shortage of lands, the value of crop
lands increased six to nine times in the affected areas compared to unaffected
areas. During the year of survey the land value was Rs.75, 17,033 per ha in the
affected villages whereas it was only Rs 12, 90,575 per ha in the unaffected
villages.
The real estate business has also flourished well in this taluk in the
recent past since the demand for land exceeds the supply.
Table 4.9. Change in Value of Agricultural Lands
Sl. No
Particulars
Affected villages
30
(Rs/ha)
Unaffected
villages
TNAU – TNSLUB Project
Introduction
1.
5 years back
37,33,816
4,17,224
2.
2003 – 04
75,17,033
12,90,575
4.1.10 Employment Pattern
The employment pattern of the household members is reported in the Table 4.10.
Among the 60 respondent households, 100 persons were earning members in
the affected villages whereas it was 111 in the unaffected villages.
In the
affected villages, none of the households depended on farm activities alone. The
employment of respondents in on - farm activities was reported to be higher
(28.33 per cent) in the unaffected villages where as it was only about two per
cent in the affected villages. Employment through the combination of both on farm and non - farm activities was observed to be much higher (81.67 per cent)
in the affected villages, whereas it was 63.33 per cent in unaffected villages.
Table 4.10 Occupational Distribution of the Households
S.No
1.
Particulars
Crop alone
2.
Crop + Dairy activities
Total households engaged in
on-farm activities alone
3.
On-farm+
Non-farm
activity
4.
On-farm + Off-farm +Non
farm activity
5.
Non –farm activity
Total
Earning
members
in
the
sample
households
(in
Numbers)
Affected Villages
Number
-
Per cent
-
Unaffected
Villages
Number Per cent
4
6.67
1
1
1.67
1.67
17
21
28.33
35.00
49
81.67
38
63.33
4
6.67
1
1.67
6
60
10.00
100.00
60
100.00
100
31
111
TNAU – TNSLUB Project
Introduction
Fig.15 Occupational Distribution of Households Tiruppur Taluk
100.00
81.67
63.33
Percentage
80.00
60.00
28.33
40.00
20.00
6.67 10.00
0.00 1.67
6.67
1.67 0.00
0.00
Affected
Unaffected
Crop alone
Crop + dairy activities
On farm+off farm+non farm
Non farm activity
On farm+ non farm
4.1.11 Income
The details of income generated by the household are reported in Table 4.11. It
is understood from the table that in the affected villages about 11.00 per cent of
the average annual income was earned through non farm activities like dyeing,
knitting, renting out houses and so on whereas there was no sample household
depending on crop activity alone. In the unaffected villages, none of the farm
households depended on non - farm activities alone.
The average annual
income earned through the combination of on- farm and non-farm activities was
found to be higher (84.98 per cent) in the affected villages compared to 70 per
cent in the unaffected villages. In the unaffected area, the income from the on
farm activities alone was higher (22.50 per cent) when compared to the affected
area (0.84 per cent).
The combination of all the three activities (on-farm, off-
farm and non-farm) was observed to be much higher (3.44 per cent) in the
affected villages than in the unaffected villages (0.71 per cent). The average
32
TNAU – TNSLUB Project
Introduction
annual income of households were Rs.1,31,264 in affected villages and
marginally higher at Rs.1,45,023 in unaffected villages.
Table 4.11 Pattern of Income of the Sample Households
(Average Annual Income - in Rs.)
Sl.N
o
Particulars
Affected Villages
1
Farm only
2.
Farm + Dairy activities
Average annual income
earned from on-farm
activities alone
3.
On-farm +Non-farm
income
4.
On-farm + Off-farm
+Non farm income
5.
Non-farm income
Average Annual income per
household
Unaffected Villages
Amount
1,100
1,100
Per cent
0.84
0.84
Amount
9,324
32,630
41,954
Per cent
6.43
22.50
28.93
1,11,547
84.98
1,02,046
70.37
4,517
3.44
1,023
0.71
14,100
1,31,264
10.74
100.00
1,45,023
100.00
Fig.16 Pattern of Income - Tiruppur Taluk
84.98
Percentage
90.00
80.00
70.37
70.00
60.00
50.00
40.00
30.00
20.00
10.00
22.50
10.74
0.00 0.84
3.44
6.43
0.71 0.00
0.00
Affected
Unaffected
Farm only
Farm + Dairy activities
On farm+ non farm income
On farm+off farm+non farm income
Non farm income
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TNAU – TNSLUB Project
Introduction
4.1.12. Migration
The migration details are presented in Table 4.12. Earning members in about 75
per cent of the households in the affected villages have migrated whereas in the
unaffected villages, it was only 11.67 per cent. In the affected area, among those
migrated the permanent migration was high (about 94 per cent). The reasons for
migration were poor household income, to earn more, poor water quality,
restricted crop activities etc. Out of these reasons, poor income from agricultural
operations alone accounted for 71.43 per cent. Next was their desire to earn
more from other sources (about 61.90 per cent).
In the unaffected villages
desire to earn more was the predominant reason (62.5 per cent).
Table 4.12. Migration Details
Sl.No
Particulars
1.
2.
Percentage of migration
Average percentage migration
from sample Household
Per centage of permanent
migration by family members
Average
number
of
days
migration
3.
4.
Sl.No
(Per cent)
Unaffected Area
Affected
Area
75.00
25.03
11.67
26.86
93.65
87.50
83.72
(305.57)
78.28
(285.71)
Particulars
Affected
Area
Unaffected
Area
Reasons
1.
2.
3.
4.
5.
Poor household income from agriculture
To earn more
Poor water quality
Labour problem
Employment in public institutions
71.43
61.90
26.98
9.52
1.59
12.5
62.5
-
6.
7.
Education
Restricted crop activity
14.29
39.68
25.0
-
Note: Figures in parentheses denotes the average days of migration in a year.
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TNAU – TNSLUB Project
Introduction
4.1.13. Sale of Assets
The extent of sale of assets by the farmers during the last 10 years is reported in
Table 4.13. About 17 per cent of the respondents in the affected area sold at
least part of their land during the last ten years but none of the respondents in
the unaffected area had sold their cropland during the same period. The reasons
for the sale of lands were poor crop income, migration, poor water quality and
water scarcity. The croplands are now converted as house sites. Forty five per
cent of the respondents in the affected villages had sold their livestock due to
various reasons like reduced milk yield, loss in weight, water scarcity and
inadequate man power (for maintenance). In the unaffected villages 41.67 per
cent of the respondents sold their livestock. Farmers who sold their livestock only
due to drying of the cattle accounted for 21.67 per cent, followed by labour
problem with 10.00 per cent.
Table 4.13. Sale of Assets
Sl.
No
Particulars
Affected
Area
Unaffected
Area
I
Sale of Land
1.
Percentage of respondents sold their land
16.67
-
2.
Area of land sold (%)
4.89
-
3.
Value of the sold land (Rs./ha)
50,087
-
45.00
41.67
Percentage
animals
of
respondents
sold
the
II
Reason for Sale of Animals
1.
Water scarcity
10.00
6.67
2.
Loss in weight
3.33
3.33
3.
Reduction in milk yield
11.67
-
4.
Labour problem
3.38
10.00
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TNAU – TNSLUB Project
5.
Introduction
Drying / Aged
16.67
21.67
4.1.14. Farm Level Availability of Livestock
Results presented in table 4.14 would reveal that the number of animals in the
unaffected villages was relatively high compared to the affected villages. Many
of the respondents were rearing sheep in the unaffected villages (about 85
numbers) to supplement household income.
Table 4.14. Availability of Livestock
(Average/household)
Sl.No
Particulars
Affected village
Un affected village
1.
Cow
1.25
1.87
2.
Buffalo
0.67
1.13
3.
Bullock
0.07
0.07
4.
Sheep
0.03
1.42
5.
Calf
0.12
0.08
4.1.15. Sufferings of Human and Animals
The table 4.15 reveals the fact that no one has reported any sufferings in the
unaffected villages. In the affected villages, an individual spends on an average
of Rs.136.67/- towards physician cost and Rs.30/- towards medicine annually. In
case of animals, the loss of milk production was about nine per cent of the
average production.
The common ill effects noticed were weight loss, poor
calving and reduction in milk yield in animals.
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TNAU – TNSLUB Project
Introduction
Table 4.15. External Effects on Human and Animals
Sl.No.
Particulars
1.
Cost to Physician (Rs./ annum / individual)
Affected
Villages
136.67
2.
Cost of medicine (Rs. / annum / individual)
29.97
Animals
1.
Loss in milk production (Rs./ annum)
1910
2.
Percentage loss in milk production
9.06
4.1.16. Drinking Water Supply
The results presented in Table 4.16 reveals that the only drinking water source in
the affected villages was the tap water. The frequency of water supply was once
in two days in Nallur and once in 20 days in Veerapandi whereas in the
unaffected areas, the people were using their own well water and to some extent
the tap water. In affected villages, all the respondents depended on the public
taps (municipality water) for drinking compared to 55 per cent of farmers in the
unaffected group.
The respondents at Veerapandi were paying Rs.10/- per
family per month for drawing water from the public tap.
In affected villages,
purchase of a tanker water at Rs.900/- was not uncommon and no respondent
was found using their own well water while in unaffected areas, 45 per cent were
using their own well water for household purposes.
In the affected villages, people were paying Re.0.75 for 12 liters of potable water
for domestic use. Average water use per month was high in unaffected locations
(6,660
litres/household)
litres/household).
when
compared
to
affected
areas
(4,745
The distance to fetch water was also more (0.71kms) in
affected villages than in the unaffected villages (0.62kms).
The problem for
drinking water exists for the past 15 years due to non availability of potable
water.
37
TNAU – TNSLUB Project
Introduction
Table 4.16.
Drinking Water Quality
Affected village
Sl.
No
Particulars
1. Source of drinking water
Number of
Responde
nt
Expense
(Rs./
family/
annum)
Mettupalayam water
Un affected village
Number of
Respondent
Expense
(Rs./
family)
Mettupalayam water and
well
a.
Public Tap*
60
120
33
-
b.
Purchase of lorry water
9
5,400**
-
-
c.
Well water
-
-
27
-
2. Average Water Requirement and Expense to buy / fetch water
a.
Monthly water use (litres
/household)
4,745
-
6,660
-
b.
Monthly water
Requirement (lit /
household)
14,040
900
-
-
c.
Amount paid for 12 litres
of water (Rs.)
-
0.75
-
-
3. Distance to fetch drinkable
water (km)
0.71
0.62
* Municipality water supplied in the public taps
** purchasing lorry water six times per year
4.1.17. Details of Well Water Quality
The well water quality in the affected village was compared with unaffected
category and results are reported in Table 4.17. The water quality parameters
like taste, colour, turbidity and odour were found to be medium.
But in the
affected villages, the taste of the well water was poor (98.25 per cent) in summer
whereas in the rainy season it was good. In 98 per cent of the wells the colour of
water was red with yellow and black tinge.
Turbidity was low (91 per cent) in
both the seasons. Medium to moderate chemical odour was reported in all these
wells.
38
TNAU – TNSLUB Project
Introduction
Table 4.17. Details of Well Water Quality
Sl.No
1.
Water Quality Characteristics
2.
Colour
Season
–
Rainy Season
3.
Turbid
Season
–
Rainy Season
4.
Poor
Medium
Good
Poor
Medium
Good
Summer High
Affected
Villages
98.25
1.75
54.39
42.11
3.51
98.25
Medium
Low
High
Medium
Low
Summer High
1.75
98.25
1.75
8.77
100.00
100.00
-
Medium
Low
High
Medium
Low
Summer High
91.23
8.77
91.23
100.00
100.00
100.00
-
Medium
Low
High
Medium
Low
100.00
-
100.00
100.00
Taste – Summer Season
Rainy Season
Odour
Season
–
Rainy Season
(Per cent)
Unaffected
Villages
2.00
98.00
100.00
-
4.1.18. Opinion of the Farmers about Irrigation Water
In one of the unaffected village, Muthanampalayam, the respondents were getting
water from PAP canal (Parambikulam Aliyar Project) once in 2 years (4 times) for
irrigation. The respondents of the affected village Nallur were getting canal water
only during the rainy season and the quality of water was reported to be medium
(Table 4.18).
39
TNAU – TNSLUB Project
Introduction
Table 4.18. Attitude of Farmers towards Irrigation Water
Sl.
No
I.
1.
2.
II.
1.
2.
3.
Total
*
**
***
Affected Village
Numbers
Per cent
Particulars
Availability
Rainy season
Through out year
Quality
Poor
Medium
Good
Un affected Village**
Numbers
Per cent
30*
-
50.00
-
30***
-
50.00
-
30
30
50.00
50.00
30
30
50.00
50.00
Canal water available only in Nallur (Affected village);
PAP canal once in 2 years –4 times (Muthanampalayam) .
30 respondents in Velampalayam
4.1.19. Willingness to Pay
Out of 60 respondents interviewed in the affected villages, only 51.67 per cent
were willing to pay for improving the soil and water quality parameters. About 40
per cent of the respondents were under the category of paying Rs.25000 to
Rs.50000. Nobody was willing to pay above Rs.75000.
Most of the respondents
were willing to pay in quarterly (16.67 per cent) and half yearly (16.67 per cent)
installments.
Table 4.19. Willingness to Pay
Sl.No.
1.
2.
3.
4.
Particulars
Number
Respondents
31
29
Households willing to pay
Households not willing to pay
WTP
Less than Rs.20, 000
Rs.20, 001 – Rs.25,000
Rs.25, 001 – Rs.50,000
Rs.50, 001 – Rs.75,000
Mode of Payment
Single payment
Quarterly installments
Half yearly installments
40
of Per cent
51.67
48.33
2
3
24
2
3.33
5.00
40.00
3.33
4
10
10
6.67
16.67
16.67
TNAU – TNSLUB Project
Introduction
Annual installments
7
Fig. 17 Willingness to Pay – Tiruppur Taluk
11.67
Willingness to Pay
50.00
40.00
40.00
30.00
20.00
10.00
5.00
3.33
3.33
0.00
Less than Rs.20, 000
Rs.20, 001 –Rs.25,000
Rs.25, 001 –Rs.50,000
Rs.50, 001 –Rs.75,000
Amount willing to pay
4.1.20. Averting Expenditure
The additional expenditure incurred by the farmers with the expectation of
obtaining the desired yield is reported in the Table 4.20.
The averting
expenditure for the crop coconut and fodder cholam was Rs.5605 and 1041
respectively for an area of one hectare.
The amount was spent mainly on
irrigation and application of organic manure.
Some farmers cultivating fodder
cholam had taken even second sowing. On an average, about Rs.389 was lost
per annum in the process of bringing drinking water from the nearby resources,
where the quality of water was found good.
Table 4.20. Averting Expenditure for Crops
Sl.No.
Particulars
Expenditure
(Rs./ha)
5605
1.
Coconut
2.
Mancha cholam (Sorghum)
1041
3.
Opportunity cost of procuring drinking water
(per household)
389
41
TNAU – TNSLUB Project
Introduction
Soil and Water Sample Analysis
4.1.21. Physico - Chemical characteristics of water samples collected at
Tiruppur
before monsoon
In Tiruppur taluk, water samples were collected before and after monsoon and
the results are presented in the tables 4.21 and 4.22.
The water samples collected from Tiruppur taluk before monsoon showed not
much variation in pH both in affected and unaffected villages recording 7.53 –
8.61 and 7.6 – 8.84 respectively. In both the samples, a slight increase in pH
above the critical limit of 6.5 – 8.5 was recorded. The EC Value is found to be
higher in affected regions which recorded 0.99 to 7.33 ds/m compared to
unaffected regions which has 0.58 –1.27 ds/m. which outranges the critical value
of 1 ds/m for drinking but lies within the maximum permissible limit of 2.25 ds/m
for irrigation; Whereas, the EC of the well water from affected villages exceeded
the critical limit for irrigation thus indicating its unsuitability for drinking.
The chloride content accounted maximum of about 205.9 – 4224 mg l-1 in
affected regions compared to unaffected regions, which is 91 - 511.2 mg l-1.
Chloride content in affected regions is nearly 8 fold higher than the limit of 500
mg l-1 prescribed for irrigation; whereas, the sulphate content of the water
samples collected from both affected and unaffected villages are well below the
critical limits.
The water samples collected from affected and unaffected villages recorded the
calcium content ranging from 580 – 3100 mg l-1 and 310 – 1850 mg l-1
respectively, which exceeded the critical limit of 100 mg l-1. The magnesium
content was found to be maximum in affected regions (20 – 65 mg l-1 ) compared
to the unaffected regions which ranged between 12– 48 mg l-1. In addition, the
BOD and COD of the water samples collected from affected regions ranged
42
TNAU – TNSLUB Project
Introduction
between 45 – 85 mg l-1, and 48-110 l-1 respectively; whereas the samples from
unaffected regions recorded a BOD of 48-110 l-1, and a COD of
95 – 380 l-1.
Both the regions exceeded the critical limit of BOD for drinking water, 6 l-1 . The
COD content of both the samples also higher than the critical limit of 250 l-1 to be
followed for irrigation. The Sodium Absorption Ratio (SAR) of water samples of
affected villages ranged between 46 - 52, which are higher than the maximum
limit of 26 whereas, the SAR of unaffected villages ranged between 24 – 29.
Further, the results on heavy metal analysis of water samples also showed the
presence of heavy metals such as chromium, nickel, cadmium and lead to some
extent. Water samples of affected villages recorded BDL - 0.10 mg l-1 chromium,
0.25 - 0.70 mg l-1 of lead, BDL - 0.05 l-1 of cadmium and 0.2 – 0.50 l-1 of nickel;
whereas the unaffected samples had BDL - 0.05, BDL - 0.40, BDL - 0.01 and
BDL - 0.25 mg l-1 of Cr, Pb, Cd and Ni respectively. Chromium, cadmium and
nickel contents of both the samples lies within the maximum permissible limits of
0.05 mgl-1, 0.10, and 0.05 mg l-1 respectively whereas, the lead content of both
the samples exceeded the prescribed limit 0.01 mg l-1 for drinking water.
Table 4.21. Physico - Characteristics of water samples collected at Tiruppur
Taluk (Before monsoon)
Parameters
Affected Villages
Unaffected
Villages
pH
7.53 – 8.61
7.60 -8.84
EC (ds/m)
0.99 – 7.33
0.58 – 1.27
BOD (mg/l)
45 – 85
48 – 110
COD (mg/l)
95 – 285
95 – 380
Chloride (mg/l)
205.9 - 4224
91 – 511.2
Sulphate (mg/l)
10.7 – 51.6
29.4 – 56.5
Calcium (mg/l)
580 – 3100
310 – 1850
Magnesium (mg/l)
20 - 65
12– 48
SAR
46-52
24 - 29
Chromium (mg/l)
BDL - 0.10
BDL - 0.05
Lead (mg/l)
0.25 - 0.70
BDL - 0.40
Cadmium (mg/l)
BDL - 0.05
BDL - 0.01
43
TNAU – TNSLUB Project
Nickel (mg/l)
Introduction
0.2 – 0.50
BDL - 0.25
4.1.22. Physico - Chemical characteristics of water samples collected at
Tiruppur
taluk after monsoon
The water samples collected from the same villages of Tiruppur taluk after
monsoon showed variation on pH ranging from 7.85 – 9.12 in affected villages
and 6.5 – 7.85 in the unaffected villages. The pH of the water samples from
affected villages is slightly higher than the limit of 8.5 but the samples of
unaffected villages recorded pH in near neutral range.
The EC was high in
affected villages ranging from 2.53 – 4.05 ds/m and 1.15 – 2.85 ds/m in
unaffected villages. Both the affected and unaffected regions exhibited higher
EC value than the maximum permissible limit.
The BOD content of water samples from affected and unaffected villages ranged
between 95 – 145 mg l-1 and 42 and 65 mg l-1 respectively; Both the values
exceeded the prescribed limits of drinking (2 mg l-1 ) as well as irrigation water
(30 mg l-1). The COD value is found to be greater in affected villages ranging
from 185 to 310 mg l-1compared to unaffected villages which recorded 85 – 135
and
30 mg l-1. The COD values of water samples from affected villages are
significantly higher than the prescribed limit of 250 mg l-1 as prescribed for
irrigation water. The chloride content of the samples varies widely between 315
to 650 mg l-1 in affected villages, which exceeded the limit of 500 mg l-1 for
irrigation purpose and 220 – 415 mg l-1 in unaffected villages, which lies within
the limit. The sulphate content accounts to about 28 – 54 ppm in affected villages
compared to unaffected villages which is about 22 – 44 ppm, which are well
below the limits. Calcium contents of water samples of both affected and
unaffected villages are found to be higher which ranged between 420 – 2300 mg
l-1 and 210 – 1150 mg l-1 respectively, which are far higher than the prescribed
limit. But the magnesium content of both the samples was found to be below the
44
TNAU – TNSLUB Project
Introduction
critical limits. The SAR of affected and unaffected villages samples were in the
range of 36 – 49 and 22-27 respectively.
In the affected villages the chromium content ranges between BDL to 0.08 mg l-1
whereas in the unaffected villages it is found to be between BDL – 0.06 mg l-1.
The heavy metal lead accounts to about 0.18 – 0.55 mg l-1
villages and BDL to 0.32 mg l
-1
in the affected
in unaffected villages. These values are little
higher when compared to the limit of 0.1 mg l-1. The cadmium content is about
BDL –
0.02 mg l-1 in the affected villages samples and BDL – 0.01 mg
l-1 in the water samples of unaffected villages . The standard limit prescribed for
this heavy metal is 0.01 mg l-1. The samples from affected and unaffected
regions recorded a nickel content of about 0.1 – 0.35 mg l-1 and BDL – 0.35 mg l1
respectively which are higher than the maximum prescribed limit.
Table 4.22. Physico - Characteristics of water samples collected at
Tiruppur Taluk
(After monsoon)
Parameters
Affected Villages
Unaffected Villages
pH
7.85 – 9.12
6.85 - 7.85
EC (ds/m)
2.53 - 4.05
1.15 - 2.85
BOD (mg/l)
95 - 145
42 – 65
COD (mg/l)
185 - 310
85 – 135
Chloride (mg/l)
315 - 650
220 – 415
Sulphate (mg/l)
28 – 54
22 – 44
Calcium
420 - 2300
210 – 1150
Magnesium
56 - 96
16 - 35
SAR
36 - 49
22- 27
Chromium (mg/l)
BDL - 0.08
BDL - 0.06
Lead (mg/l)
0.18 - 0.55
BDL - 0.32
Cadmium (mg/l)
BDL - 0.02
BDL - 0.01
Nickel (mg/l)
0.1 – 0.35
BDL - 0.35
4.1.23. Assessing the changes in soil properties of Tiruppur taluk
The results of the soil samples collected from the study villages of Tiruppur taluk
are presented in table 4.23. The results showed that the pH values ranging from
45
TNAU – TNSLUB Project
Introduction
6.10 – 7.50 in affected regions and 6.15 – 7.36 in the unaffected regions. The
EC values were found to be higher in the affected villages (0.69 - 1.80 ds/m)
when compared to unaffected villages (0.12 - 0.29 ds/m).
The available N content was found to be greater in affected villages (240 – 450
mg/kg) which comes under the medium rating (280 – 450 kg/ha) when compared
to the unaffected regions which recorded 100 – 267 kg/ha which comes under
the low rating (0 – 280 kg/ha) status. The available P content in affected regions
was in the range of
8 – 25 kg/ha which exhibited high rating (>22 kg/ha)
whereas, in the unaffected region it varies from 14 – 34 kg/ha which is classified
under high rating (>22 kg/ha). Similarly, the higher available K content was
observed in affected regions (124 – 282 kg/ha) which is classified under high
rating (>280 kg/ha).
The unaffected villages recorded 48 – 197 kg/ha, of
available K which comes under medium status of 118 – 280 kg/ha.
The chromium content was found to be maximum in the soils of affected regions
(55 – 87 ppm) when compared to the unaffected regions, which ranges from 25 –
58 ppm. But the samples of both the regions do not exceed the critical limit of
100 ppm. The heavy metal lead accounts for higher value of about 38 – 87 ppm
in affected regions when compared to unaffected regions ranging from 0.14 –
2.10 ppm. Both the regions come under the standard limit of 100 ppm. The
samples of affected villages recorded 2.36 – 3.85 ppm of cadmium which is
slightly higher than the maximum allowable concentration of 3.0 ppm. . Whereas,
the cadmium level of soil samples of unaffected villages were in the range of 0.12
– 1.89 ppm.. The nickel content was higher in affected regions recording about
25 – 58 ppm which is higher than the limit and it was only 8–18 ppm in
unaffected regions.
46
TNAU – TNSLUB Project
Introduction
Table 4.23. Characteristics of soil samples collected at selected villages of
Tiruppur taluk
Parameters
Affected Villages
Unaffected Villages
pH
6.10 - 7.50
6.15 - 7.36
EC (ds/m)
0.69 - 1.80
0.12 - 0.29
Available N (kg/ha)
240 – 450
100 – 267
8 – 25
14 – 34
124 – 282
48 – 197
Chromium (mg/kg)
55 – 87
25 – 58
Lead (mg/kg)
38 – 87
0.14 - 2.10
2.36 - 3.85
0.12 - 1.89
25 – 58
8 – 18
Avail.P (kg/ha)
Avail. K (kg/ha))
Cadmium (mg/kg)
Nickel (mg/kg)
Workers
Majority of the workers interviewed were migrants from the other taluks. They
were either from Trichy or Karur. Many of the migrants have settled in the study
area.
4.1.24. Nature of Work
The nature of work carried out by the respondents in both affected and
unaffected villages is presented in Table 4.24.
It could be seen from the table
that most of the respondents in the affected area were engaged in industrial
activities such as Dye-master (20 per cent), Supervisor (15 per cent), Chemical
Supervisor (15 per cent), Winch runner (15 per cent), Hydropher (15 per cent)
and Dye mixer (10 per cent) whereas in the unaffected areas, occupations
related to knitting and garment export were found high. A vast majority of 45 per
cent of the respondents were engaged in maintaining the quality of the yarn in
the near by knitting factories.
47
TNAU – TNSLUB Project
Introduction
Table 4.24. Nature of Work
(Per
cent)
Sl.No
Nature of Work
Affected
Un Affected
Villages
Villages
1.
Dye master
20
-
2.
Supervisor
15
10
3.
Cashier
5
-
4.
Chemical supervisor
15
-
5.
Winch runner
15
-
6.
Hydropher
15
-
7.
Dye mixer
10
-
8.
Fitter
5
5
9.
Quality control supervisor
-
45
10.
Other type of labourers
-
20
11.
Sweeper
-
5
12.
Accountant
-
5
13.
Labour – Colouring
-
-
14.
Watchman
-
5
15.
Office boy
-
5
100
100
Total
4.1.25 Employment
From Table 4.25 it could be understood that the average days of employment per
month did not show much variation and it was only 22.70 days in affected areas
while in unaffected areas it was 25 days. Monthly wages earning was higher in
affected villages (Rs.3200) compared to unaffected locations (Rs.2580). The
average annual income of the respondents was Rs.38, 400 in affected locations
compared to Rs.30, 960 in unaffected areas.
48
TNAU – TNSLUB Project
Introduction
Table 4.25. Employment Particulars of the Head of the Family
Sl.
No
Particulars
Affected
Villages
Unaffected
Villages
1.
Average days of monthly employment
22.70
25.00
2.
Average Wage earning (Rs./Month)
3200
2580
3.
Average Number of Family
Working in Dyeing Industry
Members
0.15
-
4.
Average Number of Family
Working in Other Industries
Members
-
0.50
5.
Average Annual Income of the Respondent
38,400
30,960
4.1.26. Benefits Availed by the workers
The industrial workers were availing the benefits as detailed in Table 4.26. In the
affected villages about 39 per cent were claiming ESI and 25 per cent availing
medical benefits when compared to 6.90 per cent in unaffected villages. About
four per cent was getting personal loan also from industries. Most of the workers
in the unaffected area were working in knitting company and they were enjoying
the benefits of both ESI and bonus.
Table 4.26. Benefits Availed by the Workers
Sl. No
Benefits
Affected Villages
Un Affected
Villages
1.
Accident Claims
10.71
13.79
2.
Medical Benefits
25.00
6.90
3.
ESI*
39.29
44.83
4.
Personal loan
3.57
-
5.
Bonus
21.43
34.48
*Eligible after 5 years
49
TNAU – TNSLUB Project
Introduction
4.1.27. Problem of Illness
No chronic illness was reported in both affected as well as unaffected areas. The
details are presented in table 4.27. Fifteen per cent of the respondents reported
problem of skin cracks and another 15 per cent expressed the problem of skin
rashes. Five per cent reported weight loss. The affected respondents were
spending annually Rs.93 towards the cost to physician and Rs.135 towards
medicine.
Table 4.27. Externality effects to Workers
Sl.
No
1.
2.
3.
4.
5.
6.
Particulars
Affected Villages
Number
Per cent
Weight loss
Skin cracks
Skin rashes/itching
No illness
Cost
to
(Rs./annum/individual)
Cost
of
(Rs./annum/individual))
Physician
1
3
3
13
93.00
5
15
15
65
-
medicine
135.00
-
4.2. Karur
4.2.1. Family Size
The family size of the sample respondents is presented in the table 4.28. The
overall size of the family of the sample farmer was 4.19.
Between the two
categories, the average size of the family was found to be comparatively large in
the unaffected areas.
Table 4.28. Average Family Size
(Numbers)
Sl. No
1.
2.
Category
Affected
Unaffected
Average Size
4.13
4.25
50
TNAU – TNSLUB Project
Introduction
Overall
4.2.2. Educational Status
4.19
It is obvious from Table 4.29 that the percentage of illiterates in the affected
village was higher (29.44 per cent) than that of unaffected village (24.71 per
cent). There was not much difference in literacy levels of both categories.
Table 4.29. Educational Status
Particulars
Affected Villages
Unaffected Villages
Sl.No
Numbers
1.
2.
3.
4.
5.
Illiterates
Primary
Secondary
Higher Secondary
Graduates
Total
73
48
66
22
39
248
Percentag
e
29.44
19.35
26.61
8.87
15.72
100.00
Number
s
63
68
54
23
47
255
Percentage
24.71
26.67
21.18
9.02
18.43
100.00
4.2.3. Land Holding Pattern
The land area possessed by the sample households and the area under
cultivation are presented in Table 4.30. There were wet, dry and garden lands.
The average operational area of the sample households in the unaffected area
was higher (2.09 ha) than the affected area (1.28 ha). The average area under
cultivation was 1.61/ha in unaffected villages when compared to 0.89 ha in
affected villages.
Table 4.30. Land Holding Pattern
Nature of
land
Wet land
Garden
land
Dry land
Total
Affected Villages
Operational
Area
Area
Cultivated
0.34
0.23
(26.47)
(25.29)
0.83
0.64
(64.84)
(71.69)
0.11
0.03
(8.69)
(3.02)
1.28
0.89
51
(Average ha)
Unaffected Villages
Operational
Area
Area
Cultivated
0.83
0.54
(39.88)
(33.80)
1.00
0.97
(47.86)
(60.55)
0.26
0.09
(12.26)
(5.66)
2.09
1.61
TNAU – TNSLUB Project
Introduction
(100.00)
(100.00)
(100.00)
(100.00)
Figures in parentheses indicate the percentage to total
4.2.4. Irrigation
The river Amaravathy and its canals, openwells and bore wells are the chief
sources of irrigation in both affected and unaffected villages. Somur is benefited
by both Cauvery and Amaravathy rivers. There are three canals and the area
covered is 245.79 ha. The village Pallapalayam is benefited by Raja Vaykal,
which is about two km long and covers an area of about 335 ha. Due to the
dyeing factory effluents both the canal and the open wells are not used by many
farmers for irrigation in the Sanapparetti village. In the affected villages, many of
the sample farmers reported that the well water quality has been affected by
effluents.
Table 4.31. Well Irrigation
Sl.
No.
Particulars
Affecte
d
Villages
Unaffected
Villages
55
35
1.
Total number of wells in the sample farms
2.
Average depth of open well (in mts.)
13.67
12.33
3.
Percentage of well with water throughout the
year *
74.55
57.14
4.
Percentage of well with water only during the
rainy season *
21.82
40.00
5.
Percentage of abandoned wells *
13.64
2.86
6.
Number of bore wells in the sample farms
1
9
7.
Average depth of bore wells (mts.)
13.33
14.33
8.
Percentage of wells affected by effluents in
the sample farms
100.00
-
* Percentage calculated upon the total number of wells in the sample farms
4.2.5. Sources of Irrigation
52
TNAU – TNSLUB Project
Introduction
The sources of irrigation are given in Table 4.32. Area under canal irrigation in
the affected villages was very less (9.33%) when compared to unaffected areas
(18.06%). Rainfed cultivation did not show any significant difference between the
unaffected (32.67 %) and affected (32.59 %) villages. No area is irrigated by
bore well in affected villages while in the unaffected villages it accounted for 8.49
per cent.
Table 4.32. Irrigation Sources
(Per cent)
Sl.No
Particulars
Affected Villages
Unaffected Villages
1.
Canal
9.33
18.06
2.
Open well
43.33
25.92
3.
Canal + Open well
14.75
8.62
4.
Canal + River water Scheme*
-
5.95
5.
Openwell + Bore well
-
8.49
6.
Water purchased from outside
-
0.29
7.
Purely Rainfed
32.59
32.67
*In the village Somur the farmers pay a deposit of Rs.12,000/annum for availing water from the canal of
the river “Cauvery”.
Fig. 18 Sources of Irrigation – Karur Taluk
53
TNAU – TNSLUB Project
Introduction
S ource s of Irriga tion
50
43.33
40
32.59
32.67
30
25.92
20
18.06
14.75
10
9.33
8.62
8.49
5.95
0
0
0 0.29
0
Canal
-10
Open well
Canal +
Canal +
Openwell +
Water
Open well River water Bore well purchased
Scheme*
from
outside
Purely
Rainfed
Affected Villages
Sources of Irrigation
Unaffected Villages
4.2.6. Area and Productivity of Crops
The area and productivity of crops grown in the affected and unaffected sample
households are presented in Table 4.33. The table shows that the area under
coconut in the unaffected area was higher (28.67 %) than in affected area
(11.19%). Also, the area under paddy was higher (22.68%) in unaffected areas
compared to affected villages (19.34 %). The same trend was observed for
fodder cholam also. Even the major crop of this taluk ‘korai’ was not grown well
in the affected localities due to poor soil and water qualities.
The productivity of almost all the crops was found higher in unaffected villages
compared to affected locations. Ten years back sugarcane, turmeric and paddy
were the major crops grown in both affected and unaffected villages. These
crops occupied an area of about 60 per cent of the total cultivable lands. By
now, the area under turmeric is almost zero in the affected villages. Sugarcane
and paddy occupied only less than 20 per cent of the total cultivated area. Total
area under cultivation had also declined during recent years.
54
TNAU – TNSLUB Project
Introduction
Table 4.33. Crop Area and Productivity
Sl.
No.
Name of
the Crop
1.
2.
3.
4.
Coconut*
Paddy
Turmeric
Fodder
Cholam
Grain
Cholam
Ragi
Banana
Sunflower
Sugarcane
Cotton
Groundnut
Vegetables
Greens
Korai
Tapioca
Total
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Affected Area
Area
Yield
(%)
(tons/
ha)
11.19
14705
19.34
4.35
35.37
6.17
Unaffected Area
Area
Yield
(%)
(tons/
ha)
28.67
26073
22.68
5.07
4.25
5.79
16.32
8.15
Difference
Yield
Percen
(tons/
-tage
ha)
11368
(-)44
0.72
(-)14
1.98
(-)24
7.46
1.85
0.86
1.24
0.61
49
1.69
9.84
10.04
0.67
3.38
1.02
100.00
0.62
59.21
1.36
1.73
61.75
741
-
0.69
0.87
4.30
0.86
3.65
16.65
0.25
100.00
0.99
98.12
93.83
2.49
2.19
6.99
74.10
-
34.62
1.13
0.46
-
(-)37
(-)83
(-)21
-
* yield in nuts/ha.
Fig. 19 Crop Area and Productivity – Karur Taluk
55
TNAU – TNSLUB Project
Introduction
Crop Area and Productivity
120.00
98.12
100.00
93.83
80.00
61.75
59.21
60.00
40.00
20.00
4.35 5.07
6.17 8.15
Paddy
Fodder
Cholam
1.73 2.19
0.00
0.00
0.00
Banana
Sugarcane
Crops
Groundnut
Vegetables
Affected villages
Unaffected villages
4.2.7. Farmers Opinion about Decline in Agricultural Activities
The respondent’s opinion towards decline in agricultural operations are reported
in the Table 4.34. Scarcity of good quality water and non-availability of farm
labourers were the main reasons for decline in agricultural operations, which
accounted for 83.33 and 73.33 per cent, respectively.
Labour scarcity was due
to the mobility of agricultural labourers from farming to industrial sector.
Due to
the deterioration of land and water quality, the crop stand was also observed
poor.
All these factors together contributed to huge decline in agricultural
activities.
Table 4.34. Farmers’ Opinion Towards Decline in Agricultural Activities
Sl.No
Opinion
Affected Category
1.
Water scarcity
83.33
2.
Labour scarcity
73.33
56
TNAU – TNSLUB Project
Introduction
3.
Poor water quality
70.00
4.
Decline in water table
28.33
5.
Decline in agricultural income
30.00
6.
Poor crop stand
43.33
Fig. 20 Opinion of Sample Farmers on Decline in Agricultural
Activities – Karur Taluk
Opinion of S a mple Fa rme rs on D e cline in Agricultura l Activitie s
100.00
83.33
80.00
73.33
70.00
60.00
43.33
40.00
28.33
30.00
Decline in
water table
Decline in
agricultural
income
20.00
0.00
Water
scarcity
Labour
scarcity
Poor water
quality
Poor crop
stand
Affe cte d ca te gory
4.2.8. Changes in the Value of Agricultural Lands
The changes in the value of agricultural lands are compared over years and the
details are presented in Table 4.35. The agricultural land value in the affected
villages declined considerably (9 per cent) due to poor soil and water qualities
while the land price had improved by 55 per cent in the unaffected area. Fifteen
years back, the value of agricultural lands in the affected village was higher than
the unaffected villages. The same trend was noticed till early part of nineties. By
now, the value of the land had been reduced by 9.32 per cent in the affected
villages. Whereas in the unaffected villages, an increase of 55 per cent in the
value of agricultural land was noticed over years.
57
TNAU – TNSLUB Project
Introduction
Table 4.35. Value of Crop Land
(Rs
ha)
Sl.No
Particulars
per
Affected Village
Unaffected Village
1.
5 years back
1,56,600.00
1,25,000.00
2.
2003 – 04
1,42,000.00
1,94,000.00
3.
Change in value of land
(-)9.32
55
(in per cent)
4.2.9 Employment Pattern
The employment distribution of the household is presented in the Table 4.36. In
the affected villages none of the households was found to undertake farm activity
alone. About two per cent of the sample households in the unaffected villages
were engaged in agricultural activities alone. In the affected villages, about 12
per cent of the sample households were employed in the combined activities of
agriculture and dairy while in the unaffected villages it was about 17 per cent.
The percentage of sample households engaged in the combined activities of onfarm plus non-farm (36.67 per cent) and off farm plus non farm (3.33 per cent)
were found to be equal in both the categories.
About 22 per cent of the
households in the affected villages were employed in the combined activities of
both on-farm and off-farm while it was only about 13 per cent in the unaffected
villages.
Table 4.36 Occupational Distribution of the Households
S.
No
Particulars
Affected Villages
Number
58
Per
cent
Unaffected
Villages
Number
Per
cent
TNAU – TNSLUB Project
Introduction
On-farm
1.
Crop alone
-
-
1
1.67
2.
Crop alone + dairy activities
7
11.67
10
16.67
7
11.67
11
18.34
Total households engaged in onfarm activities alone
3.
On-farm + Off farm activity
13
21.67
8
13.33
4.
On-farm + Non-farm activity
22
36.67
22
36.67
5.
On-farm + Off- farm + Nonfarm activity
14
23.33
17
28.33
6.
Off-farm + Non-farm activity
2
3.33
2
3.33
7.
Non-farm activity (petty shop)
2
3.33
-
-
Total Sample Households
60
100.00
60
100.00
Earning members in the sample
households
133
59
121
TNAU – TNSLUB Project
Introduction
0
0
3.33
5
23.33
21.67
0
10
3.33
15
3.33
11.67
20
13.33
25
16.67
30
1.67
Percentage
35
28.33
40
36.67
36.67
Fig.21 Occupational Distribution of Households - Karur Taluk
Crop alone Crop + dairy On farm +
activities
off farm
activity
Affected
On farm+
non farm
activity
On farm+off Off farm +
farm+non
non farm
farm
activity
Non farm
activity
Unaffected
4.2.10. Income
The income pattern of the household is presented in the Table 4.37.
In the
affected villages, 11.70 per cent of the household income was from both
agriculture and dairy, but it was high (29.24 per cent) in the unaffected villages.
About five per cent of the income in the affected villages were involved from non
farm activities like money lending, wage earning in private companies and so on.
Income from both on-farm and non-farm activities was observed higher at 52.44
and 50.32 per cent respectively, in the affected and unaffected villages. About
18 per cent of income of households in the affected villages were from the
combination of all the three activities viz, on-farm, off-farm and non-farm
activities. The average annual income earned by the households was Rs.74,
666 and Rs 1, 30,072 respectively, in the affected and unaffected sample
households where the difference happened to be larger.
Table 4.37 Pattern Average Annual Income of the Sample Household
60
TNAU – TNSLUB Project
Sl.No
Introduction
Particulars
Affected Villages
(in Rs.)
Unaffected
Villages
Amount Percent
Amount
Percen
t
-
-
1,000
0.77
8,733
8,733
11.70
11.70
38,033
39,033
29.24
30.01
On -farm
1.
Farm income
2.
Farm + Dairy activities
Average annual income from onfarm activities only
3.
On-farm + Off -farm income
6,525
8.74
7,033
5.41
4.
On-farm+Non-farm income
39,158
52.44
65,458
50.32
5.
On-farm + Off-farm + Nonfarm income
Off-farm + Non -farm
income
Non-farm income
14,050
18.82
17,231
13.25
2,400
3.21
1,317
1.01
3,800
5.09
-
-
74,666
100.00
1,30,07
2
100.00
6.
7.
Average Annual
Household
Income Per
Farm
income
Farm +
dairy
activities
Affected
On farm+
non farm
income
Unaffected
61
5.09
3.21
1.01
18.82
On farm +
off farm
income
0.00
0.00
8.74
10.00
0.77
20.00
5.41
30.00
11.70
40.00
13.25
52.44
29.24
50.00
0.00
Percentage
60.00
50.32
Fig.22 Pattern of Inc ome - Karur Taluk
On
Off farm + Non farm
farm+off non farm
income
farm+non
income
farm
income
TNAU – TNSLUB Project
Introduction
4.2.11. Labour Migration
In the affected villages, earning members in 55 per cent of the households
interviewed have migrated in search of employment. The details of the labour
migration are reported in the Table 4.38.
The analysis of reasons for the
migration of farm households had indicated that poor water quality was found to
be the main reason (52.22 per cent) followed by poor income from agriculture
(48.94).
Table 4.38.
Labour Migration
Sl.No
Particulars
Affected (Percent)
1.
2.
Percentage of migration (out of 60 households)
Percentage migration from sample households
55.00
18.12
3.
Percentage of permanent migration by the
family members
Number of days migration
Reasons for migration
Poor water quality
Less income from agriculture
To earn more income
Employment in public / private institutions
To pursue higher education
95.74
4.
5.
a.
b.
c.
d.
e.
79.66
52.22
48.94
40.43
14.89
12.77
4.2.12. Sale of Assets
It is inferred from Table 4.39 that in the affected villages 30 per cent of the
respondents had disposed off at least part of their land due to poor water quality
and labour scarcity. In these villages 75 per cent of the respondents interviewed
had sold their livestock due to various reasons like poor water quality, non
availability of water, labour shortage, poor milk yield and reduced calving rate. In
62
TNAU – TNSLUB Project
Introduction
the unaffected villages these values were only 10 and 46.67 per cent,
respectively.
Table 4.39.
Sale of Assets
Sl.No
Particulars
I.
1.
Sale of Land
Percentage of respondents sold
land
Extent of land sold (%)
Sale of Animals
Percentage of respondents sold
animals
Reasons for sale of animals
Poor Water Quality
Labour Scarcity
Drying / Aged animal
Poor Milk Yield
Reduced Calving rate
To meet out unexpected expenses
2.
II.
1.
a.
b.
c.
d.
e.
f.
(Per cent)
Un affected
Villages
Affected
Villages
25
10
4.60
1.74
75
46.67
15
10
35
1.67
10
3.33
5
25
16.67
-
4.2.13. Farm Level Availability of Livestock
From the Table 4.40 it is understood that the number of animals in the affected
village had been marginally low compared to unaffected villages.
Sheep was
reared by majority of the farmers in the unaffected villages because of the
availability of grazing lands and good quality water, whereas in affected areas, it
was only 50 per cent of the animals available with farmers in unaffected areas
because of the non-availability of good quality water, fodder and grazing lands.
Table 4.40. Possession of Livestock
Sl.No
1.
2.
Category
Cow
Buffalo
Affected Area
0.78
1.03
63
(Numbers)
Unaffected Area
0.82
1.02
TNAU – TNSLUB Project
3.
4.
4.2.14.
Introduction
Bullock
0.08
Sheep
0.28
Sufferings by Human and Animals
0.02
0.60
Occasionally the people in the affected areas have been experiencing morbidity
problems viz., itching, skin rashes, eye boils etc. In animals also, reduction of
milk yield, weight loss and poor calving were reported.
Milk production in the
affected area was reported to be reduced by 12.35 per cent.
Table 4.41.
Sl.No.
Externalities on Human and Animal Health
Affected Villages
(per individual)
Particulars
Human Health
1.
Average cost of medicine (Rs./annum)
2.
Average
cost
to
physician
(Rs./annum)
Animal Health
1.
Loss in value (Rs./ annum)
2.
Percentage loss in milk production
70.25
110
4170
12.35
4.2.15. Sources of Drinking Water
The river Cauvery is the chief source of drinking water in the affected villages
whereas in unaffected villages, river Amaravathy is the major source of water
supply. The respondents of
Panchamadevi were getting drinking water daily
either from their own tap or public tap; whereas in Sanapparatti, people were
getting water only once in 15 days from the public tap. They were forced to bring
water from Vadakupalayam, located about 5 km from the village and about 97
per cent of the respondents depended on public tap only (Table 4.42).
Six
respondents were also purchasing mineral water (45 lts. can) and seven
respondents reported purchasing water transported by lorries.
But in the
unaffected villages, the availability of drinking water was not a severe problem.
About 85 per cent of the respondents depended on public taps while 15 per cent
64
TNAU – TNSLUB Project
Introduction
of the respondents had their own tap. The water use in the affected households
was found to be marginally less (5,250 litres/month) than the unaffected villages
(5,336 litres/month).
Water was however not purchased from outside in the
unaffected areas and availability of good quality water is reported to be acute
during the last ten years in the affected villages.
Table 4.42. Sources of Drinking Water
Sl.
No
Particulars
Affected Village
Number
Expense
(Rs. /
househol
d/annum)
Cauvery
1. Sources of Drinking Water
Unaffected Village
Numbe
r
Expense
(Rs. /
househol
d)
Amaravathy
a.
No. of people having
own water connection
2
360
9
360
b.
No. of people having
public water connection
No.
of
people
purchasing water from
outside (in 45 lts cans)
58
-
51
-
6
195
-
-
No. of people using
water transported by
lorries
No. of people using well
water
7
6,146
-
-
1
-
-
-
c.
e.
f.
2. Average Water Requirement and Expense towards procuring water
a.
b.
Average
water
requirement per month
(litres/family)
Average quantity of water
transported by lorries per
month/family (in litres)
5,250
-
5,336
-
10,320
753.00
-
-
65
TNAU – TNSLUB Project
3.
Introduction
Average
Distance
between the household
and the source of water
(km)
0.64
-
0.50
-
4.2.16. Well Water Quality
Out of 51 wells in the affected area, ten wells were reported to be having very
poor water quality during summer. The quality was reported as poor in 37 wells
out of 50. In the unaffected villages, the quality of water was good to medium
and very few wells had poor quality water. The colour of water was normal in
unaffected localities whereas in affected area, it was black, occasionally red or
dull white in few cases. Mild odour was also present in affected areas.
Table 4.43. Quality of Well Water
Sl.No
Particulars
Total No. of Wells*
Taste
1.
Poor
2.
Medium
3.
Good
Colour
1.
High
2.
Medium
3.
Low
Turbidity
1.
High
2.
Low
Odour
1.
High
2.
Low
Affected Area
Summer
Rainy
Season
Season
51
(Per cent)
Unaffected Area
Summer
Rainy
Season
Season
31
92.16
7.84
-
49.02
50.98
-
6.45
83.87
9.68
83.87
16.13
1.96
3.92
94.12
1.96
3.92
94.12
100.00
100.00
1.96
98.04
-
100.00
100.00
100
0
-
100.00
100.00
* One well has no water. Three respondents are having two wells.
4.2.17. Willingness to Pay (WTP)
66
TNAU – TNSLUB Project
Introduction
The problem of water and soil quality was comparatively high only in the affected
areas and out of 60 respondents about 62 per cent were willing to pay some
amount to replenish the degraded resources.
About 57 per cent of the
respondents were willing to pay in the range of Rs.25,000 to Rs.50,000 and
about 43 per cent were willing to pay annually.
Table 4.44. Willingness to Pay
Sl.No.
1.
2.
3.
a.
b.
c.
d.
4.
a.
b.
c.
d.
Particulars
Households willing to pay
Households not willing to pay
Willingness to pay
Less than Rs.20, 000
Rs.21, 000 – Rs.25, 000
Rs.25, 001 – Rs.50, 000
Rs.50, 001 – Rs.75, 000
Mode of Payment
Monthly
Quarterly
Half yearly
Annual
Numbers
37
23
Value (Per cent)
61.67
38.33
3
8
21
5
8.11
21.62
56.76
13.51
7
5
9
16
18.92
13.51
24.32
43.24
Fig.23 Willingness to Pay – Karur Taluk
67
TNAU – TNSLUB Project
Introduction
Willingness to Pay
56.76
60
50
40
30
21.62
20
13.51
8.11
10
0
Less than Rs.20, 000
Rs.20, 001 –Rs.25,000
Rs.25, 001 –Rs.50,000
Rs.50, 001 –Rs.75,000
Amount willing to pay
4.2.18. Averting Expenditure
From the table 4.45 it could be understood that the farmers cultivating paddy and
fodder cholam spent about Rs.687 and Rs.510 per ha respectively, towards
averting expenditure on seeds, organic manure, etc. Similarly, for sugarcane
about Rs.1122 per ha was spent as averting expenditure and for sunflower it was
Rs.200 per ha. For getting good quality drinking water from the nearby locations,
respondents had to spend 8.44 man-days amounting to Rs.844 / annum /
household.
Table 4.45. Averting Expenditure
Sl.
No.
1.
2.
3.
4.
5.
Particulars
Averting Expenditure
(Rs./ha)
687
510
1123
200
844
Paddy
Fodder Cholam
Sugarcane
Sunflower
Drinking water (Rs. / annum)
Soil and Water Sample Analysis
68
TNAU – TNSLUB Project
Introduction
4.2.19. Physico - Chemical characteristics of water samples collected at
Karur taluk (Before monsoon)
The results of the water sample analysis of Karur taluk, before and after
monsoon are given in the tables 4.46 and 4.47.
The water samples taken from villages of Karur before monsoon showed not
much variations in pH values in both affected and unaffected regions (7.38 – 8.50
and 7.56 – 8.30 respectively) and are well within the standard limit of 6.5 – 8.50.
The EC values were found to be more or less similar in both the regions
exhibiting 0.95 – 3.20 ds/m in affected regions and 0 – 3.15 ds/m in unaffected
regions water samples. Both the samples exceeded the maximum permissible
limit of 2.25 prescribed for irrigation water.
The chloride content was maximum in affected regions (49 – 134 mg l-1)
compared to unaffected villages ranging from 56 – 110 mg l-1. Both the regions
are well within the prescribed limits (500 mg l-1). The sulphate content was
maximum in affected villages of about 110-386 mg l-1 compared to unaffected
villages ranging from 180 - 380 mg l-1.
The calcium content in affected villages was found to be 435 – 3550 mg l-1 and
550 – 3850 mg l-1 in the unaffected villages. Both the regions exceed to a
greater extent when compared with critical limit of 100 mg l-1. The magnesium
content ranges from 13 –65 mg l-1 in affected regions and 15 – 67 mg l-1 in
unaffected regions. Both the regions fall with in the critical limit of 150 mg l-1.
In general, the BOD and COD values affected villages water samples were
higher than the samples from unaffected villages. Water samples collected from
affected villages recorded a BOD value ranging from 35 – 110 mg l-1 and 27 –
104 mg l-1 in unaffected regions. Whereas the COD values ranged between 165
– 420 mg l-1 and 95 – 240 mg l-1 in affected and unaffected regions respectively.
69
TNAU – TNSLUB Project
Introduction
Though the BOD values of unaffected samples are higher than the limit, the COD
lies within the limit but both the BOD and COD values of samples from affected
villagers are higher than the maximum permissible limit of 250 mg l-1. The
samples of affected villages recorded the SAR ranging between 39 – 46, which
are higher than the maximum limit of 26, whereas, the unaffected villages
samples recorded SAR of below permissible level.
With regard to heavy metal contents of samples, all the samples collected from
affected and unaffected villages recorded the presence of heavy metals such as
chromium, lead, nickel and cadmium. The water samples from affected villages
recorded 0.02 - 0.10, 0.02 - 0.55, 0.02 - 0.05 and 0.25- 0.50 and unaffected
villages recorded BDL - 0.05, BDL - 0.42, BDL - 0.05 and 0.10 - 0.48 mg l-1 of
Cr, Pb, Cd and Ni respectively. All the four heavy metal contents of affected
villages’ samples exceeded the critical limits and water samples from unaffected
villages have higher levels of heavy metals except Cr, which is within the limit.
4.2.20. Physico - Chemical characteristics of water samples collected at
Karur taluk after monsoon
The water samples collected after monsoon recorded more or less similar pH
values in both affected and unaffected regions ranging from 6.82 - 8.45 and 6.99
- 7.85 respectively. These values in both the regions do not vary from the critical
limit of about 6.5 – 8.50. The EC value was recorded as 2.05 - 4.12 ds/m in
affected villages compared to 1.22 - 3.11 ds/m in unaffected regions, which are
exceeding the standard limit of 2.25 ds/m for irrigation water.
Table 4.46. Physico - Characteristics of water samples collected at Karur
Taluk
(Before monsoon)
70
TNAU – TNSLUB Project
Parameter
pH
EC (ds/m)
Chloride (ppm)
Sulphate (ppm)
Ca (ppm)
Mg (ppm)
COD (mg/l)
BOD (mg/l)
SAR
Chromium (mg/l)
Lead (mg/l)
Cadmium (mg/l)
Nickel (mg/l)
Introduction
Affected Villages
7.38 – 8.50
0.95 – 3.20
49 – 134
110 – 386
435 – 3550
13 – 65
165 – 420
35 - 110
39 - 46
0.02 - 0.10
0.02 - 0.55
0.02 - 0.05
0.25- 0.50
Unaffected Villages
7.56 – 8.30
0.50 – 3.15
56 – 110
180 – 380
550 – 3850
15 – 67
95 – 240
27 – 104
18 - 24
BDL - 0.05
BDL - 0.42
BDL - 0.05
0.10 - 0.48
The BOD values in affected regions ranged between 99 – 148 mg l-1 when
compared to 34 – 60 mg l-1 in unaffected regions and the COD values are also
found to be greater in affected villages ranging from 215 – 305 mg l-1 compared
to unaffected villages which recorded about 85 - 120 mg l-1. There was no much
variation between
the chloride and sulphate contents of both the samples. The
samples of affected villages and unaffected villages recorded 245 – 415 mg l-1
and 215 – 445 mg l-1 of chloride respectively, and 25 – 50 mg l-1 and 23 – 45 mg
l-1 of sulphate respectively, which are well between the critical limits. Calcium
and magnesium contents of affected villages are
higher recording 585– 3150
and 45-75 mg l-1 respectively. The SAR values of affected samples exceeded the
critical limit but unaffected samples lies within the limit of 26.
Regarding heavy metal analysis, chromium content was found to be higher in the
affected regions ranging from 0.02 –0.08 mg l-1 whereas in the unaffected
villages, it is found between BDL – 0.06 mg l-1 which is slightly higher than the
limit. The water samples colleted from unaffected region also recorded the
presence of other heavy metals such as lead, cadmium and nickel well above
critical limits.
71
TNAU – TNSLUB Project
Introduction
Table 4.47. Physico - Characteristics of water samples collected at Karur
Taluk (Aftermonsoon)
Parameters
Affected Villages
Unaffected Villages
pH
6.82 - 8.45
6.99 - 7.85
EC (ds/m)
2.05 - 4.12
1.22 - 3.11
BOD (mg/l)
99 - 148
34 – 60
COD (mg/l)
215 - 305
85 – 120
Calcium
585– 3150
510– 2850
Magnesium
45-75
32-56
Chloride (mg/l)
245 – 415
215 – 445
Sulphate (mg/l)
25 -50
23 – 45
SAR
32 - 38
20 - 24
Chromium (mg/l)
0.02 – 0.08
BDL – 0.06
Lead (mg/l)
BDL – 0.34
BDL – 0.40
Cadmium (mg/l)
BDL – 0.04
BDL – 0.04
Nickel (mg/l)
BDL – 0.45
BDL – 0.52
4.2.21. Assessing the changes in soil properties of Karur taluk
The results of analysis of soil samples collected from the study villages of Karur
taluk are presented in table 4.48. pH values ranged between 7.56 – 8.31 in
affected villages and 6.10 and 7.23 in unaffected regions. The EC value too was
greater in the affected villages recording 1.25 – 4.10 ds/m when compared with
the values in the unaffected villages (0.14 - 1.28 ds/m).
The available N content was higher in affected villages (189 – 547 kg/ha) which
comes under high rating (>450 kg/ha); whereas, the unaffected regions showed
values between 102 – 178 kg/ha which comes under the low rating (0 – 28
kg/ha). The available P content showed values ranging from 19 – 89 kg/ha in
affected regions and in the unaffected region (23 – 64 kg/ha). Both the regions
come under high rating (>22 kg/ha). Similarly, the available K content was
maximum in affected regions (189 – 359 kg/ha) and comes under high rating
(>280 kg/ha) when compared with the unaffected villages which recorded 20 – 91
kg/ha which lies in low rating (0 - 118 kg/ha).
72
TNAU – TNSLUB Project
Introduction
Chromium content was found to be high in the affected regions (39 -99 ppm) and
low (23 – 58 ppm) in soil samples of unaffected villages. But both the samples lie
well within the critical limit of 100 ppm. Soil samples of affected villages of Karur
taluk recorded 2.36 – 5.69 ppm of lead, 1.89 – 5.96 ppm of cadmium, and 12 - 45
ppm of nickel when compared to unaffected regions which recorded 1.37 – 2.10
ppm of Pb, 1.10 - 2.10 ppm of Cd and 9 – 24 ppm of nickel.
73
TNAU – TNSLUB Project
Table 4.48.
Introduction
Characteristics of soil samples collected at selected villages
of Karur taluk
Parameters
Affected Villages
Unaffected Villages
pH
7.56 - 8.31
6.10 - 7.23
EC (ds/m)
1.25 – 4.10
0.14 - 1.28
Available N (kg/ha)
189 – 547
102 - 178
Avail.P (kg/ha)
19 – 89
23 - 64
Avail. K (kg/ha)
189 – 359
20 - 91
39 – 99
23 - 58
Lead (mg/kg)
2.36 -5.69
1.37 - 2.10
Cadmium (mg/kg)
1.89 -5.96
1.10 - 2.10
12 – 45
9 - 24
Chromium (mg/kg)
Nickel (mg/kg)
Workers – Karur
Majority of the workers interviewed were mainly natives of this taluk. Both the
educated and uneducated youth of the farm families were employed themselves
in the nearby dyeing or bleaching industries. The main reason for this was the
higher wage rate in the industry when compared to agricultural sector. Physical
strain was also reported to be less in non-farm industrial occupations.
4.2.22. Nature of Work
The table 4.49 reveals the occupational distribution of the labourers in the
sample villages. Almost all the respondents in the affected areas maintained
their livelihood by working as wage earners in the dyeing factories. They were
employed in the categories such as; supervisor, cashier, accountant, dye master,
skilled labourers (colouring and dyeing), and so on. In the unaffected villages
about 25 per cent of the workers interviewed were agricultural labourers, 15 per
cent were masons and 10 per cent were casual workers. Of the remaining 50
74
TNAU – TNSLUB Project
Introduction
per cent, 15 per cent were either working as dye master or in the boiler section,
10 per cent as RO plant operators and 10 per cent as ETP managers.
Table 4.49. Nature of work
Sl.No
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Category
Dye master
Labour (doing colouring of yarn)
Supervisor
Cashier
Accountant
Typist
Hydropher
Unskilled Labour (Sweeper)
Watchman
Agricultural labourer
Mason
Casual labourer
Boiler operators
RO (Reverse Osmosis) Plant operator
ETP
(Effluent
Treatment
Plant)
Managers
Affected
Area
25
30
10
10
5
5
5
5
5
-
(Per cent)
Unaffected
Area
15
25
15
10
15
10
10
4.2.23. Employment
It is implicit from the table 4.50, that the average days of employment for the
workers in the affected area were more by 15 per cent. The average annual
income earned by the worker respondent in the affected village was also high by
Rs.8535 compared to the earnings of workers in the unaffected area due to
continued employment and high wage rate in industries.
Table 4.50. Employment Particulars
75
TNAU – TNSLUB Project
Sl.No
Introduction
Particulars
Affected
Villages
Unaffected
Villages
25
(82 %)
20.5
(67.39 %)
1.
Mandays of employment (per month)
2.
Number of family members in dyeing
factories
0.60
-
3.
Number
of
companies
0.20
-
4.
Annual income of the respondent (in
Rs)
4.2.24.
people
in
knitting
29,040
20,505
Benefits Availed by Workers
Twenty per cent of the respondents in the affected study villages had availed
accident and medical claims (for the accidents or disorders that had happened
while working) from the owners. It was reported that 15 per cent of the workers
in affected area were under ESI coverage and it was 25 per cent for accident
claims and 10 per cent in ESI (Table 4.51) in unaffected villages.
Table 4.51 Benefits Availed by the Workers
(Per cent)
Sl.No
Particulars
1.
Accident
Claims
and
2.
ESI Coverage
Medical
Affected
Villages
Unaffected
Villages
20
25
15
10
4.2.25. Sufferings Faced by the Respondents
It could be seen from the table 4.52 that a vast majority of about 60 per cent of
the workers were found to suffer from skin rashes, (skin rashes were reported to
occur throughout the year), 25 per cent from dysentery, 10 per cent from either
76
TNAU – TNSLUB Project
Introduction
fever or headache and only five per cent reported that they were not
encountering any health oriented problems. The respondents were reported to
spend on an average Rs.225 per annum towards cost to physician and Rs.415
per annum towards cost of medicine. They also reported to have lost on an
average of 2.33 man days of employment per annum. In the unaffected villages
only 15 per cent were reported to suffer from skin rashes and they spent on an
average about Rs.150 per annum towards cost of illness.
Table 4.52. Sufferings of the Respondents
(Per cent)
Sl.No
Particulars
Affected
Villages
Unaffected
Villages
1.
Skin rashes
60
15
2.
Dysentery
25
-
3.
Occasional fever / Head ache
10
-
4.
Not encountering any problems
5
85
5.
Frequency of occurrence of the
above diseases
Four- five
times/year
Occasionally
6.
Working days lost per annum
2.33
-
7.
Loss of earnings
(Rs./annum/individual)
217
-
8.
Average physician cost (Rs./annum)
225
-
9.
Ave. medical expenses (Rs./ annum)
415
-
4.2.26. Drinking Water
In the affected village Panchamadevi, Cauvery water is supplied daily for drinking
purpose through public taps by the municipality whereas in the other affected
village Sanapparetti, the workers used to fetch water from Vadakkupalayam. It
was observed that none of the respondents was provided with individual tap
connection.
77
TNAU – TNSLUB Project
Introduction
Table 4.53. Drinking Water Quality
Sl.No
Particulars
Affected
Villages
Unaffected
Villages
1.
Public tap and well (numbers)
20
20
2.
Time taken to fetch good quality water from
the unaffected areas (minutes/day)
54
52.5
3.
Water usage (lts/month)
1855
1932
4.3. Bhavani
4.3.1. Family Size
It is clear from table 4.54 that the overall family size of the respondents was 3.67
and it was 3.93 for the unaffected category and 3.40 for the affected groups.
Table 4.54. Average Family Size
(Numbers)
Sl.No.
Category
Average Size of the
Family
1
Affected area
3.40
2
Unaffected area
3.93
Overall
3.67
4.3.2 Educational status
From the table 4.55, it is inferred that about 29 per cent were illiterates in the
affected villages where as it was only 18.64 per cent in the unaffected area.
About 22 per cent had completed their secondary education in the affected area.
This might be due to the availability of immense employment opportunities in and
around the sample villages.
78
TNAU – TNSLUB Project
Introduction
Table 4.55. Educational Status
Sl.No
.
Affected Area
Particulars
Numbers
Unaffected Area
Per cent
Numbers
Per
cent
1.
Illiterates
60
29.41
44
18.64
2.
Primary
42
20.59
75
31.78
3.
Secondary
45
22.06
89
37.71
4.
Higher secondary
18
8.82
11
4.66
5.
Graduates
39
19.12
17
7.21
204
100.00
236
100.00
Total
4.3.3. Land Holding Pattern
The land area possessed by the sample farmers and area under cultivation are
presented in Table 4.56. The average area under cultivation was 1.54 ha in the
affected area whereas in the unaffected area it was 1.72 ha. It was revealed that
the effluents of the dyeing factories had reduced the usage of water for irrigation
purposes. This has forced many farmers to convert their croplands to nonagricultural purposes. The declivity of cropland area in the affected villages was
5.17 per cent. This has brought down to a great extend the crop income. The
main reasons for the decline in crop income were change in cropping pattern and
low crop productivity. The pollution has also created changes in cropping area
and employment opportunities.
79
TNAU – TNSLUB Project
Introduction
Table 4.56. Land Holding Pattern
(Ha)
Sl.No
Land
Affected Villages
Unaffected Village
Average
Land
Holding
Net Area
Sown
Average Land
Holding
Net Area
Sown
1
Wet
0.64
(39.22)
0.61
(39.61)
0.37
(20.52)
0.36
(20.83)
2
Garden
0.92
(56.44)
0.86
(55.81)
1.33
(73.67)
1.33
(77.60)
3
Dry
0.07
(4.34)
0.07
(4.58)
0.11
(5.81)
0.03
(1.57)
1.63
(100.00)
1.54
(100.00)
1.86
(100.00)
1.72
(100.00)
Total
Percentage of
cropland under
cropping
94.83
92.38
Decline in the
area (%)
5.17
7.2
Note: figures in parentheses indicate the percentage to total.
4.3.4. Details of Irrigation
The river Bhavani and both the open and bore wells are the major sources of
irrigation. From table 4.57 it could be revealed that the total numbers of open
wells in the affected villages were 43 whereas, it was 56 in unaffected area. The
average depth of the open well was almost equal in both the categories. But, the
depth of bore well in the unaffected villages was deep by 15mts. The
examination of the results also shows that the percentage of open wells
abandoned in the affected villages was 6.98 whereas it was only 1.79 per cent in
the unaffected area. This might be due to the non-availability of quality water in
the shallow depth and improper maintenance of water table by conservation and
abatement techniques.
80
TNAU – TNSLUB Project
Introduction
4.3.5. Sources of Irrigation
The table 4.58 reveals the share of area irrigated by various sources in the
affected and unaffected areas. From the table, it is clear that in the affected
villages, the crop area is irrigated only by canal and wells. But, the area irrigated
by canal and wells together has increased by 24.10 per cent over the last 10 year
period.
The total area under irrigation has increased by 1.55 times in the
affected villages, whereas, an increase of about 2.79 folds was noticed in the
unaffected villages, which is marginally higher than the affected area.
Table 4.57. Well Irrigation
Sl.
No.
Particulars
Affected
Village
Unaffected
Village
43
56
1.
Number of wells
2.
Depth of open well (in mts.)
18.80
18.78
3.
Percentage of wells abandoned
6.98
1.79
4.
Percentage of wells with quality water
throughout the year*
16.28
98.21
5.
Percentage of wells with water only during
rainy season*
76.74
-
6.
No of bore wells in the sample farms
17
25
7.
Average depth of bore wells (mts.)
101
116
8.
Water quality (%) **
Good
62.50
56.36
Medium
12.50
43.64
Poor
25.00
-
*Percentage calculated based on the total number of open wells in the sample farms
** - As perceived by the respondents
Table 4.58. Sources of Irrigation
81
TNAU – TNSLUB Project
Introduction
(Per cent)
Sl.No
Affected Villages
Sources
Unaffected Villages
10 years
Back
2003-04
10 years
Back
2003-04
1.
Canal
46.63
27.91
12.87
7.80
2.
Well
15.45
12.45
64.35
75.90
3.
Canal+ well
8.78
32.86
15.86
8.51
4.
Rainfed
23.08
21.50
6.92
5.31
5.
Bore well
-
0.23
-
-
6.
Open well+
Bore well
6.04
5.05
-
2.48
Fig.24 Sources of Irrigation - Bhavani Taluk
Sources of Irrigation
90.00
75.90
80.00
70.00
60.00
50.00
40.00
30.00
32.86
27.91
21.50
20.00
10.00
12.45
8.51
7.80
5.31
5.05
2.48
0.00
-10.00
Canal
Well
Canal+ well
Rainfed
Open well+
Bore well
Affected Villages
Sources of Irrigation
4.3.6. Area and Productivity
82
Unaffected Villages
TNAU – TNSLUB Project
Introduction
The critical analysis of the area and productivity of crops in the study area
reported in table 4.59 reveals that the productivity of the crops declined in the
affected villages. In the past, the major crops grown in the affected areas were
turmeric, sugarcane, paddy, fodder cholam, cotton, vegetables, gingelly and
banana. In the unaffected villages area under turmeric was about 17 per cent
whereas in the affected villages it was only 8 per cent.
The productivity of
sugarcane was higher (97 tons) in the unaffected villages when compared to the
productivity in the affected villages (90 tons). In the affected villages, about 16
per cent of the total cultivated area was under fodder cholam compared to five
per cent in the unaffected area.
Table 4. 59. Cropped area, Productivity and Cropping Intensity
Sl.N
o
Crops
Affected
Villages
Area
Yield
(%)
( t /ha)
8.17
7.79
23.34
90.26
38.41
5.02
Unaffected
Villages
Area
Yield
(%)
(t /ha)
17.01
12.87
23.04
96.96
30.49
5.11
Difference
Yield
(t /ha)
(-)5.08
(-)6.07
(-)0.09
Per
centage
1.
2.
3.
Turmeric
Sugarcane
Paddy
4.
Fodder
Cholam
Gingelly
Banana
Coconut*
16.57
6.17
5.31
6.91
(-)0.74
(-)10.71
8.07
3.30
0.38
0.68
110.10
9880
10.64
2.84
0.75
16,207
(-)0.07
(-)6327
(-)9.33
(-)39.04
Tapioca
Green
gram
Groundnut
1.36
0.39
36.68
1.01
0.71
-
37.05
-
(-)0.37
-
(-)1.00
-
-
-
9.96
20.4
-
-
5.
6.
7.
8.
9.
10.
* yield in Nuts/ha.
Fig.25 Crop Area and Productivity
83
(-)39.47
(-)6.91
(-)1.76
TNAU – TNSLUB Project
Introduction
Crop Area and Productivity
120.00
96.96
100.00
Affected villages
Unaffected villages
90.26
80.00
60.00
36.68 37.05
40.00
20.00
12.87
7.79
5.02
5.11
6.17
6.91
0.00
Turmeric
Sugarcane
Paddy
Fodder Cholam
Tapioca
Crops
4.3.7. Proximity of Cultivated Lands to Dyeing Industries
The distance between the respondents’ farm and the dyeing industries was less
than a kilometer (0.80 km).
Dyeing, bleaching, tanning and sago units are
located all around the villages (Bhavani and Andikulam). The factories are in
operation almost throughout year, and the type of effluents let out was
predominantly liquid in nature.
Table 4.60. Proximity of Dyeing Industries
Sl. No
Particulars
Affected Village
1.
Proximity (Km)
0.80
2.
Average months in operation / year
11.45
84
TNAU – TNSLUB Project
4.3.8.
Introduction
Attitude of the Respondents Towards the Decline in Agricultural
Activities
It is obvious from the table 4.61 that the interest of the farmers towards agriculture
is declining. It is clear that about 95 per cent of the respondents in the affected
villages expressed that the scarcity of water was the main reason for this decline.
About 75 per cent were of the view that the labour scarcity was the major reason
for the poor performance of agriculture and about 53 per cent of the respondents
opined that poor water quality might be the reason for the declivity.
Table 4.61. Farmers Opinion Towards Decline in Agricultural Activities
Sl. No
1.
2.
3.
4.
5.
Particulars
Water Scarcity
Labour Scarcity
Poor Water Quality
Decline in Agricultural Income
Poor Crop Stand
Percentage
95
75
53
40
5
Fig.26 Farmers Opinion towards decline in Agricultural Activities - Bhavani Taluk
Fa rme rs opinion towa rds de cline in Agricultura l Activitie s
100
95
80
75
60
53
40
40
20
5
0
Water Scarcity
Labour Scarcity
Poor Water
Quality
Affe cte d ca te gory
85
Decline in
Agricultural
Income
Poor Crop Stand
TNAU – TNSLUB Project
Introduction
4.3.9 Employment Pattern
The employment distribution of the household is reported in Table 4.62. In the
affected villages only about two per cent of the households were engaged in
agriculture alone whereas it was about 43 per cent in the unaffected villages. In
the affected villages about 37 per cent of the households were employed in farm
and non-farm activities whereas it was about 22 per cent in the affected villages.
The farm and diary activities constituted the second largest proportion at 31.67
per cent in affected villages and it was only 6.67 per cent in the unaffected
villages. The combination of all the three activities constituted 21.67 per cent in
affected villages and it was 13.33 per cent in unaffected villages.
Table 4.62 Occupational Distribution of Households
Sl.No
Particulars
Affected Villages
Un affected
Villages
Numbe
r
Percent
Numbe
r
Percent
1.
Farm activity only
1
1.67
26
43.33
2.
Farm + Dairy activities
19
31.67
4
6.67
20
33.34
30
50.00
Households engaged in on-farm
activities only
3.
Farm and off-farm activity
5
8.33
9
15.00
4.
Farm, non- farm and offfarm activity
13
21.67
8
13.33
5.
Farm and non-farm activity
22
36.67
13
21.67
Total Sample households
60
100.00
60
100.00
Earning members in Sample
Households (in numbers)
116
86
106
TNAU – TNSLUB Project
Introduction
Farm activity
only
Farm + dairy
activities
Affected
21.67
21.67
15.00
Farm and off
farm activity
13.33
6.67
8.33
31.67
36.67
43.33
50.00
45.00
40.00
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
1.67
Percentage
Fig.27 Occupational Distribution of Households - Bhavani
Taluk
Farm, non farm Farm and non
and off farm
farm activity
activity
Unaffected
4.3.10 Income
The income distribution of the sample households is given in the Table 4.63.
When the households are considered, majority earned their wages through the
combination of farm with non farm activities like working in private companies or
by running own bleaching and dyeing units or renting their land either for
factories or for residential purposes. The average annual income of the affected
household was Rs. 1,33,610/- where as in the unaffected area the average
annual income was Rs. 1,19,582/-Since the respondents has either been
employed as wage earners or running their own industrial unit, the share of nonfarm income is found to be substantial. In the affected villages, the income from
farm activities alone constituted 44.38 per cent. This was 57.39 per cent in
unaffected villages. In other categories, farm income formed a part.
87
TNAU – TNSLUB Project
Introduction
Table 4.63 Pattern of Average Annual Income in the Sample Households
(in Rs.)
Sl.No
Particulars
Affected Villages
Amount
Per
cent
1,500
1.12
1.
Farm income only
2.
Farm + Dairy activities
Total income from on-farm
activities alone
3.
Farm and off- farm
income
4
Farm, non-farm and
off- farm income
5.
Farm and non- farm
income
Average Annual income per
Household
Un affected Villages
Amount
Per cent
53,687
44.90
52,327
39.16
11,366
9.51
53,827
40.28
65,053
54.41
5,483
4.10
3,562
2.98
20,967
15.69
14,433
12.07
53,333
39.92
36,533
30.55
1,33,610
100.00
1,19,582
100.00
39.92
Farm Income
Farm + dairy
activities
Farm and off
farm income
Affected
Unaffected
4.3.11 Labour Migration
88
12.07
2.98
4.10
9.51
15.69
30.55
39.16
44.90
50.00
45.00
40.00
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
1.12
Percentage
Fig.28 Pattern of Income - Bhavani Taluk
Farm, non farm
and off farm
income
Farm and non
farm income
TNAU – TNSLUB Project
Introduction
From the table 4.64 it is implicit that in the affected area about 53 per cent of the
households migrated from agriculture to other non-farm activities when compared
to 20 per cent in the unaffected area. The percentage of people migrated from
the households in the affected village was 19.92 per cent which was about 10 per
cent high when compared to the unaffected area. The main reasons contributed
for this migration was poor income from agricultural activities and their interest to
earn more from the assured sources without much hard work.
Table 4.64. Migration Details
Sl.No
Particulars
1.
2.
Percentage of Migration
Percentage of migration in the sample
households
Permanent migration of the family
members
Average number of days migrated
Reasons for Migration
Poor income
To Earn more
Poor water quality
Labour problem
To pursue higher education
3.
4.
1.
2.
3.
4.
5.
Affected
Villages
53.33
19.92
Unaffected
Villages
20.00
9.25
95.00
-
296
74
65.00
45.00
27.56
20.00
20.00
4.55
95.45
-
4.3.12 Assets Position
It is observed from the table 4.65 that in the affected villages, about 15 per cent
of the respondents sold atleast part of their lands. Similarly, about 18 per cent of
the respondents sold their livestock due to various reasons like non-availability of
water, labour scarcity etc.
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Introduction
Table 4.65. Sale of Assets
Sl.
No
1.
Particulars
Affected
Villages
Unaffected
Villages
15
28
b.
c.
Percentage of respondents sold their
lands
Extent of area sold (%)
Value of sold cropland (Rs./ha)
3.12
2,98,472
8.77
2,47,915
2.
Animals
a.
Percentage of Respondents sold their
Cattle
Reasons for sale of livestock
18.33
26.67
a.
b.
Land
i
Water Scarcity
9.36
3.33
ii
Labour Scarcity
13.21
7.21
iii
iv
Drying of animals
To meet unexpected Expenses
10.00
1.67
6.67
4.33
4.3.13. Live stock Position
From the table 4.66, it is noticed that the possession of livestock was found to be
less in affected villages.
In the affected villages, the percentage of buffalo
population was high and in the unaffected area cow population was more by 18.8
per cent. Degradation of water has contributed to changes in the composition of
livestock population. It was observed that the farmers in the affected villages have
invested more in buffalo. Rearing of livestock was less because of the nonavailability of fodder due to restricted agricultural activities. Owing to the
deterioration of water quality, farmers in the affected villages had to spend more on
purchasing fodder. Majority of the farmers have largely engaged themselves in
non-farm activities as wage earners and attached only secondary importance to
agricultural occupations. Now the farmers are of the habit of allowing their livestock
to graze their own fallow croplands, which were once the promising fields for
bumper crop outputs.
90
TNAU – TNSLUB Project
Introduction
Table 4.66. Possession of Live stock
Sl.No Category
1.
2.
3.
4.
5.
6.
Cow
Buffalo
Bullock
Sheep
Calf
Poultry
(Number/household)
Affected Villages
Number
Per cent
1.18
36.98
1.57
48.96
0.02
0.52
0.33
10.42
0.02
0.52
0.08
2.60
Unaffected Villages
Number
Per cent
1.37
55.78
0.98
40.14
0.03
1.36
0.07
2.72
4.3.14. Externalities on Human and Animal Health
As stated already, the effluents discharged from the industries have affected
substantially the quality of water and soil, which in turn created disorders in
human and animal health. It could be understood from the table 4.67 that the
respondents in the affected area had to spend more than the unaffected area. In
the affected area, an average amount of Rs.100 was spent towards physician
cost and Rs.30 towards the medicine. About six per cent loss in milk production
was reported in the dairy sector. Other disorders like no calving and weight loss
were also witnessed.
Sl.No
1.
2.
1.
2.
Table 4.67. Externalities on Human and Animal Health
Particulars
Affected village
Human Health
Cost to physician (Rs/annum/household)
1200
Cost of medicine (Rs./month/household)
360
Animal Health
Loss of income from milk production (Rs./ annum)
2719
Percentage loss in milk yield
6.32
4.3.15. Opinion of Respondents about Water Quality
The respondents in the unaffected villages use their well water for drinking and
other domestic purposes whereas, their counter parts in the affected areas
depend on the public taps (municipality water). On an average people travel a
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TNAU – TNSLUB Project
Introduction
distance of about 0.52 km to fetch water. The respondents were also asked
about the deterioration in water quality in terms of taste, colour, turbidity and
odour and the results obtained are reported in Table 4.68. As noticed in other
sample villages, the quality was observed to be poor in the summer season when
compared to rainy season.
Table 4.68. Opinion of Respondents about Water Quality
Sl.No Characters
Parameters
Per cent
1.
Poor
Taste
Summer Season
medium
25
Good
75
Rainy Season
Poor
medium
25
Good
75
2.
High
Colour
Summer Season
Medium
25
Low
75
Rainy Season
High
Medium
25
Low
75
3.
High
25
Turbidity
Summer Season
Medium
Low
75
Rainy Season
High
25
Medium
Low
75
4.
High
Odour
Summer Season
Medium
Low
100
Rainy Season
High
Medium
Low
100
4.3.16. Willingness to Pay (WTP)
92
TNAU – TNSLUB Project
Introduction
The WTP of the households to pay for improving their agricultural activities and
for internalizing externalities was estimated. Majority of the households
expressed that poor income was the major hurdle affecting the ability to pay.
About 53 per cent of the farmers were willing to pay between Rs.25, 001 and
Rs.50, 000 towards internalizing externalities.
About 42 per cent were for
quarterly mode of payment, 10 per cent for half yearly mode and 15 per cent for
annual mode of payment.
Table 4.69. Willingness to Pay
Sl.No Particulars
Number
Per cent
40
66.67
Rs.20, 001-Rs.25,000
3
5.00
Rs.25, 001-Rs.50,000
32
53.33
Rs.50, 001-Rs.75,000
5
8.33
20
33.33
Quarterly
25
41.67
Half yearly
6
10.00
Annual
9
15.00
1.
Households’ willing to pay
2.
Amount
3.
Not willing to pay
4.
Mode of Payment
Fig.29 Willingness to Pay – Bhavani Taluk
93
TNAU – TNSLUB Project
Introduction
Willingness to Pay
60.00
53.33
50.00
40.00
30.00
20.00
10.00
8.33
5.00
0.00
Rs.20, 001 –Rs.25,000
Rs.25, 001 –Rs.50,000
Rs.50, 001 –Rs.75,000
Amount willing to pay
4.3.17. Averting and Defensive Expenditure
Dyeing factory effluents have made the farmers to incur the averting expenditure
on cropland and irrigation water, which is indicated in Table 4.70.
It is obvious
from the table that farmers had to spend more for banana.
Table 4.70. Averting Expenditure for Crops
Sl.No
Particulars
Expenditure Rs/ha
1.
Paddy
988
2.
Sugarcane
844
3.
Turmeric
823
4.
Banana
3705
5.
Tapioca
988
Soil and Water Sample Analysis
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TNAU – TNSLUB Project
Introduction
4.3.18. Physico – Chemical characteristics of water samples collected at
Bhavani taluk
The results of the water sample analysis of Bhavani taluk is presented in table
4.71.
Table 4.71. Physico – Characteristics of water samples collected at
Bhavani Taluk
S.No
Parameters
Affected
Unaffected
1.
pH
8.56 – 9.20
6.55 – 7.22
2.
EC (ds/m)
2.56 – 5.27
0.58 – 1.98
3.
BOD (mg/l)
96 – 170
24 – 85
4.
COD (mg/l)
235 – 425
60 – 210
5.
Chloride (mg/l)
198 – 490
85 – 147
6.
Sulphate (mg/l)
30 – 60
15 – 45
7.
Calcium
610-3650
356– 1850
8.
Magnesium
25-85
20-48
9.
SAR
32 - 37
24 - 28
10.
Chromium (mg/l)
0.25 – 0.89
BDL – 0.003
11.
Lead (mg/l)
0.14 – 0.79
BDL – 0.003
12.
Cadmium (mg/l)
0.12 – 0.48
BDL – 0.005
13.
Nickel (mg/l)
0.17 – 0.87
0.001 – 0.08
The pH of the water samples collected from affected villages of Bhavani taluk
were high (8.56 to 9.20) when compared to samples collected from unaffected
villages of same taluk (6.55 to 7.22). Samples of affected region recorded higher
EC value of 2.56 to 5.27ds/m which is much higher than the critical limit of 2.25
dsm-1 prescribed for irrigation water; It is very high when compared to unaffected
regions which recorded 0.58 – 1.98ds/m which is slightly higher than the critical
limit.
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TNAU – TNSLUB Project
Introduction
In general, the BOD values of samples from affected villages were found to be
higher recording 96 to 170mg l-1 compared to 24 to 85 mg l-1 in the unaffected
regions. The BOD values of both the regions are much higher than
recommended limit 2 mg l-1 for drinking and also 30 mg l-1 for irrigation. The COD
in affected area water samples are 235 – 425 mg l-1, which are higher than the
prescribed limit whereas in the unaffected villages it ranges between 60 and 120
mg l-1 only.
The chloride content recorded higher value of about 198 to 490 mg l-1 in the
affected regions than in the unaffected areas which recorded 85 – 147 mg l-1.
The sulphate content in the affected regions accounts to about 30 – 60 mg l.compared to 15 – 45 mg l-1 in unaffected regions. Both the chloride and
1
sulphate values of water samples of both the affected and unaffected regions are
well below the critical limits. Calcium contents of the affected samples are also
very high when compared to unaffected region samples. The water samples of
affected villages recorded 32-37 sodium absorption ratio which is well above the
critical limit and the samples of unaffected villages also recorded SAR, which is
slightly higher than the limit.
The heavy metals like chromium, lead and cadmium contents were higher in
affected areas compared to unaffected areas where they are below detectable
limits. Whereas, the water samples collected from affected regions recorded the
Cr ranging from 0.25 – 0.89, Pb ranging from 0.14 – 0.79, Cd ranging from 0.12 –
0.48 and 0.17 – 0.87 mg l-1 of Ni which are higher than the maximum permissible
limits.
4.3.19. Assessing the changes in soil properties of Bhavani taluk
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TNAU – TNSLUB Project
Introduction
The soil samples collected from the study villages of Bhavani taluk are presented
in table 4.72.
Table 4.72. Characteristics of soil samples collected at selected villages of
Bhavani taluk
Parameters
Affected
Unaffected
pH
7.70 – 8.94
6.20 – 7.12
EC (ds/m)
2.14 – 3.99
0.12 – 0.69
Available Nitrogen (kg/ha)
120 – 350
115 – 169
20 – 78
10 – 36
105 – 174
21 – 147
23 – 85
BDL
Lead (mg/kg)
1.47 – 4.25
BDL – 0.05
Cadmium (mg/kg)
1.36 – 4.78
BDL
9 - 19
0.001 – 0.07
Available Phosphorus (kg/ha)
Available Potash (kg/ha)
Chromium (mg/kg)
Nickel (mg/kg)
The soil samples collected from Bhavani recorded the highest pH in affected
regions (7.70 – 8.94) compared to unaffected regions (6.20 – 7.12).
The
EC value was also higher in samples of affected villages which recorded 2.14 –
3.99 ds/m when compared to EC values of samples of unaffected villages (0.12 –
0.69 ds/m).
The available N content higher in affected villages (120 – 350 kg/ha) which
comes under the medium rating (280 - 450kg/ha). The unaffected regions
showed values between 115 – 169 kg/ha which comes under the low rating (0 –
280 kg/ha). The available P content was ion the range of 20 – 78 kg/ha in
affected regions and in the unaffected region, it was between 10 – 36 kg/ha.
Both the samples come under high rating of >22 kg/ha. The available K content
was maximum in affected regions (105 – 174/ha) which is classified under low
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TNAU – TNSLUB Project
Introduction
rating (<280kg/ha) when compared with the unaffected villages which exhibited
an available K content of 21 – 147 kg/ha and lies in medium rating (118 280kg/ha).
In general, all the four heavy metal contents were maximum in soil samples
collected from affected villages than unaffected villages. The level of chromium
was found to be in the range of 23 -85 ppm in affected regions but it was below
detectable limit in unaffected regions. However, the chromium level of affected
villages is also well with in the critical limit of 100 ppm.
Concentration of lead in affected soil samples ranged between 1.47 – 4.25 ppm
when compared to unaffected regions which recorded BDL – 0.05 ppm, which
are well below the permissible limit 100 ppm. The heavy metal cadmium was at
higher level (1.36 – 4.78 ppm) in affected villages when compared to unaffected
villages (BDL). The affected villages contain higher values than the unaffected
villages. It exceeds the critical limit of 3.0 ppm. The soil samples of affected
villages recorded a nickel content ranged between 9- 19 ppm whereas, it was in
the range of 0.001 and 0.07 in samples of unaffected regions, which are well
within the prescribed limit of 50 ppm.
Workers
The youths in the affected villages employed themselves in the industries located
in and around the sample villages. The wage rate of the industrial units was high
when compared to the agricultural labour wage. It was reported that the work
culture was quite comfortable when compared to the agricultural activities.
4.3.20. Nature of Work
In the affected villages almost all the workers were employed in dyeing
industries. Whereas, in the unaffected area about 70 per cent of the workers earn
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TNAU – TNSLUB Project
Introduction
their wages by being in agricultural operations. About 15 per cent worked as
permanent agricultural labourers and only 15 per cent employed in spinning mills
and five per cent have run their own business and about five per cent employed
in government services.
Table 4.73. Nature of Work
Sl.No.
Nature of Work
Affected Area
Unaffected Area
1.
Dye master
30.00
-
2.
Hydropher (Dye unit)
20.00
-
3.
Supervisior (Dye unit)
5
-
4.
Labourer (Dye unit)
35
-
5.
Sampler (Dye unit)
10
-
6.
Agricultural labourers
-
55
7.
Permanent agricultural
labourers
-
15
8.
Worker in Spinning mills
-
15
9.
Petty shop owners
-
5
10.
Employed in Government
services
-
5
4.3.21. Employment
The duration of the employment and the wages earned by the sample
respondents of the workers category are presented in Table 4.74. It is revealed
that the average days of employment in the affected area are more.
Also, the
average wage earning is high in the affected area by 25.39%. This is due to the
luring employment opportunities provided by the industry to the people in the
affected area. Also, the annual income is high in the affected area when
compared to unaffected area. The employment of other family members in the
affected area shows that only 36.84 per cent were found to depend on agriculture
while it was about 87 per cent for the unaffected category.
99
Employment in
TNAU – TNSLUB Project
Introduction
private sectors was 15.79 per cent in the affected area whereas it was only 6.25
per cent in the unaffected area. The income earned by the other family members
in the affected area was found to be more by Rs.9,895 when compared to
unaffected villages.
Table 4.74. Pattern of Employment
Sl.
No.
Particulars
Affected
Area
Unaffected
Area
1.
Days of monthly employment
23.25
21
2.
Average wages earning (Rs./month)
2530
2170
3.
Number of family members working in their own
industry
0.45
-
4.
Number of family members working in other
industries
0.50
0.75
5.
Annual income of respondents (in Rs.)
30,360
24,211
Employment of the Family Members
1.
Dyeing
47.37
-
2.
Agricultural labourers
36.84
87.5
3.
Private company
15.79
6.25
4.
SHG
-
6.25
4.3.22. Benefits Availed by the Workers
The nature of benefits enjoyed by the workers of the private companies is given
in Table 4.75. About 11 per cent has availed accident claims and that too for the
accidents that happened in the work spot. About 89 per cent enjoyed the benefit
of availing bonus. This benefit was extended to the workers based on their
experience. An average of Rs.740/- was given as bonus to celebrate pongal
festival. Other benefits like medical, ESI, and provident fund are not extended to
the workers in this study area.
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Introduction
Table 4.75. Benefits Availed by the Workers
Sl.No
1.
2.
Benefits
Accident claims
Bonus
Per cent
11.11
88.89
4.3.23. Sufferings Faced
About 20 per cent of workers were suffering from skin related ailment and
tuberculosis (TB).
The TB patients are undertaking free treatment. Some
patients are undergoing treatment at their own cost by spending about Rs.250
towards physician and Rs.300 towards medicine per month.
Other acute
problems like cracks, boils, itching, skin rashes are also reported throughout the
year. On an average, an individual spends about Rs.40 and Rs.56.67 towards
physician cost and medicine cost per annum. About 40 per cent reported for no
illness. The results are presented in Table 4.76 below.
Table 4.76. Sufferings Faced by the Respondents
Sl.No
1.
2.
3.
4.
5.
6.
7.
Particulars
Skin Cracks
Boils, itching, etc.
Skin rashes
No problem
Working days lost
Cost to physician (Rs/annum)
Cost of medicine (Rs/annum)
Affected (Per cent)
35
20
5
40
Nil
40
56.67
4.4. Erode
4.4.1. Family Size
The details on total number of persons and the overall family size are presented
in Table 4.77. The overall size of family was 3.86. Between the two categories,
the average family size was found to be relatively high at 3.93 for the unaffected
category as compared to 3.78 for the affected groups.
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Introduction
Table 4.77. Family Size
Sl. No.
1.
2.
Category
Respondents
Affected area
Unaffected area
Overall
(Numbers)
Family Size
of
3.78
3.93
3.86
4.4.2. Education
In the affected and unaffected villages, 20 per cent and 22 per cent of the sample
respondents were observed to be illiterates, respectively (Table 4.78). Mainly the
elders of the households were observed to be illiterates. About 30 per cent had
primary education in the affected villages, which was higher by 4.11 per cent
when compared to the respondents in unaffected area. Only 26.87 per cent and
6.62 per cent of the affected villages were observed to have secondary and
higher secondary education. About 17 per cent of households in the affected
villages was reported to hold a diploma and / or degrees.
This was marginally
higher than that of the unaffected category.
Table 4.78. Educational Status
Sl.
No.
Affected Area
Particulars
Unaffected Area
Numbers
Percentage
Numbers
Percentage
1.
Illiterates
45
19.82
52
22.03
2.
Primary
68
29.96
61
25.85
3.
Secondary
61
26.87
74
31.36
4.
Higher
Secondary
15
6.62
19
8.05
5.
Graduates
38
16.73
30
12.71
227
100.00
236
100.00
Total
4.4.3. Land Holding Pattern
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TNAU – TNSLUB Project
Introduction
The land area possessed by individual household and area under cultivation are
presented in Table 4.79.
Table 4.79. Land Holding Details
(in ha)
Type of land
Wet
Garden
Dry
Total
Affected Area
Area
Area
Owned
Cultivated
0.94
0.89
(55.91)
(58.84)
0.59
0.55
(35.07)
(36.25)
0.15
0.07
(9.02)
(4.92)
1.68
1.51
(100.00)
(100.00)
89.58
Percentage of crop land
under cropping
Figures in parentheses indicate percentage
Unaffected Area
Area
Area
Owned
Cultivated
0.58
0.58
(31.51)
(31.51)
1.22
1.22
(66.30)
(66.30)
0.04
0.04
(2.19)
(2.19)
1.85
1.85
(100.00)
(100.00)
100.00
It may be seen from the table that the average size of land possessed by the
sample households in the affected village was 1.68 ha which less by 0.17 is ha
than the unaffected category with 1.85 hectares.
In the affected areas, the
average size of the area owned was1.68 ha of which only 1.51 ha was under
crops, compared to
1.85 ha in unaffected regions. As discussed already,
the effluents had created changes in the cropping pattern and employment
opportunities.
4.4.4. Well Irrigation
The irrigation canals namely Kalingarayan, Lower Bhavani Project Canal and
Perumpallam Oodai are the major sources of irrigation.
As the quality of the
water has deteriorated, now the respondents are relying on open wells and bore
103
TNAU – TNSLUB Project
Introduction
wells for irrigation. In wetlands, the ground water level ranges between 5 metres
and
15.3 metres whereas in garden lands the depth ranges between 15.3
metres and 36.33 metres. The total number of wells in the sample farms was 42
and 48 in the affected and unaffected villages, respectively. The depth of well
was 1.54 metres more in the affected areas. Only about 52 per cent of the wells
in the affected villages were found to have water throughout the season. The
number of bore wells in the unaffected villages was about two times high when
compared to the affected villages. However, none of the wells was abandoned.
In the affected villages only 2.5 per cent of the respondents perceived that the
quality of the well water was medium and the rest perceived it to be poor. In the
unaffected area, about 70 per cent perceived that their well water was of medium
quality.
Table 4.80. Well Irrigation
Sl.
No.
Particulars
Affected
Villages
Unaffected
Villages
42
48
16.50
15.00
1.
Number of wells
2.
Average depth of open well (in mts.)
3.
Percentage
throughout**
water
52.38
83.33
4.
Percentage of well with water in rainy
season**
47.62
16.67
5.
Number of bore wells in sample farms
13
28
6.
Average depth to bore wells (mts.)
200
94.34
(Per cent)
( Per cent)
-
-
Medium
2.50
70.73
Poor
97.50
29.27
7.
of
well
with
*
Water quality
Good
* As perceived by the respondents.
** Percentage calculated upon the total number of wells in the sample farms
4.4.5. Sources of Irrigation
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Introduction
It is implicit from the table 4.81 that in the affected locality area irrigated by canal
has declined by about 24 per cent.
The area irrigated by wells has marginally
increased by about six per cent during the year 2004-05. In the unaffected area,
the overall area under irrigation has increased. In both the study villages the
main source of irrigation was found to be canal and open wells.
In the
unaffected areas, bore wells have started gaining importance as 2.77 and 23.36
per cent area were being irrigated by bore well alone and by the bore wells and
open wells together, respectively. While the rainfed area declined substantially in
unaffected area, it increased by about 22 per cent in the affected area.
Table 4.81. Sources of Irrigation
Sl.
No.
Particulars
Affected Area
(Percentage)
Unaffected Area
(Percentage)
10
years
back
2004-05
10
years
back
2004-05
1.
Canal
66.30
42.72
39.48
11.07
2.
Open well
15.87
21.46
43.22
43.41
3.
Canal + Open well
-
14.18
-
16.22
4.
Bore well
-
-
-
2.77
5.
Open well + Bore well
-
-
-
23.36
Total Irrigated Area
82.17
78.36
82.70
96.83
Rain fed area
17.83
21.64
17.31
3.17
6.
Fig. 30 Sources of Irrigation – Erode Taluk
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TNAU – TNSLUB Project
Introduction
Sources of Irrigation
50
42.72
43.41
40
30
23.36
21.46
20
21.64
16.22
14.18
11.07
10
3.17
2.77
0
0
0
Canal
-10
Open well
Canal + Open
well
Bore well
Open well + Rain fed area
Bore well
Affected Villages
Sources of Irrigation
Unaffected Villages
4.4.6. Area and Productivity – A Detailed Analysis
The area and productivity of crops grown in the study area are reported in Table
4.82. In the affected area, the area under paddy declined by about ten per cent.
The main crops grown ten years back were paddy, fodder cholam, sugarcane,
banana, gingelly, turmeric, coconut, cotton and vegetables. Though the area
under coconut increased over years the productivity has comedown by 9500
nuts/ha. Also, new crops like daincha and mango were included in the cropping
pattern recently.
The reason for the productivity decline was due to poor soil and water qualities.
The farmers were unable to make much profit in agriculture and they had started
doing non-farm activities like undertaking job works in textile factories and
employing themselves as wage earners in the private companies.
Table 4.82. Area and Productivity of Crops
106
TNAU – TNSLUB Project
Sl.
No
Crops
Introduction
Affected Area
Unaffected Area
Difference
Area
(%)
Yield
Area
(%)
Yield
Yield
Percen
tage
1.
Paddy
55.36
5.06
57.67
5.78
(-)0.72
()12.46
2.
Fodder
Cholam
25.67
6.17
3.17
6.92
(-)0.75
()10.84
3.
Sugarcane
1.53
80.28
2.21
104.45
()24.17
()23.14
4.
Banana
0.77
86.45
-
-
-
-
5.
Gingelly
3.07
0.60
15.66
1.80
(-)1.20
()66.67
6.
Turmeric
1.53
3.21
0.95
4.32
(-)1.11
()25.69
7.
Coconut*
7.85
13675
4.74
26346
(-)
12671
()48.09
8.
Cotton
-
-
0.63
0.90
-
-
9.
Cholam
-
-
2.63
4.06
-
-
10.
Groundnut
0.38
0.72
8.54
1.86
(-)1.14
()61.29
11.
Tapioca
-
-
3.80
23.05
-
-
12.
Mango
2.07
-
-
-
-
-
13.
Daincha
0.77
1.24
-
-
-
-
* Yield in tons/ha except Coconut (nuts/ha.)
107
TNAU – TNSLUB Project
Introduction
Fig. 31 Crop Area and Productivity – Erode Taluk
Crop Area and Productivity
120.00
104.45
Affected villages
Unaffected villages
100.00
80.28
80.00
60.00
40.00
23.05
20.00
5.06
5.78
6.17 6.92
3.21
4.32
0.00
0.00
Paddy
Fodder Cholam
Sugarcane
Turmeric
Tapioca
Crops
4.4.7. Farmers Opinion about Decline in Agricultural Activity
It could be seen from the table 4.83 that almost the entire group in the affected
categories expressed the scarcity of water as the main reason for the decline in
agriculture.
About 84 per cent were of the view that poor water quality was the
main reason for the weak performance of agriculture.
Similarly, 78.33 per cent
attributed labour scarcity as the prime reason for the poor agricultural operations.
Many found it difficult to get labour for the agricultural activities, as the
agricultural laborers had migrated to the nearby industries. About 57 per cent of
farmers in the affected category reported decline in agricultural income as one of
the factors that led to sluggishness in agricultural activities.
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Introduction
Table 4.83. Opinion of Sample Farmers towards Decline in Agricultural
Activities
(Per
cent)
Sl.No.
Particulars
Affected
Category
1.
Water scarcity
100.00
2.
Labour scarcity
78.33
3.
Poor water quality
83.33
4.
Decline in agricultural income
56.67
5.
Poor crop stand
58.33
Fig. 32 Farmers Opinion towards decline in Agricultural Activities - Erode Taluk
Fa rme rs opinion towa rds de cline in Agricultura l Activitie s
100.00
100.00
83.33
78.33
80.00
60.00
56.67
58.33
Decline in
agricultural
income
Poor crop stand
40.00
20.00
0.00
Water scarcity
Labour scarcity
Poor water
quality
Affe cte d ca te gory
4.4.8. Changes in Value of Agricultural Lands
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TNAU – TNSLUB Project
Introduction
The details on the changes in the value of agricultural land as perceived by the
respondents of the study villages are presented in Table 4.84.
Table 4.84. Changes in Value of Agricultural Lands
(Rs./ha)
Sl.No.
Particulars
Affected Area
Unaffected
Area
1.
10 years back
4,72,000
9,97,674
2.
2004-05
11,17,000
12,73,079
3.
Change in value of land
(per cent)
136.65
27.60
A close examination of Table 4.84 reveals that the percentage increase in the
affected area in the last 10 years was about 136 per cent whereas it is only 27.60
per cent in the unaffected area. This huge increase noticed in the affected area
might be due to the gaining importance of industries. The agricultural lands are
getting converted into industries or as house sites.
Moreover in one of the
affected village (S.P.Agraharam) farmers are selling their wetlands to the
government @ Rs. 4, 00,000 for the construction of EB barrage.
4.4.9 Employment Pattern
The particulars of employment of the households in the study area are given in
Table 4.85. The total number of workers was found to be more by about 23 per
cent in the affected study villages. Only 1.67 per cent of the sample households
depended only on agriculture in the affected villages whereas it was about 20 per
cent in the unaffected villages. In the affected areas, a vast majority of about 32
per cent depended on on -farm, non-farm and off-farm activities like agriculture,
agricultural labourers, dairy, money lending, employing in private companies as
wage earners etc.
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TNAU – TNSLUB Project
Introduction
Table 4.85 Occupational Distribution of Households
Sl.No
Affected Area
Number
Per cent
s
1
1.67
Particulars
1.
Farm only
2.
Farm + Dairy activities
Total Households engaged in
on-farm activities alone
3.
On - farm + Non-farm
activities
4.
Farm + Off-farm activities
5.
Farm + Non-farm and
Off-farm activities
Total
Earning members in Sample
Households (in numbers)
Unaffected Area
Numbers Per
cent
12
20.00
3
5.00
5
8.33
4
6.67
17
28.33
26
43.33
26
43.33
11
18.33
2
3.33
19
31.67
15
25.00
60
100.00
60
100.00
124
110
25.00
3.33
10.00
8.33
20.00
5.00
30.00
18.33
20.00
40.00
1.67
Percentage
50.00
31.67
60.00
43.33
48.33
Fig.33 Occupational Distribution of Households - Erode
Taluk
0.00
Farm only
Farm + dairy
activities
On farm + non
farm activities
Affected
Farm + off farm Farm + non farm
activities
and off farm
activities
Unaffected
4.4.10 Income Distribution
The income distribution of the household is given in the Table 4.86.
Only one
per cent of the households income came through farm activity in the affected
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TNAU – TNSLUB Project
Introduction
area as against 16.57 per cent in the unaffected area.
Income from farm
activities overall constituted 5.30 per cent in affected villages as against 34.89
per cent in unaffected villages. In the affected villages, about 55 per cent of the
income came from the combined activities of on-farm and non-farm whereas it
was relatively less at 42 per cent in the unaffected villages.
Table 4.86 Pattern of Annual Income in Sample Household
S.No
Particulars
1.
2.
Farm only
Farm + Dairy activities
(in Rs.)
Unaffected Area
Amount Per cent
Affected Area
Amount
Per
cent
1,166
1.00
5,000
4.30
Income
from
on-farm
activities alone
3.
Farm + Off-farm
4.
On-farm + Non-farm
5.
Farm + Non and Offfarm
Average Annual Income per
Household
16,209
17,917
16.57
18.32
6,166
5.30
34,126
34.89
16,500
63,375
30,242
14.19
54.50
26.01
1,512
41,109
21,061
1.55
42.03
21.53
1,16,283
100.00
97,808
100.00
54.50
Fig.34 Pattern of Income - Erode Taluk
14.19
1.55
10.00
18.32
20.00
4.30
16.57
30.00
26.01
40.00
1.00
Percentage
50.00
21.53
42.03
60.00
0.00
Farm only
Farm + dairy
income
Affected
On farm + non
farm income
Unaffected
112
Farm + off farm
income
Farm + non farm
and off farm
income
TNAU – TNSLUB Project
Introduction
4.4.11. Migration
It is implicit from the table 4.87 that in the affected areas about 58 per cent of the
households were found to migrate when compared to 30 per cent in unaffected
area. Percentage of the earning members migrated from the sample households
in the affected villages was 33.05 per cent and it was 3.5 per cent more than the
average migration in the unaffected area. Over 68 per cent of the labour force
had migrated permanently. The main reason attributed for the migration was to
earn more and also due to the poor income from the agricultural operations.
Table 4.87. Migration
Sl.No
Particulars
Affected
Area
Unaffected
Area
1.
Percentage of Households migrated
58.33
30.00
2.
Percentage of migration from sample
household
33.05
29.54
3.
Percentage of permanent migration of
the family members
68.33
15.00
4.
Number of days migration
164
87
Reasons for migration
1.
Poor income
54.29
100.0
2.
To Earn more
71.43
50.00
4.4.12. Asset Position
It is obvious that over 16 per cent of the respondents in the affected area had
disposed atleast 3.43 per cent of their cropland due to poor water quality and labour
scarcity. In the affected villages, 31.67 per cent of the respondents had sold their
livestock due to various reasons like poor water quality, water and labour scarcity. In
the affected villages however, the extent of land area disposed off was higher (11.69
per cent) and the respondents selling livestock was marginally lower (23.33 per
cent).
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TNAU – TNSLUB Project
Introduction
Table 4.88.
Sale of Assets
Sl.No
Particulars
I.
1.
Sale of Land
Percentage of Respondents
sold land
Average land area sold (ha)
Percentage of land sold
Value of the sold area (Rs./ha)
Sale of Animals
Percentage of Respondents
sold animals
Value of animals sold (Rs)
Reasons for sale of livestock
Poor Water Quality
Water Scarcity
Labour Scarcity
Drying / Aged animal
To meet out unexpected
expenses
2.
3.
4.
II.
1.
2.
III
a.
b.
c.
d.
e.
Affected
Village
Un affected
Village
16.67
26.67
0.34
3.43
2,16,488
0.37
11.69
9,62,448
31.67
23.33
14,095
1,407
11.67
10.00
6.67
3.33
-
1.67
8.33
10.00
1.67
1.67
4.4.13. Farm Level Availability of Livestock
The possession of livestock was found to be less particularly with respect to cow,
buffalo and sheep (Table 4.89).
Though the number of livestock possessed
seemed to be high in affected villages, the average possession was similar in
both cases. This was because the water in the river, community tank and well
were polluted and it affected the very basic original characteristics and the fertility
of the soil due to the accumulation of effluents in and around the affected
villages. It was observed that the farmers invested more in buffalo (than cow) in
the affected area.
The number of bullocks owned by the farmers was also
significantly less due to partial farm mechanization and poor agricultural
activities.
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TNAU – TNSLUB Project
Introduction
Owing to the poor land and water qualities, farmers had to spend more on
purchasing fodder from outside and more time in maintenance of animal’s viz.,
cows, buffaloes, goats, sheep, etc.
Majority of the farmers in the affected
villages were engaged in non-farm activities like undertaking job works and
attached only secondary importance to agricultural occupation.
Table 4.89. Possession of Livestock
(Number /
household)
Sl.No.
Category
Affected
Unaffected Villages
Villages
1.
Cow
0.58
0.50
2.
Buffalo
1.47
0.48
3.
Bullock
0.03
-
4.
Sheep
0.03
0.55
5.
Calf
0.05
0.03
4.4.14. Externalities on Human and Animal Health
The effluents discharged from the industries have affected the quality of water
and soil, which in turn had created disorder in animal and human health. The
results on externalities on human and animals health are reported in Table 4.90.
It could be seen that the respondents apply coconut oil and salt mix on the
infected area to heal the wounds caused by dyes. General problems like cracks,
boils, skin irritation and wheezing were witnessed.
The respondents in the
affected area spent on an average about Rs.125/- towards the cost of medicine.
Expenses towards physician are not reported. About 6.25 per cent loss
(Rs.1,759) in milk production was observed in animals. Besides, reduction in
weight and decline in reproduction rate were also noticed in animals.
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Introduction
Table 4.90. Externalities on Human and Animal Health
Sl.No.
I
Particulars
Affected Villages
Humans
1.
Cost of medicine (Rs. / annum)
125
2.
Cost to Physician (Rs./ annum)
-
II
Animals
1.
Loss of milk Yield (Rs./ per annum)
1,759
2.
Per centage loss in milk production
6.25
4.4.15. Opinion of Respondents about Well Water Quality
The respondents in the affected villages use well water and public tap for
drinking purposes.
Whereas the sample households of unaffected areas use
only well water. On an average, they travel about 0.32 km/day to fetch drinking
water. The respondents were also asked about the deterioration in water quality
in terms of taste, colour, turbidity and odour. Their responses are reported in the
Table 4.91.
Table 4.91. Opinion of Farmers’ on Well Water Quality
Sl.No. Water Quality Characters
1.
Taste
Poor
Medium
Good
2.
Colour
High
Medium
Low
3.
Turbidity
High
Medium
Low
4.
Odour
High
Medium
Low
Summer Season
97.50
2.50
45
55
97.50
2.50
100.00
-
116
Rainy Season
70.00
30.00
45
55
97.50
2.50
100.00
-
TNAU – TNSLUB Project
Introduction
4.4.16. Willingness to Pay (WTP)
The willingness of the household to pay for the expenses towards improving
agricultural land and water quality was estimated and reported in Table 4.92.
About 58 per cent were willing to pay a minimum of Rs.25, 000 and a maximum
of Rs.60, 000.
Majority of the household expressed that poor income was the
major constraint affecting their ability to pay. A vast majority of about 74 per cent
of the sample household were willing to pay between Rs.25, 001 and Rs.50, 000.
About
23 per cent were willing to pay between Rs.50, 001 and Rs.75, 000.
None were interested to pay more than Rs.75, 000. While 85.71 per cent opted
for the quarterly mode of payment and only 2.86 per cent preferred monthly
payment.
Table 4.92. Willingness to Pay
Sl.No.
Particulars
Number
Per cent
1.
Household willing to pay
35
58
2.
Household not willing to pay
25
42
3.
Amount of WTP
Rs.20, 001 – Rs.25,000
1
2.89
Rs.25,001 – Rs.50,000
26
74.29
Rs.50, 001 – Rs.75,000
8
22.86
Monthly
1
2.86
Quarterly
30
85.71
Half yearly
1
2.86
Annual
3
8.57
35
100.00
4.
Mode of payment
Total
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TNAU – TNSLUB Project
Introduction
Fig. 35 Willingness to Pay – Erode Taluk
Willingness to Pay
80
70
60
50
40
30
20
10
0
74.29
22.86
2.89
Rs.20, 001 –Rs.25,000
Rs.25, 001 –Rs.50,000
Rs.50, 001 –Rs.75,000
Amount willing to pay
4.4.17. Averting Expenditure
The dyeing factory effluents made the farmers to incur additional expenditure on
cropland. From the table 4.93 it could be observed that the farmers had to spend
a major share on soil amendments by applying FYM (Farm Yard Manure). A
farmer cultivating paddy and cholam had to spend on an average over Rs.919
and Rs.468 per ha respectively towards averting expenditure for extra seeds,
organic manure etc.
No additional expenditure was made on irrigation and
drinking water.
Table 4.93. Averting Expenditure for Crops
Sl. No.
Crops
Expenditure Rs./ha
1.
Paddy
919
2.
Cholam
468
118
TNAU – TNSLUB Project
Introduction
Soil and Water Sample Analysis
4.4.18. Physico – Chemical characteristics of water samples collected at
Erode taluk
In Erode taluk, water samples were collected from the affected and unaffected
villages and the results are presented in the table 4.94.
The water samples taken from Erode district recorded a pH of 8.60 to 9.26 in
affected regions compared to a pH of 7.12 to 8.01 in unaffected regions. The EC
value was high in affected area recording 2.98 to 5.55ds/m compared to
unaffected area which recorded about 1.12 to 2.36 ds/m.
The EC value of
affected samples indicated its unsuitability for irrigation.
The water samples of affected region recorded a maximum BOD of about 80 to
140 mg l-1 compared to about 27 – 67 mg l-1 in unaffected regions. These values
are much higher than the maximum permissible limits. Maximum COD level of
200 – 350 mg l-1 was recorded in water samples of affected regions which
exceeds the permissible limit and a low COD value was recorded in unaffected
regions (70 to 170 mg l-1).
The chloride (225 to 490 mg l-1) and sulphate contents (28 –65 mg l-1) were
maximum in water samples of affected villages of Erode taluk than the samples
collected from unaffected villages which recorded 95 to130 mg l-1 and 25 – 58
mg l-1 of chloride and sulphate respectively, which are below the critical limits of
500 and 1000 mg l-1 respectively. The calcium content in affected villages was
found to be 410-3150mg l-1 and 245– 2150 mg l-1 in the unaffected villages. Both
the regions exceed to a greater extent when compared with critical limit of 100
mgl-1. The magnesium content ranges from 35 – 80 mg l-1 in affected regions and
15-52 mg l-1 in unaffected regions. Both the regions fall with in the critical limit of
119
TNAU – TNSLUB Project
Introduction
150 mg l-1. The SAR of affected and unaffected samples were in the range of 28
– 36 and 20 -24 respectively.
The heavy metals like chromium, lead, nickel and cadmium contents were found
to be higher in affected areas compared to unaffected areas. The water samples
of affected region recorded the Cr level ranging from BDL – 0.96 mg l-1, Pb of
BDL –0.58 mg l-1, Cd of BDL – 0.11 mg l-1 and 0.10 – 0.88 mg l-1 of Ni. All the
metal contents exceeded their respective critical limits. Whereas, the water
samples collected from unaffected regions have higher levels of lead and nickel
exceeding the critical limits but the level of chromium and cadmium are very less
when compared to the limits.
Table 4.94. Physico – Characteristics of water samples collected at Erode
Taluk
S.No
1.
2.
3.
4.
5.
6.
7.
8.
9.
10..
11.
12.
13
Parameters
pH
EC (ds/m)
BOD (mg/l)
COD (mg/l)
Chloride (mg/l)
Sulphate (mg/l)
Calcium (mg/l)
Magnesium (mg/l)
SAR
Chromium (mg/l)
Lead (mg/l)
Cadmium (mg/l)
Nickel (mg/l)
Affected
8.60 - 9.26
2.98 - 5.55
80 – 140
200 – 350
225 – 490
28 – 65
410-3150
35 - 80
28 - 36
BDL – 0.96
BDL –0.58
BDL – 0.11
0.10 – 0.88
Unaffected
7.12 – 8.01
1.12 – 2.36
27 – 67
70 – 170
95 – 130
25 – 58
245– 2150
15-52
20 -24
BDL
BDL – 0.23
BDL – 0.004
BDL – 0.26
4.4.19. Assessing the changes in soil properties of Erode taluk
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TNAU – TNSLUB Project
Introduction
The soil samples collected from the study villages of Erode taluk are presented in
table 4.95.
The soil samples taken from Erode taluk recorded a higher pH of about 7.96 to
8.99 in affected regions compared to unaffected regions (6.50 to 7.56). The EC
was also higher in affected regions (2.58 to 4.57ds/m) when compared to
unaffected regions which recorded 0.12 to 1.57ds/m.
The available N was found to be higher in affected regions (214 – 440 kg/ha) and
this comes under medium rating (280 – 450 kg/ha). In the unaffected regions the
values ranged between 105 and 245 kg/ha which is classified under low rating (0
– 280 kg/ha). The available P content in affected regions was about 10 – 25
kg/ha which according to the standard limit comes under high rating (>22 kg/ha)
and unaffected region samples recorded 10 – 19 kg/ha of available P which is
classified under medium rating. Similarly, the available K content accounts for
higher value in affected regions (122 – 247 kg/ha) whereas, the unaffected
villages recorded between 12 – 156 kg/ha of available K, which comes under
medium rating (118-280 kg/ha).
Table 4.95. Characteristics of soil samples collected at selected villages of
Erode taluk
Parameters
Affected
Unaffected
pH
7.96 – 8.99
6.5 – 7.56
EC (ds/m)
2.58 – 4.57
0.12 – 1.57
Available Nitrogen (kg/ha)
214 – 440
105 – 245
Available Phosphorus (kg/ha)
10 – 25
10 – 19
Available Potash (kg/ha)
122 – 247
12 – 156
Chromium (mg/kg)
27 – 84
BDL
Lead (mg/kg)
1.58 – 74
BDL – 0.06
Cadmium (mg/kg)
1.20 – 3.26
BDL – 0.003
Nickel (mg/kg)
9 - 65
0.001 – 0.09
The chromium content in the affected regions was (27 – 84 ppm) when
compared to the unaffected regions which is below detectable levels (BDL). Both
the regions do not exceed the critical limit of 100 ppm. The heavy metal lead
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TNAU – TNSLUB Project
Introduction
accounts for about 1.58 – 74 ppm in affected regions when compared to
unaffected regions ranging from BDL – 0.06 ppm. Both he samples lies within
the standard limit of 100 ppm.
Cadmium concentration was higher (1.20 – 3.26 ppm) in soil samples from
affected villages and it was in the range of BDL – 0.003 ppm in unaffected
regions and they are well within the critical limit of 3.0 ppm. The samples of
affected villages recorded maximum nickel content that ranged between 9 –
65mg/kg, which are above the critical limit of
50 ppm than the samples of
unaffected villages which recorded 0.001 – 0.09mg/kg of nickel.
Workers
A vast majority of the workers interviewed in this taluk were employed in private
factories located in and around Erode.
They preferred working in dyeing
industries rather than employing in agricultural activities because of the relatively
high wage rate and less drudgery. It was also reported that mobilization of fund
is easy for those who go for a salaried job than those who take up agriculture, at
times of crisis.
4.4.20 Distribution of Labour Force
The distribution of industrial labourers is presented in Table 4.96.
All the
labourers interviewed were found to work in private companies for various
activities ranging from cashier or supervisor to sweeper on weekly wage basis.
Only 15 per cent were found to be employed as labourers in agricultural activities
in the unaffected areas.
Table 4.96. Nature of Work
122
TNAU – TNSLUB Project
Sl.No
Nature of Work
Introduction
Affected Area
Unaffected Area
Number
Per cent
Number
Per cent
1.
Dye Master
3
15
6
30
2.
Dye Mixer
2
10
-
-
3.
Supervisor
1
5
2
10
4.
Hydropher
2
10
1
5
5.
Winch runner
1
5
-
-
6.
Unskilled Labour
4
20
5
25
7.
Cashier
1
5
-
-
8.
Office assistant
1
5
-
-
9.
Agricultural
labourer
-
-
3
15
10.
Mason
5
25
1
5
11.
Handloom worker
-
-
2
10
4.4.21. Employment of Workers
The duration of employment and the wages earned by the sample respondents
of the worker category are presented in Table 4.97.
It is revealed that the
average days of employment per month in the affected villages were marginally
less.
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Introduction
Table 4.97. Employment Particulars
Sl.No
Particulars
Affected
Area
Unaffected
Area
1.
Man days of employment in farm
operations
21.95
23.75
2.
Number of family members working
in dying unit
0.25
0.15
3.
Number of Family members working
in other dyeing factories
0.65
0.90
Annual Income of Head of the Worker Family
(in Rs.)
1.
Dye Master
38,000
43,750
2.
Dye Mixer
27,000
-
3.
Supervisor
42,000
54,000
4.
Hydropher
30,000
36,000
5.
Winch Runner
30,800
-
6.
Unskilled Labour
52,400
21,000
7.
Cashier
36,000
-
8.
Office Assistant
30,000
-
9.
Agricultural Labourer
-
28,200
10.
Mason
26,000
30,000
11.
Handloom labour
-
23,250
Employment of other Family Members (Percentage)
1.
Dye Master
17.65
-
2.
Labour in dyeing units
17.65
5.00
3.
Unskilled labourers
35.29
70.00
4.
Tailor
5.88
-
5.
Mason
23.52
5.00
6.
Handloom worker
-
15.00
7.
Supervisor
-
5.00
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TNAU – TNSLUB Project
Introduction
4.4.22. Benefits Availed
About 20 per cent of the workers had availed claims over accidents that occurred
during working. Forty per cent of the workers in the affected area were covered
under ESI while, it was only 10 per cent in the unaffected area. The details are
reported in Table 4.98.
Table 4.98. Benefits Availed by Workers
S.No
1.
2.
3.
4.
Particulars
Accident claims
Medical Benefits
ESI enrollment
Bonus
Affected Area
20
40
75
(Per cent)
Unaffected Area
5
15
10
30
4.4.23. Sufferings Faced by the Respondents
It is implicit from the table 4.99, that no chronic illness was reported by any of the
respondents. However, about ten per cent of the respondents reported that they
had to suffer often from skin irritation and ulcer. About five per cent reported to
suffer from skin cracks, stomach pain, indigestion problem and hair fall.
A
majority of 60 per cent opined that they did not encounter any major health
related problems except some minor problems like skin irritation, etc.
Table 4.99 Sufferings Faced by the Respondents
(Per
cent)
Affected Area
10
5
5
5
5
10
60
Sl.No
Particulars
1.
Skin Irritation
2.
Cracks
3.
Stomach Pain
4.
Digestion problem
5.
Hair fall
6.
Ulcer
7.
No problem
4.4.24 Particulars of Drinking Water
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Introduction
The Industrial labourers used to get water from both public taps as well as from
open and bore wells. To fetch water from the public tap, they had to travel on an
average a distance of about 0.67 km. They spent about 53 minutes per day to
fetch water. The labourers used to get water daily in the village Periasemur
whereas it was supplied once in two days in S.P.Agraharam. In the unaffected
villages, water was supplied daily and five of the respondents had their own
connections.
Table 4.100. Sources of Drinking Water
(Number)
S.No
Particulars
1.
Well + Public pipe
2.
Well + Own tap
3.
Distance Travelled (km)
4.
Time (min/day)
Affected
Unaffected
Area
Area
20
15
-
5
0.67
0.63
53
39
4.5 Damage Function
4.5.1 Yield Damage (Agricultural)
Agricultural yield damage was estimated for the following households and the
results are presented in Table 4.101. From the table it could be inferred that 57
per cent of variation in agricultural yield damage was contributed by averting
input expenditure to land, proximity of cropland to dyeing or bleaching industries,
water quality and land qualities. Land quality, water quality and proximity to
dyeing or bleaching industries have significant influence on agricultural yield
damage and the impact is found to be negative. If the land quality index shifts
from poor to medium, agricultural yield damage decreases by Rs.2932.49/ha and
if proximity of cropland to industries increases by one km, the agricultural yield
damage decreases by Rs.2961/ha.
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Introduction
Table 4.101 Estimates of Yield Damage Function
S.No
Variable
Co-efficient
t-ratio
20909.92
15.096**
1.
Constant
2.
Averting Expenditure
-0.2711
-1.052
3.
Land Quality
-2932.49
-3.495**
4.
Water Quality
-594.38
-2.192*
5.
Proximity
-2960.89
-3.476**
2
R = 0.57,
4.5.2
* significant at five per cent,
** significant at one per cent level
Aggregate Damage Function
The results of the aggregate damage function for the household is presented in
Table 4.102.
One could observe from the table that 32 per cent of aggregate
damage was influenced by independent variables like averting expenditure on
drinking water, human health, water quality and proximity of cropland to dyeing or
bleaching industries. Influence of averting expenditure on human health and
water quality was found to be negative. When water quality shifts from poor to
medium aggregate damage will reduce by Rs.240 per household.
Table 4.102. Estimates of Aggregate Damage Function
Sl.No
Variable
Co-efficient
t-ratio
1.
Constant
3817.64
8.37**
2.
Averting Expenditure on Drinking Water
-0.5363
-1.316
3.
Averting Expenditure on Human Health
-4.2791
-3.649*
4.
Water Quality
-240.03
-3.418**
Proximity of Cropland to Industries
-82.03
-0.250
5.
2
R = 0.32,
* significant at five per cent, ** significant at one per cent level
4.5.3. Hedonic Model
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A Hedonic model was employed to estimate the influence of land quality, water
quality, proximity of cropland to industries, cropping intensity and share of
cropped area to total farmland area on the value of cropland and the influence
was found to be 52 per cent. The results presented in the Table 4.103, shows
that water quality, proximity of cropland to dyeing / bleaching industries and
share of cropped area have significant influence on value of cropland with
proximity and share of cropped area having negative impact. When the proximity
to the dyeing or bleaching industry increases by one kilometre, value of cropland
decreases by Rs.10, 265 per ha. This is because of reduction in the impact of
pollution on farmland and water quality parameters and that is the reason why
the crop land close to industries fetches low price than the agricultural land at a
distance.
Table 4.103. Estimates of Hedonic Model
Sl.No
Variable
Co-efficient
t-value
1.
Constant
3670.12
0.461
2.
Land Quality
179.19
0.058
3.
Water Quality
903.31
-5.194**
4.
Proximity to Industries
-10265.22
-4.196**
5.
Cropping Intensity
-86.02
-0.574
Share of Cropped area
-269.01
-5.440**
6.
2
R = 0.52,
** significant at one per cent level
4.5.4. Land Averting Expenditure Model
The results of land averting expenditure model is presented in Table 4.104. It is
revealed that 53 per cent of variation in land averting expenditure was explained
by independent variables like farm size, education, share of cropped area to total
farm land area, proximity of cropland to industries, land quality, quantity of
organic manure applied, awareness on environmental externalities and water
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quality.
Introduction
Land averting expenditure was significantly influenced by household
education, quantity of organic manure applied and water quality. Among the
variables, farm size, proximity to dyeing / bleaching industries, land quality,
quantity of organic manure applied and water quality
averting expenditure significantly.
did not influence the
Increase in one tonne of organic manure per
ha results in decrease of land averting expenditure by Rs. 553 per ha.
Table 4.104. Estimates on Land Averting Expenditure Model
Sl.No
Variable
Co-efficient
t-value
1.
Constant
2175.26
1.203
2.
Farm Size
-12.198
-0.073
3.
Household Education
554.811
3.353**
4.
Share of cropped area
7.634
0.932
5.
Proximity of Cropland to Industries
-295.591
-0.787
6.
Land Quality
-187.673
-0.476
7.
Quantity of organic manure
-552.966
-2.539*
8.
Awareness on environmental externalities
307.770
0.754
9.
Water Quality
-190.731
-2.636*
2
R = 0.53,
* significant at five per cent,
** significant at one per cent level
4.5.5. Drinking Water Averting Expenditure
Drinking
water
averting
expenditure
was
found
to
be
influenced
by
household income, education, household size, water quality, awareness etc.
From the table 4.105, it could be inferred that the household income and
awareness on environmental externalities have positive influence on drinking
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water averting expenditure.
When awareness on environmental externality
increases by one stage ie, poor to medium drinking water averting expenditure
increases by Rs.187 per household.
Table 4.105. Drinking Water Averting Expenditure
Sl.No
Variable
Co-efficient
t-value
1.
Constant
-119.91
-0.847
2.
Household Income
0.0759
2.496*
3.
Education
46.90
1.767
4.
Household Size
-6.746
-0.332
5.
Water Quality Index
-5.032
-0.543
6.
Awareness on
externalities
187.45
5.935**
2
R = 0.58,
environmental
* significant at five per cent,
** significant at one per cent level
4.5.6 Willingness to Pay (WTP)
WTP was used to assess the values of change in the quality of agricultural land,
irrigation and drinking water in the study area. The results of WTP presented in
table 4.106 reveals that 57 per cent variation in WTP was explained by the
independent variables like age, household size, education, income, per capita
agricultural land, per capita standard cattle units, interest in improving agricultural
activities, perception of land and ground water degradation and proximity. Per
capita agricultural land, per capita standard cattle units, interest in improving
agricultural activities had significant influence on WTP.
If interest increases by
one stage (not interested to somewhat interested) WTP increases by Rs.933 /
household.
Table 4.106. Estimates on Willingness to Pay
Sl.No
Variable
Co-efficient
130
t-value
TNAU – TNSLUB Project
-9341.351
-0.827
Age
153.816
1.214
3.
Household size
-287.469
-0.379
4.
Education
601.714
0.575
5.
Per capita agricultural land
868.324
2.932*
6.
Per capita standard cattle
units
464.618
12.805**
7.
Interest in improving
agricultural activities
932.532
2.654*
8.
Perception on land and
ground water degradation
298.982
10.200**
9.
Proximity to dyeing/bleaching
units
-333.970
-1.137
10.
Income
88.834
0.856
2
1.
Constant
2.
Introduction
R = 0.57,
* significant at five per cent level,
** significant at one per cent level
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Introduction
5. SUMMARY AND CONCLUSION
Though industrial growth plays an important role in the economic development of
the developing countries it is apparent that the pollution effects of various
industrial units in India had been alarming. In the western Tamil Nadu, the textile
dyeing industries are located in large numbers in the districts of Coimbatore,
Karur and Erode. They play a significant role in developing the local economy
and at the same time pollute the land and water resources to a large extent. To
understand the above issues a micro level study was undertaken with the
following specific objectives.
a. to analyze the external effects of industrial development on the quality of
land, water resources, crop land, crop output, employment, income,
migration, health and other related socio-economic attributes.
b. to study the long term environmental implications of dyeing factories on
the agricultural eco-systems and
c. to study the attitude of the stakeholders in conserving the valuable land
and water resources and to suggest workable policy prescriptions for
internalizing the externalities.
The study was conducted during the period 2004 -2006. Three districts namely
Coimbatore, Karur and Erode were selected since the deterioration of land and
ground water qualities and its impact on cropland, irrigation and drinking water,
crop production, human and animal health, labour employment, farm income,
etc., were significantly pronounced only in these districts due to the high intensity
of dyeing and bleaching units. Tiruppur taluk in Coimbatore district, Karur taluk
in Karur district and Bhavani and Erode taluks in Erode district were selected
based on the extent of external impacts on land and water.
Four villages, two
affected and two unaffected were selected from each taluk. Based on the
discussions held with the regulatory authorities and development departments
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like TNPCB (Tamil Nadu Pollution Control Board), Revenue department,
Agricultural department, experts of textile and dyeing associations the study
villages were selected and classified as affected and non-affected.
The critical
parameters which influence crop growth like pH, EC (Electrical Conductivity),
TDS (Total Dissolved Salts), TSS (Total Soluble salts), chloride and sulphate
concentrations were also considered while selecting the study villages.
Altogether sixteen villages were chosen and the total sample size was 640. The
households selected were of two categories viz., (i) farm households and (ii) non
farm workers.
The respondents were selected randomly at the rate of 60
numbers from category (i) and ten from category (ii) in all the sixteen villages.
Soil and groundwater samples were also collected from the earmarked wells as
per the standard procedure to analyse various physico-chemical characteristics.
Besides the conventional percentage analysis, econometric tools viz., aggregate
damage function, hedonic regression model and contingent valuation technique
were adopted to analyze the resource degradation, environmental quality and the
stakeholders’ involvement in conservation compliance.
Farmers in Tiruppur depend to some extent on wells for irrigation as the river
Noyyal is polluted to a great extent. The quality of water was affected due to the
dyeing factory effluent in and around the study villages. In the affected area,
about 58 per cent of the cropped area was under rain fed condition against 35
per cent in the unaffected area.
The productivity of many of the crops was
reported to be less; for instance the yield of coconut in the affected area was
reduced by more than 40 per cent. The averting expenditure for the crops namely
coconut and fodder cholam was Rs.5605 and Rs.1041 respectively, for an area
of one hectare.
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A vast majority of 81.67 per cent of the households in the affected villages
depended on both on-farm and non-farm activities and about 10 per cent of the
households were found employed only in non-farm activities. The major non
farm activities of these villages were renting out houses, running own dyeing or
bleaching units, knitting units, money lending and water trading. In 75 per cent of
the households in affected villages atleast one family member has migrated,
whereas in the unaffected villages, it was only 11.67 per cent. In the affected
area, among those migrated, the permanent migration was found high. The
reasons for migration were poor income, desire to earn more, poor water quality,
and unremunerative crop activities. Among the reasons, poor income from
agricultural operations alone was reported by 71.43 per cent of the sample
farmers.
The reasons attributed for the sale of croplands were less crop income,
migration, poor water quality and water scarcity.
Forty five per cent of the
respondents in the affected villages had sold their livestock due to various
reasons like reduced milk yield, loss in weight, water scarcity and inadequate
man power to tend them. In the affected villages, only 51.67 per cent were
willing to pay for improving the soil and water qualities. About 40 per cent of the
respondents were willing to pay less than Rs.50,000 for internalizing
externalities.
Most of the worker respondents in the affected area were engaged in industrial
activities as Dye-master, Supervisor, Winch runner, Hydropher, Dye mixer etc.
A vast majority of 45 per cent of the workers were engaged in maintaining the
quality of the yarn in the near-by knitting factories. About 30 per cent of the
respondents reported problems of skin cracks and rashes.
The water samples collected from wells in the affected regions of Tiruppur taluk
before monsoon showed moderately high pH and EC values which exceeding
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their critical limits indicating its unsuitability for drinking and irrigation. Further,
the results of heavy metal analysis showed the presence of metals such as
chromium, cadmium and nickel which were below the maximum permissible
limits whereas, the lead content of the sample exceeded the prescribed limit of
0.01 mg/l for drinking water.
The same water sample collected after monsoon showed variation in pH (> 8.5)
and EC (2.53 – 4.05 dSm-1) which lie above the critical limits. The heavy metals
such as lead and cadmium were slightly above the permissible limit (0.18–0.55
mg/l and BDL to 0.02 mg/l respectively).
The results of the soil samples
collected from the study villages of Tiruppur taluk showed the pH values ranged
from 6.10 – 7.50, EC of 0.69 – 1.80 dSm-1 which were found to be higher than in
the unaffected region and also they lie above the maximum permissible limit. The
soil samples of affected villages recorded 2.36–3.85 ppm of cadmium which is
marginally slightly higher than the maximum allowable concentration of 3.0 ppm.
It is understood that in Karur, due to the discharge of dyeing factory effluent in
the river Amaravathy, both the canal and open wells remained largely unusable
for irrigation, particularly during summer season. The river Cauvery is the chief
source of drinking water in the affected villages whereas in unaffected villages,
river Amaravathy is the major source of water supply. The productivity of almost
all the crops was found higher in unaffected villages compared to the affected
villages. Even the economically less important crop like “korai” did not grow well
in the affected study villages due to poor soil and water qualities. The productivity
of major crops of the taluk, viz., coconut, paddy and fodder sorghum has
declined by 44, 14 and 24 per cent, respectively over the yields of the said crops
in the unaffected locality.
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Introduction
In the affected area about 62 per cent were willing to contribute some amount to
replenish the degraded resources. For getting good quality drinking water from
the nearby area they had to spend Rs.844/year/household. Scarcity of good
quality water and non-availability of farm labourers were the major reasons
reported for decline in agricultural operations by 83.33 and 73.33 per cent of
respondents respectively. Labour scarcity was due to the mobility of agricultural
labourers from farming to industrial sector. Poor water quality was attributed to
be the main reason (52.22 per cent) for labour mobility. Due to the deterioration
of land and water quality, the crop stand was also observed to be poor. Nonremunerative crop income from agriculture was reported by 48.94 per cent of
respondents for labour migration. In the affected villages 25 per cent of the
respondents had disposed off at least part of their land due to poor water quality
and labour scarcity. While the agricultural land value in the affected villages
declined considerably (9 per cent) due to poor soil and water qualities, the
cropland (only agricultural land) price had increased over 50 per cent in the
unaffected area. About 75 per cent of the respondents interviewed had sold their
livestock due to various reasons like poor water quality, non availability of water,
labour scarcity, reduced milk yield and reduction in calving rate.
The people in the affected areas experienced occasional skin problems, viz.,
itching, skin rashes, eye boils, etc. Milk production in the affected area was
reduced by 12.35 per cent. Farmers growing paddy and fodder sorghum had to
spend about Rs.687 and Rs.510 per ha, respectively, towards averting
expenditure. For getting good quality drinking water from the nearby places,
households had to spend 8.44 man-days a month.
Almost all the worker
respondents in the affected areas of Karur taluk maintained their livelihood by
working as wage earners in the dyeing factories.
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Introduction
supervisors, accountants, dye masters, etc. In the unaffected villages only about
25 per cent of the workers interviewed were agricultural labourers.
The water samples taken from villages of Karur before monsoon recorded normal
pH, but the EC values were found to exceed the maximum permissible limit.
The BOD and COD values were found to be in the range of 35-110 mg/l and 165420 mg/l respectively and also, SAR value of 39-46 which was higher than the
limit of 26. The water samples collected after monsoon recorded more or less
similar pH values in both affected and unaffected regions. The EC value was
recorded as 2.05 – 4.12 dSm-1 in affected villages compared to 1.22 – 3.11 dSm-1
in unaffected regions that exceeded the standard limit of 2.25 dSm-1 for irrigation
water. The water sample collected after monsoon recorded similar pH values in
both affected and unaffected regions. The water samples collected from affected
region exhibited an EC of 2.05-4.12 dSm-1, BOD of 99-148 mg/l, COD of 215-305
mg/l compared to unaffected region which recorded 1.22-3.11 dSm-1 EC, 34-60
mg/l of BOD and 85-120 mg/l of COD. The SAR values of affected samples
exceeded the critical limit but that of unaffected samples were within the limit of
26.
The results of analysis of soil samples collected from the study villages of Karur
taluk showed a pH range of 7.56 – 8.31 and EC of 1.25 – 4.10 dSm-1 which was
greater than the maximum permissible limit. Soil samples of affected villages of
Karur taluk recorded 2.36 – 5.69 ppm of lead, 1.89 – 5.96 ppm of cadmium and
12 - 45 ppm of nickel while the unaffected regions, recorded 1.37 – 2.10 ppm of
Pb, 1.10 - 2.10 ppm of Cd and 9 – 24 ppm of nickel.
The critical analysis of the area and productivity of crops in Bhavani reveals that
the productivity of majority of the crops declined in the affected villages. As in the
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case of other two study areas discussed earlier, in the unaffected villages area
under turmeric was about 17 per cent, whereas in the affected villages it was
only eight per cent. The productivity of sugarcane was higher (97 tonnes) in the
unaffected villages when compared to the productivity in the affected villages (90
tonnes). In the affected villages, about 16 per cent of the total cultivated area
was under fodder sorghum compared to five per cent in the unaffected area. The
yield of gingelly and coconut in the affected area were less by 9.33 and 39.04 per
cent, respectively. The averting expenditure for banana was to a tune of
Rs.3705/ha.
Only 33.34 per cent of the affected village households depended on on-farm
activities exclusively for their livelihood sustenance, while it was about 50 per
cent in unaffected area. About eight per cent of the households alone were
undertaking both on-farm and off-farm activities. But it was 15 per cent in the
unaffected villages.
In the affected area, about 53 per cent migrated from
agriculture to other non-farm activities compared to 20 per cent in the unaffected
area. The main reasons attributed for migration was poor income from
agricultural activities and their interest to earn more from the assured sources of
employment without much drudgery.
Majority of the households expressed that poor income was the major hurdle
affecting the ability to pay and replenish the degraded resources. About 53 per
cent of the farmers were willing to pay between Rs.25,000 and Rs.50,000
towards internalizing externalities (mainly for getting good quality water). About
42 per cent favoured quarterly mode of payment, 10 per cent for half yearly and
15 per cent for annual payment. It could however, be observed that the average
wage earning is higher in the affected area by 25.39 per cent. This is due to the
employment opportunities provided by the industry to the people in the affected
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Introduction
area. The employment of other family members in the affected area showed that
only 36.84 per cent were found to depend on agriculture while it was about 87
per cent for the unaffected category.
About 20 percent of non-farm workers have been suffering from skin related
ailment and tuberculosis (TB). The TB patients were undertaking free treatment.
Other acute problems like skin cracks, boils, itching, skin rashes were also
reported by some sections of the sample respondents.
On an average, an
individual had to spend about Rs.40 and Rs.57 a year towards the cost to
physician and medicine.
The pH and EC of the water samples collected from affected villages of Bhavani
taluk were higher (8.56 to 9.20 and 2.56 – 5.27 dSm-1) when compared to
unaffected villages of the same taluk.
In general, the BOD and COD values of
the samples from the affected villages were found to be higher recording 96 to
170 mg/l and 235-425 mg/l respectively compared to 24 to 85 mg/l and 60-210
mg/l of BOD and COD respectively in the unaffected regions. Heavy metals like
chromium, lead and cadmium contents were higher in affected areas compared
to unaffected areas.
The soil samples collected from Bhavani recorded a
relatively higher pH in affected regions (7.70 – 8.94) compared to unaffected
regions (6.20 – 7.12). The EC value was also higher in samples of affected
villages, which recorded 2.14–3.99 dSm-1 when compared to EC values of
samples of unaffected villages (0.12 – 0.69 dSm-1). The level of chromium was
found to be in the range of 23 - 85 ppm in affected regions but it was below
detectable limit in unaffected regions.
In Erode taluk, the area irrigated by canal had declined by about 21 per cent
during the recent decade. The rain fed area had increased by about 25 per cent
in the affected area. Also, in the affected area, the area under paddy declined by
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about ten per cent. Though the area under coconut increased over years, the
productivity has comedown by more than 40 per cent. The yields of major crops
like paddy, sugarcane, turmeric and groundnut had declined by 12, 23, 26 and 61
per cent, respectively compared to unaffected study villages. A majority of 74 per
cent of the sample households were willing to pay between Rs.25, 000/- and
Rs.50, 000/- per household to replenish the degraded resource with financial
support from the institutions like government.
A farmer cultivating paddy and sorghum had to spend on an average over
Rs.919/- and Rs.468/- per hectare respectively towards averting expenditure.
About 84 per cent were of the view that poor water quality was the main reason
for the weak performance of agriculture.
About 57 per cent of farmers in the
affected category reported decline in agricultural income as one of the
contributing factors that led to sluggishness in agricultural activities. The
percentage of income earned by the households from agricultural activities alone
was only 5.30 in the affected villages whereas it was 34.89 per cent in the
unaffected villages. The respondents in the affected area spent on an average
about Rs.125/- towards the cost of medicine. About six per cent loss in milk
production was reported in milch -animals. Besides, reduction in weight and
decline in reproduction rate was also noticed.
Majority of the labourers interviewed were found to work in private companies for
various activities ranging from cashier to supervisor on weekly wage basis. Only
15 per cent were found to be employed as labourers in agricultural activities in
the unaffected areas. About 10 per cent of the respondents reported that they
had to suffer often from skin irritation. About five percent reported to suffer from
skin cracks, stomach pain, indigestion and occasional hair fall.
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Introduction
The water samples taken from affected regions of Erode taluk recorded a pH of
8.60 to 9.26, EC of 2.98 to 5.55 dSm-1 compared to a pH of 7.12 to 8.01 and EC
of 1.12 – 2.36 dSm-1 in unaffected regions. Highest BOD of about 80 to 140 mg/l
and COD of 200-350 mg/l were recorded in affected region which are higher than
the limit compared to about 27 – 67 mg/l of BOD and 70-170 mg/l of COD in
unaffected regions. The heavy metals like chromium, lead, nickel and cadmium
were found to be higher and exceeded their critical limits in affected areas
compared to unaffected areas.
The soil samples taken from affected region of Erode taluk recorded a higher pH
(7.96 to 8.99) and EC of 2.58 – 4.57 dSm-1 than unaffected region (6.5-7.56 pH
and 0.12-1.57 dSm--1). The heavy metal contents of the samples from affected
region were found to be higher than unaffected region but they were below the
critical limits.
A critical analysis of the yield damage function revealed the fact that about 57 per
cent variation in agricultural yield damage was contributed by averting input
expenditure to land, proximity of cropland to dyeing or bleaching industries, water
and land qualities.
If the land quality index shifts from poor to medium,
agricultural yield damage would decrease by Rs.2932/ha and if proximity of
cropland to industries increase by one km, the agricultural yield damage would
decrease by Rs.2961/ha. The analysis of hedonic pricing techniques implied that
water quality, proximity of cropland and share of cropped area had significant
influence on value of cropland with proximity and share of cropped area having
negative impact.
When the proximity to the dyeing or bleaching industry
increased by one kilometer, value of cropland would decrease by Rs.10,265 per
ha. It was also found out that the household income and awareness on
environmental externalities had positive influence on drinking water averting
expenditure. When awareness on environmental externality increased by one
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Introduction
stage i.e., poor to medium, drinking water averting expenditure would increase by
Rs.188 per household.
It is interesting to note that about 57 per cent variation in Willingness To Pay
(WTP) was explained by age, household size, education, per capita income, per
capita agricultural land, standard cattle units, interest in improving agricultural
activities, perception of land and ground water degradation and proximity. The
functional analysis revealed that the interest in improving agricultural activities if
increased by one stage (not interested to somewhat interested) WTP would
increase by Rs.933/household. From the foregoing discussions, the following
policy prescriptions could be made for further action by the technocrats and the
enforcement authorities.
Policy Options
The Tamil Nadu Pollution Control Board (PCB) may periodically publish
the results of the analysis of effluent samples taken from the industries
along with permissible levels so as to bring in accountability and create
public awareness.
Quality monitoring of water courses and point and non-point sources of
pollution on a continuous basis may be entrusted to research institutions
like universities, colleges etc. for reporting back to Government for
remedial measures and designing conservation compliance programmes.
The affected parties should be compensated adequately, by working out
the third party effects created by the industries. Effort should also be
taken so that the compensation amount to be paid to the affected parties
is sufficiently higher than the damage cost incurred by the farmers and
other stakeholders of the local resources.
A working group comprising of farmers, industry, technocrats, policy
makers, researchers, enforcement agencies, etc., should be constituted
to look into the physical, economic, social, environmental and ecological
issues of industrial pollution, remedial and abatement measures.
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Introduction
143