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Economics Student Publications
Economics
1995
Economic- Air Pollution Models: An
Econometrics Regression Approach
Muhammed R. Yunus
Wright State University - Main Campus
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Yunus, M. R. (1995). Economic- Air Pollution Models: An Econometrics Regression Approach. .
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ECONOMIC - AIR POLLUTION MODELS:
AN ECONOMETRICS REGRESSION APPROACH
A thesis submitted in partial fulfillment
of the requirements for the degree of
Master of Science
By
Muhammad R. Yunus
B.S., Hasanuddin University, 1985
1995
Wright State University
August 30. 1995
I HEREBY RECOMENDED THAT THE THESIS PREPARED UNDER MY
SUPERVISION BY Muhammad R.Yunus ENTITLED Economic- Air
Pollution Models; An Econometrics Regression Approach BE
ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
DEGREE OF Master of Science,
Dr, Thomas Traynor
Faculty Reader
D
and Applied Economics
August 30. 1995
I HEREBY RECOMENDED THAT THE THESIS PREPARED UNDER MY
SUPERVISION BY Muhammad R.Yunus ENTITLED Economic- Air
Pollution Models: An Econometrics Regression Approach BE
ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
DEGREE OF Master of Sciencec
Dr. James A. Swaney
Faculty Supervisor
Dr. Thomas Traynor
Faculty Reader
Roger Sylvester
Director M.S., in Social
and Applied Economics
ABSTRACT
Yunuse Muhammad R. M.S., Department of Social and Applied
Economics, Wright State University, 1995. Economic- Air
Pollution Models: An Econometrics Regression Approach.
Economic- air pollution models have been developed using an
econometrics
regression
approach
for
the
ambient
air
concentration levels of total particulate matter (TPM) ,, I9601990, sulfur oxide (SOx), 1962-1992, and carbon monoxide (CO),
1970-1992.
There
are some difficulties
explanatory variables
in determining the
because many variables which
affect
ambient air levels may also be related to others explanatory
variables.
Furthermore, the
lack of available
ambient air
concentration level data is another constraint in developing
the models. Yet, this study suggests that while gross domestic
product per capita has increased over time, ambient air levels
of TPM and SOx pollutants have fallen significantly. Ambient
air
levels
of CO pollutant
have
fallen as well, but
not
significantly. This may be due to the very limited number of
observations available in this model. The Clean Air Acts have
significantly
pollutants
improved ambient air quality of those three
through
reducing
quantity of the total output
emission
rates,
emission
per
(i.e. GDP). On the other hand
increase in population has significantly increased pollution.
Page
I . INTRODUCTION .............
....
1
Background ...................................
1
Earlier Study ................................
2
Objective
5
.
Data .........................................
4
II. AIR POLLUTION:SOURCES, TRENDS, AND RESPONSE ..
7
Sources of Air Pollution
Clean Air Act
Trends
..........
.....
.....
III.EMPIRICAL MODEL
17
....
20
.......
20
D i s c u s s i o n .......
V.
CONCLUSION
BIBLIOGRAPHY ........
9
15
.....
EMPIRICAL FINDING
Results
7
10
Public Opinion
IV.
.
22
......
28
37
Table
Page
1. Air Pollution Sources ....
8
2. Uncontrolled Emission from Different Types
Of FUelS
3.
c „ .
c
, o ,
„
~ o
. .
.
o , .
a
. . . . . . . .
a
. o o
o
o «
o
. c
.
. „
National Ambient Air Quality Standards
11
13
4. Public Opinions Economic Growth vs
Environmental Protection ...............
16
5. Public Opinion; Percentage Very Concerned
About National Environmenta1 Problems ........
6.
Sample Characteristics .......
16
20
7 . Estimates of TPM Ambient Air Concentration
Level Model, 1960-1990
25
8. Estimates of SOx Ambient Air Concentration
Level Model, 1962-1992
... 26
9. Estimates of CO Ambient Air Concentration
Level Model, 1970-1992
........
27
Figure
Page
la. U.S. Trends in Ambient Air Quality for
TPM, SOx, and ozone pollutants, 1970-1992 ... 30
lb. U.S. Trends in Ambient Air Quality for
N02, CO, and lead pollutants, 1970-1992 ..... 31
2.
Number of Areas Not Attaining Air
Pollution Standards ......................... 32
3.
Air Pollution Abatement Expenditures
Source, 1972-1991
4.
by
........
U.S. Trends in Energy Consumption per GDP,
1960- 1992 ......
5.
36
Energy Conservation in Industrial Sector,
1960- 1985
6.
33
........
35
Motor Vehicle Efficiency, 1960- 1990 ........ 36
INTRODUCTION
BACKGROUND
Over the years various concepts of economic system environment relations have been proposed. Some of them have
dealt with input - output analysis, material balances, stock
flow models and the use of super models. Though there is still
lack of agreement either in the common understanding, or in
the method used, or in the results of the models in explaining
and predicting the human activity effects on the environment,
study of this issue has never decreased (Hafkamp, 1991). The
difficulties in formulating the models probably lie in the
properties of the environment itself. The biological, chemical
and physical processes in the ecosystem are too complex to be
understood in sufficient detail at present (Jorgensen, 1989).
Furthermore, what economic variables contribute to the states
of the environment or to the emission levels and how strong
they
interact
with
each
other
(related
to
the
multicollinearity problem in regression models) are not easily
determined. Another constraint is the lack of
environmental
data, perhaps because environmental monitoring
is relatively
recent
and expensive.
However, we may
pollution
released
behavior
(Hafkamp,
manufacture
cars,
say that
to
the
1991).
decisions
the
root of
environment
is
Decisions
of
of
consumers
every
human
case
decision
producers
to
of
drive
to
those
vehicles,
and decisions of farmers to apply fertilisers and
pesticides, for example, all produce pollution.
The idea of idiscommodityi, as introduced by Coddington
(1970) refers to anything that people would choose not to have
or which renders a disservice. Noise, pollution of the air by
gaseous waste, and of water and land by industrial waste, may
be categorized as discommodities. According to Coddington,
processes of consumption may be considered as transformation
of commodities into discommodities.
The
mid-19609s
of
economic
growth
theory
poses
a
compelling analogy between the laws of thermodynamics and that
of economics. The first law, the matter can not be destroyed
but only transformed from one state to others, is translated
that
pollutant
consumption
or
waste
activities
generated
must
be
from
present
production
somewhere
in
and
the
physical system. Consequently, the capacity of that system to
absorb waste or pollutants must be taken into account when
planning economic activity.
If we reduce pollutant or waste
by recycling, however, according to the second law no process
can achieve 100 percent efficiency. This is translated that
complete recycling is impossible
(Markandya and Richardson,
1995).
EARLIER STUDY
Janssen and Rotmans (1995) offer a theoretical model for
allocating fossil C02 emissions
in response to the global
green-house effect = The model supposes that such international
policy targets for €02 emission levels are to foe met.
For
this, global C02 emissions level during a fixed period are
restricted under "the global €02 emission budget", Allocation
of a (restricted)
fossil C02 emissions budget to regions is
based
on
indicators:
size,
and primary
GDP
(economic
energy use,
affluence), population
because
those
are the main
underlying factors associated with €02 emissions. Allocation
of regional emission rights, regional permissible amounts of
€02 emitted in the future,
is defined as the fractions for
regions of the global €02 budget minus the historical regional
CO2 emission.
Another
study
using
Ringquist (1993), using
United
States.
Ringquist
regression
analysis
was
done
by
state cross sectional data for the
models
changes
in
state
ambient
concentration levels for the periods 1973-75 and 1985-87 for
sulfur dioxide and nitrous oxides. Fossil fuel consumption is
an explanatory variable in his model as well. Ringquist uses
value added approach to model the seven industrial categories
most responsible
for air pollution,
along with some other
explanatory variables. Those other variables are regulatory
program strength, state expenditures for pollution controls,
the U.S. Environmental Protection Agency (EPA) abatement and
state abatement activities.
the
state
strongest.
air pollution
The
stronger
For each state, Ringquist ranks
control
programs
pollution
from weakest
control
programs
to
are
associated with greater reductions in pollution. SPA and state
abatement activities reflect the number of federal and state
activities
(i.e. enforcements) undertaken in each state„ An
earlier regression analysis was performed by MacAvoy (1979) .
This model analyzes emissions per industrial output GNP by six
industrial categories: mineral, automobile, chemical, primary
metal, electric utility,
involves
variables
and petrol
the
U.S.
1968-76
he
uses
time
annual
trends
to
refining.
data.
As
measure
Observation
explanatory
progress
in
technology, industrial rate of capacity utilization to measure
cyclical production conditions, and regulation given in dummy
variables. The study concludes that in those six industrial
categories, regulation had a significant effect in reducing
pollution
only
industries.
in
MacAvoy
the
automobile
concludes
that
and
electric
regulations
significant impact in reducing pollution (MacAvoy,
utility
have
no
1979, p.
102-103).
Despite the use of different explanatory variables and
different dependent variables (except for sulfur oxides), this
study generally supports Ringguist's finding that regulations
significantly
improve
ambient
contradicts MacAvoy's finding.
air
quality,
while
it
A rise in industrial activity
in Ringquist1s study significantly increases pollution. Our
study finds a statistically significant relationship between
increase in per capita gross domestic product and increase in
total
particulate
matter
(TPM)
and
sulfur
oxide
(Sox)
pollutants = The use of population as explanatory variable in
our
models
accords
with
Janssen
and
Rotmans9 theoretical
model.
OBJECTIVE
The objective of this study is to model the U.S. economic
activity-
air
pollution
relations
using
econometrics
regression methods. The models are then analyzed.
In those
models, one variable, called dependent variable, is given as
a linear function of one or more variables, called explanatory
or independent variables. The basic assumption is that there
is a relation between economic activity (i.e. GDP) and ambient
air concentration levels. The study is focused on ambient air
concentration
particulate
levels
matter
of
three
regulated
(TPM), sulfur
oxide
emission:
total
(SOx), and
carbon
monoxide (CO). The data of the three other ambient air levels,
nitrogen dioxide (N02) , ozone (03) and lead (Pb) may not be
sufficient for regression analysis since the data starts from
1974-1975.
DATA
The U.S. data used for empirical analysis is the time
series data, a set of period observation on the values that a
variable takes at different year. The sample size varies and
depends
on
the
availability
of
data
(i.e.
ambient
air
concentration level data), but in the range 1960-1992.
The
ambient
air
concentration
data
is
obtained
from
the
Environmental Protection Agency (EPA) data, where data prior
to 1972 is based on the National Air Sampling Network (NASN)
data. GDP is measured in 1987 U.S. billion of dollars, while
population is in thousand of people.
SOURCES OF AIR POLLUTION
Air pollution is the presence of one or more contaminants
in the ambient air in quantities,
qualities,
which
animals
cause
injuries
to
humans,
and duration
or
plants,
or
interfere with the comfortable enjoyment of life and property
(CRC i 1989 and Salvato, 1992) .
Processes
chemical
grinding,
that
are
reactions,
drying
and
sources
of
evaporation,
baking,
and
air
pollution
burning,
include
crushing
combinations
of
and
those
processes (Salvato, 1992), that we may find in many economic
activities. Sources of air pollution have been identified and
in many cases
are well characterized. Table 1 summarizes the
man-made air pollution sources with examples for each source
category.
Many of the most pressing environmental concerns in the
U.S. are linked to the consumption of energy. In fact, nearly
all the criteria pollutants are by products of combustion of
fossil fuels, which continue to be the primary energy sources
in the United States. Fossil fuels are the leading sources of
oxides of sulfur, carbon and nitrogen, and particulate matter,
four of the "criteria pollutants" targeted by the CAA (CEQ,
1990). Table 2 shows examples of the amounts of uncontrolled
emission
from
different
types
of
fuels
in
kilograms
of
pollutants per billion joules calory delivered by fossil fuels.
Table 1
Air Pollution Sources
CategoryChemical plants
Crop spraying
and dusting.
Crushing,grin­
ding and
screening.
Demolition
Field burning
Frost- damage
control
Fuel burning
Examples
Petroleum refineries,
pulp mills, super­
phosphate, fertilizer
plants, cement mills.
Pest and weed control
Road-mix plants.
Urban renewal
Stubble and slash
burning
Smudge pots
Home heating and power
plants.
Fuel fabrication
Inks
Metallurgical
plants
Gaseous diffusion.
Photography and printing
Smelters, steel mills,
aluminum refineries
Milling
Motor vehicles
Grain elevators
Autos, buses, trucks.
Nuclear- device
testing
Atmospheric explosions
Pollutants
Hydrogen sulfide,
oxides of fluorids
organic vapors,
odors, particles.
Organic phospl
lead, chlorinat hydrocarbon,
Mineral and orga
particulate.
Smoke, fly ash,
soot.
Oxides of sulfur and
of nitrogen, carbc ■
monoxide, smoke, odeFluoride.
Metal flumes (lead
zinc, arsenic),
fluoride, oxides of
sulfur
Oxides of sulfur and
of nitrogen, carbon
monoxide,smoke,odor
Radioactive fallout
(strontium 90,
ce­
sium 137,carbon-14)
Argon 41.
Uranium and
beryllium dust
Oxides of sulfur,
smoke, fly ash,
organic vapors, odoj.
Nuclear reactors
Crushing, grinding, and
screening.
Community and apartment
Refuse burning
house incinerators,open
burning dumps.
Solvent cleaning Dry cleaning, de­
greasing .
Spent- fuel
Chemical separations
processing
Iodine-131
Automobile assembly,
Hydrocarbon, other
Spray painting
furniture, appliance
oxides.
finishing.
Metal scrap yards, auto­ Smoke, soot, organic
Waste recovery
body burning, rendering
vapors, odors.
plants.
Nuclear fusion
Ore preparation
Source: Practical Handbook of Environmental Control, 1989, reprinted
from Chemical Engineering, October 14,1968.
CLEAN AIR ACT
The quality of ambient air is measured based on timeaverage pollutant concentrations in the air, usually at the
ground level,
where people, animal, plants
often exposed to the pollutants.
completely
colorless
and
Air pollutants range from
odorless
monoxide to highly visible dense
and property are
gases
such
as
carbon
soot such as particulate
matter„ Lead, asbestos, and beryllium pollutants are highly
toxic in minute amounts, Others such as carbon monoxide can
cause headaches,
angina attacks,
even death at a very high
concentration (CEQ, 1981).
The legislative framework for managing the ambient air
environment is based on the Clean Air Act
(CAA) , which was
developed in response to the increasing environmental concern
(CF, 1987). For this the U.S. Environmental Protection Agency
(EPA) has established national ambient air quality standards
(NAAQS) for six common pollutants : total particulate matter,
sulfur
dioxides,
nitrogen
dioxides,
carbon
monoxide,
the
organic compounds that contribute to the formation of ozone in
the lowest layer of the atmosphere, and lead. The NAAQS were
promulgated in April 1971 following passage of the Clean Air
Act
amendments
(CAA)
of
1970.
The
ambient
air
quality
standards specify maximum allowable concentrations of those
pollutants
in the air
(CF,
1987 and CEQ,
1989) . The acts
primary standards are intended to protect public health, while
the secondary standards are intended to protect public welfare
including
property,
vegetation
and
aesthetic
values
from
damage. The CAA of 1970 required achievement of the NAAQS to
protect
human
health
by
1975.
The
1977
CAA
extended
the
deadline for attainment of all primary standards in most areas
to 1982 (CEQ, 1981), with further extension to 1987 possible
for ozone
(03) and carbon monoxide
(CO)
(Tietenberg,
1994).
The 1977 CAA also codified prevention of serious deterioration
(PSD)
standards
to
protect
relatively
unpolluted
areas.
Moreover, the acts required the EPA to specify all areas not
meeting
the
(Tietenberg,
1970
1994).
CAA
deadline
Among
the
as
many
non-attaining
provisions
of
regions
the
CAA
amendments of 1990, the act attempts to reduce pollutants from
automobiles and other sources (HC, CO, NOx, and particulates)
and to require increased use of cleaner motor vehicle fuels
(CEQ, 1991). Title 3 of this act
mandates the regulation of
189 toxins emitted from municipal incinerators and commercial
and
industrial
amendments
sources
revised,
(Salvato,
expanded,
and
1990).
extended
The
the
1990
CAA
national
ambient air quality standards (NAAQS).
TRENDS
To provide an rough view of recent ambient air quality
trends, Figures 1-a and 1-b plot the index values (1975=100)
of the ambient air concentration levels of TPM, SOx, ozone,
N02, CO, and lead in the during period 1970- 1992. Figure 2
compares the number of areas not attaining the ambient air
quality standards
in 1978
and
growth, economic development,
in 1985.
Despite population
and enormous increases in the
use of vehicles, progress in improving the nation1s ambient
air quality is evident at least for some pollutants. Levels of
Table 2
Uncontrolled Emission from Different Types of Fuels
Fuels
Effic
iency
TPM
SOx
NOx
HC
CO
Industrial
boilers:
Wood
Anthracite
Bituminous coal
Distillate oil
Natural gas
0.70
0.80
0.80
0.90
0.90
500
2800
94
8
7
53
820
1310
1120
a)
400
320
240
83
99
400
22
4
4
2
450
45
20
19
8
Residential
heating stoves:
Wood
Anthracite
Bituminous coal
Distillate oil
0.50
0. 65
0. 65
0.5
0.85
2700
46
550
11
7
30
200
1100
1170
a)
100
250
270
71
38
6800
100
530
4
4
17000
1000
5300
20
10
0.15
3800
250
300
3200
34000
0.15
0.20
0.15
0.80
10000
280
17000
0.5
3200
2200
460
2200
a)
10
5
Residential
cooking stoves:
Tropical wood
Hawaiian
cowdung
Indian coal
Coconut husks
Natural gas
44000
27000
54000
250
Source : Statistical Record of the Environment, 1992 from Environment
December 1988. Note: a) negligible.
some pollutants seem to have dropped much more than levels of
others.
Nationally, the level of TPM concentration in the ambient
air decreased approximately 35 % between 1970 and 1980, and
approximately 25 % between 1980 and 1992. The level of CO
dropped
approximately
40
%
between
1970
and
1980,
and
approximately 25 % between 1980 and 1992. In the same periods,
the concentration level of SOx fell approximately 60 %
15
II02 level decreased
and
approximately 25 % during 1974-=
1980, and approximately 20 % during 1980- 1992. The ambient
air concentration level of ozone dropped approximately 5 %
between 1970 and 1980, and approximately 20 % between 1980 and
1992. The lead concentration level decreased by approximately
42 % from 1970 to 1980, and dropped
sharply by about
90
%
between 1980 and 1992.
A non-attaining area is an area that fails to accomplish
an EPA ambient air quality standard (CEQ, 1978). The number of
counties or portions of counties that failed to attain the
primary or secondary standards for particulate matter dropped
from 421 in 1978 to 290 in 1985. At the same time the number
of areas not attaining the S02 standards fell from 101 in 1978
to 60 counties or portions of counties in 1985. Moreover, for
C02
the
number
of
non-attaining
areas
dropped
from
190
counties or portions of counties in 1978 to 152 in 1985. The
number of non-attaining areas for ozone levels decreased from
607 counties or portions of counties in 1978 to 368 in 1985.
Even though on average the national ambient air levels of some
pollutants have met the primary NAAQS (since
around
1970 for
Table 3
National Ambient Air Quality Standards (NAAQS)
Pollutants
Averaging time
Particulate
matter (TPM)
a)
Annual
(geometric mean)
24- hour
Sulfur Oxide
(Sox)
Annual
(arithmetic
mean)
24-hour
Primary
standard
75 pg/m3
60 pg/m3
260 jag/m3
150 p.g/m3
80 ytg/m3
(0,03 ppm)
365 pg/m3
(0.14 ppm)
3-hour
Carbon
monoxide
(CO)
8-hour
Nitrogen
dioxide
(N02)
Ozone
(03)
Lead (Pb) b)
Secondary
standard
1300 pg/m3
(0,5 ppm)
10 mg/m3
(9 ppm)
40 mg/m3
(35 ppm)
No secondary
standard
Annual
(arithmetic
mean)
100 yig/m3
(0.05 ppm)
Same as
primary
Maximum daily
1 hour average
235 pg/m3
(0.12 ppm)
Same as
primary
Maximum
quarterly
average
1.5 pg/m3
Same as
primary
1-hour
Source :Environmental Trends, 1989, from National Air Quality and Emission
Trend Report, 1988, Office of Air Quality Planning and Standards Technique
Support Division, EPA.
Notes: a) PM-10 standards, 50 pg/m3 (annual arithmetic mean) and 150pg/m3
(24-hour), were promulgated in 1987 to replace TPM standards, b) Lead
standards were proposed in December 1977.
TPM and SOx, since around 1980 for CO, since around 1990 for
ozone, and before 1975 for N02 and lead), many metropolitan
areas still continue to exceed the standards at least for one
pollutant. In fact, over 100 urban areas in the U.S. have yet
to meet the primary standards for at least one of the six
"criteria" pollutants (CQ, 1991).
During the 20 years from 1972 trough 1991, the U.S. spent
approximately
a total
of
$ 500
billion
in constant
1937
dollars for air pollution control. This included abatement
expenditures for mobile sources (cars, trucks, and buses) and
stationary
sources
(industry,
private and government
and power stations)
sectors.
The expenditure
by both
share
for
mobile sources in the total air pollution control expenditures
gradually increased by 1990 and fell somewhat in 1991. That
share was only approximately 30 % in 1970, and increased to
approximately 55 % in 1990.
As mentioned earlier, the role of U.S. energy consumption
on the quality of ambient air is undeniable.
figures
illustrate
primary
indicator
how
of
the
this
country
intensity
of
The following
consumes
energy
energy. A
use
is the
relationship between total energy consumption and real gross
domestic
product.
Figure
4
shows,
however,
that
energy
consumption per dollar of GDP has declined persistently over
the period 1960- 1992. It fell from 22,000 Btu per 1987 dollar
of GDP in 1960 to 16,500 in 1992, a drop of 25 %. Two other
indicators
of
energy
use
are
energy
conservation
in
the
industrial sector and fuel efficiency in the transportation
sector exhibited in Figures 5 and 6. Energy conservation (the
use of wore energy- efficient processes) and fuel efficiency
(the increase of fuel rate) evidently seem to have occurred in
both the industrial and transportation sectors. Consumption of
energy has
fallen
from approximately
12,000
Btu per
1982
dollar of industrial output in 1960, to approximately 8,700 in
1985,
a drop of 12.25 %., On average, the fuel rate of all
vehicles including passenger cars,
motorcycles,
buses,
and
trucks has increased from approximately 12.40 miles of travel
per gallon of fuel in 1960, to approximately 16.30 in 1990, an
increase of 31.40 %. The fuel rate of passenger cars alone has
increased from approximately 14.30 miles per gallon in 1960,
to approximately 20.90 in 1990, an increase of 46.50 %.
PUBLIC OPINION
The two following tables present public opinion surveys
carried out in the US from Gallup Polls in 1984 and in 1990
with
a
coordinated
compares
the
framework
public
suggested
opinion
by
OECD.
concerning
Table
4
environmental
protection versus economic growth, while Table 5 compares the
percentage
of
persons
highly
concerned
about
national
environmental problems for both two year surveys. As shown by
the 1984 and 1990 polls the percentage of people who thought
that the environmental protection problem
should be given
more priority have increased. In fact, in general more people
have been very concerned about pollution problem. The degree
of concern appears to be correlated with the
increase
of
economic
well-being*
This
shift
in
public
opinion
has
increased the government environmental protection efforts (CF,
1984)
through
monitoring,
regulations,
enforcement,
and
abatement expenditures.
Table 4
Public Opinion : Economic growth vs environmental protection
Priority
to
economic
growth (%)
Donrt
know (%)
‘total
(%)
inter­
views
Priority to
envi­
ronmental
protection
(%)
1984
1590
62
28
10
i.OO
1990
1223
71
19
10
100
Year
Number of
Source : OECD Environmental Data Compendiurns 1987 and 1990
Table 5
Public Opinion : Percentage Very Concerned About
National Environmental Problems
Year
Number
of
inter­
views
Industrial
waste
disposal
Air
pollution
Water
pollution
Accidental
damage to
marine en­
vironment
Nuclear
waste
disposal
1984
1590
64
46
52
54
69
1990
1223
n. a .
58
64
52
48
Source : OECD Environmental Data Compendiums 1987 and 1990.
Note : n.a. = not available
The pollution (E) generated from economic activity in the
production and consumption context may be determined by the
quantity of the total output (H), the quantity of pollution
good p
(Xp)
in the total
output, and emission
rate
(e) ,
emission per quantity of the pollution goods p. Furthermore,
we assume that emission rate (e) is a function of regulations
since the role of regulations is actually to reduce emission
rate (e),
E = f (H, Xp, e(REG)) ...................
(1)
Equation (1) describes this process. If the quantity of
the total output (H) increase due to the increase of quantity
of the pollution goods p, pollution will increase, and vice
verse. Next, if the increase of the total output (H) is caused
by the decrease of quantity of the pollution goods p (Xp) and
an increase of quantity of the non-pollution goods c (Xc) ,
where
decrease
H= Xp + Xc,
in
the
then pollution may fall. Moreover,
emission
rate
(e)
(due
to
a
regulation
stimulations) obviously will reduce pollution, and vice verse.
Since production and consumption of all goods and related
products potentially cause pollution (they differ only in the
pollution intensity), we may say that most of the part of the
total output (H) comes from production and consumption of the
pollution goods p (Xp) ,
One of the assumptions of the classical linear regression
model
is
that
there
is
no
multicollinearity
among
the
explanatory variables. Many of the explanatory variables that
effect the state of the environment (e.i. ambient air levels),
however, may causally be related to the other explanatory
variables
as
well. Therefore,,
caution
must
be
given
in
choosing those explanatory variables. For example, since most
heavily polluting industries are also energy intensive, the
dependence upon
fossil
fuel may be affected by change
in
industrial activity (Ringquist, 1992). Similarly, the strength
of regulations may increase abatement expenditures spent by
both business and government sectors. Furthermore, progress in
technology, particularly in acquiring a cleaner technology,
may be related to the regulation stimulation.
The econometrics model of air pollution relation in this
study is developed based on the equation:
(A/POP)=a1+bn CAAn+ c2 CHLN(GDP/POP) + c2CHLNPOP+ u2 . (2)
where CAAn are
dummy variables controlling the effects of the
regulations. There are two assumptions regarding the Control
Air Act
(CAA). First,
that regulations are in
for simplification the model assumes
place the year following the passage
year of that acts. Second, CAAn have a value of zero before
and including the passage year of the acts,
and one after
ISthafco By this the effect of each CAA is separated in the
estimates. GDP is U.S. gross domestic product, and POP is the
U.S. population. A is the ambient air concentration levels of
pollutants, ui is the disturbance or error term
other
exogenous
explicitly,
factors,
but
such as climate.
logarithm, respectively.
are
not
taken
to capture
into
CH and LN denote
account
change and
RESULTS
The means and standard deviations of the ambient air
concentration
levels
of
total
particulate
mattert sulfur
oxides, and carbon monoxide used in estimation are provided in
Table 6. The results of the regression estimates are presented
in Tables 7, 8 and 9.
Table 6
Sample characteristics
Variables
Mean
Standard deviation
Total
particulate
matter (TPM)
62 o20 (jug/m3)
14.15
Sulfur oxide
(Sox)
47.67 (m g/m3)
28.14
Carbon monoxide
(CO)
101.16 (mg/m3)
31.74
Estimates of the parameters are typically different from
zero
(except
for
the
CHLN (GDP/POP)
parameters
in
the
CO
ambient air level model), and many of them at high levels of
significance. The R squared 0.956 in the TPM ambient air level
model indicates that 95.6 % of the variation in
the TPM air
concentration per capita is explained by
variation in the
CAAs , change in the log of GDP per capita, and change in the
log of population.
ambient
air
In the two other models,
level
models,
concentration per capita,
97.0
%
variation
Sox and CO
in
Sox
air
and 90.80 % variation in CO air
concentration per capita are explained by variations in the
independent variables. The null hypothesis that there is no
relation between the change
capita
and
ambient
air
in gross domestic product per
concentration
levels
per
capita
observed for total particulate matter and sulfur oxide
is
rejected. However, we fail to reject this null hypothesis in
the
CO
ambient
parameters
of
air
the
concentration
CAAs
are
model.
negative
The
and
estimated
statistically
significant, implying that those regulations played a positive
influence on ambient air quality. Moreover, as expected, the
estimated
parameter
of
change
in
log
of
population
are
positive and statistically significant for the three models.
Increase
in
population
is
associated
with
increase
in
pollution. The Durbin- Watson statistic for autocorrelation in
the SOx and CO ambient air concentration level models fall in
the rejection of positive or negative regions. Therefore, for
these
two models
autocorrelation, the
correlation between
members of series of observations ordered in the series data,
is not a problem. In the TPM ambient air concentration level
model the Durbin- Watson statistics fall in the indeterminate
regions.
The
Breush-
Pagan
test
is
used
to
detect
heteroscedasticity.
variance
of
each
Heteroscedasticity
disturbance
term
u*,
is
present
if
conditional
the
on the
chosen values of explanatory variables, is not some constant
number. The
5 % critical
Chi-square
values
for
4 df
(4
independent variables) is 9,487, and for 5 df (5 independent
variables) is 11,070, Since the Chi-square statistics in the
TPM and CO
air concentration level models are less than the
critical Chi square values for 4 df, we fail to reject that
there is heteroscedasticity in the error variances in the two
models. However, in the SOx ambient air concentration model
the Chi square value exceeds the critical Chi-square value for
5 df,
indicating that heteroscedasticity is present in this
model. This model may require more observations. The positive
sign of the estimated parameters of CHLN (GDP/POP) in the three
models are
as expected. However, the estimated parameter for
CO
air
ambient
level
model
is
in question
since
it
is
statistically not significant.
DISCUSSION
Perhaps the most interesting finding here is that while
gross domestic product per capita (GDP/POP) increased over the
period, the quality of ambient air per capita for two observed
pollutants, total particulate matter (TPM), and sulfur oxide
(Sox) has significantly
Since the processes
improved.
of production and consumption of
goods may cause pollution (different only in their pollutant
intensity) „ reducing the share of higher pollution
the total
goods in
output, or reducing emission rate may have the
effect in improving air quality, which is given in equation
(1). As shown by Figures 4, 5 and 6, conservation of energy,
the use of more efficient energy processes and techniques in
the
economic
activity,
and
the
fuel
efficiency
of
motor
vehicles seem to have occurred approximately after 1970, The
marginal product, that is, the change in output (i.e. GDP) for
the change in energy consumed, has increased. This may have
caused the falling emission rate (emission per total output).
The EPA reported
oxide,
carbon
that since 1970 total emissions of sulfur
monoxide,
nitrogen
oxide,
volatile
organic
compound, particulate matter, and lead have declined due to
the
use
of
cleaner
fuels
with
lower
sulfur
content,
improvement in processes and emission control devices,
and
regulation (EPA, 1991).
While changes in fossil fuel prices may have affected
energy consumption, these changes may also have had impact on
the total output. With lower energy prices, people tend to
consume more energy, and thus increase the total output, and
vice
verse.
A
study
by
John
Tatom
(1979)
suggests
this
causality. He estimates the production function model for the
U.S. private business sector for the quarterly period 1948-1
to 1978-11, by including energy price and capital and labor
resource formations in the model. One of his finding in this
study is
that a rise in the real price of energy leads to a
significant decline in the real output per the flow of capital
services. Therefore, energy price may not belong in our model
since
it
may
be
causally
be
related
to
the
explanatory
variable change in gross domestic product. In fact, we added
real energy price to our models, but it did not improve the
results.
The three models suggest that the later CAA amendments
have not contributed as much to cleaner air as the earlier
CAAs,
as shown in the estimates.
This is probably because
national average ambient air concentration levels for TPM and
SOx have met the standards since around 1970, and CO levels
have met the standards
metropolitan
cities
since around 1980, even though many
still
continue
to
exceed
quality standards for at least one pollutant.
ambient
air
Table 7
Estimates of TPM Ambient Air Level Model, 1960-1990
Dependent variable:
TPM ambient air concentration (/xg/m3/cap) x 10~5
Estimated
parameters
C.O. model
Intercept
16,453 ***)
(4,356)
16.661 ***)
(4.197)
CAA 70
-7,007 ***)
(-5.561)
-7.487 ***)
(-4.989)
CAA 77
-6.396 ***)
(-6.226)
-5.636 ***)
(-4.129)
CAA 90
-
-
CHLN(GDP/POP)
28.004
(1,456)
36.354 **)
(2.196)
CHLNPOP
1978.032 ***)
(7.915)
1939.072 ***)
(6.525)
R square
0.956
0.969
N
31
31
0.848
1.375
a
Original mode
II
variables
D
Independent
Chi square
Notes: C.O. = Cochrane Orcut
t- statistics are in parenthesis
***)
significantat the .01 level
**)
significantat the .05 level
*)
Significantat the .10 level
4.064
Table 8
Estimates of Sox Ambient Air Level Model, 1962-1992
Dependent variable:
Sox Ambient Air Concentration per capita (/Ltg/m3-cap) xl0'5
Independent
Estimated parameters
variables
Original model
C.O. model
Intercept
20.243 ***)
(3,902)
(3.892)
CAA 70
-20.554 *-'*)
(-12.067)
-20.572 ***)
(-12.082)
CAA 77
-3.149 ***)
(-5.868)
-8.147 ***)
(-5.899)
CAA 90
-4.933 **)
(-2.123)
-4.977 **)
(-2.128)
CHLN(GDP/POP)
44.832 *)
(1.741)
44.729 *)
(1.712)
CHLNPOP
1940.594 ***)
(4.709)
1942.047 ***)
(4.698)
R squared
0.970
0.970
N
31
31
DW = d
2.046
2.010
Chi squared
Notes: C.O. Cochrane Orcut
t-statistics are in parenthesis
***)
significant at the .01 level
**)
significant at the .05 level
*)
significant at the .10 level
16.193
Table 9
Estimates of CO Ambient Air Level Model, 1970-1992
Dependent variables
CO ambient air concentration per capita (mg/m3-cap)x 10~5
Estimated
Independent
parameters
variables
Original model
C.O. model
Intercept
19.05'
(1.321)
21.995
(1.356)
CAA 70
_
-
CAA 77
-26.734 ***)
(-9.544)
-26.075 ***)
(-7.332)
CAA 90
-17,644 ***)
(-3.671)
-15„764 ***)
(-3.006)
CHLN(GDP/POP)
27.319
(0.467)
30,676
(0.518)
CHLNPOP
4435.617 ***)
(3.295)
4083.277 ***)
(2.693)
R square
0.902
0.908
N
22
22
»d
ii
£
o
1.544
1.779
Chi square
Notes: C.O. = Cochrane Orcut
t-statistics are in parenthesis
***)
significantat the .01 level
**)
significantat the .05 level
*)
significantat the .10 level
1.780
CONCLUSION
This study developed economic- air pollution models using
the least squared econometrics regression approach. U.S. data
over the 1960- 1992 period is used in the models. For this,
the three states of the environment, namely the ambient air
concentration levels of total particulate matter (TPM), sulfur
oxide
(Sox) , and carbon monoxide
dependent
variables.
determining
variables,
the
which
There
explanatory
(CO) have been treated as
are
some
variables
difficulties
since
many
influence the ambient air levels,
of
in
the
may be
casually related to other explanatory variables. There is no
doubt
that
increasing
the
number
of
observations
could
significantly improve the models, but of course this will take
time.
It
does
seem
appropriate,
however,
to
offer
three
tentative conclusions. First, despite the increase in gross
domestic product (GDP), there is a significant improvement in
the national ambient air quality at least for two ambient air
concentration levels observed:
total particulate matter (TPM)
and sulfur oxide (SOx). In the carbon monoxide (CO) model this
improvement is not significant, perhaps because of the limited
number of observation available in this model. Second, this
improvement may have been related to the increase of marginal
product, the ratio between the change in gross domestic per
capita and the change in energy consumption input since 1970,
and
the
improvement
in
techniques
to
prevent
pollution
(processes, plant operations, and emission control devices).
This improvement may have lowered the emission rate.
Third,
the Clean Air Acts (CAA) have played a significant positive
role in ambient air quality performance through reducing the
emission rate (emission per quantity of the total output), at
least for the three ambient air concentration levels observed
in this study.
Figure la
U.S. Trends in Ambient Air Quality for
TPM, SOx, and Ozone Pollutants, 1970-1992
Ambient Air Quality, 1970-1992
(TPM, SOx, Ozone)
200
§150
sfe
^100
“B
>
50
0
1970
75
----------------- TPM
80
85
90 92
Ozone
----------------- SOx
Source: Environmetal Quality, 1972 and 1991, Statistical
Abstract of the US, 1994 from the EPA.
Notes:The available data for ozone starts in 1974, while for
TPM finishs in 1990.
Figure lb
U.S. Trends in Ambient Air Quality for
N02, CO, and Lead Pollutants, 1970-1992
Ambient Air Quality, 1970-1992
(N02, CO, Lead)
— _ ___
N02
CO
----------------- Lead
Source: Environmental Quality, 1991, 1990 and 1972, Statistical
Abstract of the US, from the EPA.
Notes: The available data for N02 starts in 1974, while for
lead starts in 1975.
Figure 2
Number of Areas Not Attaining Air Pollution
Standards, by Pollutant, 1978 and 1985
Areas Not Attaining Air Pollution
Standards, 1978 and 1985
700
600
*500
|400
'o
1300
E
2200
100
0
Ozone
■
TPM
1978
CO
S02
N02
1985
Source: State of the Environment, 1987 from the EPA
Figure 3
Air Pollution Abatement Expenditures by Sources
1972 - 1991
Air Pollution Abatem ent Expenditures
19 72 -19 91
Total
Mobile sources
Stationary sources
Sources: Statistical Abstract of the U.S., 1994, Survey of Current
Business, February 1984.
Figure 4
U.S. Trends in Energy Consumption per
Gross Domestic Product, 1960-1992
Energy Consumption per GDP, 1960-1992
Source: Calculated from Economic Report of the President, 1991
and 1994,
Annual Energy Review, 1991
Figure 5
Energy Conservation in Industrial Sector , 1960-1985
Industrial Energy Consumed per
Industrial Output, 1960-1985
Source : Annual Energy Review, 1989
Figure 6
Motor Vehicles Efficiency, 1960-1990
Motor Vehicle Efficiency, 1960-1990
25
20
m
»•
§
hj15
<5
■ •
0
1
--------------------------------------------------------------- ^
&
„10
5
0
i i i i i i i i i i i i i i i i i i i i i i i i
1960
65
70
...............
---------------
75
80
t
85
ri
ii
90
Passenger Cars
All Motor Vehicles
Source : Annual Energy Review, 1991
Note: In period 1960-1965 passenger cars included motor cycles
All motor vehicles include passenger cars, motor cycles, buses,
and trucks.
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