atmosphere
Article
Assessment of Air Quality Status in Wuhan, China
Jiabei Song, Wu Guang, Linjun Li and Rongbiao Xiang *
College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China;
[email protected] (J.S.); [email protected] (W.G.); [email protected] (L.L.)
* Correspondence: [email protected]; Tel.: +86-27-8728-2137
Academic Editor: Robert W. Talbot
Received: 18 February 2016; Accepted: 28 March 2016; Published: 13 April 2016
Abstract: In this study, air quality characteristics in Wuhan were assessed through descriptive
statistics and Hierarchical Cluster Analysis (HCA). Results show that air quality has slightly improved
over the recent years. While the NO2 concentration is still increasing, the PM10 concentration shows a
clearly downward trend with some small fluctuations. In addition, the SO2 concentration has steadily
decreased since 2008. Nevertheless, the current level of air pollutants is still quite high, with the
PM10 and NO2 levels exceeding the air quality standard. Seasonal variation exists consistently for all
the pollutants, with the highest concentration in winter and the lowest in summer. Cluster analysis
evidenced that nine urban monitoring sites could be classified into three clusters. Cluster I consists of
only the LY site, which is located in the famous East Lake scenic area with the best air quality. Cluster
II corresponds to three monitoring sites with heavily trafficked roads nearby, where relatively severe
NO2 pollution occurred. Cluster III is comprised of the remaining five sites, characterized by PM10
and SO2 pollution.
Keywords: air quality; cluster analysis; spatiotemporal variation
1. Introduction
Air pollution impacts human health, wellbeing and the environment. In March 2014, the WHO
issued new information estimating that outdoor air pollution in both cities and rural areas was
responsible for the deaths of some 3.7 million people worldwide under the age of 60 in 2012. In addition,
around seven million people died—one in eight of total global deaths—as a result of the joint effects of
household and ambient air pollution in 2012. This finding more than doubles previous estimates and
confirms that air pollution is now the world’s largest single environmental health risk [1].
China is now facing probably the worst air pollution problem in the world [2]. According to the
2013 Report on the State of Environment in China, although 74 cities in China adopted the new strict
air quality standards in 2013, only three out of 74 cities’ air quality met the national standard for good
air quality [3]. Matus et al. evaluated air pollution–related health impacts on the Chinese economy by
using an expanded version of the Emissions Prediction and Policy Analysis model. Results estimated
that the marginal welfare impact of ozone and particulate matter concentrations above background
levels to the Chinese economy increased from 1997 US$22 billion in 1975 to 1997 US$112 billion in 2005,
despite improvements in overall air quality [4]. As a matter of fact, air quality in China has recently
become an issue associated with increasing social unrest.
As the capital of Hubei province, Wuhan is one of the areas with high industrial development
in the country, with high coal consumption, intensive steel manufacturing and smelting activities,
accounting for high emissions of PM and gaseous precursors [5–7]. In comparison with the newly
revised national ambient air quality standard of China (GB3096-2012), the annual average of PM2.5
(particulate matter less than 2.5 µm in size), PM10 (particulate matter less than 10 µm in size), and
nitrogen dioxide exceeded the limited value in 2013. Therefore, a better scientific understanding of the
air quality conditions in Wuhan is necessary.
Atmosphere 2016, 7, 56; doi:10.3390/atmos7040056
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Atmosphere 2016, 7, 56
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nitrogen dioxide exceeded the limited value in 2013. Therefore, a better scientific understanding of
the
air quality
in Wuhan is necessary.
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2016, 7,conditions
56
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Air pollutants including NO2, SO2, CO, PM10, and O3 have been routinely monitored for many
years. Starting in 2013, PM2.5 has also been monitored. Therefore, a massive data set of air pollutants
Air pollutants
including NO
, CO,
have beenspatiotemporal
routinely monitored
for of
many
2 , SO2of
10 , and O3 including
has already
been accumulated.
Much
the PM
information,
patterns
air
years.
Starting
in
2013,
PM
has
also
been
monitored.
Therefore,
a
massive
data
set
of
air
pollutants
2.5
pollution, association among individual pollutants, and correlation with meteorological variables,
has already
accumulated.
of the
including
spatiotemporal
patterns
of air
can
possiblybeen
be assessed
from Much
the data
set.information,
Unfortunately,
exploitation
of the data
for these
pollution,
association
among
individual
pollutants,
and
correlation
with
meteorological
variables,
purposes is scarce. Feng et al. analyzed the variations of PM10 concentrations during 2006–2008can
in
possibly
be
assessed
from
the
data
set.
Unfortunately,
exploitation
of
the
data
for
these
purposes
is
Wuhan [8]. However, only descriptive statistics for PM10 were addressed. In another study, the
scarce. distribution
Feng et al. analyzed
the variations
of PM
concentrations
during
2006–2008
WuhanAir
[8].
10 was
spatial
of PM10 over
86 Chinese
cities
reconstructed
from
publicly in
available
However,
only
descriptive
statistics
for
PM
were
addressed.
In
another
study,
the
spatial
distribution
Pollution Index (API) records for summer102000 to winter 2006 and 14 groups of cities were defined
of PM
86 Chinese
cities
was reconstructed
from
publicly
Air
Pollution
10 over
by
using
a fuzzy
clustering
procedure.
Wuhan was
found
to beavailable
one of the
cities
with aIndex
high (API)
PM10
records
for
summer
2000
to
winter
2006
and
14
groups
of
cities
were
defined
by
using
a
fuzzy
clustering
level in the middle zone. Although latitudinal and longitudinal gradients and inter-annual
procedure.inWuhan
was found towere
be one
of the cities
withwere
a high
PMto
level in the
zone.
10 elucidate
variations
PM10 concentrations
discussed,
no efforts
made
themiddle
relationship
Although
and
longitudinal
inter-annual
variations
in PM
10 concentrations
with
otherlatitudinal
criteria air
pollutants
[9]. gradients
Therefore,and
in-depth
analysis
of the air
quality
data set in
were
discussed,
no
efforts
were
made
to
elucidate
the
relationship
with
other
criteria
air pollutants
[9].
Wuhan is of great significance. In this study, multivariate statistical methods, including
Cluster
Therefore,
in-depth
analysis
of
the
air
quality
data
set
in
Wuhan
is
of
great
significance.
In
this
Analysis (CA) and the non-parametric Mann-Kendall’s test, were employed to characterize the air
study, multivariate
statistical methods, including Cluster Analysis (CA) and the non-parametric
pollution
in urban Wuhan.
Mann-Kendall’s test, were employed to characterize the air pollution in urban Wuhan.
2. Materials and Methods
2. Materials and Methods
The study area is Wuhan (Longitude 113°41’E–115°05′E,
Latitude 29°58′N–31°22′N), the capital
The study area is Wuhan (Longitude 113˝ 41’E–115˝ 051 E, Latitude 29˝ 581 N–31˝ 221 N), the capital
city of Hubei province. It is situated on the east of the Jiang-Han plain, a vast area in the valley of
city of Hubei province. It is situated on the east of the Jiang-Han plain, a vast area in the valley of
the Yangtze River. Wuhan covers an area of around 8494 km22 and has a subtropical moist monsoon
the Yangtze River. Wuhan covers an area of around 8494 km and has a subtropical moist monsoon
climate with four distinct seasons. Currently, there are nine air quality monitoring stations in
climate with four distinct seasons. Currently, there are nine air quality monitoring stations in operation
operation in urban Wuhan (Figure 1), with concentrations of criteria pollutants such as PM2.5, PM10,
in urban Wuhan (Figure 1), with concentrations of criteria pollutants such as PM2.5 , PM10 , NO2 , O3 ,
NO2, O3, CO, and SO2 being routinely recorded. However, PM2.5 has been monitored
only since
CO, and SO2 being routinely recorded. However, PM2.5 has been monitored only since 2013.
2013.
Figure
Figure 1.
1. Location
Location of
of the
the nine
nine monitoring
monitoring stations
stations in
in urban
urban Wuhan.
Wuhan.
Based on
on the
themonitoring
monitoringdata,
data,the
the
daily
quality
is reported
using
thePollution
Air Pollution
daily
airair
quality
is reported
using
the Air
Index Index
(API).
(API).
The
API is calculated
from
the concentrations
of individual
pollutants
byweighting
certain weighting
The API
is calculated
from the
concentrations
of individual
pollutants
by certain
systems,
systems,
andfrom
ranges
0 to 500. only
Initially,
10, NO
2 were included
for calculating
and ranges
0 tofrom
500. Initially,
PM10only
, NOPM
SO22, and
wereSO
included
for calculating
API. CO
2 , and
API.
and
O
3 were
taken
into
account
after
2004
and
PM
2.5 was
involved
only
at
the
end
of study,
2012.
and OCO
were
taken
into
account
after
2004
and
PM
was
involved
only
at
the
end
of
2012.
In
this
3
2.5
In
this
study,
API
data
for
PM
10
,
NO
2
,
and
SO
2
were
collected
from
the
air
quality
publishing
API data for PM10 , NO2 , and SO2 were collected from the air quality publishing platform supported by
platform
by the
Wuhan Agency
Environmental
Protection
Agency
(WHEPA)
for the
period
the Wuhansupported
Environmental
Protection
(WHEPA)
for the period
2001–2011.
In order
to examine
the long-term trend of air pollution, the average concentrations of air pollutants before 2001 were
Atmosphere 2016, 7, 56
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gathered from the annual report on environmental quality issued by WHEPA. In addition, emissions
of air pollutants were obtained from the statistical yearbook.
The information provided by API data sets is limited. Therefore, the API data were converted to
mass concentration using the following formula:
C “ Clow ` rpI ´ Ilow q{pIhigh ´ Ilow qs ˆ pChigh ´ Clow q
where C is the mass concentration and I is the API value. Ihigh and Ilow are the two values closest
to value I in the API grading limited value table, standing for the values larger and lower than I,
respectively; Chigh and Clow represent the concentrations corresponding to Ihigh and Ilow , respectively.
Simple descriptive statistics were performed to obtain the annual average and the monthly
average data. Subsequently, data were compared with the National Ambient Air Quality Standard
(Table 1) to evaluate the overall pollution status in Wuhan. The annual trends in air pollutants’ time
series were investigated with the non-parametric Mann-Kendall’s test and Sen’s method using the
MAKESENS software [10]. Sen’s method uses a linear model to estimate the slope of the trend and the
variance of the residuals should be constant in time.
Table 1. Annual average concentration limits (Class II) as regulated in the standard.
Pollutant
Old Standard (µg/m3 )
New Standard (µg/m3 )
SO2
NO2
PM10
PM2.5
60
40
100
–
60
40
70
35
Multivariate analysis provides a broad range of methods for association, interpretation, modeling
and forecasting from large datasets from environmental monitoring programs [11]. Among them,
Cluster Analysis (CA) is a useful procedure for simplifying and classifying the behavior of
environmental pollutants in a specific region [12]. In order to examine the spatial pattern of air pollution
in urban Wuhan, nine monitoring stations were grouped using Hierarchical Agglomerative Cluster
Analysis (HACA), a distribution-free ordination technique to group sites with similar characteristics
by considering an original group of variables. For measuring the similarity between individual sites,
the Euclidean distance has been used [13].
3. Results and Discussions
3.1. Overview of Air Pollution in Urban Wuhan
Figure 2 shows the annual average concentrations of PM10 , NO2 , and SO2 for the period 2001–2014
and the SO2 concentration for the period 1996–2000. It can be seen that the average concentration of
SO2 remained almost constant during the 1996–1998 period, but dropped clearly in 1999 and 2000.
After that, a continuous increasing trend was witnessed and the SO2 concentration peaked in 2008.
Over the period 2009–2014, significant decline in the SO2 concentration occurred steadily. Fortunately,
all the SO2 concentrations were below the limit value of 60 µg/m3 as set in the Chinese national
ambient air quality standard (CNAAQS). Although the linear regression of annual averages in Figure 2
demonstrates an overall descending trend in SO2 concentration, the Mann-Kendall test indicates
that the trend was not statistically significant. The annual amount of SO2 emission in Wuhan was
plotted in Figure 3. Generally, the annual variation of SO2 concentration is in line with the emission of
SO2 . In 1998, the State Environmental Protection Administration (SEPA) established Acid Rain and
SO2 Pollution Control Zones to halt the increasing trend of SO2 emissions and worsening acid rain.
Therefore, both the SO2 emission and ambient concentration decreased in 1998. On the other hand, due
to rapid economic development and surging energy consumption, the SO2 pollution became worse
again during China’s 10th Five-Year Plan (FYP) (2001–2005). In recognition of this challenge, more
Atmosphere 2016, 7, 56
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control plans wereand
developed
and various
mitigation measures
were
adopted
to curtail
the
SO2
stringent
control plans
were developed
various were
mitigation
measures
were
adopted
control prevention
plans were developed
and various
mitigationand
measures
adopted
to curtail
the
SO2
emissions
during
the
11th
(2006–2010)
and
12th
FYP
(2011–2015).
As
expected,
the
emissions
and
to emissions
curtail theduring
SO2 emissions
the 11th
and 12th FYP
(2011–2015).
expected,
the 11th during
(2006–2010)
and (2006–2010)
12th FYP (2011–2015).
As expected,
the As
emissions
andthe
ambient
concentration
of
SO
2 dropped significantly in the past few years. Actually, this trend has
2D
Graph
1
emissions
ambient concentration
of SO
significantly
in the
past
few years.
ambientand
concentration
of SO2 dropped
significantly
in
the
years.
Actually,
thisActually,
trend hasthis
2 dropped
2D Graph
1 past few
been reported in other Chinese cities [14,15].
beenhas
reported
in other Chinese
[14,15].
trend
been reported
in other cities
Chinese
cities [14,15].
160
160
3
Pollutant
Pollutantconcentration
concentration(g/m
(g/m)3)
140
140
120
120
100
100
80
80
60
60
PM10
PM10
NO2
NO2
SO
SO22
PM10 trend
PM10
trend
NO2 trend
NO2 trend
SO trend
SO22 trend
40
40
20
20
0
01995
1995
2000
2000
2005
2005
2010
2010
2015
2015
Year
Year
Figure
air pollutants
pollutantsininurban
urbanWuhan.
Wuhan.
Figure2.2.Annual
Annualmean
meanconcentrations
concentrations of air
Figure 2. Annual mean concentrations of air pollutants in urban Wuhan.
Linear
regression
of annual
PM
10 concentrations
2001
2014 indicates
PM10
Linear
regression
of annual
PM10PM
concentrations
fromfrom
2001 to
2014toindicates
that PMthat
10 pollution
Linear
regression
of annual
10 concentrations from 2001 to 2014 indicates that
PM10
pollution
was
actuallytoalleviated
to some
extent
(Figure
2). The calculated
Sen’s
slope
of the
trend
was
actually
alleviated
some
extent
(Figure
2).
The
calculated
Sen’s
slope
of
the
trend
was
found
pollution was actually alleviated to some extent (Figure 2). The calculated Sen’s slope of the trend
3 per year at the 95% confidence level. Similar trends have been reported
3
was
found
to
be
−2.0
µ
g/m
3 per
to was
be ´2.0
µg/m
theyear
95%at
confidence
level. Similar
been
reported
for other
found
to be per
−2.0 year
µ g/mat
the 95% confidence
level.trends
Similarhave
trends
have
been reported
for other
Chinese
cities [16].
Owing
to the various
control
measures
and the
advances
achieved in
Chinese
cities
[16]. Owing
to theOwing
various
measures
and
the advances
achieved
in manufacturing
for other
Chinese
cities [16].
to control
the various
control
measures
and the
advances
achieved in
manufacturing
technology,
emissions
of flythe
ash in Wuhan
in the lastadecade
exhibited
a significant
technology,
emissions
of fly ash
in Wuhan
decade in
exhibited
significant
downward
trend as
manufacturing
technology,
emissions
of in
fly ashlast
in Wuhan
the last decade
exhibited
a significant
downward trend as shown in Figure 3. Due to the moderately positive correlation between the
downward
trend
as shown
in Figure 3.positive
Due to correlation
the moderately
positive
correlation
the
shown
in Figure
3. Due
to the moderately
between
the annual
PM10between
concentration
annual PM10 concentration and fly ash emissions (r = 0.67, p < 0.01), the reduction in fly ash
annual
10 concentration
and
ashthe
emissions
(r in
= 0.67,
p <emissions
0.01), theprobably
reductioncontributed
in fly ash in
and
fly ashPM
emissions
(r = 0.67,
p <fly
0.01),
reduction
fly ash
emissions probably contributed in part to the downward trend in the PM10 concentration. However,
emissions
probably contributed
part concentration.
to the downward
trend initthe
PM10 concentration.
However,
part
to the downward
trend in theinPM
However,
is worth
mentioning that
the PM
it is worth mentioning that the PM1010concentrations were still well above
the annual standard of 70 10
3
it
is
worth
mentioning
that
the
PM
10
concentrations
were
still
well
above
the
annual
standard
of 70
concentrations
were
still
well
above
the
annual
standard
of
70
µg/m
.
In
addition,
small
fluctuations
µ g/m33. In addition, small fluctuations can be observed in Figure 2. In particular, there was a sudden
g/m
. In addition,
small 2.
fluctuations
can there
be observed
in Figurerise
2. In
there was
sudden
canµrise
be in
observed
in Figure
In particular,
was
aissudden
inparticular,
2013, implying
that aparticulate
2D
Graph
1 challenging.
2013, implying that particulate matter control
really
2D Graph
1 challenging.
rise
in
2013,
implying
that
particulate
matter
control
is
really
matter control is really challenging.
4
Total
Totalemission
ton)
emissionofofpollutants
pollutants(10
(104ton)
16
16
SO
SO22
fly ash
fly ash
14
14
12
12
10
10
8
8
6
6
4
4
2
2
0
0
1996
1996
1998
1998
2000
2000
2002
2002
2004
2004
2006
2006
2008
2008
2010
2010
2012
2012
2014
2014
Year
Year
Figure 3. SO2 and fly ash emissions in urban Wuhan.
Figure
emissionsin
inurban
urbanWuhan.
Wuhan.
Figure3.3.SO
SO22 and
and fly ash emissions
2016
2016
56
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55 of
5 of 9
100
100
80
80
60
60
40
40
20
20
0
0
20 20
00 00
20 20
01 01
20 20
02 02
20 20
03 03
20 20
04 04
20 20
05 05
20 20
06 06
20 20
07 07
20 20
08 08
20 20
09 09
20 20
10 10
20 20
11 11
20 20
12 12
Fine
day
rate
(%)
Fine
day
rate
(%)
The annual variation for the NO2 concentration is not as significant as PM10 and SO2 (Figure 2).
The
variation
for the
the NO
NO22 concentration
is not
as PM
PM10
10 and
SO
2).
The annual
annual
variation for
concentration
not as
as significant
significant
and
SO22 (Figure
(Figure
2).
However,
the Mann-Kendall
test indicates
a strong is
increasing
trend atas
the 0.01
significance
level
However,
the Mann-Kendall
Mann-Kendalltest
testindicates
indicatesa astrong
strong
increasing
trend
at
the
0.01
significance
level
However,
the
increasing
trend
at
the
0.01
significance
level
and
and Sen’s method gives a positive slope of 0.67 µ g/m33 per year. Further, the NO2 concentrations
and
method
gives
a positiveofslope
of 0.673 per
µ g/m
year. Further,
the NO2 concentrations
Sen’sSen’s
method
gives II
a positive
0.67 µg/m
year.per
Further,
the NO
exceeded
2 concentrations
exceeded
the class
standardslope
in CNAAQS,
which requires
the annual
mean
to be below 40µ
g/m33.
3 . In China,
exceeded
the
class
II
standard
in
CNAAQS,
which
requires
the
annual
mean
to be below
40µ g/m
.
the
class
II
standard
in
CNAAQS,
which
requires
the
annual
mean
to
be
below
40µg/m
not
In China, not much effort was put into NO2 emission control before the 12thFYP (2011–2015). As
a
In
China,
not
much
effort
was
put intocontrol
NO2 emission
control
before
the 12thFYP
(2011–2015).
Asno
a
much
effort
was
into NO
before the
(2011–2015).
As aThat
matter
of fact,
2 emission
matter
of fact,
noput
emission
data
for NO2 was recorded
in12thFYP
the statistical
yearbook.
is the
reason
matter
of
fact,
no
emission
data
for
NO
2
was
recorded
in
the
statistical
yearbook.
That
is
the
reason
emission
data
for NO
recorded
the SO
statistical
yearbook. That is the reason why Figure 3 only
2 was the
why
Figure
3 only
plotted
fly ashinand
2 emissions. Fortunately, control of the NO2 emission
why
Figure
3 only
plotted
the
fly
ash
and
SO
2 emissions.
Fortunately,
controlbecame
of the the
NOmandatory
2 emission
plotted
the
fly
ash
and
SO
emissions.
Fortunately,
control
NO
emission
2
became the mandatory target
in the 12th FYP, when of
thethePM
2.52 pollution attracted worldwide
became
the
mandatory
target
in
the
12th
FYP,
when
the
PM
2.5
pollution
attracted
worldwide
target in the
when the
PMof
attracted worldwide
attention
andunderstood.
the important
2.5 pollution
attention
and12th
theFYP,
important
role
NO2 in secondary
PM2.5 formation
was
A
attention
and
the important
role
of NOwas
2 inunderstood.
secondary A
PM
2.5 formation
was
understood.
role
of
NO
in
secondary
PM
formation
downward
trend
in
the
NO2 level A
is
2
2.5
downward trend in the NO2 level is hopefully expected in the following years.
downward
trend in in
thethe
NO
2 level is years.
hopefully expected in the following years.
hopefully
expected
following
Figure 4 summarizes the percentage of days when the 24h mean concentrations of all criteria
Figure
44 summarizes
summarizes the
of days
the 24h
mean concentrations
concentrations of
criteria
Figuresatisfied
the percentage
percentage
days when
when
mean
of all
all slightly
criteria
pollutants
the national
air quality of
standard.
It is the
clear24h
that
the percentage increased
pollutants
satisfied
the
national
air
quality
standard.
It
is
clear
that
the
percentage
increased
slightly
pollutants
satisfied
the
national
air
quality
standard.
It
is
clear
that
the
percentage
increased
slightly
over the years until 2012. However, it should be kept in mind that the PM2.5 concentration was not
over
years until
until 2012.
2012. However,
it should
should be kept
kept in mind
mind that
that the
the PM
PM2.5
2.5 concentration
concentration was
not
over the
the years
However, it
wasinto
not
considered
before 2012.
Immediately
after the be
new air in
quality standard
(GB3096-2012)
was put
considered
before
2012.
Immediately
after
the
new
air
quality
standard
(GB3096-2012)
was
put
into
considered
before
thequality
new air
quality standard
(GB3096-2012)
was
putgood
into
effect
in 2013
and 2012.
PM2.5 Immediately
was includedafter
in air
assessment,
the percentage
of days
with
effect
in 2013
2013 and
andPM
PM2.5
2.5 was
wasincluded
includedininair
airquality
qualityassessment,
assessment,the
the
percentage
of
days
with
good
effect
in
percentage
of
days
with
good
air quality declined abruptly. Although the air quality in Wuhan improved to a certain degree air
in
air
quality
declined
abruptly.
Although
thequality
air quality
in Wuhan
improved
to a certain
degree
in
quality
declined
abruptly.
Although
the
air
in
Wuhan
improved
to
a
certain
degree
in
the
last
the last decade in terms of PM10 and SO2, the air pollution problem is still very serious.
the
last
decade
in
terms
of
PM
10
and
SO
2
,
the
air
pollution
problem
is
still
very
serious.
decade in terms of PM10 and SO2 , the air pollution problem is still very serious.
Year
Year
Figure 4. Percentage of days with good air quality in each year.
Figure
Figure 4.
4. Percentage
Percentage of
of days
days with
with good
good air
air quality
quality in
in each
each year.
year.
Pollutant
concentration
(μg/m³)
Pollutant
concentration
(μg/m³)
3.2. Monthly Variation of Air Pollution
3.2. Monthly Variation of Air Pollution
Figure 5 presents the average monthly variations of SO2, NO2, and PM10 during the period of
during the
the period of
Figure 5 presents the average
average monthly
monthly variations
variations of
of SO
SO22, NO
NO22, and PM10
10 during
2001–2014 except for the year 2012. In addition, PM2.5 data from 2013 to 2014 were included. It is
2001–2014 except for the year 2012.
data from
from 2013
2013 to 2014 were included. It is
2001–2014
2012. In addition, PM2.5
2.5 data
observed that the monthly variations of pollutants demonstrated “V”-shape curves, which indicate
observed that
demonstrated
“V”-shape
curves,
which
indicate
the
that the
themonthly
monthlyvariations
variationsofofpollutants
pollutants
demonstrated
“V”-shape
curves,
which
indicate
the low pollution levels in summer and high levels on both sides. The varying patterns of
low pollution
levels levels
in summer
and highand
levels
on both
The varying
of concentrations
the
low pollution
in summer
high
levelssides.
on both
sides. patterns
The varying
patterns of
concentrations are almost identical during the same period in each year, i.e., low levels during
are almost identical
same period
eachsame
year, period
i.e., lowin
levels
and
concentrations
are during
almost the
identical
duringinthe
eachduring
year, summer
i.e., low (June,
levelsJuly
during
summer (June, July and August) and high levels in other months. It should be mentioned that the
August)
high
levels
other months.
It should
be other
mentioned
thatItthe
concentrations
in September
summer and
(June,
July
andinAugust)
and high
levels in
months.
should
be mentioned
that the
concentrations in September were as low as those in the summer months. September in Wuhan
were
as low as those
in the summer
months.
in summer
Wuhan might
be regarded
as in
a summer
concentrations
in September
were as
low as September
those in the
months.
September
Wuhan
might be regarded as a summer month in terms of the air quality level.
monthbe
in regarded
terms of the
qualitymonth
level. in terms of the air quality level.
might
as aair
summer
250
250
200
200
PM10
PM10
SO2
SO2
NO2
NO2
PM2.5
PM2.5
150
150
100
100
50
50
0
0
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
00
00
00
00
00
00
00
00
00
00
01
01
01
01
01
c-2 0 c-2 1 c-2 2 c-2 3 c-2 4 c-2 5 c-2 6 c-2 7 c-2 8 c-2 9 c-2 0 c-2 1 c-2 2 c-2 3 c-2 4
De -200 De -200 De -200 De -200 De -200 De -200 De -200 De -200 De -200 De -200 De -201 De -201 De -201 De -201 De -201
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
De
De
De
De
De
De
De
De
De
De
De
De
De
De
De
Figure 5.
5. Monthly
Monthly average
average concentrations
concentrations of
of pollutants
pollutants during
during 2001–2014.
Figure
Figure 5. Monthly average concentrations of pollutants during 2001–2014.
Atmosphere 2016, 7, 56
Atmosphere 2016, 7, 56
6 of 9
6 of 9
In order to look at more closely the monthly variation, average monthly concentrations were
takenInover
FYP
(2001–2005),
FYP variation,
(2006–2010)
and the
first four
years of thewere
12thtaken
FYP
orderthe
to 10th
look at
more
closely the11th
monthly
average
monthly
concentrations
(2011–2014),
respectively.
Figure
6 compares
theand
monthly
concentrations
of(2011–2014),
individual
over
the 10th FYP
(2001–2005),
11th FYP
(2006–2010)
the firstaverage
four years
of the 12th FYP
pollutants
during
each
FYP
period.
The
monthly
SO
2 levels during the 12th FYP were generally
respectively. Figure 6 compares the monthly average concentrations of individual pollutants during
lowerFYP
than
thoseThe
in monthly
other two
periods, which indicates again the effectiveness of the SO2
each
period.
SOFYP
2 levels during the 12th FYP were generally lower than those in other
control
The
PM10the
levels
during 2001–2015
obviously higher than those
two
FYPmeasures
periods, implemented.
which indicates
again
effectiveness
of the SOwere
2 control measures implemented.
during
the
11th
and
12th
FYP
periods
and
the
trend
was
consistent
for
eachthe
month.
On 12th
the other
The PM10 levels during 2001–2015 were obviously higher than those during
11th and
FYP
hand,
the
concentration
variations
of
NO
2 appeared randomly over the three FYP periods, implying
periods and the trend was consistent for each month. On the other hand, the concentration variations
great
should be made to achieve a descending trend. Further, the SO2 concentrations in
of
NOefforts
2 appeared randomly over the three FYP periods, implying great efforts should be made to
summer
(June,
July, trend.
August,
September)
consistently
lower than
in spring
(March,
achieve a descending
Further,
the SO2 were
concentrations
in summer
(June,those
July, August,
September)
April,consistently
May) and lower
autumn
November).The
highest
SO
2 level was observed in winter
were
than(October,
those in spring
(March, April,
May)
and
autumn (October, November).
(December,
January,
February).
A
similar
trend
is
applied
to
PM
10 and NO2, but with some small
The highest SO2 level was observed in winter (December, January, February). A similar trend is applied
fluctuations.
to
PM and NO , but with some small fluctuations.
10
2
Figure6.6.Monthly
Monthlyvariation
variationof
ofair
airpollutant
pollutantlevels
levelsof
of(a)
(a)PM
PM1010; (b)
(b) SO
SO22; (c) NO22..
Figure
3.3. Spatial Distribution of Air Pollutants
Hierarchical
carried
outout
on on
concentration
datadata
set
Hierarchical Agglomerative
AgglomerativeCluster
ClusterAnalysis
Analysis(HACA)
(HACA)was
was
carried
concentration
of
NO
identify
setPM
of PM
10, SO
2, and
NO
2 to
identifythe
thespatial
spatialvariation
variationofofnine
ninemonitoring
monitoringstations
stations based
based on their
10 , SO
2 , and
2 to
similarity levels. The
The dendrograms
dendrograms from
from the
the cluster
cluster analysis
analysis are given in Figure 7. It can be seen
that the nine stations were classified into three clusters. Cluster
Cluster II accommodated
accommodated only
only the
the LY
LY site.
site.
Cluster IIIIwas
with
thethe
three
stations
of YH,
and
JT, and
whileJT,
Cluster
took the
wasformed
formed
with
three
stations
of ZY,
YH,
ZY,
whileIIICluster
IIIremaining
took the
five
stationsfive
of HQ,
GX, XQ,
further
explore
characteristics
in each
remaining
stations
of WJS,
HQ, and
GX,GH.
XQ,ToWJS,
and
GH. the
To pollution
further explore
the pollution
cluster,
contoursinofeach
pollutant
concentrations
were plotted
in Figure 8. Itwere
is obvious
the air quality
characteristics
cluster,
contours of pollutant
concentrations
plottedthat
in Figure
8. It is
in
Clusterthat
I is the
relatively
the best
theIlowest
PM10 , NO
, andwith
SO2 the
levels.
LY station
Cluster
obvious
air quality
in with
Cluster
is relatively
the 2best
lowest
PM10, within
NO2, and
SO2
Ilevels.
is located
in the famous
LakeI scenic
area,inwhere
industrial
and construction
high-rise
LY station
within East
Cluster
is located
the famous
Eastactivity
Lake scenic
area, whereofindustrial
buildings
areconstruction
forbidden. The
local pollutant
sources
scarce and
geometrical
favorable
activity and
of high-rise
buildings
are are
forbidden.
Thethe
local
pollutant layout
sourcesis are
scarce
for
dispersion.
andpollutant
the geometrical
layout is favorable for pollutant dispersion.
Atmosphere 2016, 7, 56
7 of 9
Atmosphere 2016, 7, 56
7 of 9
Atmosphere 2016, 7, 56
7 of 9
Figure
7. Dendrogram
of different
clusters
qualitymonitoring
monitoring stations
stations (y-axis
Figure
7. Dendrogram
of different
clusters
ofofairairquality
(y-axisreports
reportsthe
thelevel
level of
of
dissimilarity,
while
the
dotted
line
is
the
clustering
level).
Figure 7. Dendrogram
of different
of air quality
dissimilarity,
while the dotted
line isclusters
the clustering
level).monitoring stations (y-axis reports the level
of dissimilarity, while the dotted line is the clustering level).
As can be seen from Figure 1, stations of Cluster II are located right in the city centers, which
As characterized
can be seen from
Figure
1, stations of
Cluster II are
locatedand
right
inheaviest
the city centers,
which are
are
byfrom
high
concentrations
activities
the
loadings
As can be seen
Figure
1, stationsofofcommercial
Cluster II are
located right
in the city traffic
centers,
which
characterized
by
high
concentrations
of
commercial
activities
and
the
heaviest
traffic
loadings
almost
almost
entirely around
theconcentrations
clock. Consequently,
the highest
NO2 and
concentrations
observed
in
are
characterized
by high
of commercial
activities
the heaviestwere
traffic
loadings
entirely
around
the
clock.
Consequently,
the
highest
NO
concentrations
were
observed
in
this
cluster
2
this
cluster
(Figure
8c).
On
the
other
hand,
PM
10
and
SO
2
levels
were
lower
than
those
in
Cluster
3.
almost entirely around the clock. Consequently, the highest NO2 concentrations were observed in
(Figure
8c).
On
the
other
hand,
PM
and
SO
levels
were
lower
than
those
in
Cluster
3.
Stations
Stations
in
Cluster
3
are
in
the
outskirts
of
the
city,
where
various
industrial
activities
take
place.
10 hand, PM
2 10and SO2 levels were lower than those in Cluster 3. in
this cluster (Figure 8c). On the other
Cluster
3
are
in
the
outskirts
of
the
city,
where
industrial
activities
Forplace.
example,
For
example,
one
of
the
biggest
steel
companies
is located
near
the GH
station,take
andplace.
the region
of
the
Stations in Cluster 3 are in the outskirts of thevarious
city,
where
various
industrial
activities
take
XQ
station
isone
famous
for
motorsteel
vehicle
manufacturing.
Cluster
III and
features
severe
PM
one For
of the
biggest
steel
companies
is located
nearis the
GHTherefore,
station,
and
the region
of the
XQof
station
example,
of the
biggest
companies
located
near
the GH
station,
the
region
the10 is
andstation
SO2motor
pollution
(Figure
8a,b). vehicle Therefore,
XQ
is famous
for
motor
manufacturing.
Therefore,
Cluster
III features
severe
PM10
famous
for
vehicle
manufacturing.
Cluster
III features
severe
PM10 and
SO2 pollution
and 8a,b).
SO2pollution (Figure 8a,b).
(Figure
Figure 8. Spatial distribution of annual mean concentration of (a) PM10; (b) SO2; (c) NO2.
Figure 8. Spatial distribution of annual mean concentration of (a) PM10; (b) SO2; (c) NO2.
Figure
Spatial
of annual mean
concentration
of (a) monitoring
PM10 ; (b) SOsites
NO2 .
2 ; (c)belonging
Figure
9 8.
shows
thedistribution
monthly concentrations
averaged
over those
to
the same
cluster.
As
expected,
Cluster
I
had
the
lowest
concentrations
each
month
for
all
three
Figure 9 shows the monthly concentrations averaged over those monitoring sites belonging to
Figure
9 shows
the
monthly
concentrations
averaged
over
those
sites belonging
to the
pollutants.
The NO
2 concentration
in Cluster
waslowest
the highest,
and monitoring
the highest
levels
of PM
and
the
same cluster.
As
expected, Cluster
I hadIIthe
concentrations
each month
for
all 10three
same
cluster. As
expected,
Cluster I had
the lowest
each
all three
pollutants.
The
NO2 concentration
in Cluster
II wasconcentrations
the highest, and
themonth
highestfor
levels
of PMpollutants.
10 and
The NO2 concentration in Cluster II was the highest, and the highest levels of PM10 and SO2 appeared
Atmosphere 2016, 7, 56
8 of 9
Atmosphere 2016, 7, 56
8 of 9
in Cluster
III. Thein
trend
is exactly
same
as demonstrated
Figure 8, confirming
correctness of
SO2 appeared
Cluster
III. Thethe
trend
is exactly
the same asindemonstrated
in Figurethe
8, confirming
the correctness
of the clustering result.
the clustering
result.
a
Ⅰ
Ⅱ
Ⅲ
3
PM10(g/m )
150
100
50
b
Jan Feb Mar Apr May Jun
Jul Aug Sep Oct Nov Dec
Jan Feb Mar Apr May Jun
Jul Aug Sep Oct Nov Dec
Month
60
3
SO2(g/m )
80
c
40
20
Month
80
3
NO2(g/m )
60
40
20
Jan Feb Mar Apr May Jun
Jul Aug Sep Oct Nov Dec
Month
Figure
9. Monthly
concentration
siteswithin
within
the
same
cluster.
PM
Figure
9. Monthly
concentrationaveraged
averaged over
over monitoring
monitoring sites
the
same
cluster.
(a) (a)
PM10
; 10 ;
(b)2SO
(c) NO
2
.
(b) SO
; (c)2; NO
.
2
4. Conclusions
4. Conclusions
In this
study,
pollutionindexes
indexesfor
forSO
SO22,, PM
PM10
, and NO2 were gathered from the Wuhan
In this
study,
air air
pollution
10 , and NO2 were gathered from the Wuhan
Environmental
Protection
Bureau
and
converted
to
mass
these
data,
status
Environmental Protection Bureau and converted to mass concentrations.
concentrations.Using
Using
these
data,
status
and variation trends of urban air quality in Wuhan were assessed through descriptive statistics.
and variation trends of urban air quality in Wuhan were assessed through descriptive statistics.
Furthermore, hierarchical cluster analysis (HCA) was performed on the concentration data set from
Furthermore, hierarchical cluster analysis (HCA) was performed on the concentration data set from
nine monitoring stations to identify the spatial pattern of air quality in urban Wuhan.
nine monitoring stations to identify the spatial pattern of air quality in urban Wuhan.
Thanks to the environmental regulations and pollution control measures, air quality has
Thanksimproved
to the environmental
regulations
and10pollution
control
measures,
airdownward
quality hastrend
slightly
slightly
over the recent
years. The PM
concentration
showed
a clearly
improved
over
the
recent
years.
The
PM
concentration
showed
a
clearly
downward
trend
102 concentration has steadily decreased since 2008, due before
before rising in 2013. In addition, the SO
to
rising
2013.implementation
In addition, theofSOflue
has steadily
decreasedpower
since 2008,
the strict
2 concentration
theinstrict
gas desulphurization
in coal-fired
plants.due
A to
notable
implementation
fluethe
gasnumber
desulphurization
in coal-fired
A notable
advance
was2012.
that the
advance wasofthat
of days with
good air power
quality plants.
increased
continuously
until
However,
it dropped
abruptly
in 2013
due to the
implementation
of new
CNAAQSit(GB3095-2012),
number
of days
with good
air quality
increased
continuously
until 2012.
However,
dropped abruptly
in which
PM
2.5 is
taken into account.
The CNAAQS
variation in(GB3095-2012),
annual NO2 concentration
was
in 2013
due to
the
implementation
of new
in which PM
is taken into
2.5 negligible
beforeThe
an variation
increasingintrend
appeared
in 2007, because
the lag in before
emission
legislations
and
account.
annual
NO2 concentration
wasofnegligible
an control
increasing
trend appeared
the
increase
in
fuel
consumption
by
power
plants
and
vehicles.
Nevertheless,
it
is
evident
that
in 2007, because of the lag in emission control legislations and the increase in fuel consumption by
current
level
of vehicles.
air pollutants,
especially PM
and PM2.5that
, is still
quitelevel
high.of
Seasonal
variationespecially
exists
power
plants
and
Nevertheless,
it is10 evident
current
air pollutants,
consistently for all the pollutants, with the highest concentrations in winter and the lowest in
PM10 and PM2.5 , is still quite high. Seasonal variation exists consistently for all the pollutants, with the
summer when the meteorological condition favors pollutant dispersion.
highest concentrations in winter and the lowest in summer when the meteorological condition favors
Based on the concentrations of PM10, SO2, and NO2 over the years, nine urban monitoring sites
pollutant
dispersion.
were classified into three groups. Group I consists of only the LY site, which is located in the
Based
the
concentrations
of PM
, SO2air
, and
NO2 Group
over the
years, nine urban
monitoring
famous on
East
Lake
scenic area with
the10best
quality.
II corresponds
to three
monitoringsites
weresites
classified
into three
groups.
Group
I consists
of only the
LY site,
is located
the famous
with heavily
trafficked
roads
nearby,
where relatively
severe
NOwhich
2 pollution
occurs.in
Group
III
EastisLake
scenic
area
with
the
best
air
quality.
Group
II
corresponds
to
three
monitoring
sites
with
comprised of the remaining five sites, characterized by PM10 and SO2 pollution.
heavily trafficked roads nearby, where relatively severe NO2 pollution occurs. Group III is comprised
Acknowledgments:
was financially
supported
by the National Science Foundation of China (No.
of the
remaining five This
sites,study
characterized
by PM
10 and SO2 pollution.
41275164) and by the Ministry of Science and Technology in South Korea through the Institute of Science and
Acknowledgments: This study was financially supported by the National Science Foundation of China
(No. 41275164) and by the Ministry of Science and Technology in South Korea through the Institute of Science and
Atmosphere 2016, 7, 56
9 of 9
Technology for Sustainability (United Nations University & Gwangju Institute of Science and Technology Joint
Programme) in 2015.
Author Contributions: All authors contributed immensely. Rongbiao Xiang designed the study and modified the
paper; Jiabei Song performed the cluster analysis and drafted the paper. Wu Guang and Linjun Li collected and
analyzed the data.
Conflicts of Interest: The authors declare no conflict of interest.
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