Introduction
Bottom-up emission inventories, which are compiled from activity rates and
emission factors, provide crucial information for understanding the
variability of atmospheric compositions and for regulating climate and air
quality policies. However, the current understanding of anthropogenic
emissions in China is insufficient because of a lack of underlying data such
as detailed activity rates and local measured emission factors (Zhao et al.,
2011). This paper is the second in a series that aims to reduce these
uncertainties and to improve the spatial and temporal resolution of
bottom-up emission inventories in China. The first paper developed a
high-resolution emission map for on-road vehicles (Zheng et al., 2014), and
this paper focuses on coal-fired power plants.
Power plants have consumed approximately half of the total coal production in
China over the past decade (China Energy Statistical Yearbook, National
Bureau of Statistics (NBS), 1992–2011) and contributed significantly to the
total national emissions of greenhouse gases and air pollutants (32 % of
CO2, 33 % of SO2, 33 % of NOx, and 6 % of PM2.5 in
2010, Y. Zhao et al., 2013). Therefore, developing a coal-fired power plant
emission inventory with high spatial and temporal resolution can
significantly improve the accuracy of the anthropogenic emission inventory
in China. In the meanwhile, because the power plant sector plays a key role
in energy and environmental policies, a well-developed power plant database
with accurate energy consumption and emission data could help to guide
future policies and evaluate the dynamic changes in emissions induced by
those policies.
As one of the major anthropogenic emitting sources, coal-fired power plant
emissions in China have been estimated in many national, regional, and
global inventories. Early studies (Kato and Akimoto, 1992; Klimont et al.,
2001; Hao et al., 2002; Ohara et al., 2007) used yearly activity data with
fixed emission factors to estimate emissions, which ignored the fact that
the net emission rates were changing rapidly with the emergence of new
technologies into the market. In recent studies, technology-based
methodologies and locally measured emission factors have been used to represent
the dynamic changes in emissions, which has improved the accuracy of the
magnitudes of and trends in power plant emissions throughout China (e.g.,
Zhang et al., 2007, 2009a; Klimont et al., 2009, 2013; Lei et al., 2011; Tian et al., 2013; Y. Zhao et al., 2013).
In addition to the accuracy of the magnitudes, accurate information for each
generation unit (i.e., location, emissions) is also critical for a power
plant inventory because power plant emissions are typically large, and
improper treatment may lead to significant bias in the spatial distribution
of emissions. Owing to the difficulties in acquiring information for all of
the power plants in China, many bottom-up inventories only identified
emissions from large power plants and allocated them according to their
latitude and longitude coordinates, whereas emissions from other small units
were distributed as area sources (e.g., Streets et al., 2003; Ohara et al.,
2007; Zhang et al., 2009a; Lu et al., 2011). For the first time, Zhao et al. (2008) used unit-level coal consumption to calculate emissions of
individual electric generation units for the years of 2000 and 2005 and
assigned them to each location. Subsequent studies developed unit-based
power plant emission inventories for NOx for the period of 2005–2007
(Wang et al., 2012) and for SO2, NOx, particulate matter and
PM2.5 for 2011 (Chen et al., 2014). The Carbon Monitoring for Action
(CARMA) database (Wheeler and Ummel, 2008), a global power plant database at
the factory level, has been widely used in bottom-up emission inventories to
allocate power plant emissions (EC-JRC/PBL, 2011; Oda and Maksyutov, 2011;
Kurokawa et al., 2013; Wang et al., 2013). However, the accuracy of the
emission strengths and locations in the CARMA database is questionable given
that it is not a scientific-level data set that has undergone critical
evaluation (Oda and Maksyutov, 2011; Gurney, 2012).
There are two major deficiencies in the current power plant inventories
throughout China for revealing emissions at the unit level. First, owing to
the lack of detailed information at the unit level, emissions from each
plant are generally divided by the provincial totals according to capacity
(e.g., Zhang et al., 2009a; Lu et al., 2011), which ignores the differences
in the emission rates among units introduced by different technologies.
Second, in a rapidly developing country such as China, emission factors for
a given power plant may change over time as new combustion or emission
control technologies are applied following the implementation of new
emission standards. Therefore, these time-dependent parameters should be
included dynamically when constructing an accurate emission trend for the
power plants in China.
The purpose of this study was to develop a high-resolution inventory of the
technologies, activity rates, and emissions of coal-fired power plants in
China for the period of 1990–2010 using extensive underlying data at the
unit level, supplemented with aggregated data where unit-based information
is not available. This is the first time that coal-fired power plant
emissions in China were estimated for each unit from the bottom-up for a
2-decade period. We construct a unit-based database, called the China
coal-fired Power plant Emissions Database (CPED), by collecting information
regarding the technologies, activity data, emission factors, and locations
of individual electricity generating units. To improve the accuracy of the
emission estimates at the unit level, the database developed in this study
includes not only the type and removal efficiency of emission control
equipment for each unit but also the operating conditions of the equipment
(i.e., when the equipment was commissioned).
Based on the unit-specific parameters from the CPED (e.g., unit capacity,
boiler type, operation and phasing-out procedures, the sulfur content and
ash content of coal, the type of emission control equipment and the time at
which the equipment was commissioned, along with its removal efficiency),
the SO2, NOx, fine particulate matter (PM2.5), PM10, and
CO2 emissions were estimated on a monthly basis for each coal-fired
power generation unit over the period of 1990–2010. CO, Volatile Organic Compound (VOC), Black Carbon (BC) and Organic Carbon (OC)
emissions were not estimated in this work because coal-fired power plants
contributed very small fractions to national total emissions of these
species (e.g., less than 1 % of total CO emissions in 2010 estimated by Y.
Zhao et al., 2013).
Unit-based methodology and data
The CPED database developed in this study consists of 7657 coal-fired
electric-generating units in mainland China, including ∼ 5700
units in use in 2010 and ∼ 1900 units that have retired since 2005. The
SO2, NOx, PM2.5, PM10 and CO2 emissions from a
specific unit in a given month from 1990 to 2010 were estimated using the
following equation:
Emiss,y,m=U×P×(H0/Hy)×Ty×fm,y×EFs,k,y×∏n(1-ηn,s×τn,m,y),
where s represents the emission species, k represents the boiler type, n
represents the emission abatement technology type, y represents the year, and
m represents the month. U is the unit capacity, in MW, P is the coal
consumption rate presented in grams coal equivalent per kWh supplied
(gce kWh-1), H is the heating value of coal used for each unit in kJ g-1,
H0 is the heating value of standard coal, which is 29.27 kJ gce-1,
and the ratio of H0 to H converts the coal equivalent (gce) to the
physical quantity of coal (gram). T is the annual operation in hours, the
product of U and T is the annual electricity generation, f is the monthly
fraction of annual electricity generation, and EF is the unabated emission
factor, in g kg-1 of coal. The parameter η is the removal efficiency of the
abatement equipment, and τ is the state factor for the abatement
equipment; τ= 1 when the equipment is present and running,
otherwise τ= 0.
Activity rates
Detailed activity data are available for each generation unit for the period
of 2005–2010 from China's Ministry of Environmental Protection (MEP;
unpublished data, referred to hereafter as the MEP database). We used the
MEP database as the basis of deriving the activity rates for each unit for
the period of 1990–2010 from a combination of different data sets. The
capacity (U) and operational status (when the unit was
commissioned/decommissioned) for each unit were collected from the
MEP database and the National Development and Reform Commission (NDRC,
2013). The annual coal use and power generation of each unit from 2005 to
2010 were also obtained from the MEP database and were used to calculate the
coal consumption rate (P) for each unit. The details about the generation
unit fleet mix according to capacity size and efficiency are presented in
Sect. 3.1.
The heating value of the coal (H) used for each unit in 2010 was obtained
from the MEP database. In other years for which the unit-level data are not
available, the average heating values of the coal used in power plants were
derived by year and by province from the energy statistics (NBS, 1992–2011)
and were then adapted to scale the 2010 value of each unit to the
corresponding years. The heating values of coal have decreased remarkably since
2007 (from 20.0 kJ g-1 coal in 2007 to 18.8 kJ g-1 coal in 2010 as the national
average), indicating the downgraded coal quality in the power sector due to
a shortage of coal induced by a surge of electricity demand in recent years
(Liu, 2007; Shen and Song, 2010). Table S3 in the Supplement
summarizes the provincial average of coal consumption rate and heating value
for the year 2010.
The annual operating hours (T) for each unit from 2005 to 2010 were obtained
from the MEP database. In other years for which the unit-based data are not
available, operating hours were scaled from the 2005 data according to the
ratio of the provincial average operating hours in 2005 and the
corresponding year. The provincial average operating hours before 2005 were
estimated from the provincial total coal consumption (NBS, 1992–2011) and
the product of the corresponding unit capacity and the coal consumption rate
obtained from our database. It should be noted that emissions estimates
prior to 2005 are more uncertain because the extrapolated parameters were
used.
The monthly fraction of annual electricity generation (f) is quantified by
province, due to the lack of data at unit level. For 2003–2010, f was
derived from the statistics (NBS, 2013) and was applied to the units with
adjustments if the unit was commissioned or decommissioned within that year,
following Eq. (2). For the years prior to 2003, a monthly climatological
profile of the 2003–2007 average was used.
fm=γmFm∑m=112γmFm,
where m represents the month. f and F is the monthly fraction of annual
electricity generation at unit and province level respectively. γ is
the state factor for the unit; γ= 1 when the unit has been
commissioned and in operation, otherwise γ= 0.
Coordinates of each unit (latitude and longitude) were obtained from the
MEP database and then individually validated using Google Earth to ensure
that the accurate locations are presented in the CPED.
Emission factors
SO2
The unabated SO2 emission factors for a specific unit were estimated
via the sulfur mass balance approach using the following equation:
EFSO2,y=2×SCCy×(1-Sr),
where y represents the year, EFSO2 is the unabated SO2 emission
factor in g kg-1, SCC is the sulfur content of coal, and Sr is the fraction of
sulfur retention in ash.
The SCC for each unit from 2005 to 2010 was obtained from the MEP database. The
SCC ranges widely, with a mean value of 0.95 %. The SCC in the northeast power
plants is lowest, whereas the SCC in the central and south power plants is
significantly higher than that of plants in other regions, reflecting the
different sulfur content in coal production in the various regions (Tang et
al., 2008). For the years before 2005, the SCC for each unit was scaled from
2005 data using the ratio of the provincial average SCC in 2005 and the
corresponding year. The provincial average SCC before 2005 was calculated from
the sulfur contents of coal production in each province using the coal
transportation matrix approach (Zhang et al., 2012). The sulfur retention
ratio was assumed to be 15 % for all of the units (Zhang et al., 2009a; Lu
et al., 2010) because of the lack of unit-specific data.
Flue gas desulfurization (FGD) systems have been widely installed in
coal-fired power plants in China since 2005. This has been the most important step
for the emission reduction plan to reduce national SO2 emissions by
10 % during the 11th Five-Year Plan (2005–2010). In this study,
the operating conditions of FGD for each unit were obtained from the
MEP database. The actual SO2 removal efficiencies for each unit in 2010
were also obtained from the MEP database and were applied to every year
because no data are available for the other years. The coal-consumption
weighted mean SO2 removal efficiency of all FGD facilities in 2010 is
78 %. Surveys and satellite observations confirmed that some of the early
installed FGD facilities were not actually in operation prior to 2008 as the
factories reported (Xu et al., 2009; Li et al., 2010; Xu, 2011), implying
that our assumption may underestimate the SO2 emissions from 2005 to
2007 for some units. SO2 emissions can also be removed from wet
scrubbers as a co-benefit of particulate matter removal. In this study, we
assumed that the removal efficiency of wet scrubbers for SO2 is 20 %
(Yao, 1989; Xie, 1995).
NOx
NOx emission rates from coal-fired power plants vary significantly by
boiler size, combustion technology, and coal type. In this study, we
classified the units into three categories by size: large units (≥ 300 MW), medium units (≥ 100 and < 300 MW), and small units (< 100 MW). We
also classified the units into three categories by combustion technology
(traditional low-NOx burner technology (traditional LNB), advanced LNB,
and without LNB (non-LNB)) and into two categories by coal type (bituminous
and anthracite). Table 1 summarizes the measured NOx emission factors
in China's coal-fired power plants from each category.
Summary of NOx emission factors for different types of
coal-fired power plants.
Unit size
Combustion
Bituminous coal, g kg-1a
Average emission
Anthracite coal, g kg-1a
Average emission
technology
factor, g kg-1a
factor, g kg-1a
Large (≥ 300 MW)
Advanced LNBb
2.881,3.052,3.283,3.554,4.135, 4.176,4.647
4.06
6.147,6.584,6.998
6.50
Traditional LNB
4.409,4.9810,5.2311,5.0612, 5.658, 7.784
5.08
4.6111,4.9912,7.777,7.948,8.0510,8.739
8.04
Medium (≥ 100 MW
Traditional LNB
4.3410,5.5211,6.9713
6.78
7.0711,7.5610
7.29
and < 300 MW)
Non-LNB
5.4614,8.1211
7.63
8.2510,12.1111
10.46
Small (< 100 MW)
Non-LNB
6.5515,6.8811
6.66
10.0115,11.5011
10.50
a Sample weighted mean. b LNB: low-NOx burners. Data sources: 1 Qian (2010), 2 Cao and Liu (2011), 3 Zhu (2009),
4 Wang et al. (2008), 5 Yi et al. (2006), 6 Zhu et al. (2009), 7 Xie et al. (2008), 8 Wang et al. (2007), 9 Bi and Chen (2004), 10 Tian (2003),
11 Zhu (2011), 12 Zhu et al. (2004), 13 Feng and Yan (2007), 14 Zhao et al. (2010), 15 Zhao et
al. (2008)
Selective catalytic reduction (SCR) and selective noncatalytic reduction
(SNCR) are two major de-NOx technologies used in coal-fired power
plants. In 2010, 194 coal-fired electric generation units (13 % of the
national total capacity) with a total capacity of 84 GW were equipped with
SCR or SNCR. However, the actual operating conditions of the installed
de-NOx devices are questionable due to the lack of inspections by local
environmental protection bureaus before 2010. Our recent study also found
that satellite-recorded tropospheric NO2 columns around the power
plants with de-NOx devices were stable before 2010, indicating the poor
operating conditions of these devices (Wang et al., 2015). In this study, we
assumed that the de-NOx devices were not in operation until 2010 by
setting the state factor in Eq. (1) to 0.
Prior to 2010, LNB technology was the only widely used technology in China's
power plants to reduce NOx emissions. Beginning in 1997, the use of LNB
technologies in China's power plants increased, following the strengthened
emission standards for thermal power plants (State Environmental Protection
Administration of China (SEPA), 1996, 2003) in China. Since approximately
2005, newly established large generation units have been widely equipped
with advanced LNB technologies, i.e., the stereo-staged combustion
technology (Zhang et al., 2009b) and the so-called “double-scale”
combustion technology, which can significantly reduce the emission rates of
NOx. Recent measurements of China's coal-fired power plants confirmed
that NOx emission rates from large units with advanced LNB technologies
are remarkably lower than units with traditional LNB technologies (e.g., Zhu
et al., 2009; Zhu, 2011; Cao and Liu, 2011; see Table 1).
Based on the discussion above, we assigned the appropriate LNB technology to
each generation unit according to the following assumptions, given that the
LNB information was absent from the MEP database. (1) All large units
constructed before 2006 are equipped with traditional LNB, and units
constructed after 2006 are equipped with advanced LNB; (2) medium units
constructed after 1997 are equipped with traditional LNB to meet the
emission standards (SEPA, 1996), whereas units constructed before 1997 are
not equipped with LNB; and (3) no small units are equipped with LNB during
the study period. We then used the emission factors presented in Table 1 to
calculate the NOx emissions for each unit.
PM
PM emissions were estimated for two size fractions: PM2.5 and
PM2.5-10 (PM with diameter more than 2.5 µm but less than 10 µm, coarse particles). The unabated emission factor of PM was calculated
using the following equation:
EFk,d=AC×(1-ark)×fk,d,
where k represents the boiler type, d represents the diameter range of PM;
EFd is the emission factor of PM in diameter d, AC is the ash content of
coal, ar is the mass fraction of retention ash, and fd is the mass
fraction of PM in diameter d to the total particulate matter in fly ash.
When calculating PM emissions, coal-fired generation units are classified
into three boiler types: pulverized coal boilers, circulating fluidized
beds, and grate furnaces. The boiler-type information for each unit was
obtained from the MEP database. For each boiler type, the fraction of
retention ash was derived from the Greenhouse Gas and Air Pollution
Interactions and Synergies (GAINS) database (Klimont et al., 2002; Amann et
al., 2011), with values of 20, 44, and 85 % for pulverized coal
boilers, circulating fluidized beds, and grate furnaces, respectively. The
mass fraction of PM in diameter d to total particulate matter in fly ash was
derived from the GAINS (Klimont, et al., 2002; Amann et al., 2011) and local
databases (Zhao et al., 2010), as presented in Table 2. The ash content of
coal for each unit in 2010 was obtained from the MEP database and was
applied to every year. Table S3 presents the provincial average of coal
sulfur content and ash content for the year 2010.
The four types of technologies used in power plants to remove particulate
matter are cyclones, wet scrubbers, electrostatic precipitators, and bag
filters. The technology type for each unit was obtained from the
MEP database. The removal efficiencies of each technology were obtained from
our previous study (Lei et al., 2011) and are shown in Table 3. Particulate
matter can also be removed via wet FGD as a co-benefit of SO2 removal.
In this study, we assume the same PM2.5 removal efficiency for wet FGD
equipment as that for wet scrubbers (Zhao et al., 2010). The uncertainty of
the effect of the assumption on PM emissions was discussed in Sect. 4.1.
Summary of the mass fractions of particulate matter of different
size fractions to the total particulate matter in fly ash for different
types of boilersa; values are given as percentages (%).
Size
Boiler type
fraction
Pulverized
Circulating
Grate
boilers
fluidized beds
furnaces
PM>10
77
71
63
PM2.5-10
17
22
23
PM2.5
6
7
14
a Data sources: Klimont et al. (2002) and Zhao et al. (2010).
CO2
The emission factor for CO2 was calculated using guidelines from the
Intergovernmental Panel on Climate Change (IPCC, 2006), as follows:
EFCO2,y=A×O×44/12×Hy,
where y is the year, EFCO2 is the CO2 emission factor in g kg-1, A is the
carbon content in kg C GJ-1, O is the oxidization rate, and H is the heating
value in kJ g-1 of coal. In this study, we used 25.8 and 26.7 kg C GJ-1 for the
carbon contents of bituminous and anthracite coal, respectively, and 100 %
for the oxidization rate; these values were obtained from the IPCC
guidelines (IPCC, 2006). The data source of the coal heating value is
presented in Sect. 2.1.
Removal efficiencies of different control technologies for SO2
and particulate matter; values are given as percentages (%).
Technology
SO2
PM2.5
PM2.5-10
PM>10
Cyclones
10
70
90
Wet scrubbers
20
50
90
99
Electrostatic precipitators
93
98
99.5
FGDa
78b
50
90
99
Bag filters
99
99.5
99.9
a FGD: flue gas desulfurization. b Time-dependent parameter, 78 % is the coal-consumption weighted mean efficiency in
2010.
Uncertainty analysis
An uncertainty analysis was performed for our estimates using a Monte Carlo
approach. The term “uncertainty” in this study refers to the lower and
upper bounds of a 95 % confidence interval (CI) around a central estimate.
The Monte Carlo simulation uses specified probability distributions for each
input parameter (e.g., activity data, emission factors) to generate random
variables. The probability distribution of emissions is estimated according
to a set of runs (10 000 runs in this study) in a Monte Carlo framework with
probability distributions of the input parameters (Lu et al., 2011; Zhao et
al., 2011). Table S1 summarizes the
probability distributions of all of the input parameters used to estimate
the uncertainties of the national total emission estimates. For parameters
with adequately measured data (e.g., NOx emission factors),
distribution functions were fitted from the distributions of those data.
Probability distributions of other parameters were obtained from previous
studies (Zhao et al., 2010, 2011; Lu et al., 2011) or were based on our own
discretion.
Uncertainties associated with emission estimates could vary with time. The
uncertainties for a unit in 1990 can be considered larger than the
uncertainties in 2010, for which all of the specific information is
available in the CPED. In this study, we also calculated the emission
uncertainties of one selected generation unit for 2000 and 2010 to
demonstrate the uncertainties at the unit level. The probability
distributions of the unit-level parameters are presented in Table S2. In contrast to uncertainty analyses for national
total emissions, we used discrete distributions (i.e., “yes/no”
distributions) to represent the probability distributions of the
technologies which represent situations in which our assumptions about the
technology for a specific unit are correct/incorrect.
Results
Evolution of technologies in coal-fired power plants
The energy efficiency of power plants in China has improved significantly
over the past 2 decades. As shown in Fig. 1, the average coal consumption
per unit electricity supplied decreased from 407 gce kWh-1 in 1990 to
327 gce kWh-1 in 2010, representing an improvement of 20 % in energy efficiency
over 20 years. This significant change could be attributed to the measures
imposed by the Chinese government to encourage large-scale power units and
to decommission small units. Figure 1 also presents the variation trend in
the share of units of different sizes from 1990 to 2010. The share of the
unit capacity of large units (≥ 300 MW) increased sharply from 18 % in
1990 to 74 % in 2010, whereas the share for small units (< 100 MW)
dropped to 9 %. In particular, the construction rate of large units equal
to or larger than 600 MW began to accelerate after 2005. The capacity of
units equal to or larger than 600 MW was only 46 GW in 2005 but increased to
262 GW by 2010, accounting for 39 % of the national total capacity.
Trends in generation mix by capacity and the average coal
consumption rates (black line) during 1990–2010.
Figure 2 further examines the measures taken to drive the rapid change from
2005 to 2010. To fulfill the increasing demand for electricity, China
constructed 417 GW capacities from 2005 to 2010, of which 83 % were large
units. Figure 2a shows the growth of new power units since 2005. During this
time, large units began to account for a greater share of new units. For all
of the newly constructed units, the percentage of large units increased
significantly from 29 to 49 % from 2006 to 2010, whereas the percent
of small units decreased from 57 to 41 %. In addition, the
construction of new power generation capacity decreased from 86 GW in 2006
to 66 GW in 2010. In the meanwhile, China has taken measures to phase out
low-efficient power plants. Figure 2b illustrates that small units,
especially those smaller than 25 MW, constitute the largest component of
retired units, accounting for 89 % of the number of retired units in 2006.
However, this ratio dropped to 62 % in 2010 because the phase-out strategy
gradually pursued larger units once the majority of units smaller than 25 MW
had been phased out. The average capacity of the units retired in 2010 was
40 MW, 3 times the value in 2006 (13 MW).
Cumulative ratio of unit number for (a) newly constructed and
(b) retired electric-generating units for 2006, 2008, and 2010. The units are
sorted according to ascending capacity along the x axis.
Distribution of coal consumption rates in coal-fired power
plants in 2005 and 2010.
The great effort from 2005 to 2010 to construct large units and phase out
small units significantly improved China's power plant energy efficiency,
which is indicated by the shift of the coal consumption rate shown in Fig. 3. Figure 3 compares the number of plants by coal consumption rate (gce/kWh)
in 2005 and 2010. In 2005, 62 % of power plants in China had a coal
consumption rate of 400–700 gce kWh-1, and 20 % of power plants had a
consumption rate greater than 700 gce kWh-1. In 2010, 57 % of power plants
in China had a coal consumption rate of 400 gce kWh-1 or lower. Generally,
large units consume less coal than small units for the same amount of
electricity generated because of the more advanced combustion technology
used in larger units such as supercritical and ultra-supercritical technology. From
2005 to 2010, with the increase in the number of large units, the average
coal consumption rate decreased from 356 to 327 gce kWh-1,
representing an 8 % total efficiency improvement from 2005 to 2010.
Interannual emissions
Figure 4 and Table 4 summarize the emissions of each species from China's
coal-fired power plants during 1990–2010. The total coal consumption in
China's coal-fired power plants increased significantly by 479 % in China
from 1990 to 2010, whereas SO2 emissions from the power plants
increased by 56 %, NOx emissions increased by 335 %, CO2
emissions increased by 442 %, PM2.5 emissions decreased by 23 %,
and PM10 emissions decreased by 27 % during the same period,
indicating that significant technological changes occurred in the power
sector. Table 4 also presents the variation in technology penetration rates
and emission factors of coal-fired power plants from 1990 to 2010.
Capacity sizes, technology penetrations, fuel qualities, emission
factors, and emissions of coal-fired power plants in China from 1990 to 2010.
Category
Subcategory
1990
1995
2000
2005
2006
2007
2008
2009
2010
< 100 MW
39.3 %
34.0 %
29.1 %
25.5 %
23.1 %
19.1 %
15.3 %
13.1 %
11.5 %
Capacity
(100, 300) MW
48.7 %
44.0 %
35.7 %
31.1 %
29.1 %
26.7 %
23.9 %
21.4 %
18.7 %
sizea
(300, 600) MW
10.9 %
19.9 %
30.1 %
33.4 %
34.0 %
33.2 %
33.3 %
34.3 %
35.4 %
≥600 MW
1.2 %
2.2 %
5.0 %
9.9 %
13.8 %
21.0 %
27.5 %
31.2 %
34.4 %
Traditional LNB
12.0 %
22.1 %
38.7 %
53.7 %
51.8 %
46.6 %
44.2 %
42.1 %
39.4 %
Advanced LNB
0.0 %
0.0 %
0.0 %
0.0 %
7.4 %
19.8 %
29.2 %
35.9 %
42.0 %
Technology
FGD
0.1 %
1.0 %
2.1 %
12.2 %
29.5 %
49.9 %
70.2 %
81.9 %
85.6 %
penetrationa
Cyclones
7.6 %
7.4 %
5.2 %
3.6 %
3.0 %
2.3 %
1.6 %
0.7 %
0.3 %
Wet scrubbers
46.3 %
40.4 %
19.0 %
6.9 %
6.1 %
5.0 %
3.9 %
3.1 %
2.5 %
Electrostatic precipitators
44.3 %
49.8 %
72.5 %
86.1 %
87.5 %
89.1 %
90.8 %
92.0 %
92.8 %
Bag filters
1.7 %
2.3 %
3.3 %
3.4 %
3.4 %
3.5 %
3.7 %
4.2 %
4.4 %
Heating value
20.1
20.2
21.0
19.0
19.3
20.0
19.3
18.9
18.8
(kJ g-1 of coal)
Fuel quality
Coal consumption rate
406.7
389.0
374.3
356.4
351.8
343.5
335.3
330.5
327.1
(gce kWh-1)
Sulfur content (%)
1.07
1.12
1.10
1.04
1.03
1.00
0.97
0.95
0.95
SO2 (g kWh-1)
10.73
9.82
9.15
8.69
7.47
5.34
4.06
3.00
2.48
NOx (g kWh-1)
4.14
3.82
3.37
3.41
3.23
2.92
2.84
2.78
2.67
PM2.5 (g kWh-1)
2.34
1.84
1.12
0.73
0.62
0.48
0.39
0.31
0.27
Emission
PM10 (g kWh-1)
3.89
3.11
1.92
1.29
1.09
0.83
0.66
0.50
0.42
factor
CO2 (g kWh-1)
1126.1
1077.1
1036.5
986.9
974.1
951.2
928.4
915.1
905.6
SO2 (g kg-1 of coal)
18.12
17.42
17.52
15.85
14.03
10.62
7.98
5.84
4.89
NOx (g kg-1 of coal)
7.00
6.78
6.46
6.23
6.07
5.81
5.58
5.41
5.26
PM2.5 (g kg-1 of coal)
3.95
3.26
2.14
1.33
1.17
0.96
0.77
0.61
0.53
PM10 (g kg-1 of coal)
6.58
5.51
3.67
2.35
2.05
1.66
1.29
0.97
0.83
CO2 (g kg-1 of coal)
1902.9
1910.8
1984.8
1801.2
1828.1
1890.6
1822.9
1784.3
1781.9
SO2 (Tg yr-1)
4.94
7.74
9.27
16.70
16.73
14.15
10.96
8.22
7.71
NOx (Tg yr-1)
1.91
3.01
3.42
6.56
7.24
7.75
7.67
7.62
8.29
Emissions
PM2.5 (Tg yr-1)
1.08
1.45
1.13
1.40
1.39
1.28
1.06
0.85
0.83
PM10 (Tg yr-1)
1.79
2.45
1.94
2.48
2.44
2.21
1.77
1.37
1.32
CO2 (Pg yr-1)
0.52
0.85
1.05
1.90
2.18
2.52
2.51
2.51
2.81
a Shares of coal consumption for each capacity size/technology.
SO2
Figure 4 shows the SO2 emissions from power plants estimated in this
study. From 1990 to 2005, SO2 emissions increased at an annual rate of
8 %, driven by the ever-increasing demand for electricity, at a growth
rate of 10 %. The improved energy efficiency and co-benefit of wet
scrubbers on SO2 removal slightly mitigated the emission growth trend.
In 2005, to control emissions, China began to require the installation of
FGD in power plants (Table 4). Therefore, the SO2 emissions peaked at
16.7 Tg in 2006 and began to decrease sharply. By 2010, 84 % of the total
unit capacity in our database was equipped with FGD, which was estimated to
reduce SO2 emissions to 7.7 Tg, 54 % lower than the 2006 emission
level.
Figure 5 presents the FGD installation process. As shown in Fig. 5, in 2006,
FGD was primarily installed for new units, and the share of unit capacity
installed with FGD was 69 % for new units, whereas it was only 15 % for
those over 10 years old. Influenced by the premium price for desulfurized
electricity and the penalties incurred for non-desulfurized electricity
since 2007 (Xu et al., 2009), the deployment of FGD sharply increased for
new and aged units. As Fig. 5 shows, there was no difference in the FGD
installation ratio between new and aged units younger than 20 years old in
2010, and the share of the unit capacity with FGD reached 63 % for units
over 10 years old.
Coal consumption and emissions of SO2, NOx, PM2.5,
PM10, and CO2 of coal-fired power plants in China from 1990 to
2010.
However, the SO2 removal efficiencies vary among the different units.
As presented in Fig. 6, FGD equipped on larger units exhibited better
SO2 removal efficiencies than that on small units. In 2010, the average
SO2 removal efficiencies were approximately 80 % for large units but
only 60 % for small units. Figure 7 presents the cumulative ratio of
SO2 emissions by unit size for 2005 and 2010. The cumulative ratio of
the unit capacity was comparable to that of the SO2 emissions in 2005
(Fig. 7a), but they differed significantly in 2010 (Fig. 7b). The capacity
share of small units decreased from 20 % in 2005 to 9 % in 2010, but the
contribution to the total SO2 emissions remained unchanged at
∼ 20 %. Before 2005, the emission contribution to SO2
of a power unit was largely dependent on its capacity because
desulfurization devices were seldom employed at that time. Thus, the
cumulative ratios of the unit capacity and SO2 emissions could be
similar. However, in 2010, 92 % of large units were equipped with FGD,
which is considerably higher than the number of small units (52 %). In
addition, large units tend to have higher SO2 removal efficiencies. In
2010, large units contributed to 55 % of the total SO2 emissions in
2010, while comprising 76 % of the total capacity.
Distributions of FGD penetration for electric generating units of
various ages in 2006, 2008, and 2010.
NOx
As shown in Fig. 4, NOx emissions from power plants continued to
increase from 1990 to 2010, except for the period of 2007–2009. NOx
emissions from power plants increased by a factor of 3.4 from 1990 to 2010,
from 1.9 Tg (all of the values herein are calculated as NO2) in 1990 to
8.3 Tg in 2010. This dramatic growth was largely driven by the increasing
electricity demand and was partially offset by the installation of LNB. Our
study suggests that the average NOx emission factor (in g kg-1 of coal)
slightly decreased at an annual rate of 1 % from 1990 to 2005 with
increasing LNB penetrations (Table 4). From 1990 to 2005, NOx emissions
increased at an annual growth rate of 8.6 %, comparable to the 9.4 %
annual growth rate of coal consumption during the same period. After 2005,
the decreased rate of average NOx emissions accelerated (at 3 % per
year) because of the higher NOx removal efficiencies of advanced LNB
technologies compared with traditional LNB. From 2005 to 2010, NOx
emissions increased by 126 %, which is remarkably lower than the 150 %
increase in coal consumption. Owing to the decline in emission factors and
the reduction in electricity demand led by the global economic crisis,
NOx emissions decreased in 2008 and 2009 but increased again in 2010 at
a growth rate of 9 % after recovery from the economic crisis.
PM
PM2.5 and PM10 emissions from power plants decreased from 1.08 and
1.79 Tg in 1990 to 0.83 and 1.32 Tg in 2010 respectively, with two
fluctuating peaks occurring in 1996 and 2005, which were due to the combined
effect of electricity demand and environmental regulations. Our estimates
for the period of 1990–2005 are generally consistent with our previous
estimates (Lei et al., 2011). The decline of emissions after the first peak
was driven by the technology renewal progress following the implementation
of the first emission standards for power plants in 1996 (SEPA, 1996), and
the deceleration of the Chinese economy. PM emissions rebounded after the
1998 financial crisis but decreased again after 2005, in compliance with the
implementation of stricter emission standards for power plants (SEPA, 2003).
PM2.5 and PM10 emissions decreased by 40 and 47 %, respectively, from
2005 to 2010, which may be due to the following reasons. First,
small units with poorly efficient PM emission control facilities were phased
out from the unit fleet. Second, electrostatic precipitators and bag filters
with high removal efficiencies were widely equipped in generation units
under the requirement of the new emission standards. In addition, FGD
installation further removed PM emissions from the end pipe. Due to the
combination of these three factors, the average PM2.5 and PM10
emission factors decreased by 60 and 65 %, respectively, from 2005 to 2010, completely offsetting the effect of the 50 % increase in
coal consumption.
FGD removal efficiencies for electric generating units of
various sizes in China in 2010. The blue horizontal line represents the
median of the removal efficiencies, the red horizontal line represents the
mean removal efficiencies, the box denotes the 25 and 75 %
percentiles, and the whiskers denote the 5 and 95 % percentiles.
Cumulative ratio of SO2 emissions by unit capacity for
the years (a) 2005 and (b) 2010. The units are sorted according to ascending
capacity along the x axis.
Reductions in SO2, NOx, PM2.5, and CO2
emissions from major emission control measures during the 11th
Five-Year Plan (2005–2010). The solid blue bar denotes our estimates of
interannual power plant emissions. The green and yellow bars illustrate the
reduction in emissions due to FGD installations and optimization of the
generation unit fleet mix, respectively.
CO2
Of the examined species emitted from power plants, CO2 emissions
increased most rapidly from 1990 to 2010 because, in contrast to SO2,
NOx, and PM2.5, no control measures were implemented to remove
CO2. We estimated that China's coal-fired power plants emitted 2.8 Pg
CO2 in 2010, an increase of 442 % compared with emissions in 1990.
The increase is in line with the 574 % growth in electricity generation
(China Energy Statistical Yearbook, NBS, 1992–2011) but is slightly offset
by the improved energy efficiency resulting from the spread of large and
efficient units. Due to the improvement in energy efficiency, CO2
emissions per unit of electricity supplied were reduced by 20 % from 1990
to 2010, which is a great achievement, although far from constraining the
growth of CO2 emissions.
Evaluation of major policies for emission mitigation
This section evaluates the effects of the major emission control measures on
reducing SO2, NOx, PM2.5, and CO2 emissions during the
11th Five-Year Plan (2005–2010). As described in Sect. 3.1, China
primarily implemented two policies for power plants during this period,
including the installation of FGD and the optimization of the mix of
generation unit fleets by promoting large power plants and decommissioning
small plants. We developed two hypothetical scenarios to evaluate the
effects of these two policies on emission mitigation, as follows. (1)
Scenario I: we assumed that China did not adjust its fleet mix, i.e., its
distribution of capacity size. In this scenario, the amount of newly built
capacity is the same as the actual case, but the fleet mix was assumed to be
unchanged during 2005 and 2010. (2) Scenario II: based on Scenario I, we
further assumed that no new FGD installations were performed after 2005.
Figure 8 compares the emission differences between the hypothetical
scenarios I and II and the actual cases during 2005 and 2010. Restructuring
the unit fleet resulted in coal savings by improving efficiency, which
contributed to emission abatement for all of the species. In 2010, the
restructuring aided in the reduction of 83.7 Tg of coal use, 4.3 Tg
SO2, 1.8 Tg NOx, 0.4 Tg PM2.5, and 238.6 Tg CO2 emissions compared with the hypothetical Scenario I.
The differences between the hypothetical Scenario I and Scenario II
represent the effects of FGD installations. As shown in Fig. 8, FGD
installation was a significant contributor to emission mitigation of
SO2 and PM2.5. During the 6-year period from 2005 to 2010, FGD
installation was estimated to reduce 51.6 Tg of cumulative SO2
emissions or 36 % of the cumulative SO2 emissions from power plants
compared with the hypothetical Scenario II. In 2010, FGD installation
prevented 16.3 Tg of SO2 emissions, a value that is 2.1 times higher
than the total actual emissions. In addition, FGD facilities aided in the
reduction of PM2.5 by 0.54 Tg in 2010, owing to the co-benefit of wet FGD
on particulate matter removal.
Capacity sizes, technology penetrations, and emission factors of
coal-fired power plants in China's six interprovincial power grids in 2005
and 2010.
Year
Grid
Capacity size (MW)a
Technology penetrationa
Sulfur
Emission factor (g kWh-1)
(0, 100)
(100, 300)
(300, 600)
≥600
FGD
LNB
ESP
Content (%)
SO2
NOx
PM2.5
PM10
CO2
North
20.0 %
29.6 %
36.4 %
14.0 %
14.5 %
62.6 %
89.1 %
1.05
8.74
3.36
0.66
1.20
954.6
Northeast
23.9 %
41.2 %
24.5 %
10.4 %
2.1 %
43.7 %
79.6 %
0.41
4.01
3.99
1.18
2.01
1094.0
2005
East
17.6 %
18.4 %
39.7 %
24.3 %
27.1 %
70.5 %
92.2 %
0.74
5.28
2.96
0.45
0.78
958.9
Central
22.3 %
30.6 %
45.0 %
2.1 %
9.5 %
57.6 %
87.1 %
1.45
12.56
3.76
0.96
1.75
971.4
Northwest
23.3 %
29.4 %
40.4 %
6.9 %
0.2 %
59.9 %
92.0 %
1.21
11.09
3.40
0.69
1.23
1001.5
South
18.4 %
30.7 %
39.1 %
11.8 %
18.3 %
66.9 %
88.6 %
1.45
12.66
3.52
0.74
1.28
1038.2
North
11.1 %
21.4 %
38.4 %
29.2 %
88.0 %
81.4 %
91.0 %
1.00
2.45
2.79
0.26
0.41
914.7
Northeast
12.9 %
24.5 %
31.1 %
31.5 %
60.1 %
73.6 %
89.0 %
0.51
2.23
3.32
0.55
0.88
1042.9
2010
East
10.0 %
7.1 %
25.7 %
57.2 %
94.3 %
87.2 %
96.2 %
0.69
1.26
2.28
0.16
0.25
877.3
Central
6.2 %
17.5 %
36.1 %
40.2 %
78.7 %
86.6 %
92.6 %
1.18
3.27
2.73
0.34
0.55
821.7
Northwest
10.1 %
20.2 %
39.8 %
29.9 %
77.0 %
83.8 %
95.7 %
0.98
3.44
2.78
0.27
0.43
956.7
South
4.4 %
14.4 %
39.8 %
41.4 %
92.7 %
91.4 %
98.0 %
1.32
3.41
2.56
0.20
0.31
904.4
a Shares of coal consumption for each capacity
size/technology.
Spatial distribution of emissions
Table 5 summarizes the unit fleet mix by capacity size and technology
penetration rates, as well as the emission factors of China's six large
interprovincial power grids, which are named according to the regions they
serve, as follows: northeast China, north China, central China, east China,
northwest China, and south China. A significant decrease in the emission
factors of each of the five species can be observed for all of the power
grids from 2005 to 2010, especially for SO2 and PM, which is consistent
with the national trend. The emission factors are different among the grids
due to their different mix of unit fleets, fuel qualities, and penetrations
of emission control technologies. Of the six grids, the east and central
grids exhibited the lowest CO2 emission factors in 2010, primarily due
to their high percentage of large units in the generation mix (the capacity
share of units larger than 300 MW was more than 75 % in 2010) and the
higher combustion efficiency of large units. The variations of SO2
emission factors among the grids represent the differences in FGD
penetration and the sulfur content of coal. The SO2 emission factors
for the south and central grids are higher than the other grids due to the
high sulfur content of coal. The FGD penetration rate of the northeast grid
was significantly lower than that of the south grid in 2010 (60.1 % in the
northeast vs. 92.7 % in the south). However, the northeast grids had a
lower SO2 emission factor (2.23 g kWh-1 in the northeast vs. 3.41 g kWh-1 in the south) due to the differences in the sulfur content of coal
between the two regions. The PM2.5 emission factors varied remarkably
due to the regional differences in the penetration rates of efficient
PM2.5 removal facilities (electrostatic precipitators and bag filters).
In 2010, the average PM2.5 emission factor in the northeast grid was
more than 2 times higher than that of the east grid due to its lower
penetration rates of electrostatic precipitators (89.0 % vs. 96.2 %).
Because an electrostatic precipitator has very high removal efficiency for
PM2.5 (93 %) compared with wet scrubbers (50 %) and cyclones
(10 %), small differences in technology penetration among regions could
result in significant disparities in the final emission factors.
Figure 9 depicts the yearly evolution of the SO2 emissions from China's
coal-fired power plants from 1990 to 2010 at the unit level (only eastern
China is shown on the map). New power plants were constructed throughout the
country after 2000. Specifically, large units were rapidly constructed in
the north regions, where large coal mines are located, and along the eastern
coastal regions, where economies are most active. In addition, SO2
emissions from large units have declined significantly since 2005, and many
small units were terminated. Figure 10 shows NOx emissions by unit for
the years 1990, 2000, 2005, and 2010. In contrast to SO2, NOx
emissions continuously increased over the entire study period given that no
effective NOx emission control facilities (e.g., SCR) were operated
after the generation units were commissioned.
Evolution of SO2 emissions from coal-fired power plants
in China, 1990–2010. Units: Gg yr-1.
Monthly variation in emissions
Figure 11 presents the monthly profiles of power generation, CO2
emissions, and SO2 emissions from 2005 to 2010, which were aggregated
from the monthly profiles of each unit. Power generations and emissions
typically peaked in December of each year due to high year-end industrial
activities, with the exception of 2008 during the financial crisis. The
second emission peak occurs in July and August, which is driven by the
electricity demand of air conditioners. The low point of emissions occurs in
January or February of each year, depending on the time of the Spring
Festival.
Spatial distribution of NOx emissions from China's
coal-fired power plants in 1990, 2000, 2005, and 2010. Units:
Gg-NO2 yr-1.
Monthly profiles of thermal power generation and coal-fired power-plant SO2 and CO2 emissions in China. The y axis values represent
the fraction of monthly emissions of annual emissions.
As shown in Fig. 11, monthly variations in CO2 emissions generally
follow the variation in power generation, whereas the monthly variation in
SO2 emissions differs from that of the power generation after 2007 when
FGD installations were widespread. After 2007, the monthly fraction of
SO2 emissions was typically higher than the fraction of power
generation during the first half of the year but reversed during the second
half of the year, reflecting the fact that many FGD facilities were installed toward the
end of the year to meet the government requirements of that year. In this case, the
monthly emission profiles developed in this study differ from previous
inventories for which temporal variations in power plant emissions were
derived from the monthly electricity generation of each province (e.g.,
Streets et al., 2003; Zhang et al., 2007).
Discussion
Uncertainty in emission estimates
The uncertainty ranges of emissions estimated in this study are presented in
Fig. 12. The average uncertainties of emissions from coal-fired power plants
in China in 2010 are estimated as -22 to 23 % for SO2,
-15 to 15 % for NOx, -31 to 38 % for PM2.5,
-26 to 30 % for PM10, and -15 to 16 % for CO2. The
higher uncertainty range of the PM emission estimates is dominated by the
uncertainties in the unabated emission factors and the efficiencies of PM
removal facilities. The development of a local database of the actual
removal efficiencies for emission control in the future will help to reduce
the uncertainties. The uncertainty ranges narrowed gradually from 1990 to
2010, representing the improved knowledge of the underlying data over time.
The uncertainty ranges declined from -36–38,
-24–26, -43–55,
-32–39, and -24–27 % in 1990 to
-22–23, -15–15,
-31–38, -26–30, and
-15–16 % in 2010 for SO2, NOx, PM2.5,
PM10, and CO2 respectively. As discussed in Sect. 2, many of the
input data in the CPED in 1990 were determined by extrapolations and
assumptions associated with high uncertainties, whereas the uncertainty
ranges for the 2010 emission estimates are significantly reduced because of
the extensive use of unit-specific data. The unit-specific annual coal use
in 2010 contributed to the improved accuracy for all five species. In
addition, a better understanding of sulfur content and removal efficiency of
FGD, coal type, ash content, and heating value of coal for each unit in 2010,
on which the accuracy of SO2, NOx, PM, and CO2 emission
factors depend, respectively, is the primary reason for the narrowed
uncertainties for corresponding species.
We further demonstrated how the emission uncertainties changed over time at
the unit level. For the selected generation unit (600 MW, pulverized boiler,
equipped with FGD, LNB, and an electrostatic precipitator), the uncertainty
ranges of the emission estimates for 2000 and 2010 are presented in Table 6.
The uncertainty ranges for the 2010 estimates are significantly reduced
compared with the uncertainties for 2000 because more unit-specific
information became available in 2010. For 2010, the uncertainties at the
unit level are comparable with the national average, given that all of the
available unit-specific input data correspond to low uncertainties. However,
in 2000, the uncertainties at the unit level are significantly higher than
the national average because several key parameters (e.g., annual operating
hours, sulfur content and heating value of coal) were derived from
extrapolations and assumptions.
Uncertainty ranges of emission estimates for a large coal-fired
generation unit (600 MW, pulverized boiler, equipped with FGD, LNB, and an
electrostatic precipitator) in China; the values represent the 95 % CI
around the mean.
Species
Year
2000
2010
SO2
-58–56 %
-21–14 %
NOx
-100–179 %
-28–47 %
PM2.5
-61–95 %
-38–49 %
PM10
-81–112 %
-39–44 %
CO2
-28–33 %
-16–18 %
In addition, we quantified uncertainties of other potential sources by
sensitivity analysis. The assumption of SO2 removal efficiencies for
FGD prior to 2008 may have underestimated SO2 emissions, as some of the
early installed FGD facilities were not actually in operation then. Assuming
20 % of FGD did not operate properly, national total emissions could
increase by 2, 4, and 9 % for 2005, 2006, and 2007 respectively. The
assumption of PM2.5 removal efficiency for wet FGD may have
underestimated PM2.5 emissions for power plants with wet limestone-gypsum FGD.
Particulate matters in desulfurizers of the spray slurry from scrubbers of
wet FGD is likely to exhaust from stacks along with plumes. Those particulate matters would offset PM2.5 emissions absorbed by scrubbers
of wet FGD (Meij and te Winkel, 2004). By assuming 10 % changes of
PM2.5 emissions are induced by gypsum spray (Meij and te Winkel, 2004),
PM2.5 emissions could be increased by 0.3 % in 2005 and 6.4 % in
2010, depending on the penetrations of wet FGD. We further quantified the
uncertainties induced by the assumption that de-NOx devices were not in
operation until 2010. By assuming that de-NOx devices were put into
operation in Beijing, Shanghai, and Guangdong in 2010, NOx emission
estimates could be reduced by 67 Gg (1 % of national total emissions), indicating that our
assumptions have small impacts on national total NOx emission
estimates. Overall, the sensitivity studies indicate that our assumptions
have relatively small impacts on national total emission estimates.
Comparisons of SO2, NOx, PM2.5 and CO2
emissions from China's coal-fired power plants during 1990 and 2010.
Comparison with previous estimates of emission trends
In this section, we compared our new inventory with other bottom-up emission
inventories, as shown in Fig. 12, in which multi-year estimates are provided
(more than five data points from 1990 to 2010). The discussion is focused on
inventories that are available for multiple species and are widely used in
the community, i.e., Emission Database for Global Atmospheric Research
version 4.2 (EDGAR 4.2, EC-JRC/PBL, 2011) and Regional Emission inventory in
Asia version 2 (REAS 2, Kurokawa et al., 2013). We initially compared the
CO2 emission estimates among the different emission inventories. Our
estimate is consistent with Guan et al. (2012) but is approximately
16–25 % lower than the estimates by three other studies (EDGAR 4.2,
REAS 2, and Y. Zhao et al., 2013). Our estimates are similar to those of
Guan et al. (2012) because both estimates used a lower coal heating value
(an average of ∼ 20 kJ g-1) derived from energy statistics,
which was approximately 20 % lower than the IPCC's recommended value (25.8 kJ g-1) used in other studies. The lower estimate in this study compared with
EDGAR 4.2 might also be because the public electricity and heat production
sector in EDGAR 4.2 includes emissions from heating plants.
For SO2 emissions, EDGAR 4.2 and the official estimates by the MEP
(China Statistical Yearbook, NBS, 1997–2011) exceed the boundary of the
95 % CI calculated in this study. EDGAR 4.2 estimated a positive trend
until 2008, which differs from other studies, likely because EDGAR 4.2
failed to characterize the SO2 emission control progress in China's
power plants after 2005. Three other inventories (REAS 2; Lu et al., 2011;
and this study) provided consistent trajectories for SO2 emissions and
are higher than the official estimates for the period of 1998 to 2008,
likely due to underreported emissions by the MEP. All of the studies
presented a similar growth trend for NOx emissions over the last 2
decades, whereas EDGAR 4.2 and REAS 2 are slightly higher than the upper
bound of the 95 % CI calculated in this study. By revisiting the local
emission factor measurements (Table 1), our new estimates for NOx
emissions are 15–24 % lower than previous estimates (Zhang et al.,
2007) for the period of 1995–2004. REAS 2 used emission factors from Zhang
et al. (2007) and then derived higher emissions than those in this study
(Kurokawa et al., 2013). REAS 2 concluded that NOx emissions from
China's power plants increased by 136 % from 2000 to 2008, higher than the
value of 125 % of growth estimated in this study during the same period
due to different assumptions in the evolution of combustion technologies.
The PM emission trends presented in this study generally agree well with
previous studies (Lei et al., 2011; Y. Zhao et al., 2013) but significantly
differ from REAS 2. REAS 2 presented a 36 % increase in PM2.5
emissions from 2005 to 2008, whereas we estimated a 24 % decrease during
the same period, most likely due to different assumptions regarding the
penetration of PM2.5 removal devices.
(a) Spatial distribution of CO2 emissions in CPED in 2009.
(b) Spatial distribution of CO2 emissions in CARMA in 2009.
(c) Comparisons of CO2 emissions between CARMA and CPED by plant numbers in
2009. The plants are sorted according to ascending CO2 emissions along
the y axis. The red and blue lines denote the plant number cumulative ratio
for CARMA and CPED, respectively. (d) Comparisons of the spatial
distribution of CO2 emissions in southwest China between CARMA and CPED
in 2009.
Comparison with the CARMA database
The CARMA database (Wheeler and Ummel, 2008; Ummel, 2012) has been widely
used to allocate power plant emissions in different global and regional
emission inventories (e.g., EDGAR 4.2 and REAS 2). In this section, we
compared the magnitude and spatial distribution of CO2 emissions
between this study and the CARMA database throughout China for 2009. The
total magnitude of CO2 emissions for the two inventories is comparable,
with a large discrepancy in the numbers of power plants. In this study, we
estimated 2.51 Pg CO2 emissions from 2320 power plants, whereas CARMA
estimated 2.47 Pg CO2 emissions from 945 plants.
Figure 13a and b show the spatial distributions of CO2 emissions for
CPED and the CARMA database, which illustrate that CARMA neglects many small
power plants. Figure 13c depicts the cumulative curves of the power plant
numbers sorted by CO2 emissions from low to high. In this study, power
plants with annual CO2 emissions less than 1 Tg accounted for 76 % of
the total plants, whereas the share of these plants was only 44 % in
CARMA. In summary, CARMA omitted ∼ 1300 small power plants
throughout China (annual CO2 emissions less than 1 Tg) in 2009. In
addition, for power plants consisting of several generating units, CARMA may
omit information on partial units. For example, the Tuoketuo power plant
located in Inner Mongolia is composed of 10 generating units with a total
capacity of 5400 MW. Its CO2 emission estimated by CARMA is 15.1 Tg,
which is only 56 % of the value estimated in this study, indicating
CARMA's significant underestimation of coal consumption for the plant, which
is most likely caused by missing information on some units.
Comparisons of CO2 emissions between CARMA and CPED for
various spatial resolutions (from 0.1 to 2∘) in 2009.
The box plots show the binned relative differences (a–b)/(a+b), where a is
the CARMA estimate, and b is the CPED estimate. The blue horizontal line is
the median of the relative differences, the red horizontal line is the mean
of the relative differences, the box denotes the 25 and 75 %
percentiles, and the whiskers denote the 10 and 90 % percentiles. A
perfect agreement would correspond to a median and mean equal to 0.
Another major difference between the two inventories is the
locations of the power plants and their emissions. Figure 13d shows a magnified comparison of
the spatial distributions of CO2 emissions between the two inventories
over the southwest region of China, which illustrates the plant-specific
emissions and locations. The power plant locations in CARMA deviate from
those in our inventory due to the different geographical allocation methods
used in the two data sets. In this study, the location of each power plant
was obtained from the MEP database and was manually verified using Google
Earth, which allowed for a high accuracy in the geographical distribution of
emissions. CARMA generally treats the city-center latitudes and longitudes
as the approximate coordinates of the power plants in China (Wheeler and
Ummel, 2008). Ummel (2012) reported that the precise coordinates are only
available for 10 % of the plants worldwide in CARMA, and the reported
emissions are within 20 % of the actual values for only 75 % of plants.
For 46 power plants included in both CARMA and in CPED over the southwest
region, the average distance between the locations reported in CARMA and in
CPED is approximately 50 km, indicating that the CARMA database may be
insufficient to support air quality modeling on regional and urban scales.
Figure 14 further presents the relative differences in the CO2 emission
flux (g m-2) at various spatial resolutions (0.1,
0.5, 1, and 2∘) in 2009 for the two
data sets. The degree of differences between the two data sets is highly
correlated to the spatial resolution. The differences are diminished as the
spatial resolution decreases. The average differences between the two
data sets are within 10 % at a 2∘ resolution and 20–30 % at a
1∘ resolution, indicating that CARMA has an acceptable accuracy to
support modeling studies at the global scale. However, at a 0.1∘
resolution, the relative differences between the two inventories are as high
as 70 %, suggesting that CARMA is not appropriate for high-resolution
modeling.
Concluding remarks
This is the first study to develop a unit-based inventory of technologies,
activities, and emissions for China's coal-fired power plants for the period
of 1990–2010. The CPED database developed in this study includes
∼ 5700 in-use electricity generating units in 2010 and
∼ 1900 units that have retired since 2005. From the high-resolution CPED
database, spatial and temporal variations of China's power plant emissions
were presented from 1990 to 2010. In 2010, SO2, NOx, PM2.5,
PM10, and CO2 emissions from China's coal-fired power plants were
estimated to be 7.7, 8.3, 0.83, 1.32 Tg, and 2.8 Pg respectively.
From 1990 to 2010, SO2, NOx, and CO2 emissions from power
plants increased by 56, 335, and 442 %, respectively, and
PM2.5 and PM10 emissions decreased by 23 and 27 %
respectively during the same period. The energy efficiency of coal-fired power
plants in China has been improved by approximately 20 % in 20 years owing
to measures imposed by the Chinese government to encourage large-scale power
units and to decommission small units.
The most significant changes in power plant emissions occurred during
2005–2010, driven by the dramatic economic growth and offset by the
strengthened emission control measures. Large units were rapidly constructed
in the north regions and eastern coastal regions to meet the high
electricity demand, while growth trend of emissions has been effectively
curbed since 2005 by installation of FGD and the optimization of the
generation fleet mix. 84 % of the total unit capacities were equipped with
FGD in 2010, which helped reducing SO2 emissions to half of the 2006
emission level. The increasing penetration of advanced LNB after 2006 has
reduced the average NOx emission factor by 16 %, but still did not
constrain the growth of NOx emissions. New environmental regulations,
including the phase-out of small units with inefficient PM emission control
facilities, the widespread use of electrostatic precipitators and bag
filters, and FGD installations that are a co-benefit to PM removal, have led
to the 40 % decrease of PM2.5 emissions from 2005 to 2010.
Great emission reduction potentials from coal-fired power plants are
expected in the near future through the implementation of new policies
including the promotion of ultra-low emission units, the decommissioning of flue gas bypass
systems, and the strengthening of supervision and management, etc. The removal
efficiencies of existing FGD and de-NOx devices are expected to be
improved with the decommissioning of the flue gas bypass system. More efficient
emission control technologies are expected to continuously come into the
marketplace, with the implementation of the government plan (NDRC, 2014)
which requires the reduction of emissions from coal-fired plants down to the level
of gas-fired plants.
The new inventory developed in this work has several advantages as compared
to previous studies. First, to the best of our knowledge, it is the most complete
coal-fired power plant database for China with inclusion of 7657
in-use and retired units, enabling more accurate emission estimates at unit
level. Second, CPED has dynamic information for a given unit including
commission/decommission time of units, changes in technologies, and
operating condition of emission control facilities. The above information
further improved the accuracy of emission estimates for every time step.
Third, exact locations of each unit were obtained from MEP and cross-checked
by Google Earth manually, which could be a benefit to chemical transport
modeling at high spatial resolution. The improved accuracy of CPED has been
validated by another recent study using satellite-recorded tropospheric
NO2 columns around the power plants (Liu et al., 2015). We also
compared the NOx emission trends of two isolated power plants in CPED
(Tuoketuo and Yangcheng) with OMI NO2 column trend (Fig. S1 in the Supplement). Good
agreement between NO2 column trend and NOx emission trend were
found, indicating the reasonable accuracy of emission trend estimates in
CPED. Detailed information for the comparison is presented in the
supplementary information.
Although we believe that the accuracy of CPED has been substantially
improved, it still has some uncertainties. Emission estimates for 1990s are
thought to be more uncertain than in the 2000s because a few parameters during
the 1990s were determined by extrapolations and assumptions rather than using
unit-specific data. Units that retired before 2005 were not included in our
database. However, we believe that omitting those units would have minor
impacts on the accuracy of CPED, as large-scale retirement of coal-fired
power plants only occurred after 2005. Local measurements for PM
emission factors are still rare compared to SO2 and NOx, leading
to higher uncertainties in PM emission estimates. In recent years,
continuous emission monitoring systems (CEMS) were gradually equipped in
electricity generating units, offering the opportunities of using real-time
emission data. Applying CEMS data in the future will further improve the
accuracy of emission estimates in CPED.
Data availability
The early version of CPED has been integrated into the MEIC
(Multi-resolution Emission Inventory for China) database (both MEIC 1.0 and
1.2), which is available on the following website:
http://www.meicmodel.org/. MEIC 1.0 was incorporated into the MIX Asian
emission inventory (Li et al., 2015). The most recent version of CPED
(documented in this work) will be incorporated into the next version of MEIC.