Emission characteristics of fine particulate matter from ultra-low emission power plants

Environmental Pollution 255 (2019) 113157

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Emission characteristics of fine particulate matter from ultra-low emission power plants* Xiaojia Chen a, Qizhen Liu c, Chao Yuan b, Tao Sheng c, Xufeng Zhang a, Deming Han a, Zhefeng Xu a, Xiqian Huang a, Haoxiang Liao a, Yilun Jiang b, Wei Dong b, Qingyan Fu c, Jinping Cheng a, * a b c

School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China Shanghai Baosteel Industry Technological Service Co., LTD, Shanghai, 201900, China Shanghai Environmental Monitor Center, Shanghai, 200235, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 7 June 2019 Received in revised form 16 August 2019 Accepted 31 August 2019 Available online 6 September 2019

As one of the highest energy consuming and polluting industries, the power generation industry is an important source of particulate matter emissions. Recently, implementation of ultra-low emission technology has changed the emission characteristic of fine particulate matter (PM2.5). In this study, PM2.5 emitted from four typical power plants in China was sampled using a dilution channel sampling system, and analyzed for elements, water-soluble ions and carbonaceous fractions. The results showed that PM2.5 concentrations emitted from the four power plants were 0.78 ± 0.16, 0.63 ± 0.09, 0.29 ± 0.07 and 0.28 ± 0.01 mg m
3, respectively. Emission factors were 0.004e0.005 g/kg coal, nearly 1e2 orders of magnitude lower than those reported in previous studies. The highest proportions of PM2.5 consisted of þ
organic carbon (OC), SO2
4 , elemental carbon (EC), NH4 , Al and Cl . Coefficients of divergence (CDs) were in the ranges 0.22e0.41 (for an individual plant), 0.43e0.69 (among different plants), and 0.60e0.99 (in previous studies). The results indicated that the source profiles of each tested power plant were relatively similar, but differed from those in previous studies. Enrichment factors showed elevated Se and Hg, in accordance with the source markers Se and As. Comparing source profiles with previous studies, the proportion of OC, EC and NHþ 4 were higher, while the proportion of Al in PM2.5 were relatively lower. The OC/EC ratio became concentrated at ~5. Results from this study can be used for source apportionment and emission inventory calculations after implementation of ultra-low emission technologies. © 2019 Elsevier Ltd. All rights reserved.

Keywords: Power plant PM2.5 Dilution stack sampling Emission factors Source profile Source markers

1. Introduction Power plants, one major source of fine particulate matter (PM2.5, particles with an aerodynamic diameter of 2.5 mm), contribute to regional atmospheric haze, climatic change, atmospheric visibility, and health effect (Wang et al., 2016a; Liu et al., 2015; Tang et al., 2012; Li et al., 2011; Zheng et al., 2009; Wang et al., 2005; Nicks et al., 2003). According to the Multi-resolution Emission Inventory for China (MEIC), the emission of PM2.5 from power plants was 0.85 Tg yr
1 in China, 2010, which accounted for 7% of the total emissions in China (Li et al., 2017). As part of ongoing efforts to strengthen control of power plant

* This Paper has been recommended for acceptance by Admir CrirPaTargino * Corresponding author. E-mail address: [email protected] (J. Cheng).

https://doi.org/10.1016/j.envpol.2019.113157 0269-7491/© 2019 Elsevier Ltd. All rights reserved.

emissions, the Chinese government has issued a strict ultra-low emission (ULE) control standard for coal-fired power plants; it requires that by 2020, the emission of total particulate matter (PMtotal) must not exceed 10 mg m
3 (NDRC, 2014). To meet the ULE standard, upgraded air pollution control devices (APCDs) have been developed and installed in power plants. APCDs include LowNOx combustion (LNB) technology with selective catalytic reduction (SCR) or selective noncatalytic reduction to reduce NOx emission. To control SO2 emissions, coal with low sulfur content and wet flue gas desulfurization (WFGD) systems with limestonegypsum are used. For PM, traditional decontamination devices have been further improved, such as the traditional electrostatic precipitator (ESP) accompanying a low-low temperature system (LLT-ESP, flue gas temperature is decreased to 90e95  C). By the end of 2017, approximately 71% of coal-fired units nationwide have met the ULE standard by retrofitting different APCD combinations

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X. Chen et al. / Environmental Pollution 255 (2019) 113157

(http://english.gov.cn/govtworkreport2018/). Previous studies have focused on the effect of the decontamination facilities and on emission inventories (EI) for PM emissions from ULE power plants (Chang et al., 2019; Chen et al., 2019; Liu et al., 2019; Wang et al., 2019; Wu et al., 2018; Li et al., 2017). The PM capture efficiency of a wet-ESP (WESP) was found to exceed 88%, and the PM2.5 capture efficiency ranged from 57.2% to 78.8% for 300e1000 MW ULE power plants (Zhao and Zhou, 2016; Zhang et al., 2014). High spatiotemporal resolution EIs for power plants were also compiled based on annual fuel consumption statistics, averaged emissions factors (EFs) and yearly emissions; these were used to update unit-based EIs and dynamic EFs for technologybased methodologies and included field measurements for ULE power plants (Liu et al., 2019). Sui et al. (2016) studied PM2.5 emissions and size distribution characteristics for a ULE power plant without chemical characteristics. The PM2.5 “source profile” is the chemical composition of PM2.5 from an emission source and is usually expressed as the specified mass abundance with its standard deviations (Chow et al., 2004; Watson et al., 2001). Databases including SPECIATE in US (USEPA, 2013), SPECIEUROPE in Europe (Pernigotti et al., 2016), and China Source Profile Shared Service (CSPSS) for local measured pollution sources in China (Liu et al., 2017) contain a large amount of source profiles. Among these, the SPECIATE database is the most comprehensive, but the data are mainly from the United States before year 2000. A series of measurement studies were conducted
on power plants in China and found that SO2
4 , Cl , K, organic carbon (OC) and Ca were the main components of PM (Pei et al., 2016; Zhang et al., 2016). However, compliance with the ULE standard, changes in coal quality, changes in operating parameters, and implementation of decontamination equipment will result in changes in PM2.5 components. Detailed information on PM2.5 source profiles for ULE power plants is quite limited. A better understanding of the emission characteristics of PM2.5 is an urgent need for air pollution control strategies. The objective of this study was to better understand the emission characteristics in power plants that meet the China's ULE standard. To achieve this objective, PM2.5 emissions from four typical power plants were measured using the dilution sampling method. PM2.5 emission factors were updated and chemical compositions were analyzed to establish the source profiles for local power plants and these were compared to source profiles from previous studies. 2. Method and materials 2.1. Sampling information and analytical methods Two typical coal-fired power plants (CFPPs), one mixed fuel fired power plant with coal and blast furnace gas (BFG), and one BFG-fired power plant with installed capacities ranging from 350 to 1,000 MW in eastern China were selected for the study. Three parallel samples were collected for each power plants in July, 2018. The plants were denoted Plant A, Plant B, Plant C, and Plant D, respectively. CFPPs used pulverized coal-fired boilers. CFPPs and the mixed fuel fired power plant employed LNB and SCR for NOx removal. The SCR was followed by LLT-ESP and WFGD to control PM and SO2 in sequence. Table 1 summarizes the profiles of the four power plants. 2.2. Sampling equipment and method Dilution stack sampling was used at the four power plants (Fig. S1). The dilution sampling system designed by the Desert Research Institute was used (Pei et al., 2016). The flue gas in the

chimney was pumped isokinetically with a buttonhook nozzle, transferred through a 2.5 m heated probe, and entered into a residence chamber to be diluted with clean air to give a dilution ratio of ~10. The flue gas was diluted and aged for ~10 s, then passed through a PM2.5 cutter to remove particles >2.5 mm, and the particles less than 2.5 mm were collected through four channels onto the quartz-fiber filters (47 mm diameter, Whatman) at a flow rate of ~23 L min
1 per channel. The dilution sampling system was made of stainless steel, and the sampling probe and the diluter were connected with flexible conductive silicone tubes to reduce particulate loss. 2.3. Chemical analysis and quality control The 21 elements (Al, As, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sb, Se, Ti, V and Zn) were analyzed using an inductively coupled plasma optical emission spectrometer (ICP-OES, Agilent, Model 5110, USA) and an inductively coupled plasma mass spectrometer (ICP-MS, PerkinElmer, NexION-350X, USA). Hg was determined using cold vapor generation-atomic fluorescence detection (CV-AFS, MA-2, Nippon Instruments Corp., Tokyo, Japan).

þ

þ 2þ þ 2þ 10 ions (SO2
4 , NO3 , NO2 , Cl , F , NH4 , K , Ca , Na and Mg ) were analyzed using an ion chromatograph (IC, DIONEX, Model ICS1600, USA). Carbonaceous substances such as organic carbon (OC), elemental carbon (EC) were analyzed using a thermal/optical carbon analyzer (DRI, Model 2001, Desert Research Institute, USA) following the Interagency Monitoring of Protected Visual Environments (IMPROVE) thermal/optical protocol (Chow et al., 1993, 2004). Four OC fractions OC1, OC2, OC3 and OC4 were measured in a pure helium atmosphere at 120  C, 250  C, 450  C, and 550  C, respectively. Three EC fractions, EC1, EC2 and EC3, were determined in a 2% oxygen/98% helium atmosphere at 550  C, 700  C, and 800  C, respectively. The pyrolyzed carbon fraction (OP) was obtained when the reflected laser light reaches its initial intensity after the addition of oxygen to the combustion atmosphere. OC represents the sum of four OC fractions plus OP, while EC represents the sum of three EC fractions minus OP. For quality control and quality assurance, filters were stored under controlled temperature (20 ± 5  C) and relative humidity (40 ± 2% RH) conditions before and after sampling. Immediately after in situ sampling, filters were placed in aluminum foil and stored in a refrigerator at ~4  C until brought back to the lab. The filters were weighed using an analytical balance accurate to 0.01 mg. Each filter was weighed three times and the average of the three weighing data was used. For chemical analysis, laboratory filter blanks and field blanks samples were analyzed. The instruments were periodically checked using standard reference materials, and showed good linearity and sensitivity. The relative standard deviation for measurements were within 3%. 2.4. Coefficients of divergence (CD) Coefficients of divergence (CD), a self-normalizing parameter measuring how much a certain constituent weighs, helps evaluate similarities and differences between profiles (Kong et al., 2011; Zhang and Friedlander, 2000; Wongphatarakul et al., 1998). The calculation of CDs was accomplished using equation (1):

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u p u1 X Xij
Xik 2 CDjk ¼ t ð Þ p i¼1 Xij þ Xik

(1)

where j and k represent two source profiles, p is the number of components analyzed in each source profile, Xij and Xik represent

X. Chen et al. / Environmental Pollution 255 (2019) 113157

3

Table 1 Description of four power plants studied in this research. Unit

Plant A

Plant B

Plant C

Plant D

Generation capacity (MW) Fuel type Energy consumption (Tg yr
1 of coal or km3 yr
1 of gas) Power generation (  109 kWh) Ash content (%) Sulfur content (%) Air pollution control devices

1000 Bituminous coal 3.8 10.2 11.7 0.37 LNB þ SCR þ LLT-ESP þ WFGD

600 Bituminous coal 1.4 2.9 11.6 0.41 LNB þ SCR þ LLT-ESP þ WFGD

350 Bituminous coal 0.6 1.9 11.8 0.49 LNB þ SCR þ LLT-ESP þ WFGD

350 BFG 4.8  106 1.7

abundances of a chemical component i measured in source profile j or k, respectively. The smaller is CDjk , the more similar are the two sources. A CD  0.5 indicates similarities between profiles. 2.5. Enrichment factor (EnF) Enrichment factors (EnFs) have been used widely as a simple method for analyzing element enrichment conditions and environmental pollution characteristics (Bano et al., 2018; Wang et al., 2018; Chen et al., 2017; Reimann and de Caritat, 2005; Zoller et al., 1974). The EnF for each component in the source emissions of particulate matter relative to the abundance of the component in local soil was used to identify and evaluate the origins of the components (natural or anthropogenic), and reveal elemental markers of sources (Chen et al., 2017). The EnF of a component was calculated using equation (2):

Enrichment factorðEIÞemis ¼

 ½EIemis ½Xemis  ½EIsoil ½Xsoil

(2)

where [EI]emis is the abundances of element from the emission source. [EI]soil is the abundances of elements in soil dust, and was obtained from MEE (1990) for surface soil in Shanghai. [X] is the reference element, which is often taken to be Al (Reimann and de Caritat, 2005; Zoller et al., 1974). Generally, high values of EnF indicate that the content of anthropogenic material in the emission is substantial. On the basis of EnF, the degree of enrichment was classified as no enrichment (EnF < 1), slightly enriched (1 < EnF < 10), moderately enriched (10 < EnF < 100) and heavily enriched (EnF > 100) (Chen et al., 2017; Kara et al., 2014). 3. Results 3.1. PM2.5 concentration and emission factors Average concentrations of PM2.5 and the standard deviation of three parallel samples from the four tested power plants are summarized with those from other studies in Table 2. PM2.5 concentrations from power plants AeD were 0.78 ± 0.16, 0.63 ± 0.09,

LNB

0.29 ± 0.07 and 0.28 ± 0.01 mg m
3, respectively. These were similar to those for ULE-retrofitted coal-fired power plants (0.45e1.8 mg m
3), coal-oil fired power plants (0.75 mg m
3), and waste incineration power plants (0.68e3.33 mg m
3) (Wang et al., 2019; Wang et al., 2018; Wu et al., 2018; Yang et al., 2014). Compared with previous study when the emission limit was 20 mg m
3 for PM according to GB 13223-2011, PM2.5 concentrations from power plants were drastically reduced from 7.8 to 12.2 mg m
3 to less than 1 mg m
3, which shows the effectiveness of the ULE policy (Pei et al., 2016). According to Wu et al. (2018), PMtotal mass concentrations in the ULE-retrofitted CFPPs meeting the Chinese National ULE standard (10 mg m
3) were 4.2e8.7 mg m
3, with corresponding PM2.5 mass concentrations of 0.45e1.25 mg m
3. In this study, PM2.5 average concentrations emitted from the four power plants were all lower than 1 mg m
3, which suggested that the power plants in this study have essentially complied with the Chinese national ULE standard for PM mass concentration. The emission factor (EF) is a key parameter in the establishment of power plant emissions inventories; as the installation of APCDs evolves, EFs should be continuously updated to reduce uncertainty in the emissions inventory. In this study, EFs of the four tested power plants were calculated based on the measured concentrations of PM2.5, daily reports on total flue gas flow, and fuel consumption. Average EFs of PM2.5 in this study are compared with those from other studies in Table 2. EFs of PM2.5 were 4.1 ± 0.4 and 5.4 ± 0.8 mg (kg
1 of coal) from plant A and plant B, respectively, while the PM2.5 EF for the plant D (BFG plant) was 0.07 ± 0.01 mg m
3. The EFs were relatively lower than those reported previously for ULE coal-fired power plants (8e90 mg kg
1) (Wang et al., 2019; Wu et al., 2018). In addition, compared with the particulate emission factors monitored online after ULE implementation, the temporal mean EF of PM was reduced from 80 to 250 to 10e70 mg kg
1 (Chen et al., 2019; Liu et al., 2019). By assuming the mass fraction of PM2.5 to total PM was 6% from Zhao et al. (2010), the mean EF of PM2.5 can be assumed to be 1e10.2 mg kg
1 coal, which was consistent with findings from the current study. However, the EFs determined in this study were much lower than AP-42 determined by the USEPA

Table 2 Comparisons of PM2.5 concentrations and emission factors (EFs) observed in this study and previous studies. Sources

APCDs

PM2.5 concentrations (mg m
3)

PM2.5 EFs (mg kg
1 of coal or mg m
3 of gas)

References

Plant A Plant B Plant C Plant D Coal-fired power plants Coal-fired power plants Coal-fired power plants Coal-fired power plants Coal-oil-fired power plant Waste incineration power plants

ULE ULE ULE / / ULE ULE ULE / /

0.78 ± 0.16 0.63 ± 0.09 0.29 ± 0.07 0.28 ± 0.01 7.8e12.2 0.45e1.53 0.6e1.8 / 0.75 0.68e3.3

4.09 ± 0.41 5.39 ± 0.78 / 0.07 ± 0.01 / 8e90 <10 (operation temperature from 85 to 100  C) 10e70 (for PM) / 6e9

This study

retrofitted retrofitted retrofitted

retrofitted retrofitted retrofitted

Pei et al. (2016) Wu et al. (2018) Wang et al. (2019) Liu et al. (2019) Yang et al. (2014) Wang et al. (2018)

4

X. Chen et al. / Environmental Pollution 255 (2019) 113157

(35.0e71.6 mg kg
1) (Pei et al., 2016; USEPA, 2013) as well as the value of 1.20e2.0 g/kg coal as determined by Zhang et al. (2009). The differences may reflect the constant upgrading of APCDs. 3.2. Chemical characteristics of PM2.5 The source profiles consist of the average of chemical species abundances and their corresponding standard deviation. For profiles that cover only one sample, standard deviation of which was calculated by dividing the average value by 10% (Kong et al., 2011). The abundances and individual source profiles of the four power plants are summarized in Table 3 and Table S1. The average abunþ
dances show that OC, SO2
4 , EC, NH4 , Al and Cl were the main components (>1%) in PM2.5 from the plants. These values were consistent with the higher abundances of SO2
4 (12.7e22.7%) and total carbon (OC þ EC, 1e10%) found in the profile of coal-fired boilers in Northwestern Colorado, which also showed slightly less Al (4.2%) and Ca (3.5%) (https://www.sciencedirect.com/science/ article/pii/S0048969717309415?via%3Dihub%20/l%20bb0165 Watson et al., 2001). The profile from plant A was dominated by OC (28.9%), Al (8.3%),
þ
EC (5.7%), SO2
4 (3.9%), Ba (2.3%), Cl (2.1%), NO2 (2.0%) and NH4 (1.4%). The emission from plant B was enriched in OC (14.2%), EC (3.0%) and NO
2 (1.1%), while that from plant C was enriched in OC þ
(51.7%), SO2
4 (24.1%), NH4 (9.7%), EC (9.3%), Cl (4.2%) and Al (2.0%). Emission from the gas-fired power plant D was enriched in OC 2
(31.0%), EC (8.7%), Cl
(1.6%), NHþ 4 (1.5%), Al (1.2%) and SO4 (1.2%). Overall, all four power plants had high abundances of OC in their þ
emissions, but the relative proportions of SO2
4 , EC, NH4 , Cl and Al were quite variable among the plants, with plant C having much larger proportion of SO2
4 , and plant A having a greater proportion of Al. The results were similar to those of Chen et al. (2017), which were also quite variable between power plants, with one having much higher abundances of OC (7.6e27%) and SO2
4 (0.1e3.5%), and the other enriched in Al (7.1e11.2%) and Ca (1.9e2.3%). 3.2.1. Elements The abundances of the total detected elements in PM2.5 were 11.4%, 0.9%, 2.5% and 1.9% from plants AeD, respectively (Table S1). Al was the most abundant component and accounted for 63.3e81.7% of the total detected elements, followed by Ba (2.2e20.3%), Zn (3.6e15.9%), Cr (0.5e3.6%), Mn (1.0e2.8%), Cu (0.3e3.0%), V (0.5e2.3%) and Ni (0.4e2.0%). Se and As are often used as markers for coal-fired power plant emissions (Thurston and

Spengler, 1985). Se abundance (0.018e0.034%) was similar compared with the proportion of Se in other coal-burning profiles (0.001e0.034%) (USEPA, 2013), but lower compared with that reported in a Texas, USA study before 2004 (0.5776 ± 0.8325%) (Chow et al., 2004). The proportion of As (0.005e0.023%) was slightly lower compared with that in Shanghai emission profiles before 2016 (0.029e0.114%)https://app.yinxiang.com/shard/s22/nl/ 4952159/e5cdf361-d9ee-478e-a1c9-5425b836050b, higher than that in the aforementioned Texas study before 2004 (0.003 ± 0.055%), and similar with PM10ePM2.5 source profiles in India (0.00513 ± 0.0008%)(Bano et al., 2018; Pei et al., 2016). Other elements (Ti, Cd, Co, Be, Sb and Hg) comprised less than 0.01% of the PM2.5 profiles in this study. 3.2.2. Water-soluble ions The abundances of total water-soluble ions (TWSI) in PM2.5 from plants AeD were 10.8%, 2.8%, 38.0%, 4.2%, respectively (Table S1). þ
SO2
4 , NH4 and Cl constituted the largest fractions, accounting for 0.32e24.11%, 0.78e9.74% and 0.17e4.16%, respectively. The high emissions of SO2
4 may due to the reactions between the gas phase precursor (SO2) and the desulfurizer (CaO) in the installed WFGD to remove SO2 emissions from the flue gas. NHþ 4 emissions also accounted for a higher proportion, which mainly derived from the addition of excessive NH3 during the SCR process (Wu et al., 2018; Pei et al., 2016 https://app.yinxiang.com/shard/s22/nl/4952159/ 4f8af1b4-8634-41db-a12c-e2528889db33). The concentration of Cl
(0.2e4.2%) was consistent with that in Shanghai PM2.5 prior to 2016 (0.6e3%)(https://app.yinxiang.com/shard/s22/nl/4952159/ e5cdf361-d9ee-478e-a1c9-5425b836050b Pei et al., 2016). 3.2.3. Carbon The total carbon (TC) abundances in PM2.5 from plants AeD were 34.6%, 17.3%, 61.0%, and 39.7%, respectively (Table S1). As shown in Fig. 1, the proportions of eight carbon fractions were different, which were in the ranges 0.2e0.7% (OC1), 7.8e26.0% (OC2), 4.9e15.8% (OC3), 1.1e7.0% (OC4), 0.9e4.9% (EC1), 2.3e8.1% (EC2), 0.00.3% (EC3) and 0.4e3.7% (OP). The major carbon components were consistent within the emissions from each plant, and were enriched in OC2, OC3 and EC2. Compared with results reported by Pei et al. (2016) and Chow et al. (2004), the proportions of higher OC components in those studies were similar to the proportions of OC2 and OC3 in this study. However, the proportions of the higher EC component were different among the three studies, with EC1 in previous studies higher than in this study. EC1 is mainly

Table 3 Summary of chemical species abundances in power plant source profiles. Sources

Chemical abundances in percent mass <0.1%

0.1e1%

1e10%

>10%

Plant A

EC3, Hg, Ti, Kþ, Cd, Naþ, Mg2þ, Be, Fe, K, Mg, Na, Sb, Ca2þ, Co, Ca, Se, As, Pb, Cu, Ni, Cr, V Hg, Naþ, Be, Ca2þ, Se, Mg2þ, Kþ, Ti, Cd, As, K, Co, Fe, Mg, Sb, Ca, Na, Pb, Cu, EC3, F -, V, Ni, Mn, Cr, Ba, þ
Be, Ti, K, Fe, F
, Zn, NO
3 , NO2 , Na , Cd, Mg2þ, Ca2þ, Co, Kþ, Sb, Hg, Mg, As, Ca, Pb, Ni, EC3, Se, V, Na, Ba, Cr, Mn, Cu 2þ
Be, F
, NO
, Naþ, Ti, Kþ, 3 , NO2 , Mg Ca2þ, Cd, Co, Mg, Hg, Co, K, Fe, Sb, Na, As, Ca, Se, Mn, Pb, Ni, Cu, V, Cr Ti, Naþ, Be, Mg2þ. Cd, K, Kþ, Ca2þ, Fe, Co, Hg, Mg, Sb, As, Ca, Na, Se, Pb, Ni, V, Cu, Mn, Cr, EC3, F


Mn, OC1, Zn, F
, NO
3 , OP


2
NHþ 4 , NO2 , Cl , Ba, EC1, SO4 , EC2, EC, OC4, Al, OC2

OC3, OC


þ Zn, Cl
, OC1, OP, SO2
4 , NO3 , Al, NH4 , EC1

OC4, NO
2 , EC2, EC, OC3, OC2

OC

Cr, Mn, Cu, OC1

Al, OP, Cl
, EC1, OC4, EC2, EC, NHþ 4

OC3,SO2
4 , OC2, OC

OC1, Ba, EC3, Zn


þ SO2
4 , OP, Al, NH4 , Cl , EC1, OC4, EC2, EC

OC3, OC2, OC


Zn, NO
3 , OC1, Ba, NO2

OP, Cl
, Al, EC1, NHþ 4 , OC4, EC2, EC, SO24

OC3, OC2, OC

Plant B

Plant C

Plant D

Plants

X. Chen et al. / Environmental Pollution 255 (2019) 113157

5

Fig. 1. Carbon fractions in four power plant profiles from this study. (OC ¼ organic carbon; EC ¼ elemental carbon; OP ¼ pryrolyzed carbon; TC ¼ total carbon; OC1, OC2, OC3 and OC4 were measured in a pure helium atmosphere at 120  C, 250  C, 450  C, and 550  C, respectively; EC1, EC2 and EC3, were determined in a 2% oxygen/98% helium atmosphere at 550  C, 700  C, and 800  C,respectively.)

obtained from heating organic substances or is formed directly from pyrolysis, while EC2 is formed via gas-to-particle conversion (Han et al., 2010). 4. Discussion

plant coal combustion (Liu et al., 2018; Thurston and Spengler, 1985). As, less volatile elements than Se and Hg, was found to be more particularly enriched in the bottom ash (Quick and Irons, 2002). Therefore, the proportion of As collected by the dilution channel sampling may be less than that of the sampling method of the bottom ash collection resuspension analysis.

4.1. Implication for source markers 4.2. Comparability among tested power plant profiles of PM2.5 The EnF can be used to reveal elemental markers of sources for PM2.5 from power plant emissions (Chen et al., 2017). The EnF of elemental enrichment factors in PM2.5 from power plants are shown in Fig. 2. The EnF for Se, Hg exceeded 100 and Cd, Zn, Sb, Cu, Ba, Ni and As all had average values that exceeded 20 The corresponding mean (and range) in EnF values were 1413.7 (Se, 538e4243), 337.2 (Hg, 34e1387), 63.9 (Cd, 44e197), 63.4 (Zn, 42e186), 56.6 (Sb, 32e115), 37.6 (Cu, 1e125), 32.3 (Ba, 4e46), 23.5 (Ni, 10e63), and 20.5 (As, 2e39), respectively. That indicated their strong effects from power plants especially those for Se and Hg; Se and Hg can be used as elemental markers for modern power plants that use up-to-date emission control techniques. In general, in addition to Se, As is also often used as source markers for coal-fired power plant emissions, and 64% of total As emissions is from power

Similarities and differences among measured source profiles for the four power plants were identified using coefficients of divergence (CD) (Table S2). The CD values for an individual power plant (0.22e0.41) were relatively lower than that for all power plants (0.43e0.69), indicating that the source profiles collected from the same source were relatively similar, while differences in PM2.5 composition existed among the different power plants. A relatively low CD was found between Plant C and plant D (CD ¼ 0.43), which may have been due to their same unit capacities, or because the BFG that was partly used in plant C had a similar energy usage as plant D. A relatively high CD was found between coal-fired power plants A and B, which may have been due to their different unit capacities, coal quality or operation of decontamination equipment.

Fig. 2. Comparison of elemental enrichment factors in PM2.5 from power plants in this study.

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X. Chen et al. / Environmental Pollution 255 (2019) 113157

4.3. Comparison of PM2.5 profiles with other studies and implication for effects of ULE policy Several published power plants source profiles were collected and listed in Table S3. Similarities and differences in the PM2.5 profiles between this study (four power plants complying with the ULE standard) and published source profiles were evaluated using CDs. According to Fig. S2, the CD between this study and previous studies exceeded 0.6 (0.60e0.99), indicating high differences between the source profiles. Fig. 3 further compares the major components of PM2.5 profiles from power plants in this study with those from previous studies, including OC, EC, and major ions and elements. Compared with those reported in earlier studies, the proportion of OC, EC and NHþ 4 were relatively higher, while the content of geological elements such as Al in PM2.5 were relatively lower. The OC/EC ratio became concentrated at ~5. The implementation of ultra-low emissions policy mainly influences the PM2.5 emission characteristics from power plants in two ways: (i) the improvements of fuel quality; and (ii) emission control technologies retrofit. First, higher ash content (28.5e33.5%) and sulfur content (1.71e1.72%) were typically used in power plants (Kong, 2012). In this study, higher quality coal with lower ash content (11.6e11.8%) and sulfur content (0.37e0.49%) were used in ULE power plants. A similar result was found by Liu et al. (2019), the ash content and sulfur content in ULE CFPPs were concentrated at 0.3e0.8%, 9.3e22.3%, respectively. Therefore, the lower ash content and sulfur content could contribute to the comparatively lower

generation of geological elements and SO2. In addition, the proportion of SO2
4 was relatively reduced through the formation of fewer SO2. Second, to meet the ULE standard, LLT-ESP and WFGD were widely used in sequence. Especially WFGD systems with limestonegypsum are wildly used about 97.3% nationally (https://www. sciencedirect.com/science/article/pii/S0048969719300865?via% 3Dihub CEC, 2017). LLT-ESP, with lower temperatures in gas at the ESP inlet, has a better performance in terms of decreasing particulate matter, could reach a removal efficiency of 96.5e99.9% for PM2.5 (Qi et al., 2017; Wang et al., 2015). Lower temperature can reduce the viscosity, resistivity, and velocity of flue gas to improve the ESP efficiency (Li et al., 2016; Wang et al., 2015). As the temperature decreases, the volatile elements are condensed from the gas phase to the particles, and the downstream ESP device exhibits good removal efficiency of the geological element and ions (Chang et al., 2019; Wang et al., 2019). As for OC and EC, the efficiency of ESP in capturing carbon particles is lower compared with other components (Hao et al., 2008). Due to the largely decrease of other components and particulate matter concentrations, the proportion of OC and EC components relatively increased. For WFGD, over-injected NH3 from SCR could be absorbed into the gypsum slurry downstream in WFGD. With the conversion of SO2 to SO2
4 in the gypsum slurry, high conversion of extra NH3 to þ 2
NHþ 4 could lead to a large increase of NH4 and SO4 in PM2.5. Ac2
cording to Li et al. (2017), WFGD could increase the NHþ 4 and SO4 by approximately 18.9 and 4.2 times, respectively. Therefore,

Fig. 3. Comparison of PM2.5 profiles from this study and from previous studies. (a) All published data in chronological order (Bano et al., 2018; Chen et al., 2017; Chow et al., 2004; Jin, 2007; Kong, 2012; Ma et al., 2015; Pei et al., 2016; Qi et al., 2017; Song et al., 2007; Wang et al., 2016a, b; Watson et al., 2001; Xiao et al., 2012; Zhang et al., 2016; Zhao, 2013; Zheng et al., 2013); (b) Published data in China before 2017 in blue boxes with this study in orange boxes. (OC ¼ organic carbon; EC ¼ elemental carbon.). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

X. Chen et al. / Environmental Pollution 255 (2019) 113157

although the sulfur contents in fuel is decreased significantly, the excess NH3 slipped from SCR to WFGD could contribute the con2
version of SO2 to SO2
4 , which lead to the similar proportion of SO4 in PM2.5 compared with previous studies. In addition, the widely used WFGD influences on the proportion of OC/EC. The OC/EC ratio in PM2.5 emissions from power plants with WFGD or wet dust removal technology is generally higher than that of equipped with dry FGD or dry dust removal technology. OC/EC ratio is close to 5 for WFGD while OC/EC ratio is close to 1 for dry FGD or without WFGD (Wang et al., 2016b; Hao et al., 2008). EC is mainly from incomplete combustion, while OC origins from both the combustion process and secondary generated by the chemical reactions of organic gaseous precursors to particulate aerosols. Higher values of OC/EC ratio were presented for WESP rather than dry-ESP, in which the environment with higher humidity promoted the higher intensity of chemical reactions which significantly increased the concentration of secondary organic carbons. Therefore, with the coverage of large-scale WFGD, the OC/EC ratio in PM2.5 from power plants will become relatively higher and concentrated in ~5. To improve mitigation of power plants of PM2.5 emissions, it is important to understand the influence of fuel quality and decontamination technology on the chemical characteristics of emitted PM2.5. These results underscored the importance that source profiles specific to local emission sources needs to be established as policy changes. Differences in source profiles under different emission standard may increase the uncertainty of source apportionment. More tests are also needed to determine the statistical significance and representatives of the source profiles measured in this study, and to understand their variations as a function of fuel, combustion process and emission control processes.

5. Conclusions PM2.5 and corresponding chemical compositions emitted from four power plants meeting China's ULE standard were analyzed. The results showed that the PM2.5 concentrations emitted from plants A, B, C and D were <1 mg m
3, and emission factors of PM2.5 were 1e2 orders of magnitude lower than those reported in previous studies. The results from this study supported the following conclusions. Carbon (OC þ EC) is the most abundant fraction in the tested power plant emissions (17e61%) with OC/EC ratios z5, whereas geological materials are less abundant in industrial sources, accounting for 1e11% of the total measured mass. The source profiles from the same power plant were similar; however, there were differences between the PM2.5 profiles among different power plants, with divergence coefficients (CDs) in the range 0.43e0.69. Enrichment factors were elevated in terms of Cu, Sb, Zn, Cd, Hg and Se for thermal power plants, and were consistent with the tracer elements. Compared with source profiles from a previous study, higher OC abundance and a lower proportion of geological elements were characteristic of PM2.5 profiles in this study. The study provides updated PM2.5 emission factors and local source profiles, both of which can be used to revise emission inventories and improve particulate source apportionment for ULE power plants.

Conflict of interest We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

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