Sources apportionment of PM 2.5 in a background site in the North China Plain

Yao, Lan; Yang, Lingxiao; Yuan, Qi; Yan, Chao; Dong, Can; Meng, Chuanping; Sui, Xiao; Yang, Fei; Lü, Yanbin; Wang, Wenxing

doi:10.1016/j.scitotenv.2015.09.123

Cited by 203 publications

(71 citation statements)

References 42 publications

(53 reference statements)

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“…Furthermore, compared to the NCANHP, the concentrations of Cr, Cu, Fe, Mn, Ti, Zn, and Pb increased by 0.02, 0.02, 0.34, 0.02, 0.02, 0.28, and 0.07 µg m −3 , respectively, and the P i−heating values of these species were 72.7, 33.1, 34.4, 21.0, 45.8, 48.3, and 36.2 %, respectively, during the NCAHP. Cr, Cu, Fe, Mn, Ti, Zn, and Pb were closely related to industrial sources (Kabala and Singh, 2001;Morishita et al, 2011;Mansha et al, 2012;Liu et al, 2015;Yao et al, 2016); thus, the industrial emissions might have a higher influence on PM 2.5 during the NCAHP than during the NCANHP. Also, it might be closely associated with the unfavourable meteorological factors (Table 1 and Fig.…”

Section: Variations In Chemical Speciesmentioning

confidence: 96%

“…Factor 3 was represented by relatively high loadings of OC (55.9 %), EC (70.9 %), Cu (26.9 %), and Zn (26.5 %). OC and EC are generally predominant in the reported source profile of vehicle exhaust (Yao et al, 2016;Liu et al, 2016Liu et al, , 2017a, Zn is widely used as an additive for lubricant in two-stroke engines, and Cu is closely associated with brake wear (Begum et al, 2004;Canha et al, 2012;Shafer et al, 2012;Lin et al, 2015;Liu et al, 2017a). Therefore, factor 3 was identified as vehicle emissions.…”

Section: Variations In Pm 25 Source Contributionsmentioning

confidence: 99%

“…The contribution proportions of factor 4 to PM 2.5 increased from 26.2 % (51.7 µg m −3 ) during the WY, 28.0 % (63.2 µg m −3 ) during the NCANHP, and 29.5 % (84.0 µg m −3 ) during the NCAHP to 31.7 % (85.2 µg m −3 ) during the CAHP, and lightly increased to 32.6 % (96.3 µg m −3 ) during the ACA. Factor 5 was identified as industrial emissions, with high loadings of Cr (66.7 %), Cu (63.7 %), Fe (83.2 %), Mn (51.3 %), Ti (70.0 %), Zn (69.2 %), Pb (42.1 %), and Cl − (41.0 %) (Morishita et al, 2011;Mansha et al, 2012;Almeida et al, 2015;Liu et al, 2015;Liu et al, 2016;Yao et al, 2016). The contribution proportions of factor 5 to PM 2.5 ranged from 5.0 % (11.3 µg m −3 ) during the NCANHP and 5.1 % (10.0 µg m −3 ) during the WY to 5.9 % (16.7 µg m −3 ) during the NCAHP, and decreased to 5.3 % (14.2 µg m −3 ) during the CAHP and 4.9 % (14.4 µg m −3 ) during the ACA.…”

Section: Variations In Pm 25 Source Contributionsmentioning

confidence: 99%

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Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

et al. 2018

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Abstract. To evaluate the environmental effectiveness of the control measures for atmospheric pollution in Shijiazhuang, China, a large-scale controlling experiment for emission sources of atmospheric pollutants (i.e. a temporary emission control action, TECA) was designed and implemented during 1 November 2016 to 9 January 2017. Compared to the no-control action and heating period (NCAHP), under unfavourable meteorological conditions, the mean concentrations of PM 2.5 , PM 10 , SO 2 , NO 2 , and chemical species (Si, Al, Ca 2+ , Mg 2+ ) in PM 2.5 during the control action and heating period (CAHP) still decreased by 8, 8, 5, 19, 30.3, 4.5, 47.0, and 45.2 %, respectively, indicating that the control measures for atmospheric pollution were effective. The effects of control measures in suburbs were better than those in urban area, especially for the control effects of particulate matter sources. The control effects for emission sources of carbon monoxide (CO) were not apparent during the TECA period, especially in suburbs, likely due to the increasing usage of domestic coal in suburbs along with the temperature decreasing.The results of positive matrix factorization (PMF) analysis showed that crustal dust, secondary sources, vehicle emissions, coal combustion and industrial emissions were main PM 2.5 sources. Compared to the whole year (WY) and the no-control action and no-heating period (NCANHP), the contribution concentrations and proportions of coal combustion to PM 2.5 increased significantly during other stages of the TECA period. The contribution concentrations and proportions of crustal dust and vehicle emissions to PM 2.5 decreased noticeably during the CAHP compared to other stages of the TECA period. The contribution concentrations and proportions of industrial emissions to PM 2.5 during the CAHP decreased noticeably compared to the NCAHP. The pollutants' emission sources during the CAHP were in effective control, especially for crustal dust and vehicles. However, the necessary coal heating for the cold winter and the unfavourable meteorological conditions had an offset effect on the control measures for emission sources to some degree. The results also illustrated that the discharge of pollutants might still be enormous even under such strict control measures.

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Section: Variations In Chemical Speciesmentioning

confidence: 96%

Section: Variations In Pm 25 Source Contributionsmentioning

confidence: 99%

Section: Variations In Pm 25 Source Contributionsmentioning

confidence: 99%

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Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

et al. 2018

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“…In China, agricultural fires mostly occurred in central and north China in early/late June and October. In recent years, crop residue burning often induced serious air pollution in east China and drew increasing attention from public and scientific community (Yang et al, 2008;Li et al, 2010;Tao et al, 2013;Mukai et al, 2014;Long et al, 2016;Yao et al, 2016). A detailed agricultural open fire emission inventory over China with a spatial resolution of 1 km and temporal resolution of 10 days was developed by Huang et al (2012), with the estimated annual emission of PM 2.5 being 0.27 Tg yr -1 .…”

Section: Introductionmentioning

confidence: 99%

A Modeling Study of the Impact of Crop Residue Burning on PM2.5 Concentration in Beijing and Tianjin during a Severe Autumn Haze Event

Zhou

Han

Liu

et al. 2018

Aerosol Air Qual. Res.

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Crop residue burning is one of the important types of biomass burning in China and has potentially important effect on air quality and climate. A coupled meteorology and aerosol/chemistry model (WRF-Chem) with ground and satellite observations and biomass burning emission inventory were applied to investigate the spatial/temporal distribution and transport pathways of air pollutants and to quantify the contribution of crop residue burning to aerosol concentration in the North China Plain, with focus on Beijing and Tianjin during a severe haze episode on 7-11 October 2014, when the daily mean surface PM 2.5 concentration in Beijing reached 317 µg m -3 . During this period, intensive crop fires were detected over wide areas of eastern Henan, southern Hebei and western Shandong, and the crop residue burning emission was much larger than anthropogenic emission in major fire areas. Model comparison with ground observations demonstrated the WRF-Chem was able to generally reproduce surface meteorological variables and PM 2.5 concentration, although it tended to overpredict wind speed and aerosol concentration in some locations. Taking crop residue burning into account can apparently improve PM 2.5 prediction during the haze episode. The stagnant weather condition favored haze formation and maintenance in this region, and crop residue burning intensified haze pollution in both fire source and downwind regions. The crop residue burning emission on average contributed 19% to surface PM 2.5 concentration in Beijing during the haze episode, in which it contributed 40% and 29% to organic carbon aerosol and primary PM 2.5 , respectively, and less to black carbon aerosol (4.9%). The impact of crop residue burning in Tianjin was smaller than that in Beijing, with an average contribution of 7.4% due to different fire sources and transport pathways.

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“…At present, coal is the primary fuel in Hebei province and emissions of PM 2.5 are much higher than in other areas, leading to a rapid deterioration of air quality in Shijiazhuang (Yao et al, 2016). According to the 2015 air quality status reports of 74 cities in China (MEP, 2016), Shijiazhuang city was ranked 8 th among the 10 most polluted cities.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of PM2.5 and Assessing Effects of Emission-Reduction Measures in the Heavy Polluted City of Shijiazhuang, before, during, and after the Ceremonial Parade 2015

Gang

Cheng

Lang

et al. 2017

Aerosol Air Qual. Res.

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The measurement of PM 2.5 was conducted from 15 th August to 17 th September, 2015 in Shijiazhuang, China, covering the period of a ceremonial parade. The PM 2.5 concentrations and the major chemical components were analyzed. The concentrations of PM 2.5 was 26.5 µg m -3 during control, which were 57.0% and 51.1% lower compared to before and after control, respectively. The lowest concentrations of elements and water-soluble ions were also found during control with a decreasing tread of 31.1%-44.2%, and 57.1%-64.2%, respectively. Two typical pollution episodes characterized by significantly elevated PM 2.5 concentration were found during no control due to the combination of no emission-reduction measures and unfavorable weather conditions. The mass percentage of secondary inorganic ions was larger during no control (38.1%-40.3%), pointing to the strong contribution of atmospheric chemical processes. The NO 3 -/SO 4 2-ratios were 0.85, 0.94, and 0.85 before, during, and after control, respectively, and the elevated ratios during control indicate a greater proportion of the PM 2.5 originated from vehicle exhaust. The WRF-CMAQ modeling system was also used to assess the effectively of emission reduction measures and weather conditions. The results indicated that the PM 2.5 concentration increased by 21.6% and 32.1% if no emission-reduction measures were taken and weather conditions in 2014 were used.

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Sources apportionment of PM 2.5 in a background site in the North China Plain

Cited by 203 publications

References 42 publications

Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

A Modeling Study of the Impact of Crop Residue Burning on PM2.5 Concentration in Beijing and Tianjin during a Severe Autumn Haze Event

Characteristics of PM2.5 and Assessing Effects of Emission-Reduction Measures in the Heavy Polluted City of Shijiazhuang, before, during, and after the Ceremonial Parade 2015

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