scholarly journals Efficiency of Emission Control Measures on Particulate Matter-Related Health Impacts and Economic Cost during the 2014 Asia-Pacific Economic Cooperation Meeting in Beijing

2016 ◽  
Vol 14 (1) ◽  
pp. 19 ◽  
Author(s):  
Qichen Liu ◽  
Jing Huang ◽  
Bin Guo ◽  
Xinbiao Guo
Keyword(s):  
Particulate Matter ◽  
Emission Control ◽  
Economic Cost ◽  
Economic Cooperation ◽  
Control Measures ◽  
Asia Pacific ◽  
Health Impacts ◽  
Asia Pacific Economic Cooperation ◽  
Emission Control Measures

scholarly journals Characterization of ambient volatile organic compounds and their sources in Beijing, before, during, and after Asia-Pacific Economic Cooperation China 2014

2015 ◽  
Vol 15 (8) ◽  
pp. 12453-12490 ◽  
Author(s):  
J. Li ◽  
S. D. Xie ◽  
L. M. Zeng ◽  
L. Y. Li ◽  
Y. Q. Li ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Control Period ◽  
Economic Cooperation ◽  
Control Measures ◽  
Asia Pacific ◽  
Gas Chromatography Mass Spectrometry ◽  
Asia Pacific Economic Cooperation ◽  
Mixing Ratios ◽  
Volatile Organic

Abstract. Ambient volatile organic compounds (VOCs) were measured using an online system, gas chromatography–mass spectrometry/flame ionization detector (GC-MS/FID), in Beijing, China, before, during and after Asia-Pacific Economic Cooperation (APEC) China 2014, when stringent air quality control measures were implemented. Positive matrix factorization (PMF) was applied to identify the major VOC contributing sources and their temporal variations. The secondary organic aerosols potential (SOAP) approach was used to estimate variations of precursor source contributions to SOA formation. The average VOC mixing ratios during the three periods were 86.17, 48.28, and 72.97 ppbv, respectively. The mixing ratios of total VOC during the control period were reduced by 44%, and the mixing ratios of acetonitrile, halocarbons, oxygenated VOCs (OVOCs), aromatics, acetylene, alkanes, and alkenes decreased by approximately 65, 62, 54, 53, 37, 36, and 23%, respectively. The mixing ratios of all measured VOC species decreased during control, and the most affected species were chlorinated VOCs (chloroethane, 1,1-dichloroethylene, chlorobenzene). PMF analysis indicated eight major sources of ambient VOCs, and emissions from target control sources were clearly reduced during the control period. Contributions of vehicular exhaust were most reduced (19.65 ppbv, the contributions before the control period minus the values after the control period), followed by industrial manufacturing (10.29 ppbv) and solvent utilization (6.20 ppbv). Contributions of evaporated or liquid gasoline and industrial chemical feedstock were slightly reduced, with values of 2.85 and 0.35 ppbv, respectively. Contributions of secondary and long-lived species were relatively stable. Due to central heating, emissions from fuel combustion kept on increasing during the whole campaign; because of weak control of liquid petroleum gas (LPG), the highest emissions of LPG occurred in the control period. Vehicle-related sources were the most important precursor sources likely responsible for the reduction in SOA formation during this campaign.

scholarly journals Characterization of ambient volatile organic compounds and their sources in Beijing, before, during, and after Asia-Pacific Economic Cooperation China 2014

2015 ◽  
Vol 15 (14) ◽  
pp. 7945-7959 ◽  
Author(s):  
J. Li ◽  
S. D. Xie ◽  
L. M. Zeng ◽  
L. Y. Li ◽  
Y. Q. Li ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Control Period ◽  
Economic Cooperation ◽  
Control Measures ◽  
Asia Pacific ◽  
Gas Chromatography Mass Spectrometry ◽  
Asia Pacific Economic Cooperation ◽  
Mixing Ratios ◽  
Volatile Organic

Abstract. Ambient volatile organic compounds (VOCs) were measured using an online system, gas chromatography–mass spectrometry/flame ionization detector (GC-MS/FID), in Beijing, China, before, during, and after Asia-Pacific Economic Cooperation (APEC) China 2014, when stringent air quality control measures were implemented. Positive matrix factorization (PMF) was applied to identify the major VOC contributing sources and their temporal variations. The secondary organic aerosols potential (SOAP) approach was used to estimate variations of precursor source contributions to SOA formation. The average VOC mixing ratios during the three periods were 86.17, 48.28, and 72.97 ppbv, respectively. The mixing ratios of total VOC during the control period were reduced by 44 %, and the mixing ratios of acetonitrile, halocarbons, oxygenated VOCs (OVOCs), aromatics, acetylene, alkanes, and alkenes decreased by approximately 65, 62, 54, 53, 37, 36, and 23 %, respectively. The mixing ratios of all measured VOC species decreased during control, and the most affected species were chlorinated VOCs (chloroethane, 1,1-dichloroethylene, chlorobenzene). PMF analysis indicated eight major sources of ambient VOCs, and emissions from target control sources were clearly reduced during the control period. Compared with the values before control, contributions of vehicular exhaust were most reduced, followed by industrial manufacturing and solvent utilization. Reductions of these three sources were responsible for 50, 26, and 16 % of the reductions in ambient VOCs. Contributions of evaporated or liquid gasoline and industrial chemical feedstock were slightly reduced, and contributions of secondary and long-lived species were relatively stable. Due to central heating, emissions from fuel combustion kept on increasing during the whole campaign; because of weak control of liquid petroleum gas (LPG), the highest emissions of LPG occurred in the control period. Vehicle-related sources were the most important precursor sources likely responsible for the reduction in SOA formation during this campaign.

scholarly journals Air quality improvement in a megacity: implications from 2015 Beijing Parade Blue pollution control actions

2017 ◽  
Vol 17 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Wen Xu ◽  
Wei Song ◽  
Yangyang Zhang ◽  
Xuejun Liu ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Air Quality ◽  
Control Period ◽  
Emission Control ◽  
Monitoring Network ◽  
Control Measures ◽  
Integrated Analysis ◽  
Air Quality Improvement ◽  
Emission Control Measures ◽  
Control Regions

Abstract. The implementation of strict emission control measures in Beijing and surrounding regions during the 2015 China Victory Day Parade provided a valuable opportunity to investigate related air quality improvements in a megacity. We measured NH3, NO2 and PM2.5 at multiple sites in and outside Beijing and summarized concentrations of PM2.5, PM10, NO2, SO2 and CO in 291 cities across China from a national urban air quality monitoring network between August and September 2015. Consistently significant reductions of 12–35 % for NH3 and 33–59 % for NO2 in different areas of Beijing during the emission control period (referred to as the Parade Blue period) were observed compared with measurements in the pre- and post-Parade Blue periods without emission controls. Average NH3 and NO2 concentrations at sites near traffic were strongly correlated and showed positive and significant responses to traffic reduction measures, suggesting that traffic is an important source of both NH3 and NOx in urban Beijing. Daily concentrations of PM2.5 and secondary inorganic aerosol (sulfate, ammonium and nitrate) at the urban and rural sites both decreased during the Parade Blue period. During (after) the emission control period, concentrations of PM2.5, PM10, NO2, SO2 and CO from the national city-monitoring network showed the largest decrease (increase) of 34–72 % (50–214 %) in Beijing, a smaller decrease (a moderate increase) of 1–32 % (16–44 %) in emission control regions outside Beijing and an increase (decrease) of 6–16 % (−2–7 %) in non-emission-control regions of China. Integrated analysis of modelling and monitoring results demonstrated that emission control measures made a major contribution to air quality improvement in Beijing compared with a minor contribution from favourable meteorological conditions during the Parade Blue period. These results show that controls of secondary aerosol precursors (NH3, SO2 and NOx) locally and regionally are key to curbing air pollution in Beijing and probably in other mega cities worldwide.

scholarly journals Enhanced hydrophobicity and volatility of submicron aerosols under severe emission control conditions in Beijing

2017 ◽  
Author(s):  
Yuying Wang ◽  
Fang Zhang ◽  
Zhanqing Li ◽  
Haobo Tan ◽  
Hanbing Xu ◽  
...  
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Control Period ◽  
Emission Control ◽  
Control Measures ◽  
Particle Sizes ◽  
Industrial Emissions ◽  
Aerosol Hygroscopicity ◽  
Emission Control Measures

Abstract. A series of strict emission control measures were implemented in Beijing and the surrounding seven provinces to ensure good air quality during the 2015 China Victory Day parade, rendering a unique opportunity to investigate anthropogenic impact of aerosol properties. Submicron aerosol hygroscopicity and volatility were measured during and after the control period using a hygroscopic and volatile tandem differential mobility analyzer (H/V-TDMA) system. Three periods, namely, the control clean period (Clean1), the non-control clean period (Clean2), and the non-control pollution period (Pollution), were selected to study the effect of the emission control measures on aerosol hygroscopicity and volatility. Aerosol particles became more hydrophobic and volatile due to the emission control measures. The hygroscopicity parameter (κ) of 40–200 nm particles decreased by 32.0 %–8.5 % during the Clean1 period relative to the Clean2 period, while the volatile shrink factor (SF) of 40–300 nm particles decreased by 7.5 %–10.5 %. The emission controls also changed the diurnal variation patterns of both the probability density function of κ (κ-PDF) and the probability density function of SF (SF-PDF). During Clean1 the κ-PDF showed one nearly-hydrophobic (NH) mode for particles in the nucleation mode, which was likely due to the dramatic reduction in industrial emissions of inorganic trace gases. Compared to the Pollution period, particles observed during the Clean1 and Clean2 periods exhibited a more significant non-volatile (NV) mode throughout the day, suggesting a more externally-mixed state particularly for the 150 nm particles. Aerosol hygroscopicities increased as particle sizes increased, with the greatest increases seen during the Pollution period. Accordingly, the aerosol volatility became weaker (i.e., SF increased) as particle sizes increased during the Clean1 and Clean2 periods, but no apparent trend was observed during the Pollution period. Based on a correlation analysis of the number fractions of NH and NV particles, we found that a higher number fraction of hydrophobic and volatile particles during the emission control period.

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