TY - JOUR
T1 - Source Contributions to PM2.5 under Unfavorable Weather Conditions in Guangzhou City, China
AU - Wang, Nan
AU - Ling, Zhenhao
AU - Deng, Xuejiao
AU - Deng, Tao
AU - Lyu, Xiaopu
AU - Li, Tingyuan
AU - Gao, Xiaorong
AU - Chen, Xi
N1 - Funding Information:
Acknowledgements. This study was supported by the Na-
Funding Information:
tional Key R&D Program of China: Task 3 (Grant No. 2016 YFC0202000); Guangzhou Science and Technology Plan (Grant No. 201604020028); National Natural Science Foundation of China (Grant No. 41775037 and 41475105); Science and Technology Innovative Research Team Plan of Guangdong Meteorological Bureau (Grant No. 201704); Guangdong Natural Science Foundation-Major Research Training Project (2015A030308014); and a science and technology study project of Guangdong Meteorological Bureau (Grant No. 2015Q03). The author also thanks Tsinghua University for providing MEIC.
Publisher Copyright:
© 2018, Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2018/9/1
Y1 - 2018/9/1
N2 - Historical haze episodes (2013–16) in Guangzhou were examined and classified according to synoptic weather systems. Four types of weather systems were found to be unfavorable, among which “foreside of a cold front” (FC) and “sea high pressure” (SP) were the most frequent (>75% of the total). Targeted case studies were conducted based on an FC-affected event and an SP-affected event with the aim of understanding the characteristics of the contributions of source regions to fine particulate matter (PM2.5) in Guangzhou. Four kinds of contributions—namely, emissions outside Guangdong Province (super-region), emissions from the Pearl River Delta region (PRD region), emissions from Guangzhou–Foshan–Shenzhen (GFS region), and emissions from Guangzhou (local)—were investigated using the Weather Research and Forecasting–Community Multiscale Air Quality model. The results showed that the source region contribution differed with different weather systems. SP was a stagnant weather condition, and the source region contribution ratio showed that the local region was a major contributor (37%), while the PRD region, GFS region and the super-region only contributed 8%, 2.8% and 7%, respectively, to PM2.5 concentrations. By contrast, FC favored regional transport. The super-region became noticeable, contributing 34.8%, while the local region decreased to 12%. A simple method was proposed to quantify the relative impact of meteorology and emissions. Meteorology had a 35% impact, compared with an impact of -18% for emissions, when comparing the FC-affected event with that of the SP. The results from this study can provide guidance to policymakers for the implementation of effective control strategies.
AB - Historical haze episodes (2013–16) in Guangzhou were examined and classified according to synoptic weather systems. Four types of weather systems were found to be unfavorable, among which “foreside of a cold front” (FC) and “sea high pressure” (SP) were the most frequent (>75% of the total). Targeted case studies were conducted based on an FC-affected event and an SP-affected event with the aim of understanding the characteristics of the contributions of source regions to fine particulate matter (PM2.5) in Guangzhou. Four kinds of contributions—namely, emissions outside Guangdong Province (super-region), emissions from the Pearl River Delta region (PRD region), emissions from Guangzhou–Foshan–Shenzhen (GFS region), and emissions from Guangzhou (local)—were investigated using the Weather Research and Forecasting–Community Multiscale Air Quality model. The results showed that the source region contribution differed with different weather systems. SP was a stagnant weather condition, and the source region contribution ratio showed that the local region was a major contributor (37%), while the PRD region, GFS region and the super-region only contributed 8%, 2.8% and 7%, respectively, to PM2.5 concentrations. By contrast, FC favored regional transport. The super-region became noticeable, contributing 34.8%, while the local region decreased to 12%. A simple method was proposed to quantify the relative impact of meteorology and emissions. Meteorology had a 35% impact, compared with an impact of -18% for emissions, when comparing the FC-affected event with that of the SP. The results from this study can provide guidance to policymakers for the implementation of effective control strategies.
KW - Community Multiscale Air Quality model
KW - fine particulate matter
KW - source contribution
KW - unfavorable weather system
KW - WRF
UR - http://www.scopus.com/inward/record.url?scp=85049579581&partnerID=8YFLogxK
U2 - 10.1007/s00376-018-7212-9
DO - 10.1007/s00376-018-7212-9
M3 - Journal article
AN - SCOPUS:85049579581
SN - 0256-1530
VL - 35
SP - 1145
EP - 1159
JO - Advances in Atmospheric Sciences
JF - Advances in Atmospheric Sciences
IS - 9
ER -