Source Contributions to PM2.5 under Unfavorable Weather Conditions in Guangzhou City, China

Nan Wang*, Zhenhao Ling, Xuejiao Deng, Tao Deng, Xiaopu Lyu, Tingyuan Li, Xiaorong Gao, Xi Chen

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

24 Citations (Scopus)


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.

我们收集、调研了2013~2016年期间广州的灰霾日,并将其按照主导天气型进行了分类,得到四类不利的天气型. 其中,“冷锋前部型”(FC)和“海上高压型”(SH)发生的频率是最高的(发生概率大于75%). 因此,为了了解广州PM2.5可能的贡献来源,我们开展了针对性的案例研究来解析FC和SH下PM2.5的来源可能. 通过利用WRF-CMAQ模式,解析了不利天气条件下四类潜在的来源贡献,即,广东省以外的贡献(超远距离输送)、珠三角区域的贡献、广州-佛山-深圳的贡献(广佛深)输送和广州本地的贡献. 结果表明,不同天气型主导的条件下PM2.5的污染来源也不同. “海上高压型”是一种静稳的天气,解析表明本地排放是占据主导的贡献(37%),珠三角区域的贡献、广佛深的贡献和外省的贡献仅占据8%,2.8%和7%. 相反,“冷锋前部型”是利于区域输送的天气,外省的贡献(超远距离输送)变得十分显著,贡献量为34.8%,而在这类天气条件下,本地的贡献将降低为12%. 此外,我们提出了一个简化的方法来评估排放和天气条件的影响. 同“海上高压型”相比,天气条件在“冷锋前部型”的影响为35%,而排放的贡献为-18%. 本文研究成果有助于政府相关部门减排施测.

Original languageEnglish
Pages (from-to)1145-1159
Number of pages15
JournalAdvances in Atmospheric Sciences
Issue number9
Early online date5 Jul 2018
Publication statusPublished - Sept 2018

Scopus Subject Areas

  • Atmospheric Science

User-Defined Keywords

  • Community Multiscale Air Quality model
  • fine particulate matter
  • source contribution
  • unfavorable weather system
  • WRF


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