Cai Zi-Ying, Yan Xu, Han Su-Qin, Yao Qing, Liu Jin-le
Tianjin Environmental Meteorological Center, Tianjin 300074, China.
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China.
Huan Jing Ke Xue. 2020 Nov 8;41(11):4855-4863. doi: 10.13227/j.hjkx.202004252.
Regional transport is an important factor when considering the prevention and control of air pollution. The aim of this study was to provide support for the joint prevention and control of air pollution in the Beijing-Tianjin-Hebei region. With a focus on an analysis of the relationship between regional transport and meteorological conditions based on the weather background, an atmospheric chemical model was developed to quantitatively estimate the impact of regional transport on Tianjin from October 2016 to September 2017. The results showed that the contribution percentage of regional transport in cities in plains in the Beijing-Tianjin-Hebei region was significantly higher than in cities in mountains. The local contribution of PM in the Tianjin area was 62.9% and the contribution of regional transport was 37.1%. This was mainly affected by transmissions of Chanzhou, Langfang, central and southern Hebei, Beijing, Tanshan, and Shandong. Regional transport was the most significant from April to June, the weakest from July to August, and the highest contributor to local emissions. Regional transport was closely related to weather situation, wind field, precipitation, and other meteorological conditions. Post-high pressure and pre-frontal low pressure were the two types of pollution weather with the highest proportion in regional transport, and the impact of air pollution transport under the southwest wind, westerly wind and south wind was the most apparent. Wind speed of 2-3 m·s was beneficial to the regional transport of PM, and precipitation above 5 mm will effectively reduce the regional transport of air pollutants. For different pollution types and heavy pollution stages, the contribution of regional transport was the most apparent in light pollution weather, being 20.5% higher than the average. The heavy pollution weather was controlled by static stable air mass, and because of the migration of high PM concentrations, pollution air mass in the surrounding area had a significant impact on the accumulation of pollution and transport in the region. The contribution ratio of PM transport in the heavy pollution period was more than the average and was approximately 10% and 15% higher. In the process of heavy pollution, the proportion of transport contribution in the initial accumulation stage and peak stage were higher than in other periods, and 14.5% and 19.5% higher than in the outbreak stage. The contribution of local emissions in the outbreak stage was more significant, being 9.9% higher than average.
在考虑空气污染防治时,区域传输是一个重要因素。本研究的目的是为京津冀地区空气污染的联防联控提供支持。基于天气背景,重点分析区域传输与气象条件之间的关系,建立了一个大气化学模型,以定量评估2016年10月至2017年9月区域传输对天津的影响。结果表明,京津冀地区平原城市区域传输的贡献率明显高于山区城市。天津地区PM的本地贡献率为62.9%,区域传输贡献率为37.1%。这主要受沧州、廊坊、冀中南部、北京、唐山和山东的传输影响。区域传输在4月至6月最为显著,7月至8月最弱,对本地排放的贡献率最高。区域传输与天气形势、风场、降水等气象条件密切相关。高压后部和锋前低压是区域传输中占比最高的两种污染天气类型,西南风、西风和南风下空气污染传输的影响最为明显。2 - 3m·s的风速有利于PM的区域传输,5mm以上的降水将有效减少空气污染物的区域传输。对于不同的污染类型和重污染阶段,区域传输的贡献在轻度污染天气中最为明显,比平均值高20.5%。重污染天气受静态稳定气团控制,由于高PM浓度的迁移,周边地区的污染气团对该地区污染的积累和传输有显著影响。重污染时段PM传输的贡献率高于平均值,分别高出约10%和15%。在重污染过程中,传输贡献在初始积累阶段和峰值阶段的占比高于其他时期,分别比爆发阶段高出14.5%和19.5%。爆发阶段本地排放的贡献更为显著,比平均值高9.9%。