Zhu Yuan-Yuan, Gao Yu-Xiao, Liu Bing, Wang Xiao-Yan, Zhu Li-Li, Xu Rong, Wang Wei, Ding Jun-Nan, Li Jian-Jun, Duan Xiao-Li
China National Environmental Monitoring Centre, Beijing 100012, China.
School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Huan Jing Ke Xue. 2019 Dec 8;40(12):5191-5201. doi: 10.13227/j.hjkx.201905007.
This paper discusses the concentration characteristics of PM, as well as its relationship with meteorological factors in autumn and winter (from September to the following February), from 2013 to 2018 in the Beijing-Tianjin-Hebei (BTH) region. The accuracy and uncertainty of the air quality forecast models NAQPMS(nested air quality prediction modeling system), CMAQ(community multiscale air quality modeling system), and CAMx (comprehensive air quality model with extensions) were analyzed based on the model-predicted and measured PM concentration in autumn and winter from 2015 to 2018. The accuracy of NAQPMS, CMAQ, and CAMx during typical heavy air pollution was also tested. Moreover, methods to improve the accuracy of the model forecast were discussed. The results showed that the mean concentrations of PM in the BTH region were 122, 98, 82, 99, and 65 μg·m in the five autumn and winter periods, respectively. When the air quality index (AQI) exceeded 150 during each autumn and winter, it reached 229, 198, 210, 204, and 180 μg·m, respectively. There were 64 occurrences of heavy regional PM air pollution in autumn and winter from 2013 to 2018. The average duration was longest in the 2013 to 2014 period, and shortest in the 2017 to 2018 period. The peak concentration and average concentration of PM decreased year on year, except for the period from 2016 to 2017. In autumn and winter, PM concentration had a relatively close relationship with relative humidity, wind and sunshine duration, compared with a weak relationship with temperature and air pressure. Regional heavy air pollution always happened under the condition of low wind speed(less than 2 m·s),higher relative humidity(greater than 65%),and southwest and northeast wind direction. In addition, the heavy air pollution of PM in BTH in autumn and winter can be effectively forecasted by NAQPMS, CMAQ, and CAMx. The predicted and measured PM concentration showed a close relationship. The models performed well in forecasting Zhangjiakou, Chengde, and Qinhuangdao, but by contrast overestimated in Tangshan, Shijiazhuang, Baoding, Beijing, and Tianjin. The uncertainty of emission sources, measured and predicted meteorological data, and the atmospheric chemical reaction mechanism may be the main reasons for the overestimate.
本文讨论了2013年至2018年京津冀地区秋冬季节（9月至次年2月）细颗粒物（PM）的浓度特征及其与气象因素的关系。基于2015年至2018年秋冬季节模型预测和实测的PM浓度，分析了空气质量预测模型NAQPMS（嵌套空气质量预测建模系统）、CMAQ（社区多尺度空气质量建模系统）和CAMx（扩展的综合空气质量模型）的准确性和不确定性。还测试了NAQPMS、CMAQ和CAMx在典型重度空气污染期间的准确性。此外，还讨论了提高模型预测准确性的方法。结果表明，京津冀地区五个秋冬季节PM的平均浓度分别为122、98、82、99和65μg·m³。每个秋冬季节空气质量指数（AQI）超过150时，分别达到229、198、210、204和180μg·m³。2013年至2018年秋冬季节共出现64次区域性PM重度空气污染。平均持续时间在2013年至2014年期间最长，在2017年至2018年期间最短。除2016年至2017年期间外，PM的峰值浓度和平均浓度逐年下降。在秋冬季节，PM浓度与相对湿度、风速和日照时长的关系较为密切，与温度和气压的关系较弱。区域性重度空气污染总是在低风速（小于2m·s）、较高相对湿度（大于65%）以及西南和东北风向的条件下发生。此外，NAQPMS、CMAQ和CAMx能够有效预测京津冀地区秋冬季节PM的重度空气污染。预测的PM浓度与实测浓度显示出密切关系。这些模型在预测张家口、承德和秦皇岛时表现良好，但相比之下，在唐山、石家庄、保定、北京和天津则出现高估。排放源的不确定性、实测和预测的气象数据以及大气化学反应机制可能是高估的主要原因。
