Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China.
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
Environ Pollut. 2020 Jan;256:113419. doi: 10.1016/j.envpol.2019.113419. Epub 2019 Oct 23.
Ozone has become a major atmospheric pollutant in China as the pattern of urban energy usage has changed and the number of motor vehicles has grown rapidly. The Beijing-Tianjin-Hebei Urban Agglomeration, also known as the Jing-Jin-Ji Urban Agglomeration (hereafter, JJJUA), with a precarious balance between protecting the ecological environment and sustaining economic development, is challenged by high levels of ozone pollution. Based on ozone observation data from 13 cities in the JJJUA from 2014 to 2017, the spatio-temporal trends in the evolution of ozone pollution and its associated influencing factors were analyzed using Moran's I Index, hot-spot analysis, and Geodetector using ArcGIS and SPSS software. Five key results were obtained. 1) There was an increase in the annual average ozone concentration, for the period 2014-2017. Comparing the 13 prefecture-level cities, ozone pollution in Chengde and Hengshui decreased, while it worsened in the remaining 11 cities. 2) Ozone pollution was worse in spring and summer than in autumn and winter; the peak ozone pollution season was from May to September; the average ozone concentration on workdays was higher than that on non-workdays, showing a counter-weekend effect. 3) Annual average concentrations were high in the central and southern parts of the study region but low in the north. 4) Prominent positive spatial correlations were observed in ozone concentration, with the best correlations shown in summer and autumn; concentrations were high in Baoding and Xingtai but low in Beijing and Chengde. 5) Concentrations of PM, NO, CO, SO, and PM, as well as average wind speed, sunshine duration, evaporation, precipitation, and temperature, all had significant effects on ozone pollution, and interactions between these influencing factors increased it.
臭氧已经成为中国的主要大气污染物,因为城市能源使用模式发生了变化,机动车数量迅速增加。京津冀城市群,又称京畿城市群(以下简称 JJJUA),在保护生态环境和维持经济发展之间保持着脆弱的平衡,面临着臭氧污染水平高的挑战。本研究基于 2014 年至 2017 年京津冀城市群 13 个城市的臭氧观测数据,利用 Moran's I 指数、热点分析和 Geodetector 等方法,结合 ArcGIS 和 SPSS 软件,分析了臭氧污染的时空演变趋势及其相关影响因素。得出以下五个主要结果:1)2014-2017 年期间,京津冀城市群臭氧浓度呈逐年上升趋势;在 13 个地级市中,承德和衡水臭氧污染呈下降趋势,而其余 11 个城市则呈恶化趋势。2)臭氧污染在春夏季比秋冬季更为严重;臭氧污染高峰期为 5 月至 9 月;工作日的平均臭氧浓度高于非工作日,呈现出反周末效应。3)年平均浓度在研究区域的中部和南部较高,而在北部较低。4)臭氧浓度具有显著的正空间相关性,在夏季和秋季表现最好;保定和邢台的臭氧浓度较高,而北京和承德的臭氧浓度较低。5)PM、NO、CO、SO 和 PM 的浓度以及平均风速、日照时间、蒸发量、降水量和温度对臭氧污染都有显著影响,这些影响因素之间的相互作用增加了臭氧污染的程度。