人为管控下典型城市空气质量及经济指标特征
Air Quality and Industrial Characteristics of Typical Cities During Control Period in China
周岳 1屈垚 1张勇 1刘卉昆 1师菊莲 2朱崇抒3
作者信息
- 1. 中国科学院地球环境研究所,黄土与第四纪地质国家重点实验室,中国科学院气溶胶化学与物理重点实验室,陕西 西安 710061;陕西关中平原区域生态环境变化与综合治理国家野外科学观测研究站,陕西 西安 710061;陕西省大气污染与雾霾防治重点实验室,陕西 西安 710061
- 2. 西安地球环境创新研究院,陕西 西安 710061
- 3. 中国科学院地球环境研究所,黄土与第四纪地质国家重点实验室,中国科学院气溶胶化学与物理重点实验室,陕西 西安 710061;中国科学院第四纪科学与全球变化卓越创新中心,陕西 西安 710061;陕西关中平原区域生态环境变化与综合治理国家野外科学观测研究站,陕西 西安 710061;陕西省大气污染与雾霾防治重点实验室,陕西 西安 710061
- 折叠
摘要
为探讨中国典型城市在极端人为源管控条件下空气质量和产业特征,文章分析了 2018-2020年1-5月武汉、北京、上海、广州、西安、成都和拉萨等7个城市空气质量及产业发展指标;同比了极端人为管控期大气污染物浓度及经济产业指标变化特征.结果表明:受极端人为管控影响,管控期各污染物浓度同比、环比均出现显著降低,其中NO2浓度环比下降幅度最大,约为50％,其次是PM2.5和PM10,百分比为30％～40％.但O3浓度总体呈现上升趋势,未来需进一步采取措施,加强PM2.5和O3协同控制,推动城市空气质量持续改善.各城市不同管控力度对大气污染浓度变化有显著影响.此外,对比了 2020年第一和第二季度3类产业发展状况,北京、广州、西安和成都均为第一产业产值恢复速度较快,第三产业增长率最慢为10％;同比3类产业表明管控措施对第二产业影响较大.
Abstract
The research was conducted in seven cities,including Wuhan,Beijing,Shanghai,Guangzhou,Xi'an,Chengdu,and Lhasa.The variations of several pollutants were investigated from January to May 2020,the air quality was discussed among the three periods,including the epidemic prevention and control period,before and after the epidemic prevention and control period.Basing on the indicators of economic development,the interannual variations of the industrial characteristics were explored for the period from 2018 to 2019.The results show that the concentrations of major pollutants decreased signifi-cantly during the period of epidemic prevention and control year on year.During the period of epidemic prevention and control,the concentrations of NO2 decreased the most with around 50％in different cities,followed by PM2.5 and PM10 with the percentages of 30％～40％.The concentrations of O3 showed increasing trends.The development of primary industry recovered faster in Beijing,Guangzhou,Xi'an,and Chengdu in the first and second quarters of 2020.While the growth rate of the tertiary industry in these cities was the slowest with the percentage of 10％.
关键词
空气质量/大气污染特征/产业结构/人为源管控Key words
air quality/air pollution characteristics/industrial structure/anthropogenic source control引用本文复制引用
基金项目
国家重点研发计划项目(2017YFC0212200)
出版年
2024
NETL
NSTL
万方数据