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2017~2019年秦皇岛市昌黎县空气质量评价与分析 被引量:3

Evaluation and Analysis of Air Quality in Changli County from 2017 to 2019
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摘要 为了解河北省昌黎县2017~2019年空气质量状况,应用秦皇岛市生态环境局提供的监测数据,对空气质量各级别的时间比例、首要污染物、月均质量浓度变化、污染物相关性进行了统计分析。结果表明:河北省昌黎县空气达标时间比例由2017年的64.4%上升至2019年的75.1%,空气质量持续改善;2017年和2018年,空气首要污染物是PM_(10)和PM_(2.5);2019年,O_(3)成为了首要污染物,且时间比例接近40%,空气污染防控的重点应该由对颗粒物控制转为对O_(3)和颗粒物的联合控制;O_(3)月均质量浓度最大值出现在5月和6月,其他5种污染物质的月均最高质量浓度集中出现在1月份、11月份和3月份,冬季的防控重点是颗粒物,夏季的防控重点是O_(3);控制PM_(10)和NO_(2)的排放,可以较好抑制PM_(2.5)的产生。 To understand the air quality of Changli County from 2017 to 2019,the monitoring data provided by Qinhuangdao Bureau of Ecology and Environment were used to conduct statistical analysis on the proportion of time with air quality levels,the primary pollutant,the change of average monthly mass concentration and the correlation of pollutants.The results showed that the proportion of days in which the air reached the standard in Changli County had risen from 64.4%in 2017 to 75.1%in 2019,and air quality had continued to improve.In 2017 and 2018,the primary air pollutants were PM_(10) and PM_(2.5).In 2019,O_(3) became the primary pollutant,and the proportion of days was close to 40%.The focus of air pollution prevention and control should be shifted from the control of PM to the combined control of O_(3)&PM.The highest monthly average mass concentration of O_(3) occurred in May and June,and the highest monthly average mass concentration of other 5 pollutants occurred in January,November and March.The prevention and control focus was PM in winter and O_(3) in summer.PM_(10) and NO_(2) emission control could better reduce the production of PM_(2.5).
作者 谢新宇 闫妍 XIE Xinyu;YAN Yan(College of Agronomy and Biotechnology,Hebei Normal University of Science&Technology,Qinhuangdao Hebei,066600;Qinhuangdao Warning Center of Environmental Emergency and Heavy Pollution Weather,China)
出处 《河北科技师范学院学报》 CAS 2021年第2期72-77,共6页 Journal of Hebei Normal University of Science & Technology
关键词 空气质量 评价与分析 空气污染物 昌黎县 air quality evaluate and analyze air pollutant Changli County
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