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基于机器学习量化气象和排放对2014-2023年杭州城乡臭氧演变的影响
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1.浙江省遂昌县气象局;2.福建省灾害天气重点实验室;3.杭州市气象局;4.中国科学院大气物理研究所;5.浙江临安大气成分本底国家野外科学观测研究站

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Quantifying the Impact of Meteorology and Emission on the Evolution of Ozone in Urban and Rural Hangzhou from 2014 to 2023 Based on Machine Learning
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1.Suichang County Meteorological Bureau of Zhejiang Province;2.Fujian Key Laboratory of Severe Weather;3.Hangzhou Meteorological Bureau;4.Institute of Atmospheric Physics, Chinese Academy of Sciences;5.Zhejiang Lin'an, Atmospheric Background, National Observation and Research Station

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    摘要:

    自2013年国务院开始执行空气质量改善行动计划以来,我国空气质量得到全面改善,但臭氧(O3)污染凸显。由于气象和前体物的非线性影响,O3演变趋势与排放变化的响应关系在杭州不同区域存在差异,分离气象和排放对O3污染演变的影响,评估减排措施的管控成效,对制定精准的防治政策具有重要意义。本文利用2014-2023年暖季(4-10月)杭州15个监测站点的观测数据,综合分析了与O3相关的多个指标的城乡演变规律,并采用基于随机森林算法的去气象方法,剥离O3长期演变趋势中气象和排放的各自贡献,定量评估了O3污染治理效果。结果显示,杭州MDA8 O3和Ox年增长率分别为1.4和0.07 μg/m3/yr,其中城区增幅和浓度值均明显高于乡镇,城乡O3和Ox差异持续增大,NOx减排未能有效抑制臭氧上升。从2018年起气象条件由不利O3生成转为有利,且气象对O3浓度最高的5月和9月影响显著,整体O3年际上升趋势中64%由于气象条件导致,36%为管控不利导致。剔除气象影响后,长期管控措施有效降低了城市和乡镇地区的大气氧化能力,遏制了乡镇地区O3浓度的增加,但对城市O3以及局部光化学生成的管控未见成效。上述结果显示在不利气象条件下(重点为5月和9月)继续加强人为管控是抑制杭州臭氧污染的关键。

    Abstract:

    Since the State Council began to implement the Air Quality Improvement Action Plan in 2013, the air quality in China has been comprehensively improved. However, ozone (O3) pollution has become prominent. Due to the nonlinear influences of meteorology and precursors, the response relationship between the evolution trend of O3 and the change in emissions varies in different regions of Hangzhou. Separating the impacts of meteorology and emissions on the evolution of O3 pollution and evaluating the management and control effectiveness of emission reduction measures are of great significance for formulating precise prevention and control policies.This paper utilizes the observational data of 15 monitoring stations in Hangzhou during the warm seasons from 2014 to 2023, comprehensively analyzes the urban and rural evolution laws of multiple indicators related to O3, and adopts the de-meteorological method based on the random forest algorithm to separate the respective contributions of meteorology and emissions in the long-term evolution trend of O3, so as to quantitatively evaluate the effect of O3 pollution control.The results show that the annual growth rates of MDA8 O3 and Ox in Hangzhou as a whole are 1.4 μg/m3/yr and 0.07 μg/m3/yr respectively. Among them, the increase range and concentration values in urban areas are significantly higher than those in rural areas. The differences in O3 and Ox between urban and rural areas in Hangzhou continue to increase, and the reduction of NOx emissions has failed to effectively suppress the rise of ozone. Since 2018, meteorological conditions have changed from being unfavorable to favorable for ozone generation, which is most significant in May and September, the months with the most serious pollution. In the overall interannual upward trend of O3, 64% is caused by meteorological conditions, and the rest is due to ineffective management and control. After excluding the influence of meteorology, long-term management and control measures have effectively reduced the atmospheric Oxidation capacity in both urban and rural areas and curbed the increase in O3 concentration in rural areas. However, there has been no effect on the control of O3 in urban areas and local photochemical generation. The above results indicate that continuing to strengthen anthropogenic control measures under unfavorable meteorological conditions (focusing on May and September) is key to suppressing ozone pollution in Hangzhou.

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  • 收稿日期:2025-03-28
  • 最后修改日期:2025-06-06
  • 录用日期:2025-07-16
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