基于数值模拟天津臭氧污染特征及其气象影响评估分析方法研究  

Research on the characteristics of ozone pollution and meteorological impact assessment method in Tianjin based on numerical simulation

作　　者：蔡子颖 郝囝[3] 张敏 樊文雁 韩素芹 邱晓滨 唐颖潇[1,2] 杨旭 姚青 CAI Zi-ying;HAO Jian;ZHANG-min;FAN Wen-yan;HAN Su-qin;QIU Xiao-bin;TANG Yin-xiao;YANG Xu;YAO Qing(Tianjin Environmental Meteorological Center,Tianjin 300074,China;CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research,Tianjin 300074,China;Tianjin Institute of Meteorology,Tianjin 300074,China)

机构地区：[1]天津市环境气象中心,天津300074 [2]中国气象局-南开大学大气环境与健康研究联合实验室,天津300074 [3]天津市气象科学研究所,天津300074

出　　处：《中国环境科学》2025年第4期1810-1819,共10页China Environmental Science

基　　金：气象能力提升联合研究专项(23NLTSQ009)。

摘　　要：针对现有臭氧污染气象条件评估方法缺少边界层指标导致表征能力偏差问题,基于2019~2023年气象和环境观测数据,结合臭氧数值模拟,在实现模式臭氧标记法源追踪和过程速率分析技术嵌入基础上,联合观测数据构建天津臭氧污染气象条件评估指数(OWI),实现天津臭氧污染气象条件精准评估.研究结果表明:臭氧浓度和气象条件密切相关,基于平均气温、最高气温、相对湿度、日降水量、白天紫外辐射、午间紫外辐射、日照时数、平均风速和风向构建OWI指数,可初步实现气象条件对臭氧浓度影响表征,该指数与O_(3)浓度相关系数0.82,可识别82%的臭氧轻度及以上污染.分析白天和夜间边界层高度对前体物扩散、近地面氮氧化物滴定和臭氧垂直交换影响,针对垂直扩散条件较好时,OWI指数表征O_(3)浓度较实况偏高问题,增加白天和夜间边界层高度指标优化OWI指数.通过臭氧数值模拟,实现水平、垂直输送、对流、化学生成、湍流混合和区域输送对臭氧浓度影响计算,联合模拟结果和观测,优化特定条件下OWI指数,如白天垂直输送大于15μg/(m^(3)·h),白天臭氧化学生成量大于20μg/(m^(3)·h),适当调高OWI指数;区域输送过强时,计算周边臭氧污染气象条件指标,综合判断气象条件对臭氧影响.To address the issue of biases in the representational capabilities of existing assessment methods for ozone pollution meteorological conditions,stemming from a lack of boundary layer indicators,this study utilized meteorological and environmental observation data collected from 2019 to 2023.By integrating ozone numerical simulations and incorporating source tracking along with process rate analysis techniques within the model framework,we developed a joint model and observation-based Tianjin Ozone Pollution Meteorological Condition Assessment Index(OWI).This index aims to accurately assess ozone pollution meteorological conditions in Tianjin.The research findings reveal a strong correlation between ozone concentrations and various meteorological factors.The OWI index was constructed based on parameters such as average temperature,maximum temperature,relative humidity,daily precipitation,daytime ultraviolet radiation,midday ultraviolet radiation,sunshine duration,average wind speed,and wind direction.It effectively characterizes the impact of these meteorological conditions on ozone levels.Notably,this index exhibits a correlation coefficient of 0.82 with O_(3) concentration and demonstrates an ability to identify 82%of mild or more severe ozone pollution incidents.Furthermore,by analyzing the effects of daytime and nighttime boundary layer heights on precursor diffusion processes—such as near-surface nitrogen oxide titration and vertical exchange of ozone—the study addresses potential overestimations in O_(3) concentrations by the OWI index under favorable vertical diffusion conditions.To optimize the OWI index further,we incorporated indicators for both daytime and nighttime boundary layer heights.Through ozone numerical simulations,the study calculated the effects of horizontal and vertical transport,convection,chemical generation,turbulent mixing,and regional transport on ozone levels.By combining simulation results with observations,the OWI index was oized under specific conditions,such as adjusting upwa

关 键 词：臭氧 污染气象条件评估 环境模式 边界层 天津 

分 类 号：X513[环境科学与工程—环境工程]