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邢台市影响PM2.5和O3浓度多时间尺度演变的重要因素

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为了揭示邢台市大气PM2.5-O3复合污染的演变特征及其影响因素,基于在线监测平台提供的气象要素及污染物浓度数据,使用KZ滤波法分解邢台市PM2.5和O3的原始浓度序列,之后将多元逐步回归法与KZ滤波法结合定量识别污染物的长期分量中源排放及气象因素对污染物浓度的贡献.同时使用随机森林方法,定性探究具体的源排放和气象因子对于邢台市PM2.5和O3原始序列浓度的影响.结果表明:邢台市PM2.5浓度的长期分量呈现显著的下降趋势,短期分量是PM2.5浓度的主要贡献者.O3浓度长期分量呈现增加的趋势,季节分量是O3浓度的主要贡献者.源排放和气象因素对PM2.5长期分量浓度变化的贡献占比约为5:1,两者对于O3长期分量浓度变化贡献占比接近3.5:1,源排放过程是邢台市长期大气PM2.5-O3复合污染的主因.相对湿度(RH)对邢台市PM2.5原始序列浓度的影响最大,其次为工业源排放和机动车尾气排放;影响O3原始序列最大的的3个因子分别是气象因素中的短波辐射强度(SR)、温度(T)以及机动车尾气排放.
Significant factors influencing the multi-temporal-scale evolutions of PM2.5 and O3 concentrations in Xingtai City.
To reveal the evolution characteristics and influencing factors of atmospheric PM2.5-O3 complex pollution in Xingtai City,this study,based on the meteorological elements and pollutant concentration data provided by the online monitoring platform,deployed the KZ filtering method to decompose the original concentration sequences of PM2.5 and O3 in Xingtai City,and combined the multiple stepwise regression method to quantitatively identify the contribution of source emissions and meteorological factors to pollutant concentration in long-term component.Meanwhile,Random Forest method was used to qualitatively explore the effects of specific source emissions and meteorological factors on the original concentration series of PM2.5 and O3 in Xingtai City.The results showed that the long-term component of PM2.5 concentration in Xingtai City showed a significant downward trend,however,short-term component was major contributor to PM2.5 concentration.The long-term component of O3 concentration showed an increasing trend,and the seasonal component was main contributor to O3 concentration.The contribution ratio of source emissions to meteorological factors in the long-term component concentrations of PM2.5 was about 5:1,and that for O3 was close to 3.5:1.The source emission processes were the main cause of long-term atmospheric PM2.5-O3 complex pollution in Xingtai City.Relative humidity(RH)presented a significant influence on the original concentration series of PM2.5 in Xingtai City,followed by industrial source emission and vehicle exhaust emission.The three factors effectively affecting the original O3 concentration sequences were the short-wave radiation intensity(SR),temperature(T)and vehicle exhaust emission.

Xingtai CityPM2.5O3KZ filteringrandom forestinfluencing factors

兰童、韩力慧、田健、齐超楠、肖茜

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北京工业大学环境科学与工程学院,区域大气复合污染防治北京市重点实验室,北京 100124

邢台 PM2.5 O3 KZ滤波 随机森林 影响因素

国家自然科学基金重点项目国家重点研发计划

523300022018YFC0213203

2024

中国环境科学
中国环境科学学会

中国环境科学

CSTPCDCHSSCD北大核心
影响因子:2.174
ISSN:1000-6923
年,卷(期):2024.44(9)