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天津市郊夏季的臭氧变化特征及其前体物VOCs的来源解析
引用本文:罗瑞雪,刘保双,梁丹妮,毕晓辉,张裕芬,冯银厂.天津市郊夏季的臭氧变化特征及其前体物VOCs的来源解析[J].环境科学,2021,42(1):75-87.
作者姓名:罗瑞雪  刘保双  梁丹妮  毕晓辉  张裕芬  冯银厂
作者单位:南开大学环境科学与工程学院, 国家环境保护城市空气颗粒物污染防治重点实验室, 天津 300350
基金项目:大气重污染成因与治理攻关项目(DQGG0105-01);中国博士后科学基金项目(2019M660986);中央高校基本科研业务费专项
摘    要:本文利用天津市南开大学津南校区大气环境综合观测站的臭氧及其前体物(VOCs和NOx)、气象参数等在线监测仪器,获取了2018年夏季(6~8月)小时分辨率的数据信息;分析臭氧及其前体物的相互关系及变化特征;根据光化学年龄计算出VOCs的初始浓度对其日间(06:00~24:00)VOCs体积分数的光化学损耗进行修正;将初始体积分数和直接监测的VOCs体积分数分别纳入PMF模型进行人为源的来源解析.结果表明,夏季天津O3的平均体积分数为(41.3±25.7)×10-9,而VOCs的平均体积分数为(13.9±12.3)×10-9,其中烷烃的平均体积分数(7.0±6.8)×10-9明显高于其它VOCs物种.烷烃中浓度较高的物种分别为丙烷和乙烷,占总烷烃浓度贡献的47%.夏季O3的生成潜势(OFP)平均值为52.1×10-9,其中烯烃的OFP值最高,对于TVOCs臭氧生成潜势的贡献达到57%.VOCs日间光化学损耗量计算结果表明,烯烃日间损耗占VOCs损耗总量的75%.基于初始浓度解析的VOCs来源分别为:化工排放和溶剂使用(25%)、机动车尾气(22%)、燃烧源(19%)、天然气和液化石油气(19%)和汽油挥发(15%).相比于直接将监测浓度纳入PMF解析的结果,化工排放和溶剂使用贡献百分占比下降4%,机动车尾气贡献百分占比下降5%.利用PMF源解析结果结合OFP分析不同源类对臭氧污染的相对贡献,基于初始体积分数数据的结果显示,贡献最高源类为化工排放和溶剂使用(26%).与利用直接监测数据的解析结果相比,化工排放和溶剂使用的OFP值降低7%,天然气和液化石油气的OFP值明显降低13%.

关 键 词:臭氧  挥发性有机物(VOCs)  初始体积分数  正矩阵因子分解(PMF)  源解析
收稿时间:2020/5/11 0:00:00
修稿时间:2020/7/16 0:00:00

Characteristics of Ozone and Source Apportionment of the Precursor VOCs in Tianjin Suburbs in Summer
LUO Rui-xue,LIU Bao-shuang,LIANG Dan-ni,BI Xiao-hui,ZHANG Yu-fen,FENG Yin-chang.Characteristics of Ozone and Source Apportionment of the Precursor VOCs in Tianjin Suburbs in Summer[J].Chinese Journal of Environmental Science,2021,42(1):75-87.
Authors:LUO Rui-xue  LIU Bao-shuang  LIANG Dan-ni  BI Xiao-hui  ZHANG Yu-fen  FENG Yin-chang
Institution:State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
Abstract:From June to August 2018, a 1-hr resolution concentration dataset of ozone and its gaseous precursors (volatile organic compounds(VOCs) and NOx), and meteorological parameters were synchronously monitored by online instruments of the Nankai University Air Quality Research Supersite. The relationships and variation characteristics between ozone and its precursors were analyzed. According to the photochemical age, the initial concentrations of VOCs were calculated, and the photochemical loss of the concentration of VOCs during the daytime (06:00-24:00) was corrected. The initial and directly monitored concentrations of VOCs were incorporated into the PMF model for source apportionment. The results indicated that the mean concentration of O3 in Tianjin in summer was (41.3±25.7)×10-9, while that of VOCs was (13.9±12.3)×10-9. The average concentration of alkane (7.0±6.8)×10-9 was clearly higher than that of other VOC species. The species with high concentrations of alkanes were propane and ethane, accounting for 47% of the total alkane concentration. The average ozone formation potential (OFP) in summer was 52.1×10-9, and the OFP value of alkene was the highest and its contribution reached 57%. During the daytime, alkene loss accounted for 75% of the total VOC loss. The major sources of VOCs that were calculated based on the initial concentration data were the chemical industry and solvent usage (25%), automobile exhaust (22%), combustion source (19%), LPG/NG (19%), and gasoline volatilization (15%), respectively. Compared with the apportionment results based on directly monitored concentrations, the contribution of the chemical industry and solvent usage decreased by 4%, while automobile exhaust decreased by 5%. By combining the results of PMF apportionment and the OFP model to analyze the relative contributions of emission sources to ozone formation, and we found that the highest contribution source of ozone was the chemical industry and solvent usage (26%) in summer. Compared with the analysis results based on the directly monitored concentrations, the OFP values of the chemical industry and solvent usage decreased by 7%, while that of NG/LPG apparently decreased by 13%.
Keywords:ozone  volatile organic compounds (VOCs)  initial volume fraction  positive matrix factorization (PMF)  source apportionment
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