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长江三角洲2017年机动车IVOCs排放清单构建及其对SOA的生成影响
摘要点击 2521  全文点击 816  投稿时间:2019-07-21  修订日期:2019-08-11
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中文关键词  中等挥发性有机物(IVOCs)  机动车  排放清单  长江三角洲  二次有机气溶胶(SOA)
英文关键词  intermediate volatility organic compounds (IVOCs)  vehicles  emission inventory  Yangtze River Delta  secondary organic aerosols (SOA)
作者单位E-mail
王倩 上海大学环境与化学工程学院, 环境污染与健康研究所, 上海 200444 1651119057@qq.com 
黄凌 上海大学环境与化学工程学院, 环境污染与健康研究所, 上海 200444 linghuang@shu.edu.cn 
王杨君 上海大学环境与化学工程学院, 环境污染与健康研究所, 上海 200444 yjwang326@shu.edu.cn 
殷司佳 上海大学环境与化学工程学院, 环境污染与健康研究所, 上海 200444  
张琪 东华大学环境科学与工程学院, 上海 201620  
易鑫 东华大学环境科学与工程学院, 上海 201620  
李莉 上海大学环境与化学工程学院, 环境污染与健康研究所, 上海 200444  
中文摘要
      中等挥发性有机物(IVOCs)对大气中二次有机气溶胶(SOA)的生成有重要贡献,但尚未包括在目前的排放清单中.本研究以长三角地区为研究对象,分别基于排放因子法和IVOCs/POA比例系数法对长三角地区2017年机动车IVOCs的排放量进行估算,构建长三角地区2017年机动车IVOC排放清单,分析其不确定性并估算其对SOA生成潜势的影响.基于排放因子法的结果表明,2017年长三角地区机动车IVOCs排放总量为3.58万t,SOA的生成潜势为695 t,其中载货汽车的IVOCs排放量在长三角大部分城市的占比均超过70%;从燃料类型来看,柴油车的IVOCs排放量远高于汽油车.基于IVOCs/POA比例系数法的结果表明,由不同的IVOCs/POA比例以及不同的POA/PM2.5占比得到的排放清单结果差别巨大,最大值可达64.2万t,最小仅为5.2万t,造成的SOA生成潜势分别为1.55万t和1032 t.本研究表明基于不同的估算方法构建的IVOCs排放清单结果差别巨大,具有很大的不确定性,将直接影响后续空气质量模型对SOA的模拟结果.因此,需进一步将不同清单结果用于空气质量模型中对SOA进行模拟,通过与观测值的比较,从而获得较为准确的长三角地区机动车IVOCs排放清单.
英文摘要
      Intermediate volatility organic compounds (IVOCs) have a significant contribution to the formation of secondary organic aerosols (SOA) in the atmosphere, but are not included in the current emission inventory. In this study, IVOC emissions from vehicles are estimated for the Yangtze River Delta region (YRD) for 2017 based on two methods:the emission factor method and the IVOCs/POA scaling factor method. Uncertainties in the estimated IVOCs emissions and the impact on their potential formation are discussed. The results based on the emission factor method showed that the total vehicular IVOCs emission in the YRD in 2017 was 35800 tons, and that the formation potential of SOA was an estimated 695 tons. IVOCs emissions from trucks accounted for>70% of total IVOCs emissions in most cities in the YRD region. In terms of fuel type, IVOCs emissions from diesel vehicles were much higher than of those from gasoline vehicles. Results based on the IVOCs/POA scaling factor method showed that the emissions calculated by different combinations of IVOCs/POA ratios and POA/PM2.5 ratios that could vary significantly, with a maximum of 64.2×104 tons and a minimum of just 5.2×104 tons. The resultant SOA formation potential was 1.55×104 tons and 1032 tons for the maximum and minimum, respectively. This study shows that the results of IVOCs emissions based on different estimation methods are associated with large uncertainties, which could directly affect the simulation results of SOA in subsequent air quality models. Therefore, it is necessary to use different inventory results in air quality models and perform model evaluation of SOA in order to obtain more accurate IVOCs emission inventories of vehicles in the YRD region.

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