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首页> 外文期刊>Atmospheric environment >Continuous monitoring, compositions analysis and the implication of regional transport for submicron and fine aerosols in Beijing, China
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Continuous monitoring, compositions analysis and the implication of regional transport for submicron and fine aerosols in Beijing, China

机译：连续监测，成分分析及其在中国北京的亚微米和精细气溶胶的区域运输意义

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摘要

A comprehensive observation was conducted to reveal the characteristics of submicron and fine aerosols and their chemical components in Beijing in autumn. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) model, Weather Research & Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were applied to identify the impacts of emissions from surrounding areas on PM2.5 concentrations in Beijing for different study episodes. These results showed that the monthly average concentration of non-refractory submicron aerosols (NR-PM1 ) was 60.20 +/- 53.48 mu g/m(3), with organics being the major fraction (42.33%), followed by NO3- (22.87%), SO42- (18.70%), NH4+ (12.24%) and CI- (3.86%). The PSCF and CWT analysis indicated common high source regions was located in the western Shandong, northern Henan and southern Hebei, and the distribution of the source areas usually varied with species during different episodes. The regional source apportionment results revealed that 52.36% of surface PM2.5 in Beijing. was contributed by surrounding sources in terms of monthly mean and the outside contribution increased to 64.56% during the haze days, indicating the strong influence of regional transport on Beijing haze pollution. Note that the PM2.5 inflows for Beijing mainly came from Baoding and Langfang, and outflows towards Chengde and Zhangjiakou, identifying two key transport pathways: the southwest-northeast pathway and the southeast-northwest pathway. The PM2.(5) inflow fluxes from surroundings were much higher than outflows from Beijing, leading to the peaking PM2.5 pollution, with the highest concentrations occurring from 00:00 to 11:00 LT, 14 October 2016. Based on the net PM2.(5) fluxes and their vertical distributions, we discovered the PM (2.5) transport mainly occurred at 400-800 m during the entire episode, while at 600-1000 m for a heavy pollution episode, both followed by the southwest-northeast pathway. However, the PM2.5 fluxes were far lower for a clean episode, and followed by the northwest-southeast pathway.
机译：进行了全面的观察，揭示了北京秋季的亚微米和精细气溶胶的特征及其化学成分。应用潜在源贡献函数（PSCF）和浓度加权轨迹（CWT）模型，天气研究与预报（WRF）和具有扩展功能的综合空气质量模型（CAMx）来确定周围区域排放物对PM2.5浓度的影响在北京学习不同的情节。这些结果表明，非难熔亚微米气溶胶（NR-PM1）的月平均浓度为60.20 +/- 53.48μg / m（3），其中有机物为主要成分（42.33％），其次是NO3-（22.87）。 ％），SO42-（18.70％），NH4 +（12.24％）和CI-（3.86％）。 PSCF和CWT分析表明，常见的高污染源地区位于山东西部，河南北部和河北南部，并且在不同的时期，源区域的分布通常随物种而变化。区域源解析结果表明，北京市地表PM2.5占52.36％。在雾霾天，大气污染是由周围资源贡献的，外部贡献在雾霾天增加到64.56％，表明区域交通对北京雾霾污染的影响很大。请注意，北京的PM2.5流入主要来自保定和廊坊，并流向承德和张家口，这确定了两条主要的运输途径：西南-东北通道和东南-西北通道。来自周围环境的PM2。（5）流入量远高于来自北京的流出量，导致PM2.5污染达到峰值，最高浓度发生在2016年10月14日中部时间00:00至11:00。 PM2。（5）通量及其垂直分布，我们发现PM（2.5）的运输主要发生在整个事件的400-800 m，而重度污染事件的运输在600-1000 m，其次是西南-东北途径。但是，PM2.5的通量要干净得多，然后是西北-东南路径。

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  • 来源
    《Atmospheric environment》 |2018年第12期|30-45|共16页
  • 作者

    Zhang Hanyu; Cheng Shuiyuan; Wang Xiaoqi; Yao Sen; Zhu Fang;

  • 作者单位

    Beijing Univ Technol, Key Lab Beijing Reg Air Pollut Control, Beijing 100124, Peoples R China;

    Beijing Univ Technol, Key Lab Beijing Reg Air Pollut Control, Beijing 100124, Peoples R China;

    Beijing Univ Technol, Key Lab Beijing Reg Air Pollut Control, Beijing 100124, Peoples R China;

    Beijing Univ Technol, Key Lab Beijing Reg Air Pollut Control, Beijing 100124, Peoples R China;

    Beijing Univ Technol, Key Lab Beijing Reg Air Pollut Control, Beijing 100124, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Submicron and fine aerosols; Chemical components; PSCF and CWT model; WRF-CAMx; PM2.5 flux;

    机译：亚微米和细小气溶胶;化学成分;PSCF和CWT模型;WRF-CAMx;PM2.5通量;

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