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Assessment of a high-resolution NO_x emission inventory using satellite observations: A case study of southern Jiangsu, China

机译:利用卫星观测评估高分辨率的NO_x排放量清单:以中国苏南地区为例

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摘要

To evaluate the bottom-up NOx emission inventories with different data sources and spatial scales, an updated product of tropospheric NO2 vertical column densities (VCDs) from Ozone Monitoring Instrument (OMI), POMINO, was applied in chemistry transport modeling (CTM) and Gaussian function model for southern Jiangsu, a typical developed and polluted region in eastern China. Compared to the national emission inventory (MEIC), better correlation was found between spatial distributions of the high-resolution provincial inventory (JS) and POMINO VCDs. When applied in CTM, the simulated VCDs using JS were closer to POMINO data than those using MEIC, indicating the advantage of the provincial inventory that incorporated detailed information of individual plants. The simulated VCDs, however, were generally larger than observed ones, particularly for regions with high NO2 levels, partly because the improved NOx control measures for power sector were not fully considered in both national and provincial inventories. The "top-down" NOx emissions were estimated for four cities/city combinations in southern Jiangsu, using a Gaussian function model based on POMINO NO2 VCDs. The results were found to be most consistent with the estimates in JS among bottom-up inventories with different data sources. To further harmonize emissions and satellite observations at relatively small spatial scale, the online emission measurement data for individual plants are recommended for emission inventory development, and the products of satellite observation data with finer horizontal resolution are encouraged.
机译:为了评估具有不同数据源和空间规模的自下而上的NOx排放清单,将来自臭氧监测仪器(OMI)POMINO的对流层NO2垂直柱密度(VCD)的更新产品应用于化学迁移模型(CTM)和高斯模型江苏南部(中国东部典型的发达和污染地区)的功能模型。与国家排放清单(MEIC)相比,高分辨率省级清单(JS)和POMINO VCD的空间分布之间具有更好的相关性。当在CTM中应用时,使用JS的模拟VCD比使用MEIC的VCD更接近POMINO数据,这表明省级清单的优势在于它包含了各个工厂的详细信息。但是,模拟的VCD通常比观察到的VCD大,特别是对于NO2含量较高的地区,部分原因是国家和省级清单中都没有充分考虑电力部门改进的NOx控制措施。使用基于POMINO NO2 VCD的高斯函数模型,估算了苏南四个城市/城市组合的“自上而下” NOx排放量。发现结果与使用不同数据源的自下而上清单中的JS估算最一致。为了在较小的空间尺度上进一步协调排放和卫星观测,建议为排放清单开发各个工厂的在线排放测量数据,并鼓励使用水平分辨率更高的卫星观测数据的产品。

著录项

  • 来源
    《Atmospheric environment》 |2018年第10期|135-145|共11页
  • 作者

    Zhao Yu; Xia Yinmin; Zhou Yaduan;

  • 作者单位

    Nanjing Univ, State Key Lab Pollut Control & Resource Reuse, 163 Xianlin Ave, Nanjing 210023, Jiangsu, Peoples R China;

    Nanjing Univ, State Key Lab Pollut Control & Resource Reuse, 163 Xianlin Ave, Nanjing 210023, Jiangsu, Peoples R China;

    Nanjing Univ, State Key Lab Pollut Control & Resource Reuse, 163 Xianlin Ave, Nanjing 210023, Jiangsu, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Nitrogen oxide; Satellite observation; Emissions; Chemistry transport modeling;

    机译:氮氧化物卫星观测排放化学迁移模型;

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