2019冠状病毒病大流行期间全球空气污染物排放的变化:大气化学建模数据集

T. Doumbia, C. Granier, N. Elguindi, I. Bouarar, S. Darras, G. Brasseur, B. Gaubert, Yiming Liu, Xiaoqing Shi, T. Stavrakou, S. Tilmes, F. Lacey, A. Deroubaix, Tao Wang
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引用次数: 21

摘要

摘要为了应对新冠肺炎全球大流行的蔓延,世界上大多数国家都采取了几周到几个月的封锁等控制措施。这些封锁对许多国家的经济和个人活动产生了重大影响。若干利用卫星和地面观测的研究报告了大气污染物和温室气体时空分布的重要变化。目前正在进行全球和区域化学输运模式研究,以分析这些封锁对大气化合物分布的影响。这些建模研究旨在评估区域封锁在全球范围内的影响。为了为全球和区域模式模拟提供输入,开发了一个提供调整因子(AFs)的数据集,该数据集易于应用于全球和区域排放清单。该数据集提供了2020年1月至8月期间,以0.1 × 0.1纬度/经度分辨率,每天或每月为基础的交通(公路、航空和船舶交通)、发电、工业和住宅部门的网格化AFs。AFs的量化是基于从不同数据库收集的活动数据和先前发表的研究。在每个网格点上提供一系列AFs用于模型敏感性研究。将本研究开发的排放AFs应用于CAMS全球清单(CAMS- glob - ant_v4.2 _r1.1),讨论了全球不同地区和2020年前6个月主要污染物的排放变化。2月份,中国东部地区的NOx、NMVOCs和SO2的排放量与参考排放量相比平均下降了20 - 30%,降幅最大。在其他地区,4月份变化最大,欧洲和北美的NOx、NMVOCs和CO平均减少20 - 30%,南美洲的减少幅度更大(30 - 50%)。在印度和非洲地区,NOx和NMVOCs的排放量减少了15 - 30%。除南美洲外,其他物种的CO和BC的最大降幅一般小于15%,据估计南美洲CO和BC的降幅较大。正如本文所讨论的,由于封锁在部分或完全恢复之前的持续时间不同,不同地区和部门的减少情况差别很大。提供AFs(平均值和平均值±标准差)范围的数据集称为“conforme (COvid - adjustmeNt Factor fOR eMissions)”(https://doi.org/10.25326/88)。它由大气化合物排放和辅助数据汇编(ECCAD)数据库(https://eccad.aeris-data.fr/)分发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Changes in global air pollutant emissions during the COVID-19 pandemic: a dataset for atmospheric chemistry modeling
Abstract. In order to fight the spread of the global COVID-19 pandemic, most of the world countries have taken control measures such as lockdowns during a few weeks to a few months. These lockdowns had significant impacts on economic and personal activities in many countries. Several studies using satellite and surface observations have reported important changes in the spatial and temporal distributions of atmospheric pollutants and greenhouse gases. Global and regional chemistry-transport model studies are being performed in order to analyze the impact of these lockdowns on the distribution of atmospheric compounds. These modeling studies aim at evaluating the impact of the regional lockdowns at the global scale. In order to provide input for the global and regional model simulations, a dataset providing adjustment factors (AFs) that can easily be applied to global and regional emission inventories has been developed. This dataset provides, for the January–August 2020 period, gridded AFs at a 0.1 × 0.1 latitude/longitude degree resolution, on a daily or monthly basis for the transportation (road, air and ship traffic), power generation, industry and residential sectors. The quantification of AFs is based on activity data collected from different databases and previously published studies. A range of AFs is provided at each grid point for model sensitivity studies. The emission AFs developed in this study are applied to the CAMS global inventory (CAMS-GLOB-ANT_v4.2_R1.1), and the changes in emissions of the main pollutants are discussed for different regions of the world and the first six months of 2020. Maximum decreases in the emissions are found in February in Eastern China, with an average reduction of 20–30 % in NOx, NMVOCs and SO2 relative to the reference emissions. In the other regions, the maximum changes occur in April, with average reductions of 20–30 % for NOx, NMVOCs and CO in Europe and North America and larger decreases (30–50 %) in South America. In India and African regions, NOx and NMVOCs emissions are reduced by 15–30 %. For the others species, the maximum reductions are generally less than 15 %, except in South America, where large decreases in CO and BC are estimated. As discussed in the paper, reductions vary highly across regions and sectors, due to the differences in the duration of the lockdowns before partial or complete recovery. The dataset providing a range of AFs (average and average ± standard deviation) is called CONFORM (COvid adjustmeNt Factor fOR eMissions) (https://doi.org/10.25326/88). It is distributed by the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) database (https://eccad.aeris-data.fr/).
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