RAPID: Coronavirus-Driven Aerosol Reductions in East Asia and the Effect on Atmospheric Dynamics

该项目的目标是确定中国在2020年2月实施的政府强制新冠肺炎隔离是如何改变疾病传播的气象条件的。在东亚新冠肺炎疫情最严重的时候，中国政府授权关闭许多工业设施，暂时大幅减少了中国东部的空气污染。颗粒物排放的迅速减少可能会削弱进入大气层的太阳能的强度，这可能会让更多的阳光穿过大气层，从而在隔离期间提高地表气温。由于病原体的传播在更温暖、更潮湿的条件下会被减缓，地面气温上升与检疫措施减少的气雾剂同时出现，可能代表了另一种无意的机制，正是通过这种机制，大规模封锁可以减缓新冠肺炎的传播。该项目将使用卫星图像和天气模型模拟来确定2020年2月期间空气污染减少对中国东部气温以及其他几个气象条件的影响程度。该项目的发现还将揭示更多关于大气颗粒物如何在正常、非检疫的基础上影响区域天气模式的重要信息。该项目将挖掘每日NO2、气溶胶光学厚度(AOD)和气温的卫星图像以及来自世界气象组织和气溶胶机器人网络(AERONET)的现场数据，以评估污染减少和气温上升的共同演变。此外，该项目将在2020年2月在东中国上空进行数值模拟实验，其中一个模拟以正常排放初始化，第二个模拟减少与2020年2月期间收集的卫星观测相适应的排放。该项目将产生三个主要产品：(1)中国东部925和850百帕温度的逐日数据库，包括绝对值和气候学偏差；(2)中国上空典型排放和新冠肺炎减少排放的两个月天气模拟；(3)气溶胶辐射效应对气温的净影响，以及环流、云量和降水变化的摘要。这些产品对新冠肺炎大流行以及未来的疾病爆发都很有价值，因为它们可以告知隔离和封锁如何通过气溶胶减少和相关的气象反馈潜在地阻止病原体传播。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The goal of this project is to determine how China’s government-mandated COVID-19 quarantine during February 2020 altered the meteorological conditions in which the disease was being transmitted. During the height of the COVID-19 outbreak in East Asia, the Chinese government authorized closure of many industrial facilities, temporarily and dramatically reducing air pollution in East China. The swift reduction of particulate emissions, which can weaken the intensity of incoming solar energy, would have likely allowed more sunlight to pass through the atmosphere, thereby increasing surface air temperature during the quarantine. Because pathogen transmission can be retarded in warmer and more humid conditions, increased surface air temperatures concurrent with quarantine-reduced aerosols may represent another, yet unintentional, mechanism by which large-scale lockdowns can slow the spread of COVID-19. This project will employ satellite imagery and weather model simulations to determine the extent to which reduced air pollution altered air temperature, as well as several other meteorological conditions, during February 2020 in East China. The findings of this project will also reveal additional important information about how atmospheric particulates influence regional weather patterns on a normal, non-quarantine basis.This project will mine daily satellite images of NO2, aerosol optical depth (AOD), and air temperature as well as in-situ data from the World Meteorological Organization and Aerosol Robotic Network (AERONET) to assess the co-evolution of pollution decreases and air temperature increases. Additionally, the project will employ the Weather Research and Forecasting (WRF) model coupled with chemistry (WRF-Chem) in a numerical modeling experiment for February 2020 over East China, whereby one simulation is initialized with normal emissions and the second simulation reduces emissions commensurate with the satellite observations collected during February 2020. This project will yield three key products: (1) Daily database of NO2, AOD, and surface, 925-, and 850-hPa temperature over East China, both absolute values and departure from climatology; (2) Two one-month weather simulations for typical emissions and COVID-19-reduced emissions over China; (3) The net impact of aerosol radiative effects on air temperature, as well as a summary of any changes to circulation, cloud cover, and precipitation. These products are valuable for the COVID-19 pandemic, as well as future disease outbreaks, because they can inform how quarantines and lockdowns potentially impede pathogen transmission via aerosol reductions and associated meteorological feedbacks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.