The Impact of the Direct Effect of Aerosols on Meteorology and Air Quality Using Aerosol Optical Depth Assimilation During the KORUS‐AQ Campaign

Liang

J Environ Health Sci Engineer

et al. 2020

Background COVID-19 is a global pandemic. The purpose of this study is to explore correlations between the novel coronavirus (COVID-19) and meteorological indicators from cities across China. Methods We collected daily data of the cumulative number of infected, recovered and death cases, and the meteorological indicators including average temperature, wind speed, relative humidity, precipitation and air quality index (AQI) from 12 cities in China during the period of Jan 23 to Feb 22, 2020. Correlation tests were chosen for data analysis. Results The average temperature and AQI showed significant association with the mortality rate of COVID-19. The mortality rate was not correlated with wind speed, relative humidity or precipitation. Meanwhile, higher average temperatures and more precipitation were beneficial for the recovery rate of COVID-19, but the recovery rate was not correlated with wind speed, relative humidity or AQI. Conclusions Our study provides a new basis for correlations between COVID-19, meteorological indicators and air quality index, which can help authorities to combat COVID-19.

Section: Introductionmentioning

confidence: 99%

Correlations between Meteorological Indicators, Air Quality and the COVID-19 Pandemic in 12 Cities across China

Liang

J Environ Health Sci Engineer

et al. 2020

“…In contrast to satellite observations with sparse spatiotemporal coverages (Ma et al, 2014(Ma et al, , 2015Xue et al, 2019), these ground sites can provide hourly PM2.5 concentrations at high spatial resolution in urban areas. Data assimilation (DA) methods that have been widely used in meteorology can be extended to integrate those continuous observational constraints with chemical transport models (CTMs) (Bocquet et al, 2015;Chai et al, 2017;Gao et al, 2017;Jung et al, 2019;Ma et al, 2019). It has been demonstrated that the capability of several representative DA methods, such as the optimal interpolation (OI) (Chai et al, 2017), 3D/4D variational methods , and the ensemble Kalman filter algorithm (Chen et al, 2019a), can bridge the estimation gaps between observed and simulated results.…”

Section: Introductionmentioning

confidence: 99%

Significant wintertime PM<sub>2.5</sub> mitigation in the Yangtze River Delta, China from 2016 to 2019: observational constraints on anthropogenic emission controls

Wang¹,

Yu²,

Li³

et al. 2020

Preprint

Abstract. Ambient fine particulate matter (PM2.5) mitigation relies strongly on anthropogenic emission control measures, the actual effectiveness of which is challenging to pinpoint owing to the complex synergies between anthropogenic emissions and meteorology. Here, observational constraints on model simulations allow us to derive not only reliable PM2.5 evolution but also accurate meteorological fields. In this study, we isolate meteorological factors to achieve reliable estimates of surface PM2.5 responses to both long-term and emergency emission control measures from 2016 to 2019 over the Yangtze River Delta (YRD), China. The results show that long-term emission control strategies play a crucial role in curbing PM2.5 levels (> 14 μg/m3, 19 %), especially in the megacities and other areas with abundant anthropogenic emissions. The G20 summit hosted in Hangzhou in 2016 provides a unique and ideal opportunity involving the most stringent, even unsustainable, emergency emission control measures. For the winter time periods from 2016 to 2019, the most substantial declines in PM2.5 concentrations (~ 35 μg/m3, ~ 59 %) are thus achieved in Hangzhou and its surrounding areas. The following hotspots also emerge in megacities, especially in Shanghai (32 μg/m3, 51 %), Nanjing (27 μg/m3, 55 %), and Hefei (24 μg/m3, 44 %). Compared to the long-term policies from 2016 to 2019, the emergency emission control measures implemented during the G20 Summit achieve more significant decreases in PM2.5 concentrations (17 μg/m3 and 41 %) over most of the whole domain, especially in Hangzhou (24 μg/m3, 48 %) and Shanghai (21 μg/m3, 45 %). By extrapolation, we derive insight into the magnitude and spatial distributions of PM2.5 mitigation potentials across the YRD, revealing significantly additional rooms for curbing PM2.5 levels.

“…these increases corresponded to a local -31.39 W m -2 reduction in solar radiation received at the surface, and reductions in planetary boundary layer height, air temperature, and surface wind speed over land, and a deceleration of vertical transport (Jung et al, 2019). Other studies in East Asia have shown ADE decreasing local shortwave reaching the surface by -20 Wm -2 (Wang et al, 2016), as well as significant changes in surface particulate matter and gas concentrations in response to these radiation changes.…”

Section: Introductionmentioning

confidence: 95%

Forest Fire Aerosol – Weather Feedbacks over Western North America Using a High-Resolution, Fully Coupled, Air-Quality Model

Makar¹,

Akingunola²,

Chen³

et al. 2020

Preprint

Abstract. The influence of both anthropogenic and forest fire emissions, and their and subsequent chemical and physical processing, on the accuracy of weather and air-quality forecasts, was studied using a high resolution, fully coupled air-quality model. Simulations were carried out for the period 4 July through 5 August 2019, at 2.5-km horizontal grid cell size, over a 2250 x 3425 km2 domain covering western Canada and USA, prior to the use of the forecast system as part of the FIREX-AQ ensemble forecast. Several large forest fires took place in the Canadian portion of the domain during the study period. A feature of the implementation was the incorporation of a new on-line version of the Canadian Forest Fire Emissions Prediction System (CFFEPSv4.0). This inclusion of thermodynamic forest fire plume-rise calculations directly into the on-line air-quality model allowed us to simulate the interactions between forest fire plume development and weather. Incorporating feedbacks resulted in improvements in most metrics of both air-quality and meteorological model forecast performance, through comparison of no-feedback and feedback simulations with surface, radiosonde, and satellite observations. For the meteorological simulations, these improvements occurred at greater than the 90 % confidence level. Relative to the climatological cloud condensation nuclei and aerosol optical properties used in the no-feedback simulations, the fully coupled model’s aerosol indirect and direct effects were shown to result in feedback loops characterized by increased surface temperatures, decreased lower troposphere temperatures, and increased lower troposphere cloud droplet and raindrop number densities. The aerosol direct and indirect effect reduced oceanic cloud droplet number densities and increased oceanic rain drop number densities, relative to the no-feedback climatological simulation. The aerosol direct and indirect effects were responsible for changes to the aerosol concentrations at greater than the 90 % confidence level throughout the model domain, and to NO2 and O3 concentrations within forest fire plumes. The simulations show that incorporating aerosol direct and indirect effect feedbacks can significantly improve the accuracy of weather and air quality forecasts, and that forest fire plume rise calculations within a fully coupled model changes the predicted fire plume dispersion and emissions, the latter through changing the meteorology driving fire behaviour and growth.