气候变化领域集成服务门户(CCPortal): High-resolution modeling of gaseous air pollutants over Tehran and validation with surface and satellite data

CCPortal

DOI	10.1016/j.atmosenv.2021.118881
	High-resolution modeling of gaseous air pollutants over Tehran and validation with surface and satellite data
	Shahrokhishahraki N.; Rayner P.J.; Silver J.D.; Thomas S.; Schofield R.
发表日期	2021
ISSN	1352-2310
英文摘要	This study addresses the question of how skillful regional air quality modeling can be when using downscaled globally-available emission inventories. This paper applies global datasets to prepare fine-resolution priori emission inventories for an urban area. Emissions Database for Global Atmospheric Research (EDGAR), Gridded Population of the World, and output from the Fossil Fuel Data Assimilation System are used to downscale the spatiotemporal resolution of global emission inventories to the finer scale. The resultant high-resolution inventory is taken as input for an off-line run of the Community Multi-Scale Air Quality (CMAQ) modeling system to simulate the concentrations of air pollutants in Tehran during August 2018, November 2018, February 2019, and May 2019. These runs are forced with meteorology from the Weather Research and Forecasting (WRF) model. Retrievals of atmospheric composition from the TROPOspheric Monitoring Instrument (TROPOMI) and surface measurements (split into ‘road’ or ‘city’ type stations) are used to compare with the modeled concentrations of NO2, CO, and O3 to assess the capability of the applied modeling framework and emission inventories in concentration estimations. Comparison of modeled NO2 concentration with NO2 tropospheric column shows that the model captures the spatial and temporal distribution with Pearson correlation above 0.7 and 0.6, respectively and absolute bias under 0.08 ppb. The offline WRF-CMAQ simulations overestimate surface measurements of NO2 and CO and underestimate O3. The model captures the diurnal variations for NO2, CO, and O3 with a correlation between 0.7 and 0.91, 0.6–0.8, and 0.5–0.98 and absolute bias less than 69 ppb, 1.15 ppm, and 12.5 ppb, respectively. The overall performance of the observing and modeling system is sufficient for a credible inversion of surface emissions, which is the intended purpose of this modeling set-up. © 2021
关键词	Air quality Emission inventories Remote sensing Urban scale modeling
语种	英语
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248779
作者单位	School of Geography, Earth and Atmospheric Sciences, The University of Melbourne, Australia; ARC Centre of Excellence for Climate Extremes (CLEX), Australia; Melbourne Climate Futures Academy, University of Melbourne, Australia
推荐引用方式 GB/T 7714	Shahrokhishahraki N.,Rayner P.J.,Silver J.D.,et al. High-resolution modeling of gaseous air pollutants over Tehran and validation with surface and satellite data[J],2021.
APA	Shahrokhishahraki N.,Rayner P.J.,Silver J.D.,Thomas S.,&Schofield R..(2021).High-resolution modeling of gaseous air pollutants over Tehran and validation with surface and satellite data.ATMOSPHERIC ENVIRONMENT.
MLA	Shahrokhishahraki N.,et al."High-resolution modeling of gaseous air pollutants over Tehran and validation with surface and satellite data".ATMOSPHERIC ENVIRONMENT (2021).