南京大学学报（自然科学版）2025，Vol.61Issue(3)：363-372,10.DOI:10.13232/j.cnki.jnju.2025.03.002
基于变量相关性的挥发性有机物浓度及源排放协同资料同化策略研究
A correlation-based selection strategy for VOCs data assimilation
摘要
Abstract
Volatile organic compounds(VOCs)are crucial precursors for tropospheric ozone and secondary fine particulate matter(PM2.5),so the treatment strategies of VOCs concentrations and source emissions in data assimilation systems can significantly affect the accuracy of air pollutant forecasting.This study proposes a correlation-based VOCs factor to quantitatively select VOCs model variables and emission inventory items updated by observational data during the data assimilation process.The research employs the WRF-Chem(Weather Research and Forecasting model coupled with Chemistry)model along with the EnSRF(Ensemble Square Root Filter)data assimilation algorithm,focusing on case studies of extreme heat events in the Yangtze River Delta region from July to August,2022.Results show that updating variables through VOCs factor will give the total VOCs emissions a diurnal peak similar to ozone observations.This diurnal peak in VOCs emissions allows for more accurate correction of the systematic model underestimations in ozone forecasts.In terms of the forecasts of ozone and PM2.5,the assimilation strategy using the VOCs factor for updating variable selection performs the best.Compared to strategies without selective updates of VOCs variables,the RMSE(Root Mean Square Error)decreases by 5.5%for ozone and 7.2%for PM2.5.关键词
资料同化/数值模拟/挥发性有机物/空气污染预报Key words
data assimilation/numerical simulation/volatile organic compounds/air pollutant prediction分类
天文与地球科学引用本文复制引用
鞠昊星,彭珍,雷荔傈..基于变量相关性的挥发性有机物浓度及源排放协同资料同化策略研究[J].南京大学学报（自然科学版）,2025,61(3):363-372,10.基金项目
国家自然科学基金(42192553) （42192553）
