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Accueil du site → Master → Hong Kong → Synoptic meteorological modes of variability for fine particulate matter (PM2.5) air quality in major metropolitan regions of China : implications of climate change on future air quality

The Chinese University of Hong Kong (2018)

Synoptic meteorological modes of variability for fine particulate matter (PM2.5) air quality in major metropolitan regions of China : implications of climate change on future air quality

LEUNG, Min

Titre : Synoptic meteorological modes of variability for fine particulate matter (PM2.5) air quality in major metropolitan regions of China : implications of climate change on future air quality

Auteur : LEUNG, Min

Université de soutenance : The Chinese University of Hong Kong

Grade : Master of Philosophy in Earth and Atmospheric Sciences 2018

Résumé
In this study, we use a combination of multivariate statistical methods to understand the relationships of PM2.5with local meteorology andsynoptic weather patternsin different regions of China across various timescales, and to predict future air qualityover China due to climate change. Using June 2014to May 2017 daily total PM2.5observations from 1500 monitorsand 1998–2017 NCEP/NCAR meteorology, all deseasonalized and detrended to focus on synoptic-scale variations, we find strong correlations of daily PM2.5with all selected meteorological variables, e.g., positive correlation with temperature (r= 0.6) but negative correlation with sea-level pressure (r= –0.5) throughout China ;positive (r= 0.4) and negative (r= –0.4) correlation with relative humidity in northern and southern China, respectively.The spatial patterns suggest that the apparent correlations with individual meteorological variables may arise from common association with synoptic systems. iiBased on a principal component analysis on 1998–2017 meteorological data to diagnose distinct meteorological modes that dominate synoptic weather in four major metropolitan regions of China, we find strong correlations of PM2.5with several synoptic modesthat explain upto 40% of daily PM2.5variability. These modes include monsoonal flows and cold frontal passages in northern and central China associated with the Siberian high, onshore flows in eastern China, and frontal rainstorms in southern China.Using the Beijing–Tianjin–Hebei (BTH) region as a case studyfor a statistical model of interannual PM2.5variability, we further find strong interannual correlations of 1998–2016 satellite-derived annual mean PM2.5with annual mean relative humidity (RH, r= 0.49) and springtime fluctuation frequency of cold fronts from the Siberian high (r= –0.51).We apply the resulting PM2.5-to-climate sensitivities to the Intergovernmental Panel on Climate Change (IPCC) Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections to predict future PM2.5in the BTH region by the 2050s due to climate change, and find a modest decrease of 0.5 μg m-3in annual mean PM2.5in BTH due tomore frequent cold-frontalventilationunder the RCP8.5 future, but the RH-induced PM2.5change is inconclusive due to the largeCMIP5 intermodel differences in RH projections. We extend the multiple linear regression (MLR) model across different gridsfor PM2.5-meteorology sensitivities over the whole China, and find a much stronger positive dependence of PM2.5on annual mean temperature of 5 μg m-3 K-1over central China, caused by varying in reaction rate of PM2.5precursors, biogenic emissions and biomass burning. Changes of PM2.5over China due to climate change by 2050s are on average+10 μg m-3over central and eastern China, and are +15 μg m-3for 90thpercentile changes, dominated by future temperature increase, representinga strong “climate penalty” on future PM2.5air quality

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Page publiée le 20 décembre 2022