TY - JOUR
T1 - Synoptic meteorological modes of variability for fine particulate matter (PM2.5) air quality in major metropolitan regions of China
AU - Leung, Danny M.
AU - Tai, Amos P.K.
AU - Mickley, Loretta J.
AU - Moch, Jonathan M.
AU - van Donkelaar, Aaron
AU - Shen, Lu
AU - Martin, Randall V.
N1 - Publisher Copyright:
© Author(s) 2017.
PY - 2017
Y1 - 2017
N2 - In this study, we use a combination of multivariate statistical methods to understand the relationships of PM2.5 with local meteorology and synoptic weather patterns in different regions of China across various timescales. Using June 2014 to May 2017 daily total PM2.5 observations from ~1500 monitors, all deseasonalized and detrended to focus on synoptic-scale variations, we find strong correlations of daily PM2.5 with all selected meteorological variables (e.g., positive correlation with temperature but negative correlation with sea-level pressure throughout China; positive and negative 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. Based on a principal component analysis on 1998–2017 meteorological data to diagnose distinct meteorological modes that dominate synoptic weather in four major regions of China, we find strong correlations of PM2.5 with several synoptic modes that explain 10% to 40% of daily PM2.5 variability. 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 study, we further find strong interannual correlations of regionally averaged satellite-derived annual mean PM2.5 with annual mean relative humidity (positive) and springtime fluctuation frequency of the Siberian high (negative). We apply the resulting PM2.5-to-climate sensitivities to IPCC Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections to predict future PM2.5 by 2050s due to climate change, and find a modest decrease of ~0.1 µg m-3 in annual mean PM2.5 in the BTH region, which represents the compensating effects of enhanced relative humidity and synoptic frequency.
AB - In this study, we use a combination of multivariate statistical methods to understand the relationships of PM2.5 with local meteorology and synoptic weather patterns in different regions of China across various timescales. Using June 2014 to May 2017 daily total PM2.5 observations from ~1500 monitors, all deseasonalized and detrended to focus on synoptic-scale variations, we find strong correlations of daily PM2.5 with all selected meteorological variables (e.g., positive correlation with temperature but negative correlation with sea-level pressure throughout China; positive and negative 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. Based on a principal component analysis on 1998–2017 meteorological data to diagnose distinct meteorological modes that dominate synoptic weather in four major regions of China, we find strong correlations of PM2.5 with several synoptic modes that explain 10% to 40% of daily PM2.5 variability. 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 study, we further find strong interannual correlations of regionally averaged satellite-derived annual mean PM2.5 with annual mean relative humidity (positive) and springtime fluctuation frequency of the Siberian high (negative). We apply the resulting PM2.5-to-climate sensitivities to IPCC Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections to predict future PM2.5 by 2050s due to climate change, and find a modest decrease of ~0.1 µg m-3 in annual mean PM2.5 in the BTH region, which represents the compensating effects of enhanced relative humidity and synoptic frequency.
UR - https://www.scopus.com/pages/publications/85052145709
U2 - 10.5194/acp-2017-916
DO - 10.5194/acp-2017-916
M3 - Article
AN - SCOPUS:85052145709
SN - 1680-7316
VL - 18
JO - Atmospheric Chemistry and Physics
JF - Atmospheric Chemistry and Physics
IS - 9
ER -