Synoptic meteorological modes of variability for fine particulate matter (PM<sub>2.5</sub>) air quality in major metropolitan regions of China

Abstract

Abstract.In this study, we use a combination of multivariate statistical methods to understand the relationships of PM 2.5 with local meteorology and synoptic weather patterns in different regions of China across various timescales. Using June 2014 to May 2017 daily total PM 2.5 observations from 15 ~1500 monitors, all deseasonalized and detrended to focus on synoptic-scale variations, we find strong correlations of daily PM 2.5 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 20 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 PM 2.5 with several synoptic modes that explain 10% to 40% of daily PM 2.5 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 25 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 PM 2.5 with annual mean relative humidity (positive) and springtime fluctuation frequency of the Siberian high (negative). We apply the resulting PM 2.5 -to-climate sensitivities to IPCC Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections to predict future PM 2.5 by 2050s due to 30 climate change, and find a modest decrease of ~0.1 µg m -3 in annual mean PM 2.5 in the BTH region, which represents the compensating effects of enhanced relative humidity and synoptic frequency.Atmos. Chem. Phys. Discuss., https://doi

Climatic Factors and Their Availability in Estimating Long‐Term Variations of Fine Particle Distributions Over East China

“…Unlike meteorological index defined empirically, these climatic indices have clear definitions from the National Climate Center of China and have been widely used in climate diagnosis and predictions (Cantelaube et al, ; Hallett et al, ). It is acknowledged that climatic factors play vital roles in the long‐term and large‐scale distributions of aerosols, whereas the variations of meteorological parameters, such as a specific synoptic process, influence the instantaneous perturbations of PM 2.5 concentrations in the limited region (Leung et al, ; Zheng et al, ). Moreover, the variations of climatic indices can include all the changes in atmospheric circulation patterns and interactions among meteorological factors.…”

“…The large‐scale atmospheric circulations can impact on the spatial pattern of PM 2.5 mainly through changes in synoptic systems and meteorological conditions. Specific synoptic systems, such as the presence of high‐pressure systems with subsiding airflow and uniform surface pressure fields, are favorable for the enhancement of PM 2.5 concentrations (Tai et al, ; Zheng et al, ; Miao et al, ; Leung et al, ). As for meteorological conditions, many studies investigated that high relative humidity, calm wind, shallow planetary boundary layer, and reduced precipitation can be typically responsible for instantaneous aerosol accumulations at the lower atmosphere (Tie et al, ; Wang et al, ; Yang et al, ; Ye et al, ).…”

Significant Impact of Rossby Waves on Air Pollution Detected by Network Analysis

“…The geopotential height data are from the global ERA‐Interim reanalysis (2.5° × 2.5°) of the European Center for Medium‐Range Weather Forecasts (Dee et al., ). To filter out trivial seasonal effects, we first detrended the original data by subtracting the corresponding centered 30‐day “moving” means and then normalized by the standard deviation of these 30 days (see Leung et al., ; Tai et al., ).…”

Short‐Term Weather Patterns Modulate Air Quality in Eastern China During 2015–2016 Winter

“…Previous studies show that meteorological conditions often play important role in modulating air pollution. For instance, the wave patterns in a global or semihemisphere scale, synoptic circulations in a regional scale (Leung et al, 2017;Pozzoli et al, 2017;Yin & Wang, 2017;Zhao et al, 2016), and local meteorological fields related to the topography (Zhao et al, 2015), as well as their interactions among different scales (Ye et al, 2016), all associate with air pollution. Additionally, interactions between aerosols and planetary boundary layer (PBL; Ding et al, 2016;Tie et al, 2017) and feedback between dust and wind can also affect air pollution (Yang et al, 2017).…”