The impact of circulation patterns on regional transport pathways and air quality over Beijing and its surroundings

Abstract

This study investigated the air pollution characteristics of synoptic-scale circulation in the Beijing megacity, and provided holistic evaluation of the impacts of circulation patterns on air quality during the 2008 Beijing Summer Olympics. Nine weather circulation types (CTs) were objectively identified over the North China region during 2000–2009, using obliquely rotated T-mode principal component analysis (PCA). The resulting CTs were examined in relation to the local meteorology, regional transport pathways, and air quality parameters, respectively. The FLEXPART-WRF model was used to calculate 48-h backward plume trajectories for each CT. Nine CTs were characterized, with distinct local meteorology and air mass origins. CT 1 (high to the west with a strong pressure gradient) was characterized by a northwestern origin, with the smallest local and southeasterly air mass sources, and CT 6 (high to the northwest) had air mass sources mostly from the north and east. In contrast, CTs 5, 8, and 9 (unique, high to the east, and low to the northwest, respectively) were characterized by southern and southeastern trajectories, which indicated a greater influence of high pollutant emission sources. In turn, poor air quality in Beijing (high loadings of PM<sub>10</sub>, BC, SO<sub>2</sub>, NO<sub>2</sub>, O<sub>3</sub>, AOD, and low visibility) was associated with these CTs. Good air quality in Beijing was associated with CTs 1 and 6. The average visibilities (with ±1 σ) in Beijing for CTs 1 and 6 during 2000–2009 were 18.5 ± 8.3 km and 14.3 ± 8.5 km, respectively. In contrast, poor visibility values of 6.0 ± 3.5 km, 6.6 ± 3.7 km, and 6.7 ± 3.6 km were found in CTs 5, 8, and 9, respectively. The mean concentrations of PM<sub>10</sub> for CTs 1, 6, 5, 8, and 9 during 2005–2009 were 90.3 ± 76.3 μg m<sup>−3</sup>, 111.7 ± 89.6 μg m<sup>−3</sup>, 173.4 ± 105.8 μg m<sup>−3</sup>, 158.4 ± 90.0 μg m<sup>−3</sup>, and 151.2 ± 93.1 μg m<sup>−3</sup>, respectively. <br><br> Analysis of the relationship between circulation pattern and air quality during the emission control period suggests that CTs are the primary drivers of day-to-day variations in pollutant concentrations over Beijing and its vicinity. During the Olympics period, the frequency of CT 6 was twice that of the mean in August from 2000 to 2009. This CT had northerly transport pathways and favorable meteorological conditions (e.g. frequent precipitation) for clean air during the Olympics. Assuming that relationships between CTs and air quality parameters in the same season (month) were constant in different years, the relative contributions of synoptic circulation to decreases in PM<sub>10</sub>, BC, SO<sub>2</sub>, NO<sub>2</sub>, CO, AOD, and horizontal light extinction during the Olympics were estimated as 19 ± 14%, 18 ± 13%, 41 ± 36%, 12 ± 7%, 19 ± 1...

Numerical Model-Based Artificial Neural Network Model and Its Application for Quantifying Impact Factors of Urban Air Quality

“…Circulation type is generally identified objectively by air mass or atmospheric circulations. The former utilizes local meteorological parameters to classify circulation types (Tian et al, 2008) and the later uses the gridded sea level pressure (SLP), geopotential height, or wind fields to identify circulation type and is more suitable for air pollution research (Zhang et al, 2012). Here, the gridded sea level pressure (SLP) at 08:00 BT for a 713-point grid (85°E-115°E/25°N-47°N) centered over western Lanzhou (36°N, 104°E) was extracted from the NCEP FNL 1°× 1°pressure fields and used for synoptic-scale circulation classification.…”

“…Here, the gridded sea level pressure (SLP) at 08:00 BT for a 713-point grid (85°E-115°E/25°N-47°N) centered over western Lanzhou (36°N, 104°E) was extracted from the NCEP FNL 1°× 1°pressure fields and used for synoptic-scale circulation classification. There are five main circulation classification techniques: the correlation method, cluster analysis, principal component analysis (PCA), fuzzy method, and nonlinear methods (Zhang et al, 2012). In this study, the T-mode PCA combined with the K-means cluster was used, as it was proposed as the best to reveal data structure and could identify circulation type effectively (Huth, 1996).…”

“…Synoptic-scale circulation governs local meteorological conditions and is effective to identify air pollution level (Oanh et al, 2005). It is the main factor driving the day-to-day variations in pollutant concentrations (Zhang et al, 2012;Lee et al, 2012). The effect of synoptic-scale circulations on local meteorological conditions and air quality has been substantially studied in many areas, such as eastern China, Australia, New Zealand, North America (Pearce et al, 2011a;Pearce et al, 2011b;Lee et al, 2012;Zhang et al, 2012;Jiang et al 2014).…”

Impact of pollution on the optical properties of trans‐Pacific East Asian dust from satellite and ground‐based measurements

“…Figure shows the meteorological wind fields in the horizontal and vertical directions for a 4 day period that encompasses the process from dust outbreak over the deserts in the west to aerosol mixing farther to the east. Meteorological conditions are important for both aerosol entrainment and local air quality [ Zhang et al , ]. Before and during the aerosol outbreaks, low pressure systems associated with upward air current motions are found around the two key dust sources: Taklimakan desert and Gobi desert and also the two pollution sources: East China coast and south China region (Figure a).…”

GIS-based multielement source analysis of dustfall in Beijing: A study of 40 major and trace elements

“…Moreover, the multielement analysis is further extended by PCA. A great advantage of PCA is not just the potential use of dimensionality reduction, but also the qualified results for the following comparisons (Zhang et al, 2012). Thus, this study focuses on not a single element, but a set of elements with the closest connection.…”