This study investigated the air pollution characteristics of synoptic-scale circulation in the Beijing megacity, and provided quantitative 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. Each CT was characterized with distinct local meteorology and air mass origin. CT 1 (high pressure to the west with a strong pressure gradient) was characterized by a northwestern air mass origin, with the smallest local and southeasterly air mass sources, and CT 6 (high pressure to the northwest) had air mass sources mostly from the north and east. On the contrary, CTs 5, 8, and 9 (weak pressure field, high pressure to the east, and low pressure 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 PM₁₀, BC, SO₂, NO₂, NO_x, O₃, 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&sigma;) 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, low 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 PM₁₀ for CTs 1, 6, 5, 8, and 9 during 2005–2009 were 90.3 ± 76.3 μg m⁻³, 111.7 ± 89.6 μg m⁻³, 173.4 ± 105.8 μg m⁻³, 158.4 ± 90.0 μg m⁻³, and 151.2 ± 93.1 μg m⁻³, 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 are fixed in different years, the relative contributions of synoptic circulation to decreases in PM₁₀, BC, SO₂, NO₂, NO_x, CO, and horizontal light extinction during the Olympics were ...

Steady meteorological conditions are important external factors affecting air pollution. In order to analyze how adverse meteorological variables affect air pollution, surface synoptic situation patterns and meteorological conditions during heavy pollution episodes are discussed. The results showed that there were 78 RPHPDs (regional PM 2.5 pollution days) in Jiangsu, with a decreasing trend year by year. Winter had the most stable meteorological conditions, thus most RPHPDs appeared in winter, followed by autumn and summer, with the least days in spring. RPHPDs were classified into three patterns, respectively, as equalized pressure (EQP), advancing edge of a cold front (ACF) and inverted trough of low pressure (INT) according to the SLP (sea level pressure). RPHPDs under EQP were the most (51%), followed by ACF (37%); INT was the minimum (12%). Using statistical methods and meteorological condition data on RPHPDs from 2013 to 2017 to deduce the thresholds and 2018 as an independent dataset to validate the proposed thresholds, the threshold values of meteorological elements are summarized as follows. The probability of RPHPDs without rain was above 92% with the daily and hourly precipitation of all RPHPDs below 2.1 mm and 0.8 mm. Wind speed, RHs, inversion intensity(ITI), height difference in the temperature inversion(ITK), the lower height of temperature inversion (LHTI) and mixed-layer height (MLH) in terms of 25%-75% high probability range were respectively within 0.5-3.6 m s −1 , 55%-92%, 0.7-4.0 • C 100 m −1 , 42-576 m, 3-570 m, 200-1200 m. Two conditions should be considered: whether the pattern was EQP, ACF or INT and whether the eight meteorological elements are within the thresholds. If both criteria are met, PM 2.5 particles tend to accumulate and air pollution diffusion conditions are poor. Unfavorable meteorological conditions are the necessary, but not sufficient condition for RPHPDs.

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 PM₁₀, BC, SO₂, NO₂, O₃, 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 PM₁₀ for CTs 1, 6, 5, 8, and 9 during 2005–2009 were 90.3 ± 76.3 μg m⁻³, 111.7 ± 89.6 μg m⁻³, 173.4 ± 105.8 μg m⁻³, 158.4 ± 90.0 μg m⁻³, and 151.2 ± 93.1 μg m⁻³, 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 PM₁₀, BC, SO₂, NO₂, CO, AOD, and horizontal light extinction during the Olympics were estimated as 19 ± 14%, 18 ± 13%, 41 ± 36%, 12 ± 7%, 19 ± 1...

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