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 ...

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Although numerous models have been employed to address the issue of landslide susceptibility at regional scale, few have incorporated landslide typology into a model application. Thus, the aim of the present study is to perform landslide susceptibility zonation taking landslide classification into account using a data-driven model. The specific objective is to answer the question: how to select reasonable influencing factors for different types of landslides so that the accuracy of susceptibility assessment can be improved? The Qilihe District in Lanzhou City of northwestern China was undertaken as the test area, and a total of 12 influencing factors were set as the predictive variables. An inventory map containing 227 landslides was created first, which was divided into shallow landslides and debris flows based on the geological features, distribution, and formation mechanisms. A weighted frequency ratio model was proposed to calculate the landslide susceptibility. The weights of influencing factors were calculated by the integrated model of logistic regression and fuzzy analytical hierarchy process, whereas the rating among the classes within each factor was obtained by a frequency ratio algorithm. The landslide susceptibility index of each cell was subsequently calculated in GIS environment to create landslide susceptibility maps of different types of landslide. The analysis and assessment process were separately performed for each type of landslide, and the final landslide susceptibility map for the entire region was produced by combining them. The results showed that 73.3% of landslide pixels were classified into “very high” or “high” susceptibility zones, while “very low” or “low” susceptibility zones covered only 3.6% of landslide pixels. The accuracy of the model represented by receiver operating characteristic curve was satisfactory, with a success rate of 70.4%. When the landslide typology was not considered, the accuracy of resulted maps decreased by 1.5~5.4%.

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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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