Spatiotemporal characteristics of urban air quality in China and geographic detection of their determinants

Zhu, Xiaoping; Gong, Zhijun

doi:10.1007/s11442-018-1491-z

Cited by 43 publications

(15 citation statements)

References 35 publications

(32 reference statements)

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“…High rainfall occurred during summer in the study area because the monsoon climate [80] (which implies that precipitation amount as well as the occurrence of heavy rainfall events peaks in summer) reduced the air pollutants significantly and led to excellent air quality. This agrees with a national scale research study that reveals that the air quality is good in summer [81], and another research study that suggested that the precipitation is negatively correlated with air pollution [82]. The WBGT was found to be relatively low in some big cities (i.e., provincial capital city Nanchang, Jiujiang city in the north and Pingxiang city in the west), possibly because of the urban dry island effect [83].…”

Section: Heat Hazard and Exposuresupporting

confidence: 89%

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches

Zheng

Zhang

Shi

et al. 2020

IJERPH

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Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches—Crichton’s risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton’s risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman’s rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.

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Section: Heat Hazard and Exposuresupporting

confidence: 89%

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches

Zheng

Zhang

Shi

et al. 2020

IJERPH

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“…The primary atmospheric pollutants in more than 70% of the national key detection cities were PM 10 and PM 2.5 [4]. PM pollution affects urban and regional air quality [5][6][7] and visibility [8][9][10], and even plays an important role in global climate change [11][12][13]. PM at high concentrations can significantly increase the incidence of human respiratory and cardiovascular diseases and mortality [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Temporal and Spatial Distribution Characteristics of Atmospheric Particulate Matter (PM10 and PM2.5) in Changchun and Analysis of Its Influencing Factors

Xie

Fang

2019

Atmosphere

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With Changchun’s economic development, atmospheric particulate pollution has become a significant challenge in Changchun. The spatiotemporal patterns of particulate matter emissions are an inherent characteristic for particulate matter emissions. By using hourly PM (particulate matter) mass concentration measured at 10 atmospheric automatic monitoring stations and meteorological parameters, the spatiotemporal distribution characteristics of particulate matter (PM10 and PM2.5) and its relationship with meteorological parameters of Changchun have been analyzed. Pollution pathways and source distribution were investigated using HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model and cluster analysis. Results indicated that the quarterly average PM2.5 and PM10 mass concentrations in Changchun were higher in the first quarter and the fourth quarter. PM concentrations observed in all seasons generally exhibited two peaks, at 07:00–10:00 and 21:00–23:00, with the exception of PM10 in spring. PM pollution was concentrated mainly in the central, northern, and western areas of Changchun in most seasons, mainly due to anthropogenic activities and soil dust transported outside the region. PM concentrations were negatively correlated with relative humidity and temperature. PM2.5 concentrations were negatively correlated with wind speed, while PM10 concentrations were positively correlated with wind speed. The results of backward trajectory clustered showed that the northwest airflow had the greatest impact on PM of Changchun, except summer.

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“…The core of the theory is to detect the consistency of the spatial distribution patterns between the dependent variable and the independent variable by calculating the spatial heterogeneity and then to measure the explanatory degree of the independent variable to the dependent variable. Geographical detectors are extensively applied in space analysis, such as the exploration of the driving factors of green buildings development [31], evaluating indicator of surface water quality [32], influencing factors of industrial sector carbon dioxide emissions [33], [34], etc. A GeoDetector can be employed in three aspects: measuring the spatial differentiation of given data; finding the largest spatial differentiation of variables; and finding the explanatory variables of dependent variables [35]- [39].…”

Section: Methodsmentioning

confidence: 99%

Risk Assessment of COVID-19 Based on Multisource Data From a Geographical Viewpoint

Zhang

Yang

et al. 2020

IEEE Access

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In June 4, 2020, Corona Virus Disease 2019(COVID-19) cases in Wuhan were cleared, and the epidemic situation was basically controlled. Such public safety infectious disease includes influences great pressure on the national economy. At present, some countries and regions in the world are still in epidemic situation, and there is an urgent need to judge the infection situation and travel risk in the region. In a relatively fine scale down to perceive the surrounding situation, and then rational zoning decisions to promote the resumption of production and work. In this study, indicators for the evaluation of COVID-19 epidemic were constructed using multi-sourced data. A computational evaluation of 736 fine-grained grids was performed using the GeoDetector model and the decision tree model. The study found that the risk level in older neighborhoods was much higher than in newer neighborhoods; the population density was the most important determinant of infection; the number of urban people slumped to 37% of that in usual times according to Tencent data after the "city closure"; The model this paper used portrays the major factor in defining low-risk areas and high-risk areas, and offers suggestions and assessment from a geographical perspective to fight COVID-19, thus presenting great practical value. INDEX TERMS COVID-19, geographical detectors, decision tree, risk map, spatial grid.

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Spatiotemporal characteristics of urban air quality in China and geographic detection of their determinants

Cited by 43 publications

References 35 publications

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches

Temporal and Spatial Distribution Characteristics of Atmospheric Particulate Matter (PM10 and PM2.5) in Changchun and Analysis of Its Influencing Factors

Risk Assessment of COVID-19 Based on Multisource Data From a Geographical Viewpoint

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