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Land use has been demonstrated to have an important influence on PM2.5 concentrations; however, how the scale effects and regional disparities in land use influence PM2.5 concentrations remains unclear. This study investigated the scale differences in spatial variations in PM2.5 concentrations, in spatial associations between PM2.5 concentrations and land use, and explored the effects of the spatial heterogeneity and action scale of land use on PM2.5 concentrations. The main findings indicated greater intra-unit variation at small scales and greater inter-unit variation at large scales. PM2.5 concentrations had a positive association with the surrounding cultivated land and artificial surface, and had a negative association with surrounding forest and grass; the positive spatial association between PM2.5 concentrations and the surrounding artificial surface was stronger at small scales. Cultivated land and forest negatively influenced PM2.5 concentrations generally. Artificial surfaces showed a strong positive influence on PM2.5 concentrations in most urban areas. The action scale of cultivated land in influencing PM2.5 concentrations was the largest (4698.05 m). The findings provide a new interpretation of the relationship between PM2.5 concentrations and land use, and may contribute to effective policy making from the perspective of land use planning to PM2.5 pollution control and abatement. [ABSTRACT FROM AUTHOR]

• We appraise built-up land efficiency and discern inefficient land at multi scales. • We analyze the coupling between BUI and LUE based on multi-source spatial data. • Overloaded built-up land distributes in South YRD, while inefficient in West. • For where built-up land is overloaded, appropriate new urban area is necessary. • Redevelopment is more suitable for where built-up land is inefficient. Irrational built-up land expansion debilitates urban sustainability and leads to environmental decay, food security, and climate change. Using the Yangtze River Delta (YRD) urban agglomeration as an example, this research identifies the mismatch between the intensity and use efficiency of built-up land at multiple scales. Specifically, the study gauges built-up land intensity (BUI) using horizontal layout and vertical height data. Land use efficiency (LUE) is calculated by fusing multi-source spatial data, including nighttime light (NTL), land surface temperature (LST), population density (PD), gross domestic product (GDP), and points of interest (POI). The coupling index (CI) between BUI and LUE determines the misallocation of built-up land resources. The results indicate that BUI and LUE match well in YRD, whereas well-coupled built-up land with high BUI and LUE is concentrated in the eastern YRD. Based on the coupling findings, built-up land can be divided into three categories: overloaded, well-coupled, or inefficient. When built-up land is overloaded, it is essential to notice the excessive concentration of urban functions. On the other hand, reducing land resource waste should be a priority where built-up land is inefficient. This research helps confine irrational urban expansion, deploy rational urban expansion plans, and foster sustainable cities and communities. [ABSTRACT FROM AUTHOR]

Land use change has an important influence on the spatial and temporal distribution of PM2.5 concentration. Therefore, based on the particulate matter (PM2.5) data from remote sensing instruments and land use change data in long time series, the Getis-Ord Gi* statistic and SP-SDM are employed to analyze the spatial distribution pattern of PM2.5 and its response to land use change in China. It is found that the average PM2.5 increased from 25.49 μg/m3 to 31.23 μg/m3 during 2000-2016, showing an annual average growth rate of 0.97%. It is still greater than 35 μg/m3 in nearly half of all cities. The spatial distribution pattern of PM2.5 presents the characteristics of concentrated regional convergence. PM2.5 is positively correlated with urban land and farmland, negatively correlated with forest land, grassland, and unused land. Furthermore, the average PM2.5 concentrations show the highest values for urban land and decrease in the order of farmland > unused land > water body > forest > grassland. The impact of land use change on PM2.5 is a non-linear process, and there are obvious differences and spillover effects for different land types. Thus, reasonably controlling the scale of urban land and farmland, optimizing the spatial distribution pattern and development intensity, and expanding forest land and grassland are conducive to curbing PM2.5 pollution. The research conclusions provide a theoretical basis for the management of PM2.5 pollution from the perspective of optimizing land use. [ABSTRACT FROM AUTHOR]

As the spatial carrier of the emission sources and influencing factors of PM 2.5 , land use and its changes can inevitably affect local and regional PM 2.5 concentrations. The relationship between the growth of PM 2.5 and the changes of land use in China during 1998-2015 was explored in this paper using the Theil-Sen median trend analysis, Mann-Kendall and spatial econometric model. The results showed that the area where PM 2.5 concentration was less than 10 μg/m3 accounted for a small portion (18.33%) of the land area in China, and the area where PM 2.5 concentration was more than 35 μg/m3 accounted for 31.30% of the land area. High PM 2.5 concentration was found in the East China Plain and Taklimakan desert; artificial surfaces, cultivated land and deserts were coated with high PM 2.5 concentration more frequently, while the forest, grassland and unused land were usually covered with low PM 2.5 concentration. PM 2.5 concentration in desert land and artificial surfaces respectively increased at a pace of 1.07 μg/m3 and 0.80 μg/m3 per year during 1998–2015, higher than those in other land use types. They mainly came from the sand dust aerosol in northwest China, while those in the other areas mainly came from emissions in the human activities. Therefore, reasonable coordinating the proportion of construction land, cultivated land, forest land and grassland in eastern China, and strengthening desert governance in northwest China, are suggested to reduce PM 2.5 concentration in China. Image 100 • PM 2.5 concentrations increased significantly in the central and western regions. • Land use type have significant impacts on PM 2.5 in different way. • PM 2.5 was affected by artificial surfaces and cultivated land in central-eastern China. • Sandy land in the desert areas had dominated effects on PM 2.5 in the northwest. [ABSTRACT FROM AUTHOR]