PM_2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM_2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM_2.5 patterns and a spatial econometric model to quantify the socio-economic driving factors of PM_2.5 concentration changes. The results are as follows: (1) The annual average value of PM_2.5 concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM_2.5 concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014–2017, the overall PM_2.5 pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 μg/m³) regulated by Chinese government. PM_2.5 pollution patterns showed high values in central and eastern Chinese cities and low values in peripheral areas, with the distinction evident along the same line that delineates China’s uneven population distribution. (3) Population agglomeration, industrial development, foreign investment, transportation, and pollution emissions contributed to the increase of PM_2.5 concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM_2.5 concentration. The results also suggest that China in general remains a “pollution shelter” for foreign-funded enterprises.

Assessing the impacts and drivers of urban expansion on terrestrial carbon storage (TCS) is important for urban ecology and sustainability; however, a unified accounting standard for carbon intensity and research on the drivers and economic value of TCS changes are lacking. Here, urban expansion and TCS in the Yangtze River Delta were simulated based on Patch-generating Land Use Simulation and Integrated Valuation of Ecosystem Services and Trade-offs models; scenario simulation; Literature, Correction, Ratio, Verification carbon intensity measurement; and land use transfer matrix methods. The results showed that (1) from 2000 to 2020, urbanization and TCS loss accelerated, with 61.127% of TCS loss occurring in soil, and land conversion was prominent in riverine and coastal cities, mainly driven by the urban land occupation of cropland around suitable slopes, transportation arteries, and rivers. (2) From 2020 to 2030, urban land expansion and TCS loss varied under different scenarios; economic losses from the loss of the carbon sink value under cropland protection and ecological protection were USD 102.368 and 287.266 million lower, respectively, than under the baseline scenario. Even if urban expansion slows, the loss of TCS under global warming cannot be ignored. Considering the indirect impacts of urbanization, the failure to establish a regional development master plan based on ecosystem services may affect China’s carbon targets.

Food security has received extensive academic attention in recent years. However, research results analyzing cultivated land pressure from the perspective of urbanization are relatively few. This study used Jiangsu Province as the study area and analyzed the spatial pattern evolution of cultivated land pressure from 2005 to 2019 by constructing a formula for a cultivated land pressure index. The study used a spatial econometric approach to analyze the spatial relationship between urbanization and cultivated land pressure. Based on the spatial Durbin model, the impact of urbanization on the pressure on cultivated land is analyzed. According to the results, Jiangsu Province showed an obvious north–south divergence in the spatial distribution of the cultivated land pressure index, with the low-value areas of the cultivated land pressure index mainly distributed in northern and central Jiangsu, and the high-value areas mainly distributed in southern Jiangsu. The urbanization level and cultivated land pressure level in Jiangsu Province showed obvious spatial clustering characteristics, and there was a certain overlap between the high- and low-value clustering areas of the two, with significant positive spatial correlation features. The total urbanization had no significant effect on the cultivated land pressure. Population urbanization and industry urbanization showed a significant negative effect on cultivated land pressure in Jiangsu Province, while land urbanization showed a positive effect. Both population and land urbanization had a significant negative spatial spillover effect on cultivated land pressure. Plausible explanations of these results were provided and policy implications were drawn.