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City planners are increasingly drawn to ways of transforming urban spatial structure as an important strategy for reducing pollutant emissions. As its main contribution, this paper uses firm-level emissions data to quantify impact mechanisms related to factor flow, firm size, and division of labour. We examine the effects of spatial polycentricity on firm-level industrial emissions, using a pooled cross-sectional model, based on emissions data from individual firms in China. We show that, all else being equal, polycentric spatial structures help to reduce the emissions of industrial firms. This finding is not affected by index measures, changes in industrial structure, or city-sample selection. A mechanism analysis shows that polycentric structures not only enhance the emission-reduction effects of factor flow and firm size, but also reduce firm-level emissions by strengthening the urban division of labour. Our findings support the emission-reduction performance of polycentric spatial structures, promoting the integration of city planning and industrial policies that jointly contribute to reducing firm-level emissions and preventing and controlling air pollution.

Environmental regulation (ER) and local protectionism (LP) are important policy tools for Chinese local governments to improve the environment and promote growth, respectively, but we know little about their interplay in dealing with pollution-intensive industries and enterprises. Using spatial correlation analysis and spatial panel simultaneous equations models, we investigated the spatial characteristics and interactions of the ER and LP in China's 285 prefectural cities. We found that the high-ER-intensity areas were spreading from the eastern to the central and western regions, and the patterns of LP transited from high in the north and low in the south to high in the west and low in the east. There was a negative correlation spatially between ER and LP. LP could inhibit the increase in ER intensity, while the continuously increasing ER intensity could restrict LP through the competitive behavior from the "race to the bottom" to the "race to the top" among local governments. The effect of ER restricting LP was significant from 2008 to 2013 and prominent in the east, which was dominated by "race to the top" competition, while LP had a greater inhibitory effect on ER in the central and western regions, which preferred to obtain tax revenues from pollution-intensive industries. The results imply that removing the roots of local protectionism, improving the environmental governance system, and formulating differentiated regional environmental regulatory measures will help local governments balance economic growth and environmental protection.

PM 2.5 pollution has gradually attracted people's attention due to its important negative impact on public health in recent years. The influence of anthropogenic emission factors on PM 2.5 concentrations is more complicated, but their relative individual impact on different emission sectors remains unclear. With the aid of the geographic detector model (GeoDetector), this study evaluated the impacts of anthropogenic emissions from different sectors on the PM 2.5 concentrations of major cities in China. The results indicated that the influence of anthropogenic emissions factors with different emission sectors on PM 2.5 concentrations exhibited significant changes at different spatial and temporal scales. Residential emissions were the dominant driver at the national annual scale, and the NO X of residential emissions explained 20% ( q = 0.2) of the PM 2.5 concentrations. In addition, residential emissions played the leading role at the regional annual scale and during most of the seasons in northern China, and ammonia emissions from residents were the dominant factor. Traffic emissions play a leading role in the four seasons for MUYR and EC in southern China, MYR and NC in northern China, and on a national scale. Compared with primary particulate matter, secondary anthropogenic precursors have a more important effect on PM 2.5 concentrations at the national or regional annual scale. The results can help to strengthen our understanding of PM 2.5 pollution, improve PM 2.5 forecasting models, and formulate more precise government control policy.

Ground-level ozone pollution has negative impacts on human health and vegetation and has increased rapidly across China. Various factors are implicated in the formation of ozone (e.g., meteorological factors, anthropogenic emissions), but their relative individual impact and the impact of interactions between these factors remains unclear. This study quantified the influence of specific meteorological conditions and anthropogenic precursor emissions and their interactions on ozone concentrations in Chinese cities using the geographic detector model (GeoDetector). Results revealed that the impacts of meteorological and anthropogenic factors and their interactions on ozone concentrations varied significantly at different spatial and temporal scales. Temperature was the dominant driver at the annual time scale, explaining 40% (q = 0.4) of the ground-level ozone concentration. Anthropogenic precursors and meteorological conditions had comparable effects on ozone concentrations in summer and winter in northern China. Interactions between all the factors can enhance effects. The interaction between meteorological factors and anthropogenic precursors had the strongest impact in summer. The results can be used to enhance our understanding of ozone pollution, to improve ozone prediction models, and to formulate pollution control measures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)