Examining the Potential Scaling Law in Urban PM2.5 Pollution Risks along with the Nationwide Air Environmental Effort in China

Urban Scaling Functions: Emission, Pollution and Health

Urban scaling is widely used to characterize the population dependence of city indicators including greenhouse gas emission. Here we analyze the population dependence of CO2 and PM2.5 emissions and concentrations across all European cities. Our analysis reveals considerable variations in emissions among cities of comparable population size which are not captured by conventional urban scaling. We thus characterize these fluctuations by multi-parameter scaling functions and multifractal spectral analysis. We find that the distribution of emissions and population is multifractal while that of air pollution is not, leading to non-trivial relations between emission and pollution in some large cities. We also analyze the impact of forests in curbing emission and the impact of air pollution on health. Our work provides a detailed picture of the fluctuations in the scaling of urban metabolism in Europe and suggests a general strategy that goes beyond conventional urban scaling laws.

Evaluation of carbon emission efficiency based on urban scaling law: take 308 cities in China as an example

The development of urban low carbonization is an important foundation for achieving the goal of "dual carbon." The differences in spatial differences based on scientific methods revealing the characteristics of urban carbon emissions and its efficiency are of great significance for shaping the green low-carbon land space pattern. This article uses urban standard models and scale adjustments to the urban index (SAMIs) identification in 2006-2017 308 Chinese urban carbon discharge standards and efficiency time and space evolution pattern and their characteristics. The results of the study show that there is a stable secondary relationship between carbon emissions and urban population scale, which means that the growth rate of urban carbon emissions is significantly lagging behind the growth of urban systems. The analysis of urban carbon emission efficiency based on SAMI values shows significant spatial heterogeneity: the carbon emission efficiency of cities in North China, East China, and Northeast China is lower than that of other regions. In terms of temporal changes, there was a phenomenon of SAMI high-value cities moving north and low-value cities moving south between 2006 and 2017, and △SAMIs showed a pattern of hot in the west and cold in the east. This study broadens the applicability of urban scaling law models in urban environmental research, providing a new perspective for evaluating urban carbon emission efficiency and China's energy conservation and emission reduction work.