Impact of Urban Form on CO2 Emissions under Different Socioeconomic Factors: Evidence from 132 Small and Medium-Sized Cities in China

Abstract

The accurate estimation of the impact of urban form on CO2 emissions is essential for the proposal of effective low-carbon spatial planning strategies. However, few studies have focused on the relationship between urban form and CO2 emissions in small and medium-sized cities, and it is especially unclear whether the relationship varies across cities with different socioeconomic characteristics. This study took 132 small and medium-sized cities in the Yangtze River Delta in China to explore how urban form affects CO2 emissions, considering the socioeconomic factors of industrial structure, population density, and economic development level. First, nighttime light data (DMSP-OLS and NPP-VIIRS) and provincial energy data were used to calculate CO2 emissions. Second, four landscape metrics were used to quantify the compactness and complexity of the urban form based on Chinese urban land-use data. Finally, panel data models were established to analyze whether and how different socioeconomic factors impacted the relationship between urban form and CO2 emissions. The results showed that the three socioeconomic factors mentioned above all had obvious influences on the relationship between urban form and per capita CO2 emissions in small and medium-sized cities. The effect of compactness on per-capita CO2 emissions increased with a rise in the proportion of the tertiary industry, population density, and per-capita GDP. However, compactness shows no effects on per-capita CO2 emissions in industrial cities and low-development-level cities. The effect of complexity on per-capita CO2 emissions only increased with the rise in population density. The results may support decision-makers in small and medium-sized cities to propose accurate, comprehensive, and differentiated plans for CO2 emission control and reduction.

The influence of multidimensional urban form of counties on carbon emissions of residents and its planning implications: Evidence from counties in the Yangtze River Delta, China

“…The increase in the degree of a single center in counties will lead to a prominent phenomenon of uneven resource allocation between the main center (the county town) and the surrounding towns. Generally, the highly quali ed educational and medical facilities are mainly concentrated in the main center, and residents in towns need longer travel distances and times to obtain high-quality resources, increasing travel-related carbon emissions (Guo et al 2022). Meanwhile, an increase in the degree of a single center will increase the highway density.…”

A Review of the Effects of Urban and Green Space Forms on the Carbon Budget Using a Landscape Sustainability Framework

“…Urban indicators with significant impacts on carbon emissions include the city size [35][36][37][38][39], urbanization level [40][41][42], economic level [43][44][45][46], population size [47][48][49], and building volume [50,51]. We included these indicators as control variables.…”

XGBoost-Based Analysis of the Relationship Between Urban 2-D/3-D Morphology and Seasonal Gradient Land Surface Temperature

“…Through the combination of remote sensing and GIS, dynamic information, such as urban spatial distribution, impervious water ratio, and building forms, can be obtained and processed, creating a scientific foundation for urban planning and design [23], [24]. Therefore, utilizing remote sensing information to optimize urban morphology in different dimensions is vital for preventing the urban heat island effect and ensuring sustainable development [25], [26].…”