The Coupling Relationship Between Urbanization and Carbon Emissions From Land Use in Ningxia

Abstract

To understand the complex relationship between urbanization and carbon emissions, this study measures the urbanization level and land-use carbon emissions of 19 counties and districts in Ningxia from 2009 to 2019 using the integrated index method and carbon emission model, respectively, and explores the coupling relationship based on the coupling coordination degree model, to provide theoretical support for low-carbon urbanization and carbon emission reduction planning in Ningxia. The research results showed that the comprehensive evaluation index of the Ningxia urbanization system shows a linear increasing trend with an average annual growth of 1.6%, but the overall level is low, and the overall spatial pattern being high in the North and low in the South is shown. The dominant type of urbanization is population and economic urbanization. The average annual growth rate of net carbon emissions from land use in Ningxia is 4.75 106t/a. Spatially, it is characterized by higher levels in cities in the North along the Yellow River Ecological and Economic Zone and lower levels in the central arid zone and southern mountainous areas. The coupling degree and coupling coordination degree of Ningxia urbanization and land use carbon emissions show a fluctuating upward trend but belong to a low level of mutual constraints, i.e., the low level of development of Ningxia urbanization, backward industries, and low energy utilization lead to the growth of carbon emissions in Ningxia and restrict the development of urbanization. The government should take into account the regional differences when formulating carbon emission reduction policies to maintain appropriate population size, optimize the economic structure, and improve the land use efficiency.

Prediction of CO pollutant in Mashhad metropolis, Iran: Using multiple linear regression

“…In relation to NDVI, it should be noted that in the Mashhad metropolis, dense areas are associated with an abundance of urban green space, and this has caused a positive correlation between this variable and CO. The results of the relationship between CO and the two variables of population density and NDBI are aligned with the studies that argued the existence of a close relationship between urbanisation, urban land use and carbon emissions (Huang & Li, 2022; Li et al, 2020). In addition, despite the considerable distribution of NDVI in Mashhad, this variable has not been able to play an effective role in the CO reduction process due to the predominance of a high population density and the built environment.…”

The coupling coordination between health service supply and regional economy in China: spatio-temporal evolution and convergence

“…Where ( i = 1, 2) is the number of indicators in the i th subsystem, and i = 1 and 2 denote the health care service provision subsystem and the economic development level subsystem, respectively ( 49 ).…”

Research on the Geographical Pattern, Evolution Model, and Driving Mechanism of Carbon Emission Density from Urban Industrial Land in the Yangtze River Economic Belt of China

“…Therefore, an in-depth analysis of the relationship between land-use carbon emissions and economic growth is of great significance to the scientific development of energy conservation and emission reduction programs, and it is also the key to promoting regional carbon neutrality as well as the sustainable development of the society [6]. Since the 1970s, an increasing number of scholars have been involved in research on land-use carbon emissions, summarized into the following areas and features: research related to land-use carbon sources and sinks from the perspective of the carbon cycle in terrestrial ecosystems, mainly dealing with the accounting of land-use carbon stocks and fluxes and their influencing factors [7,8]; correlation analysis of the relationship between carbon emissions and economic growth or factors of production based on land carbon emissions using econometric methods such as the gray correlation model [9], the coupled coordination degree model [10], and the decoupling model [11]; and research related to low-carbon development policies for land use under the "dual carbon" goal, that is, to portray the evolution models of land-use carbon emissions through methods such as spatial autocorrelation and cold-hot spot analysis and to further propose their policy implications. For example, Sidorczuk-Pietraszko [12] studied the spatial differences in household carbon intensities between different regions in Poland by means of exponential decomposition analysis (IDA); Rong [13] also found that there is an obvious spatial correlation between land-use carbon emissions in Chinese provinces, and thus suggested that China should strengthen the inter-provincial cooperation in order to achieve an overall emission reduction across the country.…”