Spatiotemporal Evolution Characteristics of Carbon Emissions from Industrial Land in Anhui Province, China

Abstract

Carbon emissions (CE) in Anhui Province are closely related to carbon emissions from industrial land (CEIL). In this study, based on industrial land, industrial energy consumption, and related statistical data in Anhui Province from 2000 to 2016, the carbon emissions coefficient method and the standard deviational ellipse were used to measure and analyze the CEIL and their spatial and temporal evolution characteristics, aiming to provide a basis for the relevant government departments to formulate CE policies. The main results showed that: (1) The total amount of CEIL followed an inverted U-shaped trend of rapid increase followed by a decrease, while the overall carbon emission intensity from industrial land (CEIIL) followed a downward trend. (2) The CE had an evident spatial differentiation, with those from resource-based cities being much higher than those of industrial and tourism-based cities; (3) The overall pattern of CEIL in Anhui Province showed that the increase in the north-south direction is significantly higher than that in the east-west direction, and mainly expanded in the north-south direction. The overall industrial growth rate of Southern Anhui, represented by the Wanjiang City Belt, was higher than that of Northern Anhui, although its CEIL center showed to move towards Northern Anhui.

Joint principal component analysis and BP neural network to measure the development level of modern logistics in China

“…This article establishes an evaluation index system for the development level of modern logistics from four aspects: logistics transportation capacity, green logistics, logistics economic benefits, and logistics information technology [2][3][4][5]. The specific evaluation index system is shown in Table 1.…”

An Analysis of the Factors Influencing China’s Provincial Economy on Land Use Carbon Emissions Based on a Decoupling Model: a Case Study of Sichuan Province from 1990 to 2020

“…Cultivated land 0.0479 Cai [40], He [41] Forest land -0.0581 Fang [42] Meadow -0.0021 Fang [42] Unused land -0.0005 Yan [43], Lai [44] Water area -0.0253 Lai [44], Duan [45] area of Sichuan Province; GDP is the gross product of Sichuan Province; POP is the resident population of Sichuan Province; f u is the carbon emission intensity per unit land(CEIPUL); s u is the land use structure (LUS); k is the land use intensity per unit GDP (LUIPUG); g is the per capita gross product of Sichuan Province (PCG); pis the resident population of Sichuan Province; Because resident population is more appropriate than household population in calculating per capita GDP, and resident population can more accurately reflect the impact of population size on carbon emissions within a certain period of time, p is resident population (PS).…”

Spatial-Temporal Evolution Characteristics of Industrial Carbon Emissions in China’s Most Developed Provinces from 1998–2013: The Case of Guangdong

“…In the method of the standard deviational ellipse (SDE), the spatial distribution ellipse with the azimuth angle, short axis, center, and long axis as the basic parameters is adopted to quantitatively reflect the characteristics of the study object in the spatial layout, to describe the position and trend direction of the geographic element in the spatial distribution and the discretization degree in the main and secondary directions [56]. We have adopted the method of weighted standard deviation ellipse in ArcGIS software.…”