Dynamic Evolution and Regional Disparity in Carbon Emission Intensity in China

Abstract

China’s carbon reductions are of great significance to the realization of global temperature control targets. Carbon emission intensity (CEI) represents the degree of coordination between emissions and economic development to some extent. Nevertheless, there is a paucity of research on its spatial–temporal evolution and regional differences. To fill the gap, this study exploits the Theil index to shed light on the characteristics of its spatial–temporal distribution and regional disparities in China during the period of 2000–2019, and constructs a multi-regional spatial index decomposition model to analyze the differences in its drivers. The results indicate that the decreasing CEI during the period of 2000–2019 shows a distinctive imbalance in spatial–temporal distribution. The gap between north and south is greater than that between east and west. The expansion of the Theil index based on CEI reveals a widening tendency of the mismatch between emissions and economic development among provinces. CEI disparity is mainly due to growing intraregional differences. For most provinces, the energy intensity effect is the essential driver of spatial differences regarding CEI, with the energy structure and the industrial structure effects gradually changing from promoting to inhibiting effects. The carbon emission factor effect has no significant fluctuation, but regional differences are distinct.

Subjective and Objective Evaluation of Shading on Thermal, Visual, and Acoustic Properties of Indoor Environments

“…Its wind-proof capacitive microphone was pointed outdoors through a window. The measured SPL is expressed as L Aeq , defined as the single SPL with a constant value duration of the measurement, i.e., over an hour, and the completion of a one-hour measurement is indicated by placing it in brackets, e.g., L Aeq (1) . Similar to the measurement of the light environment, the measurement of the room's sound pressure level lasted for 1 h continuously, with a 15 min interval between the rooms with different levels.…”

“…The increasingly prominent carbon emission-related problems have attracted progressively more attention to energy saving [1]. The shading of buildings has become a more significant consideration in China's hot summer and cold winter areas, together with occupants' increasing awareness of energy saving.…”

“…ANOVA repeated measures of noise equivalents in one hour, L Aeq(1) , during the different daytime periods in three buildings.…”

Spatial Differences and Influencing Factors of Carbon Emission Intensity in China’s Urban Agglomerations toward the Carbon Neutrality Target

“…Regarding the spatial difference of CEI, the existing literature mainly uses the coefficient of variation [21,22], the Theil index [23,24], spatial autocorrelation [25,26], and the Gini coefficient [27] to reveal the differences of regional CEI. Yang [28] used the Theil index to study CEI's spatial and temporal distribution and regional differences from 2000 to 2019 in China and found that the decrease in CEI from 2000 to 2019 showed an obvious imbalance in spatial and temporal distribution, in which the gap between the North and the South was larger than that between the East and the West. Xu [22] used the coefficient of variation and spatial autocorrelation to study CEI's spatial and temporal characteristics in the Yangtze River Delta from 1997 to 2017 and found that the CEI of cities in the Yangtze River Delta had a strong positive spatial correlation concerning CEI, and it decreased from north to south.…”

Spatio-temporal differences and influencing factors of carbon emission equity in the Loess Plateau based on major function-oriented zones

“…If the causes of unfairness in carbon emissions are ignored, it may lead to greater difficulty in regulating and controlling total emissions. The existing research methods on carbon emission equity are becoming more diverse, with the Gini coefficient (Pan et al, 2014;Yang and Yang, 2020), Theil index (Cui et al, 2022;Yang et al, 2022) and Kakwani index (Clarke-Sather et al, 2011;Ma et al, 2019) being widely used in the study of carbon emission equity. The research scale focuses on global, national and regional carbon emission equity.…”