The ports around Bohai in China were taken as the object of study this research. In light panel data from 2014 to 2020, super-efficiency SBM model was applied measure and calculate energy conservation emission reduction efficiency ports. addition, indicator system influencing factors for constructed on basis STIRPAT model, which provided a brand-new research perspective environmental regulation...

The building sector is the second-largest energy consumer in China. With proposal to reach a carbon peak by 2030 and achieve neutrality 2060, China attaches more importance conservation emission reduction of residential sector. To study connection between socioeconomic factors consumption (REC), this paper collects data 13 prefecture-level cities Jiangsu Province, China, from 2001 2019 explore ...

This paper studies the EKC hypothesis and STIRPAT model. Based on panel data of carbon emission intensity other influencing factors 30 provinces in China from 2000 to 2018, spatial effect per capita food nitrogen footprint (FNF) different socio-economic were studied by using exploratory analysis fixed Durbin model for first time. The results show that: (1) there is a agglomeration positive depe...

The paper utilized a panel dataset to investigate the effects of impact factors, namely, economic growth, energy intensity, consumption, urbanisation, passenger vehicles and transport infrastructure investments on carbon emissions (CO2-eq). sector main buoyant provinces South Africa for consecutive period five years was investigated using STIRPAT models. Carbon coefficient method, (CECM) is mad...

Residential CO2 emissions (RCE) are an important component of anthropogenic emissions. In order to formulate reasonable reduction policies and measures, it is necessary understand the dynamics RCE production factors that influence it. This paper explores spatiotemporal evolution characteristics from perspectives eastern, central, western China, as well urban–rural areas, analyzes driving based ...

The setting of a CO2 emission peak target (CEPT) will have profound impact on Chinese industry. An objective assessment this is great significance, both for understanding/applying the forcing mechanism CEPT, and promoting optimization China’s industrial structure low-carbon transformation industry at lower cost. Based analysis internal logic operation we employed STIRPAT model. This enabled us ...

ABSTRACT The significant contribution to CO 2 emissions includes historically cumulative in the United States, Russia, Japan, South Korea, and Germany, as well current increase emerging economies, such China, India, Iran, Indonesia, Saudi Arabia, which contribute 68% of global emissions. Therefore, it is important measure changes driving mechanisms these countries. This study used LMDI STIRPAT ...

Purpose: Urban sprawl can cause an increase in economic development, and as a result, it is followed by increased consumption of energy, waste generation, urbanization, reduced green land. In this sense, the current study aims to investigate impacts urban on environmental pollution, terms CO2 emissions, while considering other control variables. Further, explores relationship between population...

Exploring the urban carbon neutrality pathway is crucial to overall achievement of net-zero emissions target in China. Therefore, taking Beijing as a case study, this paper firstly analyzes CO2 emission drivers by combining Stochastic Impacts Regression on Population, Affluence, and Technology (STIRPAT) partial least squares (PLS) methods. Subsequently, based optimized extreme learning machine ...

This study examines the impact of natural resource extraction, population, affluence, and trade openness on carbon dioxide (CO2) emissions energy consumption in 17 sub-Saharan African (SSA) countries from 1971 to 2019, using stochastic impacts technology (STIRPAT) model. The Westerlund Kao cointegration tests were employed determine long-run relationships among variables. Pooled mean group auto...