Driving Factors and Growth Potential of Provincial Carbon Productivity in China

Climate change has become a global concern, and the development of a green economy has attracted wide attention. Understanding the driving factors and growth potential of provincial-level carbon productivity is crucial for China’s green economic development in the new normal phase. In this study, the logarithmic mean Divisia index (LMDI) is adopted to systematically investigate the driving factors of provincial carbon productivity and explore the growth potential of provinces’ carbon productivity based on the clustering analysis. The results show that: (1) China’s provincial carbon productivity presents an increasing trend in 2001–2017, but the differences in carbon productivity among provinces are widening. (2) Economic activity and industrial structure are key to push up regional carbon productivity in China, while energy intensity is the main factor pulling it down. (3) The potential for carbon productivity improvement varies greatly among provinces in the four groups. Specifically, in groups 1 and 2, the developed provinces have little potential for improving carbon productivity, while the developing provinces in group 4 are just the opposite. These findings can enlighten policymakers that the development of a green economy should focus on optimizing and upgrading industrial structure and reducing energy intensity, and provincial heterogeneity must be considered when formulating green economic development policies.

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Analysis of Energy Consumption Influence Factors in Japan Based on LMDI Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.71-78.2416 ◽

2011 ◽

Vol 71-78 ◽

pp. 2416-2419

Author(s):

Hong Qin Liu ◽

Xu Yan ◽

Hai Yan Duan ◽

Xian En Wang

Keyword(s):

Economic Development ◽

Energy Consumption ◽

Energy Intensity ◽

Industrial Structure ◽

Japanese Economy ◽

Consumption Structure ◽

Structure Adjustment ◽

Industrial Structure Adjustment ◽

Rapid Industrialization ◽

Positive Effect

After World War Ⅱ Japanese economy has undergone three periods: the rapid industrialization period, the industrial structure adjustment period and the economy depression period. Affected by the speed of economic development, industrial structure and other factors, Japanese energy consumption has shown different features during specific period of time. This article use the LMDI model, analyze the effect of different factors on Japanese energy consumption which include economic development, energy intensity, energy consumption structure and population size, research on the weight of specific factors during each developing period. The results show that all the factors show positive effect in the rapid industrialization period; in the industrial structure adjustment period, economic development factor shows positive effect while energy consumed factor shows negative; and in the depression period, the trend of all the factors contribution rate are slowly, economic development and energy consumption structure also show negative effect besides the energy intensity factor.

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Analysis of China’s Industrial Green Development Efficiency and Driving Factors: Research Based on MGWR

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18083960 ◽

2021 ◽

Vol 18 (8) ◽

pp. 3960

Author(s):

Ke Liu ◽

Yurong Qiao ◽

Qian Zhou

Keyword(s):

Economic Development ◽

Technological Innovation ◽

Yangtze River ◽

Industrial Development ◽

Government Regulation ◽

Industrial Structure ◽

Driving Factors ◽

The Yangtze River ◽

Green Development ◽

The Government

With increasingly severe constraints on resources and the environment, it is the mainstream trend of economic development to reduce industrial pollution emissions and promote green industrial development. In this paper, a super-efficiency slacks-based measure (SBM) model is adopted to measure the industrial green development efficiency (IGDE) of 289 cities in China from 2008 to 2018. Moreover, we analyze their spatiotemporal differentiation pattern. On this basis, the multiscale geographical weighted regression (MGWR) model is used to analyze the scale differences and spatial differences of the driving factors. The results show that the IGDE is still at a low level in China. From 2008 to 2018, the overall polarization of IGDE was relatively serious. The number of high- and low-efficiency cities increased, while that of medium-efficiency cities greatly decreased. Secondly, the IGDE presented an obvious spatial positive correlation. MGWR regression results show that the technological innovation, government regulation, and consumption level belonged to the global scale, and there was almost no spatial heterogeneity. Other driving factors were urbanization, industrial structure, economic development, and population density according to their spatial scale. Lastly, the influence of economic development and technological innovation had a certain circular structure in space; the influence of population size mainly occurred in the cities of the southeast coast and northeast provinces; the influence of urbanization was more obvious in the most northern provinces of the Yangtze River, while that of industrial structure was mainly concentrated in the most southern cities of the Yangtze River Economic Belt (YREB). Spatially, the influence of consumption was manifested as a distribution trend of decreasing from north to south, and the government regulation was manifested as increasing from west to east and then to northeast.

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Urban Green Development towards Sustainability in Northwest China: Efficiency Assessment, Spatial-Temporal Differentiation Characters, and Influencing Factors

Complexity ◽

10.1155/2021/6630904 ◽

2021 ◽

Vol 2021 ◽

pp. 1-19

Author(s):

LiJuan Si ◽

JiaLu Wang ◽

ShuRan Yang ◽

Ye Yang ◽

Jing Zhang

Keyword(s):

Economic Development ◽

Path Dependence ◽

Industrial Structure ◽

Northwest China ◽

Driving Factors ◽

Coordinated Development ◽

Urban Green ◽

High Position ◽

Green Development ◽

The Impact

For achieving the sustainable development goals, green development has been raised to a high position for cities in China. The economic development in Northwest China is slow, the ecological environment is fragile, and the mineral resources are rich. Only through green development can we realize the comprehensive income of regional production development, rich life, and good ecology. This paper measures the green development efficiency of 30 prefecture-level cities in Northwest China by using DEA-SBM model of unexpected output, explores the differences and causes of green development efficiency from the perspective of time and space through convergence coefficient, coordination matrix, GIS, and other methods, and empirically tests the impact of industrial structure, technological progress, and other driving factors on green development efficiency by using panel Tobit model. The results show that, on the whole, the efficiency of green development in Northwest China is low, path dependence is serious and unbalanced, the coordinated development effect of different regions is weak, and the spillover effect of core urban agglomerations has not been effectively exerted; from the perspective of driving factors, economic development, population density, traffic situation, and education investment can significantly improve the efficiency of urban green development, and the second is that the proportion of industries significantly hinders the improvement of green development efficiency, while the impact of scientific and technological innovation is not significant. Based on the empirical results, this paper believes that the harmonious development of natural environment and economic society can be realized only by improving the coordinated development effect among cities, implementing the optimization and upgrading of industrial structure, introducing excellent talents, and promoting the technological upgrading.

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Investigation on the Relationship between Satellite Air Quality Measurements and Industrial Production by Generalized Additive Modeling

Remote Sensing ◽

10.3390/rs13163137 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3137

Author(s):

Chao Tong ◽

Chengxin Zhang ◽

Cheng Liu

Keyword(s):

Economic Development ◽

Air Quality ◽

Industrial Production ◽

Industrial Structure ◽

Local Economic Development ◽

Additive Model ◽

Atmospheric Pollutants ◽

Green Economy ◽

Air Quality Measurements ◽

The Relationship

The development of the green economy is universally recognized as a solution to natural resource shortages and environmental pollution. When exploring and developing a green economy, it is important to study the relationships between the environment and economic development. As opposed to descriptive and qualitative research without modeling or based on environmental Kuznets curves, quantitative relationships between environmental protection and economic development must be identified for exploration and practice. In this paper, we used the generalized additive model (GAM) regression method to identify relationships between atmospheric pollutants (e.g., NO2, SO2 and CO) from remote sensing and in situ measurements and their driving effectors, including meteorology and economic indicators. Three representative cities in the Anhui province, such as Hefei (technology-based industry), Tongling (resource-based industry) and Huangshan (tourism-based industry), were studied from 2016 to 2020. After eliminating the influence of meteorological factors, the relationship between air quality indexes and industrial production in the target cities was clearly observed. Taking Hefei, for example, when the normalized output of chemical products increases by one unit, the effect on atmospheric NO2 content increases by about 20%. When the normalized output of chemical product increases by one unit, the effect on atmospheric SO2 content increases by about 10%. When chemical and steel product outputs increase by one unit, the effect on atmospheric CO content increases by 25% and 20%, respectively. These results can help different cities predict local economic development trends varying by the changes in air quality and adjust local industrial structure.

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Refined Laspeyres Decomposition-Based Analysis of Relationship between Economy and Electric Carbon Productivity from the Provincial Perspective—Development Mode and Policy

Energies ◽

10.3390/en11123426 ◽

2018 ◽

Vol 11 (12) ◽

pp. 3426 ◽

Cited By ~ 2

Author(s):

Wei Sun ◽

Hua Cai ◽

Yuwei Wang

Keyword(s):

Economic Development ◽

Electric Power ◽

Electric Power Industry ◽

Power Industry ◽

Productivity Change ◽

Low Carbon ◽

Development Mode ◽

Productivity Improvement ◽

Carbon Efficiency ◽

Carbon Productivity

The development of low-carbon electric power industry plays a vital role in sustainable economic development due to the supporting role of electricity in the Gross Domestic Product GDP. The electric carbon productivity indicator is introduced to investigate the provincial economic development and electric industry-related indicators. The refined Laspeyres decomposition technique is adopted to decompose provincial economic change into the quantitative influence of CO2 emission, electric carbon productivity, and emission structure for the first-stage decomposition; the electric carbon productivity change is sub-decomposed into the influence of factors such as electricity-economic productivity, electricity import-export, and generation carbon efficiency. Through decomposition analysis for the research period of 2005 to 2015, scientific and reasonable suggestions are made for improvement of electric carbon productivity and provincial economic development: (1) The main obstacle to electric carbon productivity improvement is emissions from the power industry. (2) There is interaction between the green economic development mode and the low-carbon electric power industry. In others words, provincial future economy development mode formulation should consider not only economic and industrial factors but also power industry factors. (3) The issue of electric carbon productivity improvement and regional development mode is partially consistent with geographic locations, which is a comprehensive effect of economy level, power industry, energy resources, technological development level, environmental awareness, etc. (4) Due to the existence of regional protection, provincial local incentives should be promulgated to break the GDP-driven development mode to realize coordination among the economy, power industry, and the environment.

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A model of the analysis of the dynamics and structure of socio-economic development (an example of the set of the largest Polish cities in the years 1998–2015)

Urban Development Issues ◽

10.2478/udi-2019-0014 ◽

2019 ◽

Vol 63 (1) ◽

pp. 25-37

Author(s):

Lidia Mierzejewska ◽

Jerzy Parysek

Keyword(s):

Principal Component Analysis ◽

Economic Development ◽

Development Process ◽

Principal Component ◽

The State ◽

Geographical Research ◽

Development Policies ◽

Socio Economic Development ◽

Development Processes ◽

State Of Affairs

Abstract The complexity of the reality studied by geographical research requires applying such methods which allow describing the state of affairs and ongoing changes in the best possible way. This study aims to present a model of research on selected aspects of the dynamics and structure of socio-economic development. The idea was to determine whether we deal with the process of reducing or widening the differences in terms of individual features. The article primarily pursues a methodological goal, and to a lesser extent an empirical one. The methodological objective of the paper was to propose and verify a multi-aspect approach to the study of development processes. The analyses carried out reveal that in terms of the features taken into account in the set of 24 of the largest Polish cities the dominating processes are those increasing differences between cities, which are unfavourable in the context of the adopted development policies aiming at reducing the existing disparities. In relation to the methodological objective, the results of the conducted research confirm the rationale of the application of the measures of dynamics and the feature variance to determine the character (dynamics and structure) of the socio-economic development process of cities. Comparatively less effective, especially for interpretation, is the application of principal component analysis and a multivariate classification, which is mainly the result of differences in the variance of particular features.

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Formation of background of sustainable development and transition to the «green» economy strategy

10.33983/2075-1826-2020-3-75-83 ◽

2020 ◽

pp. 75-83

Author(s):

L.Z. Khalishkhova ◽

A.Kh. Temrokova ◽

I.R. Guchapsheva

Keyword(s):

Sustainable Development ◽

Economic Development ◽

Global Economy ◽

Social Problems ◽

Green Economy ◽

Human Needs ◽

Environmental Processes ◽

Environmental Development ◽

Current Stage

The article is devoted to the issues of measuring environmentally oriented economic development. The current stage of economic development requires the integration of environmental development, taking into account: environmental boundaries, biosphere processes, social problems, human needs and environmental processes. A green economy can become the main point of growth for the modern global economy. The article presents a complex of measures for the transition to a green economy, as well as tools for their implementation.

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