Spatio-Temporal Effects of Multi-Dimensional Urbanization on Carbon Emission Efficiency: Analysis Based on Panel Data of 283 Cities in China

Zhou, Zhanhang; Lanzhu, Cao; Zhao, Kuokuo; Li, Dongliang; Ding, Ci

doi:10.3390/ijerph182312712

Cited by 31 publications

(15 citation statements)

References 60 publications

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“…In addition, the LMDI approach provides evidence on the drivers of macrofactors such as economic activity, industrial structure [48], and energy intensity. Still, its inability to capture inputoutput mechanisms is frequently cited [49,51]. Nevertheless, these empirical findings are complementary, and together they warn policymakers of the importance of sustainable growth by improving factor structure and upgrading technology.…”

Section: Discussion Of Empirical Resultsmentioning

confidence: 99%

“…In recent years, nonparametric methods based on DEA have also been more widely used in environmental efficiency evaluation. Carbon emissions are considered input factors [15] or undesired outputs [50] in DEA models, and the optimal solution of the model is usually used to measure carbon efficiency [51]. Based on the multiperiod efficiency indices of different production technology DEA models, total factor productivity (TFP) can also be calculated by constructing productivity indices.…”

Section: Drivers Of Carbon Productivitymentioning

confidence: 99%

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Sustainable Growth Drivers: Unveiling the Role Played by Carbon Productivity

Song

Meng

et al. 2022

IJERPH

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In global climate change, improving carbon productivity holds great importance for China’s sustainable growth. Based on panel data of 30 Chinese provinces and cities from 1997–2017, the drivers, spatial effects, and convergence characteristics of carbon productivity in China are explored by combining a factor decomposition framework and a spatial panel model. The findings show that (1) China’s carbon productivity shows continuous positive growth, and the substitution effect of capital for energy dominates this changing pattern; (2) There is a β-convergence trend and club convergence in China’s carbon productivity, and the spatial technology spillover accelerates the convergence rate; (3) With its accelerated industrial transformation and technological upgrading, China’s current carbon productivity converges faster than its earlier stage, and the role of physical capital investment has gradually shifted to suppression. In contrast, the positive push of human capital investment has been strengthened; (4) From the perspective of the realization mechanism, the convergence of carbon productivity in China mainly comes from the convergence of energy restructuring and capital-energy substitution. These findings can help China narrow the inter-provincial carbon productivity gap in terms of improving factor structure, upgrading technology, etc., and provide references for sustainable growth decision making in China and around the world.

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Section: Discussion Of Empirical Resultsmentioning

confidence: 99%

Section: Drivers Of Carbon Productivitymentioning

confidence: 99%

Sustainable Growth Drivers: Unveiling the Role Played by Carbon Productivity

Song

Meng

et al. 2022

IJERPH

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“…This paper constructs a comprehensive city size index (

) from the urban population (pop) and the urban built-up area (area) indicators. Because a single indicator cannot accurately measure the city size, we constructed a comprehensive city size indicator from the perspective of urban population and built-up area based on Zhou’s work [ 40 ]. Weight refers to the importance of a factor or indicator relative to something.…”

Section: Research Methods and Data Sourcesmentioning

confidence: 99%

“…Weight refers to the importance of a factor or indicator relative to something. Many studies have shown that the weights of all factors or indicators add up to 1 [ 40 , 41 ]. Because the urban population affects the travel flow, the urban built-up area affects the travel scope, and the travel cost is affected by the urban built-up area and the population.…”

Section: Research Methods and Data Sourcesmentioning

confidence: 99%

How Does City Size Affect the Cost of Household Travel? Evidence from an Urban Household Survey in China

2022

IJERPH

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Travel costs are critical to the sustainable development of cities. This paper used Urban Household Survey (UHS) data from 2002 to 2014 and constructed a comprehensive city-size index from the perspectives of population and urban space to empirically test the impact of city size on the cost of household travel. The main results are as follows: (1) There is a significant positive correlation between city size and the cost of household travel. The internal mechanism is that city size affects the cost of household travel by increasing spatial distance and traffic congestion. (2) Increasing public transportation and per capita road area can restrain the positive impact of city size on the cost of household travel; moreover, the restraining effect of public transportation is stronger than that of per capita road area. (3) The impact of city size on the cost of household travel for sub-provincial cities is smaller than that for ordinary prefecture-level cities; in addition, there is an inverted U-shaped relationship between city size and the cost of household travel. This paper deepens the understanding of the impact of city size on travel costs, providing research support for the healthy development of cities in China.

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“…The urbanization rate of China has increased dramatically over the last four decades, from 17.9% in 1978 to 60.6% in 2019 [5], and the urban population of the country is expected to surpass 75% of the overall population by 2050 [6]. Urbanization is accompanied by industrial economic growth, increasing energy consumption, lifestyle changes, and changes in land use types due to economic and social progress, all of which have a significant influence on carbon emissions [7]. The Chinese government urged China at the 75th United Nations General Assembly in September 2020 to increase its efforts to reduce emissions on its own and strive to achieve peak carbon dioxide emissions by 2030.…”

Section: Introductionmentioning

confidence: 99%

Multidimensional Impact of Urbanization Process on Regional Net CO2 Emissions: Taking the Yangtze River Economic Belt as an Example

Shen

Hong

Jiang

et al. 2022

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Urbanization is a powerful symbol and an inevitable human economic and social development trend. This process affects carbon dioxide emissions by changing the human output and lifestyle and encroaches over the carbon sink areas by adjusting the land use types impacting the regional carbon balance. We systematically analyzed the influence of urbanization on regional net CO2 emissions (NCE) and built a quantitative model for the impact of urbanization on NCE based on population, economy, and land use. Based on this, the Yangtze River Economic Belt (YREB) in China has been selected as an example to measure the characteristics of the spatial and temporal evolution of NCE from 2005 to 2018 by empirically testing the contributions of population urbanization, economic urbanization, and land urbanization to the NCE changes in YREB. According to the study’s findings, the carbon-neutral pressure index of the YREB increased over the study period, with an increase in NCE from 1706.50 Mt to 3106.05 Mt. The contribution of urbanization in this process increased and subsequently decreased in an inverted U pattern with a drop in the cumulative net emission of 260.32 Mt. The inflection points of the cumulative impact of urbanization on NCE in the midstream and upstream regions occurred in 2011 and 2010, respectively. Due to the high degree of urbanization and economic growth in the downstream area, the urbanization impact demonstrated a constant reduction of NCE over the research period. In terms of sub-dimensions, the population and land urbanization effects were consistently positive, while the economic urbanization affected the NCE and displayed an inverted U pattern during the study period. If the variation in regional carbon sink space is ignored, the impact of urbanization on CO2 emission reduction will be overestimated. We investigated the realization path of differentiated synergistic emission reduction strategies in the great river economic belts based on the empirical study on YREB.

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Spatio-Temporal Effects of Multi-Dimensional Urbanization on Carbon Emission Efficiency: Analysis Based on Panel Data of 283 Cities in China

Cited by 31 publications

References 60 publications

Sustainable Growth Drivers: Unveiling the Role Played by Carbon Productivity

Sustainable Growth Drivers: Unveiling the Role Played by Carbon Productivity

How Does City Size Affect the Cost of Household Travel? Evidence from an Urban Household Survey in China

Multidimensional Impact of Urbanization Process on Regional Net CO2 Emissions: Taking the Yangtze River Economic Belt as an Example

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