Spatial-Temporal Evolution and Environmental Regulation Effects of Carbon Emissions in Shrinking and Growing Cities: Empirical Evidence from 272 Cities in China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Scope and Duration
2.2. Research Methods
2.2.1. Identification of Shrinking and Growing Cities
2.2.2. Urban Carbon Emission Calculations
2.2.3. Spatial Analysis of Carbon Emissions
- Moran’s index
- Hotspot analysis
- Standard deviation ellipse
2.2.4. Panel Data and Regression Model
2.3. Data Sources
3. Results
3.1. Temporal Trends in Carbon Emissions in Growing and Shrinking Cities
3.2. Spatial Distribution Characteristics of Carbon Emissions in Growing and Shrinking Cities
3.3. SDEs and Center of Gravity Migration Paths of Carbon Emissions for Growing and Shrinking Cities
3.4. Effect of Environmental Regulation on Carbon Emissions in Growing and Shrinking Cities in China
3.4.1. F-Test and Hausman Test
3.4.2. Linear Regression Results on the Impact of Environmental Regulations on Four City Types
3.4.3. Heterogeneity Regression Results of the Impact of Environmental Regulation on Four City Types
3.4.4. Robustness Test
4. Discussion
4.1. Characteristics of Spatial and Temporal Eevolution of Carbon Emissions in Growing and Shrinking Cities
4.2. Impact of Environmental Regulation on Carbon Emissions in Growing and Shrinking Cities
4.3. Limitations and Directions for Improvement
5. Conclusions and Policy Implications
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Dimensions | Indicators | Unit |
---|---|---|
Growth rate of the natural population | ‰ | |
Population | total population | 104 Person |
Population density | person/km2 | |
GDP per capita | Yuan | |
Economic | Per capita fiscal revenue | person/yuan |
GDP growth rate | % | |
Total sales of consumer items at retail | 104 yuan | |
Social and Land use | Fiscal expenditures per capita | person/yuan |
Built-up area | km2 |
Fuel | Discount Factor for Standard Coal (t Standard Coal/t) | Carbon Emission Coefficient (104 t Carbon/104 t Standard Coal) |
---|---|---|
raw coal | 0.7143 | 0.7559 |
coke | 0.9714 | 0.855 |
crude oil | 1.4286 | 0.5857 |
gasoline | 1.4714 | 0.5538 |
kerosene | 1.4714 | 0.5714 |
diesel | 1.4571 | 0.5921 |
fuel oil | 1.4286 | 0.6185 |
natural gas | 1.33 | 0.4483 |
heat | 34.12 | 0.67 |
electricity | / | 0.272 |
Indicator Properties | Indicator (Variable Name) | Interpretation of Indicators |
---|---|---|
Explanatory variable | Carbon emissions (CE) | Energy consumption data combined with nighttime light index measurements |
Explanatory variable | Environmental regulation (ER) | Industrial wastewater, SO2, and smoke (dust) per unit of output measured by the entropy weight method |
Control variable | Technological advancement (TA) | Patent applications for inventions |
Economic development level (ED) | GDP per capita | |
Industrial structure (IS) | Ratio of secondary sector output to GDP | |
Population size (PZ) | Total population at end of the year | |
Foreign investment intensity (FDI) | Foreign investment as a percentage of GDP for the year |
RGCs | SGCs | RSCs | SSCs | |||||
---|---|---|---|---|---|---|---|---|
Year | Moran I | Z | Moran I | Z | Moran I | Z | Moran I | Z |
2012 | 0.04 * | 1.41 | 0.15 *** | 9.37 | 0.11 * | 1.16 | 0.26 *** | 3.51 |
2015 | 0.10 *** | 2.86 | 0.11 *** | 7.37 | 0.14 * | 1.38 | 0.19 *** | 2.75 |
2018 | 0.09 *** | 2.67 | 0.09 *** | 6.18 | 0.15 * | 1.47 | 0.18 *** | 2.69 |
2021 | 0.08 *** | 2.52 | 0.06 *** | 4.50 | 0.10 * | 1.08 | 0.14 *** | 2.20 |
City Groups | F-Test | Hausman Test | ||
---|---|---|---|---|
F-Value | Prob | Shi-Sq. Statistic | Prob | |
RGCS | F = 5.804 | 0.000 | 44.11 | 0.000 |
RGCS | F = 8.638 | 0.000 | 141.536 | 0.000 |
RSCS | F = 1.637 | 0.021 | 21.339 | 0.003 |
SSCS | F = 3.810 | 0.000 | 56.336 | 0.000 |
Explanatory Variables | RGCS | SGCS | RSCS | SSCS |
---|---|---|---|---|
ER | 0.018 ** | 0.011 ** | 0.029 ** | 0.016 ** |
(2.103) | (1.980) | (2.528) | (1.884) | |
TA | 0.017 | 0.035 *** | 0.021 | 0.030 |
(1.007) | (3.134) | (0.730) | (1.618) | |
ED | 0.182 *** | 0.079 ** | −0.058 | −0.042 |
(3.603) | (2.430) | (−1.014) | (−0.808) | |
IS | 0.026 | 0.188 *** | 0.046 | 0.040 |
(0.332) | (4.052) | (0.528) | (0.507) | |
PZ | −0.389 *** | 0.004 | 0.270 | 0.121 |
(−3.412) | (0.049) | (0.964) | (0.849) | |
FDI | 0.011 | 0.008 | 0.018 * | 0.019 ** |
(1.209) | (1.609) | (1.905) | (2.120) | |
_cons | 11.071 *** | 8.611 *** | 7.141 *** | 8.475 *** |
(12.974) | (12.728) | (3.625) | (8.434) | |
N | 630 | 1390 | 270 | 430 |
R2 | 0.976 | 0.968 | 0.975 | 0.971 |
F | 289.946 | 245.268 | 214.631 | 218.604 |
Variables | 2012–2016 | 2017–2021 | ||||||
---|---|---|---|---|---|---|---|---|
RGCS | SGCS | RSCS | SSCS | RGCS | SGCS | RSCS | SSCS | |
ER | −0.016 | 0.010 | −0.005 | 0.011 | 0.042 *** | 0.014 *** | 0.040 *** | 0.041 *** |
(−1.015) | (1.036) | (−0.245) | (0.723) | (3.743) | (2.026) | (2.636) | (3.741) | |
Control Variables | YES | YES | YES | YES | YES | YES | YES | YES |
cons | YES | YES | YES | YES | YES | YES | YES | YES |
City | YES | YES | YES | YES | YES | YES | YES | YES |
Year | YES | YES | YES | YES | YES | YES | YES | YES |
N | 315 | 690 | 135 | 215 | 315 | 690 | 135 | 215 |
R2 | 0.982 | 0.973 | 0.979 | 0.977 | 0.992 | 0.989 | 0.991 | 0.988 |
F | 181.834 | 133.047 | 128.099 | 132.047 | 394.583 | 336.699 | 283.976 | 262.046 |
Variables | Eastern Region | Central Region | Western Region | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
RGCS | SGCS | RSCS | SSCS | RGCS | SGCS | RSCS | SSCS | RGCS | SGCS | RSCS | SSCS | |
ER | 0.023 ** | 0.023 ** | −0.009 | −0.023 | 0.026 | 0.003 | −0.027 | 0.003 | −0.077 ** | −0.000 | −0.016 | 0.031 * |
(2.488) | (2.340) | (−0.815) | (−0.797) | (1.379) | (0.368) | (−1.121) | (0.316) | (−2.228) | (−0.027) | (−0.388) | (1.867) | |
Control Variables | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES |
cons | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES |
City | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Year | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES | YES |
N | 368 | 420 | 110 | 80 | 180 | 500 | 90 | 200 | 80 | 460 | 70 | 150 |
R2 | 0.983 | 0.974 | 0.986 | 0.978 | 0.967 | 0.956 | 0.962 | 0.966 | 0.986 | 0.972 | 0.987 | 0.979 |
F | 359.461 | 239.536 | 244.896 | 117.102 | 134.301 | 148.733 | 72.070 | 139.967 | 176.400 | 228.545 | 179.355 | 195.128 |
Variables | Resource-Based City | Non-Resource-Based City | ||||||
---|---|---|---|---|---|---|---|---|
RGCS | SGCS | RSCS | SSCS | RGCS | SGCS | RSCS | SSCS | |
ER | 0.000 | 0.005 | 0.004 | 0.035 *** | 0.025 ** | 0.019 *** | 0.042 *** | 0.034 ** |
(0.002) | (0.633) | (0.161) | (3.386) | (2.529) | (2.744) | (3.030) | (−2.393) | |
Control Variables | YES | YES | YES | YES | YES | YES | YES | YES |
cons | YES | YES | YES | YES | YES | YES | YES | YES |
City | YES | YES | YES | YES | YES | YES | YES | YES |
Year | YES | YES | YES | YES | YES | YES | YES | YES |
N | 110 | 570 | 150 | 260 | 518 | 810 | 120 | 170 |
R2 | 0.974 | 0.969 | 0.971 | 0.962 | 0.974 | 0.970 | 0.983 | 0.984 |
F | 127.387 | 222.595 | 138.393 | 139.292 | 255.351 | 243.157 | 212.548 | 275.669 |
Explanatory Variables | RGCS | SGCS | RSCS | SSCS |
---|---|---|---|---|
ER | 0.113 *** | 0.1626 *** | 0.1039 *** | 0.2241 *** |
(0.015) | (0.014) | (0.027) | (0.018) | |
TA | −0.207 | 0.0919 *** | 0.0296 | 0.0587 * |
(0.025) | (0.020) | (0.048) | (0.030) | |
ED | 0.675 *** | 0.7844 *** | 0.6976 | 0.4219 |
(0.063) | (0.056) | (0.105) | (0.091) | |
IS | 0.144 | 1.1457 *** | 0.2586 * | 0.3430 |
(0.102) | (0.077) | (0.152) | (0.111) | |
PZ | −0.763 *** | 0.5204 * | 0.3996 | 0.5157 |
(0.045) | (0.041) | (0.093) | (0.055) | |
FDI | 0.103 * | −0.0291 | 0.0285 *** | 0.0483 ** |
(0.019) | (0.012) | (0.026) | (0.020) | |
_cons | 3.5271 *** | 9.602 *** | 3.7306 *** | 2.6267 *** |
(0.408) | (13.565) | (0.720) | (0.603) | |
N | 565 | 1242 | 243 | 387 |
R2 | 0.6436 | 0.479 | 0.524 | 0.578 |
F | 309.824 | 248.286 | 272.68 | 552.05 |
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Tang, X.; Shao, S.; Cui, J. Spatial-Temporal Evolution and Environmental Regulation Effects of Carbon Emissions in Shrinking and Growing Cities: Empirical Evidence from 272 Cities in China. Sustainability 2024, 16, 7256. https://doi.org/10.3390/su16177256
Tang X, Shao S, Cui J. Spatial-Temporal Evolution and Environmental Regulation Effects of Carbon Emissions in Shrinking and Growing Cities: Empirical Evidence from 272 Cities in China. Sustainability. 2024; 16(17):7256. https://doi.org/10.3390/su16177256
Chicago/Turabian StyleTang, Xinhang, Shuai Shao, and Jia Cui. 2024. "Spatial-Temporal Evolution and Environmental Regulation Effects of Carbon Emissions in Shrinking and Growing Cities: Empirical Evidence from 272 Cities in China" Sustainability 16, no. 17: 7256. https://doi.org/10.3390/su16177256