Spatial-Temporal Evolution Analysis of Carbon Emissions Embodied in Inter-Provincial Trade in China
Abstract
:1. Introduction
2. Research Methods and Data
2.1. MRIO Analysis
2.2. Calculation of Carbon Emissions Embodied in Inter-Provincial Trade
2.3. Construction of the ECETN
2.4. Indicators for Analyzing the ECETN
2.4.1. Centrality Analysis
2.4.2. Topology Analysis
2.4.3. Clustering Analysis
2.5. QAP Analysis
2.6. The Data
3. Empirical Results
3.1. Evolution of Carbon Emissions Embodied in Inter-Provincial Trade in China
3.1.1. Evolution of Embodied Carbon Emissions under the Provincial Perspective
3.1.2. Evolution of Embodied Carbon Emissions under the Sectoral Perspective
3.2. Evolution of Structural Characteristics of ECETN
3.3. Provincial Roles
3.3.1. Provinces with Large-Scale Influence
3.3.2. Provinces with Strong Influence
3.3.3. Provinces with Strong Intermediary Ability
3.3.4. Provinces with Strong Central Ability
3.3.5. Provinces with High Eigenvector Centrality
3.4. Clustering and Spatial Spillover Structure Characteristics
3.5. Analysis of Influencing Factors of ECETN
4. Conclusions and Policy Implications
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Index | Province | Degree-In | Degree-Out | Degree | Strength-In | Strength-Out | Strength | Betweenness | Closeness-In | Closeness-Out | Eigenvector | ||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2012 | 2015 | 2017 | 2012 | 2015 | 2017 | 2012 | 2015 | 2017 | 2012 | 2015 | 2017 | 2012 | 2015 | 2017 | 2012 | 2015 | 2017 | 2012 | 2015 | 2017 | 2012 | 2015 | 2017 | 2012 | 2015 | 2017 | 2012 | 2015 | 2017 | ||
1 | Beijing | 26 | 27 | 27 | 15 | 10 | 10 | 41 | 37 | 37 | 154.80 | 150.18 | 176.97 | 24.02 | 18.36 | 18.90 | 178.82 | 168.54 | 195.87 | 0.01847 | 0.01738 | 0.00409 | 0.938 | 0.968 | 0.968 | 0.714 | 0.600 | 0.667 | 0.312 | 0.275 | 0.293 |
2 | Tianjin | 18 | 19 | 3 | 8 | 5 | 6 | 26 | 24 | 9 | 38.04 | 40.91 | 3.84 | 11.42 | 7.68 | 14.15 | 49.47 | 48.59 | 17.98 | 0.00013 | 0.00034 | 0.00000 | 0.732 | 0.769 | 0.526 | 0.545 | 0.526 | 0.588 | 0.203 | 0.190 | 0.079 |
3 | Hebei | 21 | 12 | 21 | 26 | 26 | 22 | 47 | 38 | 43 | 61.44 | 20.89 | 77.55 | 148.95 | 148.43 | 133.51 | 210.39 | 169.32 | 211.06 | 0.14629 | 0.04326 | 0.09371 | 0.811 | 0.638 | 0.811 | 1.000 | 0.938 | 0.938 | 0.363 | 0.315 | 0.348 |
4 | Shanxi | 3 | 7 | 3 | 22 | 20 | 19 | 25 | 27 | 22 | 3.50 | 10.91 | 10.31 | 127.80 | 123.41 | 110.27 | 131.30 | 134.32 | 120.58 | 0.00043 | 0.00352 | 0.00072 | 0.484 | 0.556 | 0.526 | 0.882 | 0.789 | 0.833 | 0.210 | 0.222 | 0.195 |
5 | InnerMongolia | 7 | 5 | 8 | 24 | 26 | 20 | 31 | 31 | 28 | 10.55 | 5.49 | 12.59 | 144.93 | 185.40 | 182.26 | 155.48 | 190.89 | 194.86 | 0.04252 | 0.05272 | 0.00405 | 0.556 | 0.508 | 0.577 | 0.938 | 0.938 | 0.857 | 0.262 | 0.243 | 0.235 |
6 | Liaoning | 24 | 12 | 17 | 20 | 20 | 18 | 44 | 32 | 35 | 51.20 | 18.58 | 31.13 | 60.16 | 76.39 | 87.13 | 111.36 | 94.97 | 118.26 | 0.04974 | 0.01698 | 0.01507 | 0.882 | 0.638 | 0.732 | 0.833 | 0.789 | 0.811 | 0.343 | 0.271 | 0.318 |
7 | Jilin | 10 | 10 | 8 | 10 | 10 | 17 | 20 | 20 | 25 | 15.38 | 18.61 | 22.28 | 17.93 | 16.32 | 41.13 | 33.31 | 34.92 | 63.41 | 0.00225 | 0.00110 | 0.00094 | 0.588 | 0.612 | 0.577 | 0.566 | 0.600 | 0.789 | 0.151 | 0.160 | 0.212 |
8 | Heilongjiang | 8 | 6 | 11 | 18 | 20 | 18 | 26 | 26 | 29 | 15.95 | 8.65 | 30.30 | 39.98 | 61.77 | 101.67 | 55.93 | 70.42 | 131.97 | 0.00400 | 0.00502 | 0.00933 | 0.545 | 0.545 | 0.625 | 0.789 | 0.789 | 0.811 | 0.205 | 0.213 | 0.223 |
9 | Shanghai | 27 | 25 | 21 | 9 | 13 | 18 | 36 | 38 | 39 | 97.08 | 86.59 | 64.55 | 13.57 | 23.63 | 57.62 | 110.65 | 110.22 | 122.17 | 0.02031 | 0.00885 | 0.02412 | 0.968 | 0.909 | 0.811 | 0.625 | 0.638 | 0.811 | 0.280 | 0.304 | 0.328 |
10 | Jiangsu | 28 | 27 | 28 | 16 | 16 | 13 | 44 | 43 | 41 | 136.73 | 161.66 | 121.44 | 38.15 | 30.50 | 40.61 | 174.88 | 192.17 | 162.06 | 0.05356 | 0.04119 | 0.02200 | 1.000 | 0.968 | 1.000 | 0.732 | 0.682 | 0.714 | 0.334 | 0.327 | 0.313 |
11 | Zhejiang | 27 | 27 | 28 | 13 | 17 | 14 | 40 | 44 | 42 | 104.50 | 157.09 | 161.12 | 18.30 | 39.83 | 52.98 | 122.81 | 196.92 | 214.10 | 0.02832 | 0.04980 | 0.03457 | 0.968 | 0.968 | 1.000 | 0.682 | 0.698 | 0.732 | 0.301 | 0.332 | 0.325 |
12 | Anhui | 24 | 25 | 20 | 17 | 20 | 7 | 41 | 45 | 27 | 54.48 | 75.51 | 56.45 | 89.43 | 66.56 | 23.13 | 143.91 | 142.07 | 79.58 | 0.01913 | 0.04022 | 0.00000 | 0.882 | 0.909 | 0.789 | 0.750 | 0.750 | 0.612 | 0.321 | 0.353 | 0.205 |
13 | Fujian | 6 | 7 | 0 | 8 | 14 | 12 | 14 | 21 | 12 | 6.30 | 8.13 | 0.00 | 7.72 | 32.38 | 32.49 | 14.02 | 40.51 | 32.49 | 0.00050 | 0.00010 | 0.00000 | 0.536 | 0.577 | 0.000 | 0.536 | 0.652 | 0.667 | 0.101 | 0.169 | 0.104 |
14 | Jiangxi | 21 | 20 | 23 | 7 | 9 | 13 | 28 | 29 | 36 | 49.15 | 77.05 | 75.89 | 12.95 | 20.73 | 31.94 | 62.10 | 97.77 | 107.83 | 0.00031 | 0.00037 | 0.00445 | 0.789 | 0.789 | 0.857 | 0.500 | 0.566 | 0.698 | 0.199 | 0.216 | 0.274 |
15 | Shandong | 26 | 18 | 1 | 12 | 10 | 21 | 38 | 28 | 22 | 84.84 | 67.40 | 2.00 | 21.56 | 21.43 | 146.99 | 106.40 | 88.83 | 148.99 | 0.03678 | 0.00175 | 0.00029 | 0.938 | 0.750 | 0.462 | 0.652 | 0.600 | 0.882 | 0.298 | 0.222 | 0.196 |
16 | Henan | 18 | 26 | 27 | 25 | 25 | 23 | 43 | 51 | 50 | 29.52 | 60.13 | 183.69 | 98.48 | 79.11 | 101.84 | 128.00 | 139.23 | 285.53 | 0.06296 | 0.14758 | 0.16813 | 0.750 | 0.938 | 0.968 | 0.968 | 0.882 | 0.968 | 0.345 | 0.395 | 0.384 |
17 | Hubei | 22 | 23 | 7 | 3 | 3 | 10 | 25 | 26 | 17 | 55.43 | 111.61 | 11.30 | 3.88 | 4.43 | 23.27 | 59.31 | 116.04 | 34.57 | 0.00014 | 0.00202 | 0.00000 | 0.811 | 0.857 | 0.556 | 0.455 | 0.448 | 0.667 | 0.179 | 0.194 | 0.129 |
18 | Hunan | 16 | 23 | 24 | 16 | 11 | 11 | 32 | 34 | 35 | 21.58 | 40.72 | 71.12 | 30.64 | 23.98 | 19.03 | 52.22 | 64.70 | 90.15 | 0.00372 | 0.00309 | 0.00385 | 0.714 | 0.857 | 0.882 | 0.732 | 0.612 | 0.667 | 0.257 | 0.264 | 0.275 |
19 | Guangdong | 27 | 27 | 28 | 14 | 15 | 14 | 41 | 42 | 42 | 117.47 | 66.60 | 231.22 | 20.82 | 35.76 | 32.00 | 138.28 | 102.37 | 263.21 | 0.02069 | 0.03754 | 0.04068 | 0.968 | 0.968 | 1.000 | 0.698 | 0.667 | 0.732 | 0.313 | 0.314 | 0.323 |
20 | Guangxi | 8 | 8 | 9 | 16 | 15 | 13 | 24 | 23 | 22 | 10.22 | 11.42 | 15.78 | 28.21 | 32.08 | 32.99 | 38.43 | 43.51 | 48.77 | 0.00122 | 0.00602 | 0.00045 | 0.588 | 0.600 | 0.600 | 0.732 | 0.667 | 0.698 | 0.190 | 0.162 | 0.180 |
21 | Hainan | 1 | 3 | 1 | 2 | 3 | 1 | 3 | 6 | 2 | 1.18 | 2.75 | 1.54 | 1.59 | 2.72 | 1.40 | 2.78 | 5.47 | 2.94 | 0.00000 | 0.00000 | 0.00000 | 0.469 | 0.526 | 0.517 | 0.441 | 0.429 | 0.455 | 0.024 | 0.039 | 0.022 |
22 | Chongqing | 23 | 26 | 27 | 14 | 10 | 10 | 37 | 36 | 37 | 64.05 | 100.79 | 119.26 | 25.30 | 15.95 | 19.10 | 89.35 | 116.74 | 138.36 | 0.01424 | 0.00778 | 0.01053 | 0.857 | 0.938 | 0.968 | 0.698 | 0.577 | 0.652 | 0.291 | 0.268 | 0.290 |
23 | Sichuan | 4 | 7 | 7 | 15 | 13 | 12 | 19 | 20 | 19 | 4.20 | 10.31 | 11.50 | 23.18 | 17.86 | 24.92 | 27.38 | 28.17 | 36.42 | 0.00000 | 0.00010 | 0.00060 | 0.492 | 0.556 | 0.566 | 0.714 | 0.638 | 0.698 | 0.154 | 0.161 | 0.168 |
24 | Guizhou | 1 | 3 | 15 | 18 | 16 | 16 | 19 | 19 | 31 | 0.80 | 3.09 | 21.22 | 50.16 | 37.59 | 40.78 | 50.96 | 40.68 | 62.00 | 0.00014 | 0.00031 | 0.01399 | 0.462 | 0.517 | 0.682 | 0.769 | 0.682 | 0.789 | 0.156 | 0.152 | 0.265 |
25 | Yunnan | 9 | 13 | 18 | 16 | 13 | 10 | 25 | 26 | 28 | 8.35 | 17.85 | 30.10 | 42.18 | 26.46 | 21.12 | 50.53 | 44.31 | 51.22 | 0.00053 | 0.00135 | 0.00126 | 0.556 | 0.667 | 0.750 | 0.732 | 0.638 | 0.667 | 0.193 | 0.215 | 0.241 |
26 | Tibet | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0.00 | 0.00 | 1.03 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 1.03 | 0.00000 | 0.00000 | 0.00000 | 0.000 | 0.000 | 0.492 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.014 |
27 | Shaanxi | 21 | 21 | 26 | 22 | 24 | 18 | 43 | 45 | 44 | 46.15 | 47.05 | 87.62 | 58.70 | 67.52 | 88.42 | 104.85 | 114.58 | 176.05 | 0.04319 | 0.08824 | 0.03748 | 0.811 | 0.811 | 0.938 | 0.882 | 0.882 | 0.811 | 0.332 | 0.353 | 0.355 |
28 | Gansu | 3 | 4 | 0 | 15 | 14 | 13 | 18 | 18 | 13 | 2.50 | 3.55 | 0.00 | 32.26 | 29.66 | 30.27 | 34.76 | 33.21 | 30.27 | 0.00000 | 0.00000 | 0.00000 | 0.484 | 0.526 | 0.000 | 0.714 | 0.652 | 0.652 | 0.146 | 0.130 | 0.100 |
29 | Qinghai | 0 | 1 | 1 | 2 | 3 | 2 | 2 | 4 | 3 | 0.00 | 0.87 | 1.53 | 1.62 | 4.55 | 2.11 | 1.62 | 5.42 | 3.64 | 0.00000 | 0.00000 | 0.00000 | 0.000 | 0.353 | 0.000 | 0.435 | 0.462 | 0.448 | 0.016 | 0.026 | 0.016 |
30 | Ningxia | 1 | 2 | 1 | 14 | 14 | 12 | 15 | 16 | 13 | 0.98 | 2.42 | 1.98 | 23.27 | 25.46 | 32.42 | 24.26 | 27.89 | 34.40 | 0.00000 | 0.00000 | 0.00000 | 0.370 | 0.375 | 0.357 | 0.714 | 0.667 | 0.714 | 0.113 | 0.110 | 0.106 |
31 | Xinjiang | 4 | 3 | 3 | 17 | 22 | 21 | 21 | 25 | 24 | 6.16 | 3.36 | 3.70 | 35.39 | 114.24 | 94.52 | 41.54 | 117.61 | 98.21 | 0.00053 | 0.01530 | 0.03381 | 0.508 | 0.517 | 0.526 | 0.750 | 0.811 | 0.909 | 0.177 | 0.202 | 0.214 |
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Input | Output | |||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Intermediate Use | Final Use | Total Output | ||||||||||||||||
Province 1 | ⋯ | Provincem | Province 1 | ⋯ | Provincem | Exports | ||||||||||||
Sector 1 | ⋯ | Sectorn | Sector 1 | ⋯ | Sectorn | Category 1 | ⋯ | Categoryk | Category 1 | ⋯ | Categoryk | |||||||
Intermediate input | Sector 1 | ⋯ | ⋯ | ⋯ | ⋯ | |||||||||||||
Province 1 | ⋮ | ⋮ | ⋱ | ⋮ | ⋯ | ⋮ | ⋱ | ⋮ | ⋮ | ⋱ | ⋮ | ⋯ | ⋮ | ⋱ | ⋮ | ⋮ | ⋮ | |
Sector n | ⋯ | ⋯ | ⋯ | ⋯ | ||||||||||||||
⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ||||||||||||||
Sector 1 | ⋯ | ⋯ | ⋯ | ⋯ | ||||||||||||||
Province m | ⋮ | ⋮ | ⋱ | ⋮ | ⋯ | ⋮ | ⋱ | ⋮ | ⋮ | ⋱ | ⋮ | ⋯ | ⋮ | ⋱ | ⋮ | ⋮ | ⋮ | |
Sector n | ⋯ | ⋯ | ⋯ | ⋯ | ||||||||||||||
Imports | ⋯ | ⋯ | ⋯ | ⋯ | ⋯ | ⋯ | ||||||||||||
Value-added | ⋯ | ⋯ | ⋯ | |||||||||||||||
Total input | ⋯ | ⋯ | ⋯ | |||||||||||||||
Direct carbon emissions | ⋯ | ⋯ | ⋯ |
Year | Number of Node | Number of Edge | Average Degree | Average Strength | Network Density | Network Efficiency | Clustering Coefficient | Average Path Length | Assortativity |
---|---|---|---|---|---|---|---|---|---|
2012 | 31 | 434 | 14.000 | 40.404 | 0.467 | 0.864 | 0.657 | 1.590 | −0.272 |
2015 | 31 | 432 | 13.935 | 44.844 | 0.465 | 0.861 | 0.620 | 1.586 | −0.254 |
2017 | 31 | 414 | 13.355 | 52.871 | 0.445 | 0.824 | 0.663 | 1.560 | −0.319 |
Year | Block | Provinces | Contacts Received | Contacts Sent | Expected Internal Relationship | Actual Internal Relationship | Characteristic | ||
---|---|---|---|---|---|---|---|---|---|
Inside | Outside | Inside | Outside | ||||||
2012 | I | Beijing, Anhui, Hunan, Guangdong, Zhejiang, Liaoning, Jiangsu, Shaanxi (8) | 54 | 139 | 54 | 79 | 24.14% | 40.60% | Main inflow |
II | Tianjin, Chongqing, Shandong, Shanghai, Jiangxi, Hubei (6) | 10 | 127 | 10 | 43 | 17.24% | 18.87% | Main inflow | |
III | Henan, Jilin, Hebei (3) | 4 | 45 | 4 | 57 | 6.90% | 6.56% | Agent | |
IV | Fujian, Inner Mongolia, Guangxi, Hainan, Heilongjiang, Sichuan, Guizhou, Yunnan, Shanxi, Gansu, Qinghai, Ningxia, Xinjiang (13) | 19 | 36 | 19 | 168 | 41.38% | 10.16% | Main outflow | |
2015 | I | Beijing, Tianjin, Hunan, Guangdong, Shandong, Shanghai, Chongqing, Zhejiang, Jiangsu, Jiangxi, Hubei (11) | 73 | 184 | 73 | 41 | 34.48% | 64.04% | Main inflow |
II | Shaanxi, Yunnan, Henan, Anhui (4) | 12 | 73 | 12 | 70 | 10.34% | 14.63% | Bidirectional spillover | |
III | Liaoning, Qinghai, Heilongjiang, Inner Mongolia, Shanxi, Jilin, Hebei (7) | 26 | 27 | 26 | 99 | 20.69% | 20.80% | Bidirectional spillover | |
IV | Hainan, Guangxi, Guizhou, Sichuan, Gansu, Fujian, Ningxia, Xinjiang (8) | 7 | 30 | 7 | 104 | 24.14% | 6.31% | Main outflow | |
2017 | I | Beijing, Shanghai, Hunan, Guangdong, Anhui, Shaanxi, Chongqing, Zhejiang, Yunnan, Jiangsu (10) | 79 | 168 | 79 | 46 | 31.03% | 63.20% | Main inflow |
II | Jiangxi, Henan, Hebei (3) | 5 | 66 | 5 | 52 | 6.90% | 8.77% | Bidirectional spillover | |
III | Hainan, Qinghai, Tianjin (3) | 0 | 5 | 0 | 9 | 6.90% | 0.00% | Agent | |
IV | Heilongjiang, Hubei, Shandong, Guangxi, Liaoning, Inner Mongolia, Sichuan, Guizhou, Jilin, Shanxi, Gansu, Fujian, Ningxia, Xinjiang (14) | 49 | 41 | 49 | 173 | 44.83% | 22.07% | Main outflow |
Year | Block | Density Matrix | Image Matrix | ||||||
---|---|---|---|---|---|---|---|---|---|
I | II | III | IV | I | II | III | IV | ||
2012 | I | 0.964 | 1.000 | 0.750 | 0.125 | 1 | 1 | 1 | 0 |
II | 0.750 | 0.333 | 0.278 | 0.026 | 1 | 0 | 0 | 0 | |
III | 0.875 | 0.833 | 0.667 | 0.538 | 1 | 1 | 1 | 1 | |
IV | 0.788 | 0.821 | 0.564 | 0.122 | 1 | 1 | 1 | 0 | |
2015 | I | 0.709 | 0.682 | 0.104 | 0.034 | 1 | 1 | 0 | 0 |
II | 0.977 | 1.000 | 0.536 | 0.375 | 1 | 1 | 1 | 0 | |
III | 0.844 | 0.679 | 0.619 | 0.268 | 1 | 1 | 1 | 0 | |
IV | 0.864 | 0.750 | 0.071 | 0.125 | 1 | 1 | 0 | 0 | |
2017 | I | 0.878 | 0.800 | 0.000 | 0.157 | 1 | 1 | 0 | 0 |
II | 1.000 | 0.833 | 0.333 | 0.452 | 1 | 1 | 0 | 0 | |
III | 0.267 | 0.111 | 0.000 | 0.000 | 0 | 0 | 0 | 0 | |
IV | 0.929 | 0.976 | 0.048 | 0.269 | 1 | 1 | 0 | 0 |
Variable | 2012 | 2015 | 2017 | |||
---|---|---|---|---|---|---|
ObsValue | Significance | ObsValue | Significance | ObsValue | Significance | |
−0.024 | 0.237 | −0.071 ** | 0.024 | 0.052 * | 0.066 | |
−0.044 | 0.257 | 0.047 | 0.205 | −0.119 ** | 0.043 | |
0.211 *** | 0.000 | 0.261 *** | 0.000 | 0.303 *** | 0.000 | |
0.221 *** | 0.001 | 0.214 *** | 0.001 | 0.106 * | 0.089 | |
0.109 ** | 0.048 | −0.009 | 0.462 | −0.066 | 0.190 | |
−0.088 | 0.143 | −0.021 | 0.413 | 0.141 ** | 0.040 | |
B | 0.203 *** | 0.005 | 0.098 ** | 0.023 | 0.269 *** | 0.002 |
−0.224 *** | 0.000 | −0.206 *** | 0.000 | −0.192 *** | 0.001 | |
C | −0.218 *** | 0.000 | −0.173 *** | 0.000 | −0.138 ** | 0.034 |
0.065 ** | 0.032 | 0.033** | 0.038 | 0.115 *** | 0.000 |
Dependent Variable | Inter Provincial Embodied Carbon Emission Transfer Network | 2012 | 2015 | 2017 | |||
---|---|---|---|---|---|---|---|
Standardized Coefficient | Significance (p-Value) | Standardized Coefficient | Significance (p-Value) | Standardized Coefficient | Significance (p-Value) | ||
Influencing factors (difference matrix) | — | — | −0.073 | 0.414 | 0.131 ** | 0.032 | |
— | — | — | — | −0.107 | 0.154 | ||
0.360 *** | 0.000 | 0.329 *** | 0.000 | 0.345 *** | 0.000 | ||
0.232 *** | 0.000 | 0.182 *** | 0.000 | 0.157 *** | 0.001 | ||
0.223 *** | 0.005 | — | — | — | — | ||
— | — | — | — | 0.129 | 0.111 | ||
B | 0.184 *** | 0.000 | 0.184 *** | 0.000 | 0.197 *** | 0.000 | |
−0.409 *** | 0.000 | −0.381 *** | 0.000 | −0.378 *** | 0.000 | ||
C | −0.187 *** | 0.005 | −0.266 *** | 0.000 | −0.108 ** | 0.033 | |
0.075 *** | 0.002 | 0.082 *** | 0.007 | 0.091 *** | 0.001 | ||
Determination cofficient | 0.372 | 0.352 | 0.378 | ||||
Adjusted | 0.364 | 0.343 | 0.370 |
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Wang, T.; Chen, Y.; Zeng, L. Spatial-Temporal Evolution Analysis of Carbon Emissions Embodied in Inter-Provincial Trade in China. Int. J. Environ. Res. Public Health 2022, 19, 6794. https://doi.org/10.3390/ijerph19116794
Wang T, Chen Y, Zeng L. Spatial-Temporal Evolution Analysis of Carbon Emissions Embodied in Inter-Provincial Trade in China. International Journal of Environmental Research and Public Health. 2022; 19(11):6794. https://doi.org/10.3390/ijerph19116794
Chicago/Turabian StyleWang, Tianrui, Yu Chen, and Leya Zeng. 2022. "Spatial-Temporal Evolution Analysis of Carbon Emissions Embodied in Inter-Provincial Trade in China" International Journal of Environmental Research and Public Health 19, no. 11: 6794. https://doi.org/10.3390/ijerph19116794