CO2 Emission Allocation for Urban Public Buildings Considering Efficiency and Equity: An Application at the Provincial Level in China
Abstract
:1. Introduction
- Many earlier studies in the field of carbon emission allocation have concentrated on the distribution of CO2 emissions among provinces primarily. However, we have directed our attention to carbon emission allocation in provincial public buildings, and fill the gap created by the lack of studies shedding light on carbon emission allocation in the public building sector. We developed an optimal scheme for carbon emission allocations in provincial urban public buildings in China which provides a clear and effective strategy for reducing carbon emissions in these buildings.
- We have developed a ZSG-DEA model which takes into account the actual performance of each region in achieving its carbon emission goals. Compared to other models of previous research, this model gives more attention to the overall regional efficiency and allows for the reward of regions that achieve optimal performance in reducing their carbon emissions while penalizing those that do not meet the fixed target.
- This study not only proposes an innovative scheme for carbon emission allocations in provincial urban public buildings but also provides significant policy recommendations for provincial-level allocation quotas for urban public buildings. It is significant in addressing China’s serious challenge of decreasing carbon emissions.
2. Literature Review
2.1. Equity and Efficiency in Carbon Emission Allocation
2.2. Data Envelopment Analysis (DEA) Model
3. Methodology and Data Sources
3.1. Methodology
3.2. Data Sources
4. Results
4.1. The Initial Carbon Quotas Allocation
4.2. Efficiency and Final Carbon Quotas Allocation
5. Discussion
5.1. Pressure of Provincial Carbon Emission Reduction for Urban Public Buildings
5.2. Comparison with the Existing Literature
6. Conclusions
6.1. Main Findings
- Qinghai, Hainan, Ningxia, Tianjin, and Jilin had small carbon quotas for urban public buildings. These provinces, characterized by relatively low population density and abundant resources, have achieved a balance between economic and environmental development, facilitating the attainment of sustainable development objectives. Consequently, these provinces are encouraged to develop their economies while minimizing the negative impact on the environment. Provinces such as Guangdong, Shandon, Jiangsu, Hebei, Zhejiang, and Henan were assigned substantial carbon quotas due to their high population densities and superior input–output efficiencies. In essence, these provinces exhibit a superior ability to generate higher economic output with lower input, positioning them as significant drivers of economic growth. Nonetheless, this advantage often corresponds to increased carbon emissions. In order to balance growth and environmental protection in these provinces, the allocation scheme has awarded higher carbon quotas to enable them to continue developing their economies while minimizing the carbon footprint of their urban public buildings. This not only promotes sustainable development in these provinces but also contributes to achieving the national goal of reducing carbon emissions.
- There is variation in carbon emission quotas across different regions of China, with quotas gradually increasing from the northwest to the southeast. This is because the southeast coastal areas are more developed economically, have larger populations, and also have higher carbon emission efficiency. As a result, provinces such as Guangdong, Jiangsu, Shandong, and Zhejiang have been assigned higher carbon quotas. The allocation of higher carbon quotas to these provinces is intended to incentivize them to mitigate their carbon emissions and also improve sustainable development. In contrast, the northwest regions have fewer economic advantages, smaller populations, and lower carbon emission efficiency. Consequently, provinces such as Qinghai, Hainan, Ningxia, and Gansu have been assigned relatively lower carbon emission quotas, which may provide incentives to develop cleaner and more sustainable industries and lead to long-term economic and environmental benefits.
- According to the results of carbon emission reduction pressure, it has been observed that many of the 30 provinces in China are facing pressures to decrease carbon emissions. Out of these provinces, 17 have a surplus in their carbon emission quotas, including Guangdong, Shandong, Hubei, Hunan, and others. Guangdong and Shandong have the highest proportion of quota surplus among all the provinces. Both Guangdong and Shandong are considered highly industrialized and developed regions in China, which could contribute to their better performance in reducing carbon emissions. While some provinces are carbon emissions quota surplus, others are experiencing significant pressure to reduce emissions. Provinces such as Hebei, Beijing, Anhui, and Zhejiang are facing huge emission reduction pressure, indicating that they are struggling to bring their carbon emissions down to more sustainable levels. Provinces with abundant resources, such as Heilongjiang and Inner Mongolia, face significantly higher pressure to reduce emissions in urban public buildings. Conversely, provinces such as Sichuan, Fujian, and Hunan, which have low historical CO2 emissions and strong economic development, experience relatively lower reduction pressure.
6.2. Policy Implications
6.3. Limitations and Future Research
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Variable Classification | Specific Variable | Variable Explanation |
---|---|---|
Input variable | Population GDP Energy consumption | Population of each province in 2030 GDP of each province energy consumption of each province in 2030 |
Output variable | Carbon emissions | Estimated CO2 emissions by regions of urban public buildings |
Province | Carbon Quota (Million Tons) | Energy Consumption (Million Tce) | GDP (Billion Yuan) | Population (Million) |
---|---|---|---|---|
Beijing | 94.30 | 78.07 | 9454.55 | 24.70 |
Tianjin | 28.30 | 93.16 | 3166.36 | 14.80 |
Hebei | 208.77 | 388.43 | 7575.23 | 77.81 |
Shanxi | 45.61 | 245.37 | 3586.52 | 34.77 |
Inner Mongolia | 74.69 | 354.29 | 4027.39 | 23.56 |
Liaoning | 54.11 | 249.38 | 4585.15 | 41.57 |
Jilin | 31.84 | 54.05 | 2397.51 | 21.31 |
Heilongjiang | 42.03 | 117.17 | 2255.15 | 26.84 |
Shanghai | 66.05 | 125.82 | 9230.37 | 27.03 |
Jiangsu | 183.81 | 413.61 | 27,641.29 | 90.95 |
Zhejiang | 137.66 | 319.70 | 16,398.45 | 76.59 |
Anhui | 111.31 | 200.38 | 11,932.85 | 61.75 |
Fujian | 63.57 | 196.03 | 13,902.60 | 46.86 |
Jiangxi | 55.34 | 156.28 | 7415.71 | 45.94 |
Shandong | 137.41 | 500.11 | 16,645.72 | 107.78 |
Henan | 78.16 | 231.83 | 14,505.83 | 103.84 |
Hubei | 56.55 | 189.89 | 13,680.23 | 60.13 |
Hunan | 60.44 | 166.87 | 11,812.72 | 67.71 |
Guangdong | 141.23 | 461.97 | 29,017.68 | 151.85 |
Guangxi | 37.97 | 165.91 | 6077.94 | 53.25 |
Hainan | 23.82 | 38.82 | 1612.12 | 11.62 |
Chongqing | 40.84 | 100.34 | 8053.32 | 35.64 |
Sichuan | 78.93 | 232.33 | 14,404.98 | 86.44 |
Guizhou | 41.51 | 130.36 | 7308.79 | 41.29 |
Yunnan | 52.61 | 173.13 | 7792.94 | 48.29 |
Shaanxi | 61.01 | 211.84 | 7436.71 | 41.68 |
Gansu | 21.75 | 101.15 | 2077.54 | 24.51 |
Qinghai | 8.70 | 67.89 | 859.95 | 6.24 |
Ningxia | 13.61 | 177.15 | 1048.71 | 8.17 |
Xinjiang | 56.33 | 409.45 | 3771.64 | 30.43 |
Province | Initial Efficiency | Final Efficiency | Adjustment Amount (Million Tons) | Final Quota (Million Tons) |
---|---|---|---|---|
Hebei | 0.42576 | 1 | 95.67 | 113.1 |
Beijing | 0.44369 | 1 | 39.14 | 55.16 |
Anhui | 0.50604 | 1 | 37.16 | 74.15 |
Hainan | 0.52254 | 1 | 7.08 | 16.74 |
Heilongjiang | 0.52267 | 1 | 12.61 | 29.42 |
Jilin | 0.57153 | 1 | 7.38 | 24.46 |
Zhejiang | 0.61115 | 1 | 26.87 | 110.79 |
Shanghai | 0.61239 | 1 | 12.02 | 54.03 |
Tianjin | 0.61939 | 1 | 4.71 | 23.59 |
Inner Mongolia | 0.66326 | 1 | 8.49 | 66.2 |
Shaanxi | 0.66807 | 1 | 6.42 | 54.59 |
Jiangxi | 0.69239 | 1 | 3.93 | 51.41 |
Jiangsu | 0.74473 | 1 | 3.04 | 180.77 |
Yunnan | 0.76735 | 1 | −1.68 | 54.29 |
Liaoning | 0.78163 | 1 | −2.78 | 56.89 |
Shanxi | 0.82855 | 1 | −5.31 | 50.92 |
Guizhou | 0.86662 | 1 | −7.01 | 48.52 |
Chongqing | 0.87262 | 1 | −7.25 | 48.09 |
Sichuan | 0.90653 | 1 | −17.51 | 96.44 |
Fujian | 0.91565 | 1 | −14.97 | 78.54 |
Gansu | 0.92357 | 1 | −5.4 | 27.15 |
Hunan | 0.93201 | 1 | −15.6 | 76.04 |
Shandong | 1 | 1 | −48.47 | 185.88 |
Henan | 1 | 1 | −27.56 | 105.72 |
Hubei | 1 | 1 | −19.95 | 76.5 |
Guangdong | 1 | 1 | −49.82 | 191.05 |
Guangxi | 1 | 1 | −13.39 | 51.36 |
Qinghai | 1 | 1 | −3.07 | 11.77 |
Ningxia | 1 | 1 | −4.79 | 18.4 |
Xinjiang | 1 | 1 | −19.86 | 76.19 |
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Zhang, Z.; Liu, Y.; Du, Z. CO2 Emission Allocation for Urban Public Buildings Considering Efficiency and Equity: An Application at the Provincial Level in China. Buildings 2023, 13, 1570. https://doi.org/10.3390/buildings13061570
Zhang Z, Liu Y, Du Z. CO2 Emission Allocation for Urban Public Buildings Considering Efficiency and Equity: An Application at the Provincial Level in China. Buildings. 2023; 13(6):1570. https://doi.org/10.3390/buildings13061570
Chicago/Turabian StyleZhang, Zhidong, Yisheng Liu, and Zhuoqun Du. 2023. "CO2 Emission Allocation for Urban Public Buildings Considering Efficiency and Equity: An Application at the Provincial Level in China" Buildings 13, no. 6: 1570. https://doi.org/10.3390/buildings13061570