| Citation: | HUANG H Y,TANG Y Q,GONG Z W,et al.Dynamic evolution and influencing factors of land use carbon emissions in Chongqing based on STIRPAT-GWR model[J].Journal of Environmental Engineering Technology，2024，14（4）：1195-1205 doi: 10.12153/j.issn.1674-991X.20230873
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Exploring the spatiotemporal patterns and influencing factors of land use carbon emissions in Chongqing can provide a scientific reference for further optimizing land use structure and implementing differentiated carbon and pollution reduction policies. Based on three periods of land cover data from 2000 to 2020, the regional differences and spatiotemporal dynamic characteristics of carbon emissions in Chongqing were revealed. The impact of socio-economic factors on spatial heterogeneity of carbon emissions was explored by integrating the STIRPAT model and the geographically weighted regression (GWP) model. The results showed that the net carbon emissions of Chongqing increased by a total of 37.2314 million tons from 2000 to 2020. Its temporal changes could be divided into a sharp increase stage and a slow increase stage, and there was still an imbalance between land use carbon sinks and carbon sources. The overall distribution pattern of net carbon emissions in Chongqing was characterized by a pattern of "high in the center and low on both wings". The growth of net carbon emissions in the main urban areas was the most severe, while it showed a slight increase in all districts and counties of the southeast in Chongqing. There was a significant spatial difference in the growth of net carbon emissions in the northeast. The factors influencing land use carbon emissions presented a strong spatial heterogeneity. The carbon emission intensity and per capita GDP were the key leading factors, followed by urban population size, general budget expenditure of local finance, and industrial structure. The intensity of carbon emissions had a more significant impact in the northeast of Chongqing, and the size of the urban population had a greater positive effect in the main metropolitan areas.
| [1] |
王雅楠, 赵涛. 基于GWR模型中国碳排放空间差异研究[J]. 中国人口·资源与环境,2016,26(2):27-34. doi: 10.3969/j.issn.1002-2104.2016.02.004
WANG Y N, ZHAO T. Study on spatial difference of carbon emissions in China based on GWR model[J]. China Population, Resources and Environment,2016,26(2):27-34. doi: 10.3969/j.issn.1002-2104.2016.02.004
|
| [2] |
张文洁, 许宁, 洪名勇. 长江经济带碳排放绩效的分布动态与地区差异研究[J]. 经济问题,2023(11):105-113.
ZHANG W J, XU N, HONG M Y. Distribution dynamics and regional differences of carbon emission performance in the Yangtze River Economic Belt[J]. On Economic Problems,2023(11):105-113.
|
| [3] |
周亚虹, 杨岚, 姜帅帅. 约束性碳减排与就业: 基于企业和地区劳动力变化的考察[J]. 经济研究, 2023, 58(7): 104-120.
ZHOU Y H, YANG L, JIANG S S. Binding carbon reduction policy and employment: based on the investigation of labor force changes in enterprises and regions[J]. Economic Research Journal, 2023(11): 105-113.
|
| [4] |
王天福, 龚直文, 邓元杰. 基于土地利用变化的陕西省植被碳汇提质增效优先区识别[J]. 自然资源学报,2022,37(5):1214-1232. doi: 10.31497/zrzyxb.20220508
WANG T F, GONG Z W, DENG Y J. Identification of priority areas for improving quality and efficiency of vegetation carbon sinks in Shaanxi Province based on land use change[J]. Journal of Natural Resources,2022,37(5):1214-1232. doi: 10.31497/zrzyxb.20220508
|
| [5] |
张苗, 陈银蓉, 程道平, 等. 土地利用结构和强度变化对碳排放影响分析[J]. 资源开发与市场,2018,34(5):624-628. doi: 10.3969/j.issn.1005-8141.2018.05.006
ZHANG M, CHEN Y R, CHENG D P, et al. Research on influences of land use structure and intensity change on carbon emissions[J]. Resource Development & Market,2018,34(5):624-628. doi: 10.3969/j.issn.1005-8141.2018.05.006
|
| [6] |
张苗, 吴萌. 土地利用对碳排放影响的作用机制和传导路径分析: 基于结构方程模型的实证检验[J]. 中国土地科学,2022,36(3):96-103.
ZHANG M, WU M. Analysis on the mechanism and transmission path of the impact of land use on carbon emissions: empirical test based on structural equation model[J]. China Land Science,2022,36(3):96-103.
|
| [7] |
王少剑, 谢紫寒, 王泽宏. 中国县域碳排放的时空演变及影响因素[J]. 地理学报,2021,76(12):3103-3118. doi: 10.11821/dlxb202112016
WANG S J, XIE Z H, WANG Z H. The spatiotemporal pattern evolution and influencing factors of CO2 emissions at the county level of China[J]. Acta Geographica Sinica,2021,76(12):3103-3118. doi: 10.11821/dlxb202112016
|
| [8] |
陈占明, 吴施美, 马文博, 等. 中国地级以上城市二氧化碳排放的影响因素分析: 基于扩展的STIRPAT模型[J]. 中国人口·资源与环境,2018,28(10):45-54.
CHEN Z M, WU S M, MA W B, et al. Driving forces of carbon dioxide emission for China's cities: empirical analysis based on extended STIRPAT model[J]. China Population, Resources and Environment,2018,28(10):45-54.
|
| [9] |
莫惠斌, 王少剑. 黄河流域县域碳排放的时空格局演变及空间效应机制[J]. 地理科学,2021,41(8):1324-1335.
MO H B, WANG S J. Spatio-temporal evolution and spatial effect mechanism of carbon emission at county level in the Yellow River Basin[J]. Scientia Geographica Sinica,2021,41(8):1324-1335.
|
| [10] |
张剑, 刘景洋, 董莉, 等. 中国能源消费CO2排放的影响因素及情景分析[J]. 环境工程技术学报,2023,13(1):71-78. doi: 10.12153/j.issn.1674-991X.20210563
ZHANG J, LIU J Y, DONG L, et al. Influencing factors and scenario analysis of China's CO2 emission of energy consumption[J]. Journal of Environmental Engineering Technology,2023,13(1):71-78. doi: 10.12153/j.issn.1674-991X.20210563
|
| [11] |
赵玉焕, 李浩, 刘娅, 等. 京津冀CO2排放的时空差异及影响因素研究[J]. 资源科学,2018,40(1):207-215.
ZHAO Y H, LI H, LIU Y, et al. Identifying driving forces of CO2 emissions in Beijing-Tianjin-Hebei region from temporal and spatial angles[J]. Resources Science,2018,40(1):207-215.
|
| [12] |
CHEN W D, YANG R Y. Evolving temporal-spatial trends, spatial association, and influencing factors of carbon emissions in mainland China: empirical analysis based on provincial panel data from 2006 to 2015[J]. Sustainability,2018,10(8):2809. doi: 10.3390/su10082809
|
| [13] |
杨青, 彭若慧, 刘星星, 等. 基于地理加权回归的省域碳排放影响因素研究[J]. 环境工程技术学报,2023,13(1):54-62. doi: 10.12153/j.issn.1674-991X.20210523
YANG Q, PENG R H, LIU X X, et al. Study on influencing factors of provincial carbon emission based on geographically weighted regression[J]. Journal of Environmental Engineering Technology,2023,13(1):54-62. doi: 10.12153/j.issn.1674-991X.20210523
|
| [14] |
牛亚文, 赵先超, 胡艺觉. 基于NPP-VIIRS夜间灯光的长株潭地区县域土地利用碳排放空间分异研究[J]. 环境科学学报,2021,41(9):3847-3856.
NIU Y W, ZHAO X C, HU Y J. Spatial variation of carbon emissions from county land use in Chang-Zhu-Tan area based on NPP-VIIRS night light[J]. Acta Scientiae Circumstantiae,2021,41(9):3847-3856.
|
| [15] |
向书江, 张骞, 王丹, 等. 近20年重庆市主城区碳储量对土地利用/覆被变化的响应及脆弱性分析[J]. 自然资源学报,2022,37(5):1198-1213. doi: 10.31497/zrzyxb.20220507
XIANG S J, ZHANG Q, WANG D, et al. Response and vulnerability analysis of carbon storage to LUCC in the main urban area of Chongqing during 2000-2020[J]. Journal of Natural Resources,2022,37(5):1198-1213. doi: 10.31497/zrzyxb.20220507
|
| [16] |
徐婕, 潘洪义, 黄佩. 基于LUCC的四川省主体功能区碳排放与生态补偿研究[J]. 中国生态农业学报(中英文),2019,27(1):142-152.
XU J, PAN H Y, HUANG P. Carbon emission and ecological compensation of main functional areas in Sichuan Province based on LUCC[J]. Chinese Journal of Eco-Agriculture,2019,27(1):142-152.
|
| [17] |
魏燕茹, 陈松林. 福建省土地利用碳排放空间关联性与碳平衡分区[J]. 生态学报,2021,41(14):5814-5824.
WEI Y R, CHEN S L. Spatial correlation and carbon balance zoning of land use carbon emissions in Fujian Province[J]. Acta Ecologica Sinica,2021,41(14):5814-5824.
|
| [18] |
苑韶峰, 唐奕钰. 低碳视角下长江经济带土地利用碳排放的空间分异[J]. 经济地理,2019,39(2):190-198.
YUAN S F, TANG Y Y. Spatial differentiation of land use carbon emission in the Yangtze River Economic Belt based on low carbon perspective[J]. Economic Geography,2019,39(2):190-198.
|
| [19] |
范建双, 虞晓芬, 周琳. 南京市土地利用结构碳排放效率增长及其空间相关性[J]. 地理研究,2018,37(11):2177-2192.
FAN J S, YU X F, ZHOU L. Carbon emission efficiency growth of land use structure and its spatial correlation: a case study of Nanjing City[J]. Geographical Research,2018,37(11):2177-2192.
|
| [20] |
EHRLICH P R, HOLDREN J P. Impact of population growth[J]. Science,1971,171(3977):1212-1217. doi: 10.1126/science.171.3977.1212
|
| [21] |
孙克, 徐中民, 宋晓谕, 等. 人文因素对省域环境污染影响的空间异质性估计[J]. 生态学报,2017,37(8):2588-2599.
SUN K, XU Z M, SONG X Y, et al. Spatial heterogeneity estimation of the impacts of human factors on environmental pollution in Chinese Provinces[J]. Acta Ecologica Sinica,2017,37(8):2588-2599.
|
| [22] |
叶彬, 杨敏, 李方一, 等. 能源约束下安徽省产业结构优化目标与对策研究[J]. 华东经济管理,2017,31(3):21-27. doi: 10.3969/j.issn.1007-5097.2017.03.003
YE B, YANG M, LI F Y, et al. A study on targets and countermeasures of industrial structure optimization in Anhui Province under energy constraints[J]. East China Economic Management,2017,31(3):21-27. doi: 10.3969/j.issn.1007-5097.2017.03.003
|
| [23] |
任国平, 刘黎明, 付永虎, 等. 基于GWR模型的都市城郊村域农户生计资本空间差异分析: 以上海市青浦区为例[J]. 资源科学,2016,38(8):1594-1608.
REN G P, LIU L M, FU Y H, et al. Spatial differentiation of rural household livelihood capital in metropolitan suburbs based on GWR model: a case study of Qingpu District in Shanghai[J]. Resources Science,2016,38(8):1594-1608.
|
| [24] |
胡宇娜, 梅林, 魏建国. 基于GWR模型的中国区域旅行社业效率空间分异及动力机制分析[J]. 地理科学,2018,38(1):107-113.
HU Y N, MEI L, WEI J G. Spatial differentiation and dynamic mechanism of regional travel agency efficiency in China based on GWR model[J]. Scientia Geographica Sinica,2018,38(1):107-113.
|
| [25] |
杨秀汪, 李江龙, 郭小叶. 中国碳交易试点政策的碳减排效应如何: 基于合成控制法的实证研究[J]. 西安交通大学学报(社会科学版),2021,41(3):93-104.
YANG X W, LI J L, GUO X Y. The impact of carbon trading pilots on emission mitigation in China: empirical evidence from synthetic control method[J]. Journal of Xi'an Jiaotong University (Social Sciences Edition),2021,41(3):93-104.
|
| [26] |
廖祥, 杨鑫, 牛振生. 成渝城市群陆地碳排放时空变化及效应研究[J]. 环境科学与技术,2023,46(1):211-225.
LIAO X, YANG X, NIU Z S. Spatio-temporal changes and effects on terrestrial carbon emission in Chengdu-Chongqing urban agglomeration[J]. Environmental Science & Technology,2023,46(1):211-225.
|
| [27] |
范登龙, 黄毅祥, 蒲勇健, 等. 重庆市化石能源消耗的CO2排放及其峰值测算研究[J]. 西南大学学报(自然科学版),2017,39(6):179-186.
FAN D L, HUANG Y X, PU Y J, et al. CO2 emission from fossil energy consumption in Chongqing and prediction of its peak[J]. Journal of Southwest University (Natural Science Edition),2017,39(6):179-186.
|
| [28] |
於冉, 田思萌. 基于承载关系的合肥市土地利用碳排放效应分析[J]. 安徽农业大学学报,2016,43(6):939-945.
YU R, TIAN S M. An analysis of land use and carbon emission in Hefei City based on carrying relationship[J]. Journal of Anhui Agricultural University,2016,43(6):939-945.
|
| [29] |
杜海波, 魏伟, 张学渊, 等. 黄河流域能源消费碳排放时空格局演变及影响因素: 基于DMSP/OLS与NPP/VIIRS夜间灯光数据[J]. 地理研究,2021,40(7):2051-2065. doi: 10.11821/dlyj020200646
DU H B, WEI W, ZHANG X Y, et al. Spatio-temporal evolution and influencing factors of energy-related carbon emissions in the Yellow River Basin: based on the DMSP/OLS and NPP/VIIRS nighttime light data[J]. Geographical Research,2021,40(7):2051-2065. doi: 10.11821/dlyj020200646
|
| [30] |
余文梦, 张婷婷, 沈大军. 基于随机森林模型的我国县域碳排放强度格局与影响因素演进分析[J]. 中国环境科学,2022,42(6):2788-2798. doi: 10.3969/j.issn.1000-6923.2022.06.034
YU W M, ZHANG T T, SHEN D J. County-level spatial pattern and influencing factors evolution of carbon emission intensity in China: a random forest model analysis[J]. China Environmental Science,2022,42(6):2788-2798. ⊕ doi: 10.3969/j.issn.1000-6923.2022.06.034
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