山地城市扩张与碳排放响应——以重庆主城为例

谢玲; 黄玉航; 宋知劲; 陈展图; 刘素红

PDF(3754 KB)

中国环境科学 ›› 2026, Vol. 46 ›› Issue (2) : 1099-1113.

碳排放控制

山地城市扩张与碳排放响应——以重庆主城为例

谢玲^1,2, 黄玉航², 宋知劲², 陈展图^1,2, 刘素红³

作者信息 +

Mountain city expansion and carbon emission response—A case study of the main urban area of Chongqing

XIE Ling^1,2, HUANG Yu-hang², SONG Zhi-jin², CHEN Zhan-tu^1,2, LIU Su-hong³

Author information +

文章历史 +

摘要

基于重庆市主城区的土地利用数据、自然社会经济数据和“碳排放”数据,利用土地利用转移矩阵和斑块生成土地利用模拟(PLUS)模型,分析重庆市主城区2000~2020年间城市扩张的空间演化特征,模拟2030年自然发展情景、城市发展情景、生态保护情景的城市扩张,基于广义可加模型(GAM)解析2019~2022年研究区土地利用变化与碳排放响应关系,并计算了3种情景下碳排放总量.①2000~2020年,研究区耕地减少了928.82km²,建设用地增加了858.30km²,大量的耕地转入了建设用地之中,水域、林地、草地处于一定程度上的动态变化之中.②城市扩张受自然和社会经济因素的综合作用,主要驱动因素有高程、距水域距离和距1级道路距离,外在政策驱动因素对城市扩张同样具有重要影响.③2020~2030年重庆市主城区将继续处于快速城市化进程中,城市扩张方向以东向西向为主,林地、草地的扩张方向与城市扩张相反.m土地利用结构变化对碳排放的影响多呈现非线性关系,并可能存在潜在的阈值区,林地、水域、耕地变化与碳排放呈非线性,草地和建设用地变化与碳排放呈线性关系.n基于研究区2030年3种情景土地利用结构,估算2030年重庆主城区土地利用结构碳排分别为5929.95, 6206.77, 5820.41万t C/a.

Abstract

Based on the land use data, natural socio-economic data and carbon emission data of the main urban area of Chongqing, the land use transfer matrix and the PLUS (Patching-generating Land Use Simulation) model were used to analyze the spatial evolution characteristics of urban expansion in the main urban area of Chongqing from 2000 to 2020. The development scenarios of the natural state, urban expansion and ecological protection in 2030 were simulated under the influence of endogenous driving factors. The response relationship between land use change and carbon emissions in the study area from 2019 to 2022 was analyzed based on the Generalized Additive Model (GAM), and the total carbon emissions under the three scenarios were calculated. From 2000 to 2020, the cultivated land in the study area decreased by 928.82km², while the construction land increased by 858.30km². A large amount of cultivated land was transferred to the construction land, and water areas, forest land and grassland underwent in a certain degree of dynamic change. Urban expansion is influenced by a combination of natural and socio-economic factors, with the main driving factors including elevation, distance from water areas and distance from Grade 1roads. External policy-driven factors also have a significant impact on urban expansion. From 2020 to 2030, the main urban area of Chongqing will continue to experience in a rapid urbanization process. The direction of urban expansion will mainly be eastward and westward, while the expansion direction of forest land and grassland will be opposite to that of urban expansion. The impact of changes in land use structure on carbon emissions is mostly nonlinear, and there may be potential threshold areas. Forest land, water and cultivated land show non-linear relationships, while grassland and construction land show linear relationships. Based on the land use structure of three scenarios in the study area in 2030, it is estimated that the carbon emissions of the land use structure in study area of Chongqing in 2030 will be 59.2995million tons of C/a, 62.0677million tons of C/a, and 58.2041million tons of C/a respectively.

导出引用

谢玲, 黄玉航, 宋知劲, 陈展图, 刘素红. 山地城市扩张与碳排放响应——以重庆主城为例[J]. 中国环境科学. 2026, 46(2): 1099-1113

XIE Ling, HUANG Yu-hang, SONG Zhi-jin, CHEN Zhan-tu, LIU Su-hong. Mountain city expansion and carbon emission response—A case study of the main urban area of Chongqing[J]. China Environmental Science. 2026, 46(2): 1099-1113

中图分类号： X171.1

参考文献

[1] 李宇,孟丹,叶海鹏,等.俄罗斯典型城市扩张时空格局与驱动机制——基于遥感决策融合与多元离散回归模型[J].地理研究, 2021,40(11):2967-2985. Li Y, Meng D, Ye H P, et al. Spatiotemporal pattern and driving forces of typical Russian cities: Based on remote sensing decision fusion and multiple discrete regression model [J]. Geographical Research, 2021, 40(11):2967-2985.
[2] 方创琳.改革开放30年来中国的城市化与城镇发展[J].经济地理, 2009,29(1):19-25. Fang C L. The urbanization and urban development in China after the reform and opening-up [J]. Economic Geography, 2009,29(1): 19-25.
[3] Ghosh S, Dinda S, Das Chatterjee N, et al. Spatial-explicit carbon emission-sequestration balance estimation and evaluation of emission susceptible zones in an Eastern Himalayan city using Pressure- Sensitivity-Resilience framework: An approach towards achieving low carbon cities [J]. Journal of Cleaner Production, 2022:336,330417.
[4] 张涛,王光辉,郑利娟,等.近30年中国城市群城市建设用地扩张遥感监测与时空变化特征分析[J].遥感学报, 2024,28(11):2838-2849. Zhang T, Wang G H, Zheng L J et al. Remote sensing monitoring and spatiotemporal characteristic analysis of urban construction land expansion in the urban agglomerations of China in the past 30years [J]. National Remote Sensing Bulletin, 2024,28(11):2838-2849.
[5] 张敏,杨励雅,胡卓玮,等.长江经济带城市扩张的时空分异特征及影响机制[J].地理学报, 2024,79(2):439-461. Zhang M, Yang L Y, Hu Z W, et al. Spatiotemporal differentiation and influencing mechanism of urban expansion in the Yangtze River Economic Belt, China [J]. Acta Geographica Sinica,2024,79(2):439- 461.
[6] Wang Z, Lv C. Urban land expansion and its driving factors of mountain cities in China during 1990-2015[J]. Journal of Geographical Sciences, 2018,28(8):1152-1166.
[7] 王亚楠,苏明明,董航宇.中国资源型与非资源型城市扩张驱动机制差异[J].资源科学, 2024,46(6):1226-1237. Wang Y N, Su M M, Dong H Y. Differences in the driving mechanisms of urban spatial expansion between resource-based and non-resource-based cities in China [J]. Resources Science, 2024,46(6): 1226-1237.
[8] 欧阳晓,朱翔,贺清云.城市群城市用地扩张时空特征及驱动机制研究:以长株潭城市群为例[J].长江流域资源与环境, 2020,29(6): 1298-1309. Ou Y X, Zhu X, He Q Y. Study of spatio-temporal pattern and driving mechanism of urban land expansion in urban agglomeration: A case study of the Changsha-Zhuzhou-Xiangtan urban agglomeration [J]. Resources and Environment in the Yangtze Basin, 2020,29(6):1298-1309.
[9] Siabi E K, Kabo-Bah A T, Anornu G, et al. Future land use simulation modeling for sustainable urban development under the shared socioeconomic pathways in West African megacities: Insights from Greater Accra Region [J]. Journal of Environmental Management, 2025,376:124300.
[10] 汪韬阳,张过,李沛然,等.基于DMSP/OLS夜光遥感影像的城市扩张政策驱动因素分析[J].测绘学报, 2018,47(11):1466-1473. Wang T Y, Zhang G, Li P R et al. Analysis on the driving factors of urban expansion policy based on DMSP/OLS remote sensing image [J]. Acta Geodaetica et Cartographica Sinica, 2018,47(11):1466-1473.
[11] 高彬嫔,吴映梅,李琛,等.滇中城市群城市扩张动态演变对生态系统健康的影响[J/OL].环境科学, 1-15[2025-04-28]. https://doi. org/10.13227/j.hjkx.202410275. Gao B P, Wu Y M, Li C et al. Effects of urban sprawl dynamics on ecosystem health in the central Yunnan urban agglomeration [J/OL]. Environmental Science [2025-04-28].https://doi.org/10.13227/j.hjkx.202410275.
[12] 刘希朝,李效顺,陈鑫,等.江苏省城镇化与生态环境耦合测度及空间冲突诊断[J].农业工程学报, 2023,39(13):238-248. Liu X C, Li X S, Chen X et al. Coupling measurement and spatial conflict diagnosis between urbanization andecological environment in Jiangsu Province of China [J]. Transactions of the Chinese Society of Agricultura, 2023,39(13):238-248.
[13] Zhang J, Fu M, Wang L, et al. Impact of urban shrinkage on pollution reduction and carbon mitigation synergy: Spatial heterogeneity and interaction effects in Chinese Cities [J]. Land, 2025,14(3):537.
[14] Xiong Q, Wu X, Yu C. Characteristics of spatial and temporal evolution and coupling relationships between urbanization and atmospheric particulate matter in the Qianzhong urban agglomeration [J]. Human and Ecological Risk Assessment: An International Journal, 2025,31(3/4):605-634.
[15] Das A, Sahoo S N. Impact of land use and climate change on urban flooding: A case study of Bhubaneswar city in India [J]. Natural Hazards, 2025,121(7):8655-8674.
[16] She Z, Liu Z, Cai H, et al. Disproportionate increase of flood-exposed population in Chinese cities under urban expansion and climate variation [J]. Ecological Indicators, 2025,172:113314.
[17] 杨浩,王旭峰,张松林,等.甘肃省城市热岛效应变化特征及其对城市扩张的响应[J].遥感技术与应用, 2025,40(1):110-121. Yao H, Wang X F, Zhang S L et al. Change characteristics of urban heat island effect and its response to urban expansion in Gansu Province [J]. Remote Sensing Technology and Application, 2025,40(1): 110-121.
[18] 侯亚丽,匡文慧,窦银银.全球超大城市空间扩张及分形特征研究[J].地理学报, 2022,77(11):2687-2702. Hou Y L, Kaung WH, Dou Y Y. Analysis of urban expansion and fractal features in global 33 megacities from 2000~2020[J]. Acta Geographica Sinica, 2022,77(11):2687-2702.
[19] Jiao L M, Liu J F, Xu G, et al. Proximity expansion index: An improved approach to characterize evolution process of urban expansion [J]. Computers, Environment and Urban Systems, 2018,70: 102-112.
[20] 陈展图,冯冰,肖丽梅,等.广西北部湾经济区城市群空间扩展研究——基于夜间灯光数据[J].地域研究与开发, 2024,43(3):77-82. Chen Z T, Feng B, Xiao L M et al. Spatial expansion of urban agglomerations in Guangxi Beibu Gulf Economic Zone based on night-time lighting data [J]. Areal Research and Development, 2024, 43(3):77-82.
[21] 曹冰昱,杨永崇,钟飞,等.空间规划背景下的城镇扩张模拟研究[J].测绘科学, 2021,46(5):189-195,202. Cao B Y, Yang Y C, Zhong F et al. Simulation on urban expansion under the background of spatial planning [J]. Science of Surveying and Mapping, 2021,46(5):189-195,202.
[22] 付涛,易宏,吴俐民,等.适宜性评价与模型模拟的三类空间划定研究[J].测绘科学, 2021,46(6):164-173. Fu T, Yi H, Wu L M et al. Study on three types of space delimitation for suitability evaluation and model simulation [J]. Science of Surveying and Mapping, 2021,46(6):164-173.
[23] 张亚飞,廖和平,李义龙.基于反规划与FLUS模型的城市增长边界划定研究——以重庆市渝北区为例[J].长江流域资源与环境, 2019, 28(4):757-767. Zhang Y F, Liao H P, Li Y L. Delimitation of urban growth boundary based on anti-planning and FLUS model: A case study of Yubei District, Chongqing, China [J]. Resources and Environment in the Yangtze Basin, 2019,28(4):757-767.
[24] 李启珍,胡希军,韦宝婧,等.长沙市绿色空间与城市扩张耦合关系研究[J].经济地理, 2022,42(11):87-94. Li Q L, Hu X J, Wei B J et al. Coupling relationship between green space and urban expansion in Changsha [J]. Economic Geography, 2022,42(11):87-94.
[25] 张敏,杨励雅,胡卓玮,等.长江经济带城市扩张的时空分异特征及影响机制[J].地理学报, 2024,79(2):439-461. Zhang M, Yang L Y, Hu Z W et al. Spatiotemporal differentiation and influencing mechanism of urban expansion in the Yangtze River Economic Belt, China [J]. Acta Geographica Sinica, 2024,79(2):439- 461.
[26] 刘奎,王健,康翔,等.基于空间集散效应的中国城市空间扩张驱动机制——以中国273个城市为例[J].城市发展研究, 2022,29(6):15-24. Liu K, Wang J, Kang X et al. Research on the driving mechanism of China’s urban spatial expansion based on the spatial aggregation—apread effects [J]. Urban Development Studies, 2022,29(6):15-24.
[27] He C, Liu Z, Gou S, et al. Detecting global urban expansion over the last three decades using a fully convolutional network [J]. Environmental Research Letters, 2018,14(3),034008.
[28] Alice C, Yann L, Harold L.What drives land take and urban land expansion? A systematic review [J]. Land Use Policy, 2018,79:339- 349.
[29] Yussif K, Dompreh E B, Gasparatos A. Sustainability of urban expansion in Africa: a systematic literature review using the Drivers-Pressures-State-Impact-Responses (DPSIR) framework [J]. Sustainability Science, 2023,18(3):1459-1479.
[30] Wu Y, Li C, Shi K F, et al. Exploring the effect of urban sprawl on carbon dioxide emissions: An urban sprawl model analysis from remotely sensed nighttime light data [J]. Environmental Impact Assessment Review, 2022,93:106731.
[31] Cheng Z, Hu X. The effects of urbanization and urban sprawl on CO₂ emissions in China [J]. Environment, Development and Sustainability, 2023,25(2):1792-1808.
[32] Liu X, Liang X, Li X, et al. A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects [J]. Landscape and Urban Planning, 2017,168:94-116.
[33] 王端睿,毛德华,王宗明,等.东北地区土地覆被格局变化模拟:基于CLUE-S和Markov-CA模型的对比分析[J].地理科学, 2024, 44(2):329-339. Wang D R, Mao D H, Wang Z M et al. Simulation of land cover pattern change in Northeast China: A comparative analysis based on CLUE-S and Markov-CA models [J]. Geographical Science, 2024,44(2):329-339.
[34] Wen H, Yu H, Nghiem X H. Impact of urban sprawl on carbon emission efficiency: Evidence from China [J]. Urban Climate, 2024,55: 101986.
[35] Wang Z, Zhu C. Does urban sprawl lead to carbon emission growth? — Empirical evidence based on the perspective of local land transfer in China [J]. Journal of Cleaner Production, 2024,455:142319.
[36] 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.
[37] 张娜,孙芳城,胡钰苓,等.长江经济带三大城市群土地利用碳排放的区域差异及空间收敛性[J].环境科学, 2024,45(8):4656-4669. Zhang N, Sun F C, Hu Y L et al. Regional difference and spatial convergence of land use carbon emissions in three urban agglomerations of Yangtze River Economic Belt [J]. Environmental Science, 2024,45(8):4656-4669.
[38] 田一豆,赵先超.基于Markov-PLUS模型的长株潭城市群建设用地扩张模拟及碳排放响应分析[J].生态学报, 2024,44(1):129-142. Tian Y D, Zhao X C. Simulation of construction land expansion and carbon emission response analysis of Changsha-Zhuzhou-Xiangtan Urban Agglomeration based on Markov-PLUS model [J]. Acta Ecologica Sinica, 2024,44(1):129-142.
[39] 苏王新,孙然好.中国典型城市群城镇化碳排放驱动因子[J].生态学报, 2018,38(6):1975-1983. Su W X, Sun R H. Carbon emissions from urbanization in typical urban agglomerations of China:Spatial patterns and drivers [J]. Acta Ecologica Sinica, 2018,38(6):1975-1983.
[40] 潘浩之,施睿,蔡子攀,等.基于城市土地利用碳排放源识别的国土空间规划支撑研究——以南京市为例[J].现代城市研究, 2024,(1): 1-7,15. Pao H Z, Shi R, Cai Z P et al. Study on supporting territorial spatial panning through identification carbon emission sources in urban land use:A case study of Nanjing [J]. Modern Urban Research, 2024, (1):1-7,15.
[41] 林彤,杨木壮,吴大放,等.基于InVEST-PLUS模型的碳储量空间关联性及预测——以广东省为例[J].中国环境科学, 2022,42(10): 4827-4839. Lin D, Yang M Z, Wu D F et al. Spatial correlation and prediction of land use carbon storage based on the InVEST-PLUS model-A case study in Guangdong Province [J]. China Environmental Science, 2022, 42(10):4827-4839.
[42] 许澳康,胡梦珺,石晶,等.石羊河流域生态系统碳储量时空变化及多情景模拟[J].中国环境科学, 2024,44(6):3365-3375. Xu A K, Hu M J, Shi J, et al. Spatial and temporal variability of ecosystem carbon storages and multi-scenario simulation in the Shiyang River basin [J]. China Environmental Science, 2022,42(10): 4827-4839.
[43] 邓灵颖,李红波.武汉城市圈土地利用碳排放时空演变及驱动因素[J].水土保持研究, 2024,31(1):345-353. Deng L Y, Li H B. Spatial and temporal evolution of land use carbon emissions and analysis of driving factors in Wuhan Metropolitan Area [J]. Research of Soil and Water Conservation, 2024,31(1):345-353.
[44] 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. 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.
[45] Guan Q. Understanding spatio-temporal patterns of land use/land cover change under urbanization in Wuhan, China, 2000~2019[J]. Remote Sensing, 2021,13(16),3331.
[46] Liang X, Guan Q, Clarke K C, et al. Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China [J]. Computers, Environment and Urban Systems, 2021,85:101569.
[47] Xie L, Wang H, Liu S. The ecosystem service values simulation and driving force analysis based on land use/land cover: A case study in inland rivers in arid areas of the Aksu River Basin, China [J]. Ecological Indicators, 2022,138:108828.
[48] Hastie T J, Tibshirani R J. Generalized additive models [M]. London:Chapmanand Hall, 1990:89-90.
[49] Mclean M W, Hooker G, Staicu A M, et al. Functional generalized additive models [J]. Journal of Computational and Graphical Statistics, 2014,23(1):249-269.
[50] 邹欣怡,赵伟,蒲海霞,等.重庆市南岸区城市边界扩张及生态环境效应研究[J].水土保持研究, 2019,26(4):252-258,264. Zou X Y, Zhao W, Pu H X et al. Study on urban boundary expansion and ecological environment effect in Nanan District of Chongqing City [J]. Research of Soil and Water Conservation, 2019,26(4):252- 258,264.
[51] 重庆市“四山”地区开发建设管制规定[Z].重庆市人民政府公报, 2007,(8):7-8. Regulations on the development and construction control of the "Four Mountains" area in Chongqing municipality [Z]. Bulletin of the Chongqing Municipal People's Government, 2007,(8):7-8.
[52] 朱康文,李月臣,周梦甜.基于CLUE-S模型的重庆市主城区土地利用情景模拟[J].长江流域资源与环境, 2015,24(5):789-797. Zhu K W, Li Y C, Zhou M T. Land use scenario simulation of the main city of Chongqing based on the CLUE-S model [J]. Resources and Environment in the Yangtze Basin, 2015,24(5):789-797.
[53] 刘天林,刘明皓,荆磊,等.一种顾及驱动因子重要性的双约束RF-Patch-CA城市扩张模拟方法[J].地理与地理信息科学, 2021, 37(2):63-70. Liu T L,Liu M H, Jing L et al. An urban expansion simulation method of dual constrained RF-Patch-CA considering the importance of driving factors [J]. Geography and Geo-Information Science, 2021, 37(2):63-70.
[54] 蒋金亮,周亮,吴文佳,等.长江沿岸中心城市土地扩张时空演化特征——以宁汉渝3市为例[J].长江流域资源与环境, 2015,24(9): 1528-1536. Jiang J L, Zhou L, Wu W J et al. A Comparative study on spatiotemporal characteristics of urban expansion for the central cities along the Yangtze River——A case study of Nanjing, Wuhan and Chongqing [J]. Resources and Environment in the Yangtze Basin, 2015,24(9):1528-1536.
[55] 孙伟,刘崇刚,王苏宁.基于生态约束的城市开发边界模拟研究——以南京为例[J].自然资源学报, 2021,36(11):2913-2925. Sun W, Liu C G, Wang S N. Simulation research of urban development boundary based on ecological constraints: a case study of Nanjing [J]. Journal of Natural Resources,2021,36(11):2913-2925.
[56] 连宏萍,何琳,章文光.中国城市建设用地扩张的驱动因素及其异质性研究——基于35个大中城市面板数据的实证分析[J].北京师范大学学报(社会科学版), 2021,(3):46-57. Lian H P, He L, Zhang W G. Driving factors and divergency of urban construction land expansion in China: An empirical analysis based on panel data of 35 large and medium-sized cities [J]. Journal of Beijing Normal University (Social Sciences), 2021,(3):46-57.
[57] 马歆,和舒敏,黄婷婷,等.城市用地扩张的时空格局特征及驱动因素分析——以中原城市群为例[J].生态经济, 2020,36(3):105- 111,167. Ma Q, He S M, Huang T T et al. Analysis of spatial-temporal pattern characteristics and driving factors of urban land expansion: Taking central plains city cluster as an example [J]. Ecological Economy, 2020,36(3):105-111,167.
[58] 黄方.重庆市土地利用空间格局分析及其预测模拟[D].重庆:重庆大学, 2013. Huang F. Analysis and simulation of land use spatial pattern of Chongqing municipality [D]. Chongqing: Chongqing University, 2013.