基于碳排放模拟的控规单元空间容量优化方法与策略——以天津市为例  

Optimization Methods and Strategies for Spatial Capacity in Regulatory Planning Units Based on Carbon Emission Simulation:A Case Study of Tianjin

在线阅读下载全文

作  者:张丽莎 张赫[1,2] 王雨涵 王明竹 邓洪杰 ZHANG Lisha;ZHANG He;WANG Yuhan;WANG Mingzhu;DENG Hongjie

机构地区:[1]天津大学建筑学院 [2]天津大学科研院 [3]哥鲁科(上海)建筑规划设计有限公司 [4]成都龙泉山城市森林公园管委会

出  处:《规划师》2025年第3期42-49,共8页Planners

基  金:国家自然科学基金项目(52208073);国家重点研发计划项目(2023YFC3807701);天津市研究生科研创新项目(2022BKY089)。

摘  要:建筑碳排放是城市建设过程中最主要的碳排放来源,大量研究表明,合理的空间规划手段可以有效降低建筑碳排放强度。但既有研究主要以宏观城市尺度与微观建筑、地块等尺度为主,对中观控规单元尺度的关注不足;在优化路径方面,当前以指标约束为主的低碳建设方法难以兼顾上级规划要求和整体降碳目标。因此,通过建筑碳排放模拟,理清各主要空间要素对控规单元碳排放的影响机理,在此基础上结合多目标规划模型算法,以天津市的某控规单元为例,综合考虑降碳目标与容量要求,最终得到控规单元层级整体方案空间容量低碳优化策略。Building carbon emissions represent the primary source of carbon emissions in the process of urban construction.Numerous studies have demonstrated that reasonable spatial planning measures can effectively reduce the intensity of building carbon emissions.However,existing theoretical research primarily focuses on the macro-urban scale and micro-scales such as individual buildings and land parcels,with relatively scant attention paid to the meso-scale of regulatory planning units.Additionally,in terms of optimization pathways,current low-carbon construction methods constrained by indicators struggle to balance superior planning requirements with overall carbon reduction goals.By analyzing the influence mechanisms of key spatial elements on the carbon emissions of regulatory planning units through building carbon emission simulations,multi-objective programming model algorithms are incorporated.Consequently,a low-carbon spatial capacity optimization strategy for regulatory planning units is developed,balancing carbon reduction targets with spatial capacity demands in a comprehensive manner.

关 键 词:控规单元 低碳城市 建筑能耗模拟 天津市 

分 类 号:TU984.113[建筑科学—城市规划与设计] X503.5[环境科学与工程—环境工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象