基于GIS的热映射和预测方法,以脱碳化基于金属的住宅供暖系统:一个城市级案例研究
Daniel Maestre-Cambronel1, James Cotton1, Keena Trowell1
1Mechanical Engineering Department, McMaster University, 1280 Main Street West, Hamilton L8S 4L8, Ontario, Canada.
Waste management (New York, N.Y.)
|February 2, 2026
概括
这项研究引入了一种新的方法,使用城市废物中的废金属来为家庭产生清洁的热量. 这种方法可以显著减少住宅二氧化碳排放,并支持社区能源规划.
科学领域:
- 环境工程 环境工程
- 材料科学 材料科学 材料科学
- 能源系统 能源系统
背景情况:
- 住宅供暖是温室气体排放的主要来源,天然气是主要燃料.
- 住宅供暖脱碳的一个重要障碍是缺乏可行的技术来取代天然气.
- 为了实现有效的清洁能源转型,需要量化社区一级的能源资源.
研究的目的:
- 开发一种方法来量化社区资源的能源价值,用于住宅供暖.
- 介绍一个利用废金属用于气和热量生产的季节性储能模型.
- 评估使用城市固体废物的可行性,以产生清洁的热量.
主要方法:
- 在城市层面上对城市固体废物中合适的金属库存进行地理空间量化.
- 整合开源数据和机器学习用于废物产生预测.
- 基于金属-水反应的季节性储能模型的开发,用于按需生产热量和气.
主要成果:
- 在安大略省的汉密尔顿,从2021年到2050年,每年可以产生10-14.6千兆瓦时的清洁热量.
- 这种清洁的热量生产意味着每年减少2.9千的空间加热二氧化碳排放量.
- 一个优化的梯度增强机器学习模型准确地预测了废物数据,捕获了86%的变化.
结论:
- 开发的方法为社区能源规划和脱碳提供了一种可重复的方法.
- 使用社区废金属为可持续的住宅供暖解决方案提供了一个可行的途径.
- 这种创新模式支持住宅部门摆脱化石燃料的过渡.
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