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高校碳排放核算与分析:以北京A高校为例
摘要点击 1961  全文点击 138  投稿时间:2023-05-03  修订日期:2023-07-04
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中文关键词  高校  排放因子法  理论计算法  碳排放计算  碳吸收  不确定性
英文关键词  universities  emission factor method  theoretical calculation method  carbon emission calculation  carbon sequestration  uncertainty
作者单位E-mail
曹睿 北京林业大学环境科学与工程学院, 水体污染源控制技术北京市重点实验室, 北京 100083
北京林业大学环境科学与工程学院, 污染水体源控与生态修复技术北京高校工程研究中心, 北京 100083 
1172902074@qq.com 
封莉 北京林业大学环境科学与工程学院, 水体污染源控制技术北京市重点实验室, 北京 100083
北京林业大学环境科学与工程学院, 污染水体源控与生态修复技术北京高校工程研究中心, 北京 100083 
 
张立秋 北京林业大学环境科学与工程学院, 水体污染源控制技术北京市重点实验室, 北京 100083
北京林业大学环境科学与工程学院, 污染水体源控与生态修复技术北京高校工程研究中心, 北京 100083 
zhangliqiu@163.com 
中文摘要
      在双碳背景下,我国各行业正积极核算自身碳排放,以有效应对气候变化,大学校园也应积极参与其中.以北京A高校为例,采用排放因子法和理论计算法核算了2021年其校园碳排放量.结果表明,A高校净碳排放量(以CO2计,下同)为43 249.04 t,人均碳排放量为1.52 t.电力、通勤与差旅、热力、天然气和食物是碳排放的主要来源.热力和天然气的碳排放与月份密切相关,而电力碳排放在不同的功能区和月份都有所不同.食物的碳排放与饮食结构有关,而污水和垃圾处理的碳排放则与处理过程有关.使用蒙特卡洛模拟法讨论了碳排放清单的不确定性,发现碳排放总量的不确定性在-13.61%~26.08%之间.尽管计算结果相对科学可靠,但通勤和差旅、电力、天然气和食品是主要的不确定性来源.总体来说,研究结果为校园和其他复杂系统的碳排放核算和不确定性计算提供了参考.
英文摘要
      In the context of carbon peaking and carbon neutrality, various industries in China are actively accounting for their own carbon emissions to effectively respond to climate change, an effort that university campuses should also actively participate in. Therefore, Beijing A University served as an example to investigate carbon emissions using emission factors and theoretical calculation methods in 2021. The results showed that the net carbon emission of university A was 43 249.04 t (calculated as CO2, same below), and the per capita carbon emission was 1.52 t. Electricity, commuting and travel, heat, natural gas, and food were the main sources of carbon emissions. Carbon emissions from heat and natural gas were closely related to the month, whereas carbon emissions from electricity varied by functional area and month. Carbon emissions from food were related to the diet structure, whereas carbon emissions from sewage and waste disposal were related to the treatment process. Monte Carlo was used to simulate and discuss the uncertainty of carbon emission inventories, with the findings suggesting that the uncertainty of total carbon emissions ranged from -13.61% to 26.08%. Although the calculations were relatively scientifically reliable, commuting and travel, electricity, natural gas, and food were the main sources of uncertainty. Overall, the results provide a reference for carbon emission accounting and uncertainty calculations for campuses and other complex systems.

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