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北京市减污降碳协同控制情景模拟和效应评估
摘要点击 1726  全文点击 1487  投稿时间:2022-04-29  修订日期:2022-07-01
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中文关键词  大气污染物  二氧化碳(CO2)  协同控制  情景模拟  效应评估  北京市
英文关键词  air pollutants  carbon dioxide(CO2)  coordinated control  scenario simulation  effects assessment  Beijing
作者单位E-mail
俞珊 北京市生态环境保护科学研究院, 北京 100037
国家城市环境污染控制工程技术研究中心, 北京 100037 
yushan@cee.cn 
张双 北京市生态环境保护科学研究院, 北京 100037
国家城市环境污染控制工程技术研究中心, 北京 100037 
 
张增杰 北京市生态环境保护科学研究院, 北京 100037
国家城市环境污染控制工程技术研究中心, 北京 100037 
zhangzengjie@cee.cn 
瞿艳芝 北京市生态环境保护科学研究院, 北京 100037
国家城市环境污染控制工程技术研究中心, 北京 100037 
 
刘桐珅 北京市生态环境保护科学研究院, 北京 100037
国家城市环境污染控制工程技术研究中心, 北京 100037 
 
中文摘要
      将能源、建筑、产业和交通作为减污降碳重点领域,设置了基准情景、政策情景和强化情景,以2020年为基准年,2035年为目标年,开展北京市大气污染物和CO2减排潜力测算,并构建了一种协同控制效应分级评估方法,对政策情景和强化情景下大气污染和CO2协同控制效应进行量化评估.结果表明,与基准情景相比,政策情景和强化情景下大气污染物减排率分别在11%~75%和12%~94%,CO2分别为41%和52%.优化机动车结构对于NOx、VOCs和CO2的减排贡献最大,政策情景下减排率分别达到74%、80%和31%,强化情景下分别达到68%、74%和22%;完成农村地区散煤清洁能源改造对SO2的减排贡献最大,政策和强化情景下分别达到47%和35%;提升新建建筑绿色化水平对PM10的减排贡献最大,政策和强化情景下分别达到79%和74%.优化出行结构和推动数字基础设施绿色发展的协同控制效应最佳;强化情景下,完成农村地区散煤清洁能源改造、优化机动车结构和推进制造业绿色升级的协同控制效应提升至较好.北京市应重点关注交通领域协同减排,提高绿色出行比例,推广新能源车和货物绿色运输;同时,随着终端能源消费电气化的推进,应通过扩大本地可再生能源电力生产和增加外调绿电输送能力来提高绿电占比,以提升减污降碳协同控制效应.
英文摘要
      Focused on the key areas of energy, buildings, industry, and transportation, with 2020 as the base year and 2035 as the target year, we respectively designed the baseline scenario, policy scenario, and enhanced scenario, calculated the emission reduction potential of air pollutants and CO2 of Beijing, and constructed an assessment method of co-control effect gradation index to evaluate the co-control effect of air pollutants and CO2 in the policy scenario and enhanced scenario. The results showed that in the policy scenario and enhanced scenario, the reduction rates of air pollutants emissions will reach 11%-75% and 12%-94%, respectively, and reduction rates of CO2 emissions will reach 41% and 52%, respectively, compared with those from the baseline scenario. Optimizing vehicle structure had the largest contribution to the emission reduction of NOx, VOCs, and CO2, and the emission reduction rates will reach 74%, 80%, and 31% in the policy scenario and 68%, 74%, and 22% in the enhanced scenario, respectively. Replacing coal-fired with clean energy in rural areas had the largest contribution to the emission reduction of SO2; the emission reduction rates will reach 47% and 35% in the policy scenario and enhanced scenario, respectively. Improving the green level of new buildings had the largest contribution to the emission reduction of PM10; the emission reduction rates will reach 79% and 74% in the policy scenario and enhanced scenario, respectively. Optimizing travel structure and promoting green development of digital infrastructure had the best co-control effect. The co-control effect of replacing coal-fired with clean energy in rural areas, optimizing vehicle structure, and promoting green upgrading of the manufacturing industry will be improved to a better status in the enhanced scenario. More attention should be paid to improving the proportion of green trips, implementing the promotion of new energy vehicles, and the green transportation of goods to reduce emissions in the field of transportation. At the same time, with the continuous improvement in electrification level in the end energy consumption structure, the proportion of green electricity should be increased by expanding local renewable energy power production and increasing external green electricity transmission capacity, to enhance the co-control effect of pollution and carbon reduction.

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