DISES: Multi-scale modeling of interactions between climate change, air quality, and social inequalities
DISES: Multi-scale modeling of interactions between climate change, air quality, and social inequalities
批准号:
2420344
负责人:
Mark Budolfson
金额:
$151.33万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-10-01 至 2026-04-30
中文摘要
空气污染物和温室气体有着共同的排放源,包括通过燃烧化石燃料(煤、石油、天然气)。因此,旨在减少温室气体的气候政策将产生减少空气污染的“共同效益”,空气污染每年造成全球数百万人死亡。然而,人们对空气质量的这些共同效益如何在人群中分布以及这种分布如何取决于主要气候政策选项之间的选择知之甚少。例如,与侧重于发电厂的政策相比,交通部门的简化可能会对生活在主要道路附近的人口产生非常不同的影响-往往是不成比例的少数民族和社会经济地位较低的人。目前还没有系统的研究对这些关系进行量化,也不清楚采取何种气候政策最能实现社会的健康和公平目标。该项目将通过两个步骤调查这些复杂的社会环境动态。首先,将估计与空气质量有关的不同气候政策的共同效益,沿着这些政策将如何不同地影响社会经济亚群体的健康。然后,这些信息将用于研究如何使用包括更广泛系统的其他方面的模型来优化气候政策决策,例如经济和人口变化以及气候变化本身的影响。人类系统和大气系统是密不可分的。人类产生排放物,排放物改变大气,大气反过来影响社会,例如通过暴露于空气或水污染,风暴和野火造成的财产损失,以及对农业产量和生态系统的影响。人为排放水平可以通过政策选择来改变,而政策选择本身就是社会和伦理子系统之间相互作用的复杂产物。该项目将模拟这个高度集成的系统的动态,重点是气候政策,空气质量和公平之间的反馈。气候政策的空气质量“共同效益”很重要,因为它们具有政策相关性,因为这些效益很大,开始立即发生,并在当地发生。这些影响在空间或时间上在各区域之间并不一致,因此确定气候行动如何缓解或加剧现有的空气污染暴露不平等是很重要的。这些关系将通过新的空气质量模型和改进领先的成本效益气候政策模型来研究。目标是:[1]进行多尺度建模,以确定空气质量将如何因不同的气候政策而变化,以及这些变化将如何不同地影响城市,地区和国家内的社会经济亚群; [2]将新估计的关系纳入领先的气候政策模型; [3]分析相对于社会可能认可的不同目标的最佳政策。这些目标有许多更广泛的影响,包括减少收入不平等,减轻健康差距,确保国家之间的公平负担分担,以及代际正义。这个奖项反映了NSF的法定使命,并已被认为是值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估的支持。
英文摘要
Air pollutants and greenhouse gases share emission sources, including through the combustion of fossil fuels (coal, oil, natural gas). Therefore, climate policies aimed at reducing greenhouse gases will produce the ‘co-benefit’ of also reducing air pollution, which is responsible for millions of deaths per year globally. However, little is known about how these co-benefits in air quality are likely to be distributed across populations, and how this distribution depends on choices between leading climate policy options. As one example, electrifying the transport sector will likely have much different implications for populations living near major roads – often disproportionately minorities and people of lower socioeconomic status – compared to a policy focusing on power plants. No systematic research has yet quantified these relationships and it is unclear which ways of pursuing climate policy will best achieve society’s health and equity objectives. This project will investigate these complex socio-environmental dynamics through a two-step process. First, the co-benefits of different climate policies as related to air quality will be estimated, along with how those policies will differentially impact health across socioeconomic subpopulations. Then that information will be used to examine how climate policy decisions may be optimized using models that include other aspects of the broader system, such as economic and demographic change, as well as the impacts of climate change itself. The human system and the atmospheric system are inextricably linked. Humans produce emissions, emissions alter the atmosphere, and the atmosphere in turn affects society, for example through exposure to air or water pollution, property damage from storms and wildfires, and impacts on agricultural yields and ecosystems. The level of anthropogenic emissions is modifiable through policy choices, which are themselves a complex output of interactions between social and ethical subsystems. This project will model the dynamics of this highly integrated system, with a focus on feedbacks between climate policy, air quality, and equity. The air quality ‘co-benefits’ of climate policy are important because of their policy relevance, given that these benefits are large, begin immediately, and occur locally. These impacts will not be uniform across regions in space or time, and so it is important to determine how climate action might alleviate or exacerbate existing inequalities in air pollution exposure. These relationships will be examined through novel air quality modeling and improvements to leading cost-benefit climate policy models. The goals are to : [1] Conduct multi-scale modeling to determine how air quality will change as a result of different climate policies, and how those changes will differentially impact socioeconomic subpopulations within cities, regions and countries; [2] Incorporate the newly estimated relationships into leading climate policy models; [3] Analyze optimal policy relative to different objectives that society might endorse. These objectives have numerous broader impacts that include reducing income inequality, alleviating health disparities, ensuring equitable burden sharing between nations, and intergenerational justice.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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DISES: Multi-scale modeling of interactions between climate change, air quality, and social inequalities
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批准号:2108984
-
项目类别:Standard Grant
-
资助金额:$151.33万
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财政年份:2021
-
负责人:Mark Budolfson
-
依托单位:
国内基金
海外基金
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