Health effects of decarbonization (HEALED): Understanding key determinants for health co-benefits and co-harms

脱碳对健康的影响 (HEALED)：了解健康协同效益和协同危害的关键决定因素

• 批准号: 2423254
• 负责人: Wei Peng
• 金额: $ 39.95万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2423254&HistoricalAwards=false
• 关键词: Health; effects; decarbonization; HEALED; Understanding

Tangible human health co-benefits can motivate stronger support for climate policy. For example, decarbonizing the energy system can produce sizable health co-benefits by reducing co-emitted air pollutants. However, assessing near-term decarbonization strategies with health considerations faces two key analytical challenges: (i) unintended health co-harms from some carbon mitigation strategies; for instance, large-scale bioenergy production can drive up food prices, which leads to nutrition-related health co-harms, and (ii) deep uncertainties about the future, such as socioeconomic patterns, technology costs, and market factors. The objectives of this project are: (i) to improve the quantitative understanding of key factors and processes that determine the magnitude and distribution of health outcomes from decarbonization, and (ii) to identify features of decarbonization strategies that are most likely to yield robust net health benefits given deep future uncertainties.The investigators hypothesize that while health co-benefits and co-harms are both affected by local technology choices (e.g., electricity generation technologies and vehicle types) and socioeconomic factors (e.g., income growth and population aging), the health co-harms are further determined by complex interactions across regions and sectors, such as inter-regional trade of electricity, biofuel, and food. With a focus on the United States, the investigators will test the hypothesis by: (i) developing an integrated energy-food-health modeling framework, by improving the representation of health drivers in a state-level integrated assessment model (GCAM-USA) and connecting it with a fine- resolution health impact assessment module, (ii) constructing a large-scale ensemble of decarbonization scenarios to represent a wide range of future uncertainties in socioeconomic patterns, energy technology costs, and food/energy market setups, and (iii) identifying the key factors and processes that determine health outcomes at the county, state, and national levels. By combining knowledge from energy system modeling, health impact assessment, and decision analysis, this convergent research targets improving understanding of the non-linear interactions between low-carbon energy strategies and human health, as well as the role of the market and natural systems on which these interactions depend. Thus, this project seeks to advance quantitative understanding of the complex systems governing interconnected societal challenges on energy, health, and climate. Through a convergence of various disciplines, it seeks to provide new insights on key interacting dynamics that determine health outcomes from decarbonization. Further, by leveraging modern computational capabilities to analyze a large scenario ensemble, a data-driven approach is intended to enable quantification of the relative importance of various socioeconomic, technological, and market uncertainties in determining the health co-benefits or co-harms. The project will produce open-source model code and teaching materials for research and educational purposes. It will also train undergraduate and doctoral students in a highly interdisciplinary environment. Findings are intended to guide practitioners to improve their decisions to better navigate the climate-health nexus.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.

切实的人类健康协同效益可以激发对气候政策的更强有力的支持。例如，能源系统脱碳可以通过减少共同排放的空气污染物产生相当大的健康协同效益。然而，在考虑健康因素的情况下评估近期脱碳战略面临着两个关键的分析挑战：(i) 一些碳减排战略对健康造成的意想不到的共同危害；例如，大规模生物能源生产可能推高粮食价格，从而导致与营养相关的健康共同危害，以及（ii）未来的深刻不确定性，例如社会经济模式、技术成本和市场因素。该项目的目标是：(i) 提高对决定脱碳健康结果的程度和分布的关键因素和过程的定量理解，以及 (ii) 确定最有可能产生稳健净收益的脱碳战略的特征。鉴于未来的巨大不确定性，研究人员假设健康的协同效益和协同危害都受到当地技术选择（例如发电技术和车辆类型）和社会经济因素（例如收入增长和人口）的影响老龄化），健康的共同危害进一步取决于地区和部门之间复杂的相互作用，例如电力、生物燃料和食品的地区间贸易。以美国为重点，研究人员将通过以下方式检验这一假设：(i) 通过改善州级综合评估模型 (GCAM-USA) 中健康驱动因素的代表性，开发综合能源-食品-健康模型框架并将其与精细分辨率的健康影响评估模块连接起来，（ii）构建大规模的脱碳场景集合，以代表社会经济模式、能源技术成本和食品/能源市场设置等未来的广泛不确定性，以及（ iii) 确定关键因素和决定县、州和国家各级健康结果的过程。通过结合能源系统建模、健康影响评估和决策分析的知识，这项融合研究的目标是提高对低碳能源战略与人类健康之间非线性相互作用的理解，以及市场和自然系统对低碳能源战略的作用。这些相互作用取决于什么。因此，该项目旨在促进对管理能源、健康和气候等相互关联的社会挑战的复杂系统的定量理解。通过不同学科的融合，它寻求对决定脱碳健康结果的关键相互作用动态提供新的见解。此外，通过利用现代计算能力来分析大型场景集合，数据驱动的方法旨在量化各种社会经济、技术和市场不确定性在确定健康协同效益或协同危害方面的相对重要性。该项目将生产用于研究和教育目的的开源模型代码和教材。它还将在高度跨学科的环境中培养本科生和博士生。研究结果旨在指导从业者改进决策，以更好地应对气候与健康的关系。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。