Vulnerability to Health Effects of Wildfires under a Changing Climate in Western

描述(由申请者提供)：政府间气候变化专门委员会(IPCC)得出结论，气候变化可能会增加森林火灾的严重性，火灾燃烧更强烈，蔓延更快。美国国立卫生研究院将气候变化和森林火灾列为一项关键的研究需求。根据美国林业局的数据，火灾风险已经增加。一些研究表明，森林火灾影响健康；然而，真正的健康负担尚不清楚，因为尚未进行大规模研究。目前的研究在估计暴露于火灾烟雾的范围和方法方面是有限的。有关环境空气污染物的科学文献表明，某些人群比其他人群更容易受到健康反应的影响。我们假设，在气候变化的情况下，一些人口更容易受到森林火灾对健康的影响。要评估这一漏洞，需要新的数据和方法。我们建议开发必要的数据库和方法，以便我们能够调查美国西部森林火灾入院的脆弱性。在目标1(暴露估计)中，我们将开发一种新的方法，将化学运输模型GEOS-Chem与最新的森林火灾排放清单相结合，以估计森林火灾对空气颗粒物(PM)的贡献。我们的方法从森林火灾烟雾生成PM2.5的每日网格估计，并从其他污染源生成PM2.5的网格估计。在目标2(风险估计)中，我们将开发一个数据集，将天气状况信息、住院和合并症的个人数据以及邮政编码级别的社区因素(如失业)与森林火灾的PM2.5联系起来。我们将开发统计模型来估计暴露于森林火灾烟雾和65岁人群住院风险之间的关联。在这一目标中，我们确定哪些人口在个人因素(年龄、种族、性别、先前存在的疾病)、地区、社区因素(例如失业)和环境因素(例如天气)方面最脆弱。在目标3(到2050年的暴露和风险预测)中，我们将使用目标1中开发的方法和气候模型预测来预测到2050年的未来燃烧面积和森林火灾排放量。这些估计将与化学品运输模型一起用于估计未来的森林火灾风险。然后，我们将使用在目标2中开发的方法，在气候变化的情况下，根据脆弱性预测住院风险的变化，以说明暴露和风险估计中的许多不确定性来源。这项研究将促进人们了解森林火灾如何影响当今的健康，哪些人口最脆弱，以及气候变化如何影响森林火灾，从而影响健康和相关的脆弱性。我们的发现将有助于管理森林火灾的努力，允许更有针对性的公共卫生干预，并有助于有效分配资源，这一点尤其重要，因为 气候变化带来的风险增加。开发的数据库和方法将为研究其他环境暴露、健康结果和气候变化情景提供研究框架。

DESCRIPTION (provided by applicant): The Intergovernmental Panel on Climate Change (IPCC) concluded that climate change will likely increase forest fire severity, with fires that bur more intensely and spread more rapidly. NIH identified climate change and forest fires as a critical research need. According to the U.S. Forest Service, fire risk has already increased. Several studies suggest that forest fires affects health; however, the true health burden is unknown as no large- scale studies have been conducted. Current research is limited in scope and methods to estimate exposure to fire smoke. Scientific literature on ambient air pollutants indicates that some populations are more vulnerable than others to health responses. We hypothesize that some populations are more vulnerable to health impacts of forest fires under a changing climate. To estimate this vulnerability, new data and methods are needed. We propose to develop the necessary databases and methods so we can investigate the vulnerability to hospital admissions from forest fires in the western United States. In Aim 1 (exposure estimation), we will develop a new approach to integrate a chemical transport model, GEOS-Chem, with state-of-the-science forest fire emission inventories to estimate the contribution of forest fires to airborne particulate matter (PM). Our method generates daily, gridded estimates of PM2.5 from forest fire smoke and PM2.5 from other pollutant sources. In Aim 2 (risk estimation) we will develop a data set that links information on weather conditions, individual-level data on hospital admissions and co-morbidities, and community factors (e.g., unemployment) at the zip-code level with PM2.5 from forest fires. We will develop statistical models for estimating the association between exposure to forest fire smoke and risk of hospitalizations for persons >65 years. In this aim, we identify which populations are most vulnerable with respect to individual factors (age, race, sex, pre- existing conditions), region, community factors (e.g., unemployment) and environmental factors (e.g., weather). In Aim 3 (exposure and risk prediction through 2050), we will use the approach developed in Aim 1 and climate model projections to predict future area burned and forest fire emissions through 2050. These estimates will be used with chemical transport modeling to estimate future forest fire exposures. We will then use the approach developed in Aim 2 to predict the change in risk of hospitalizations, by vulnerability, under a changing climate accounting for the many sources of uncertainty in exposure and risk estimation. This study would advance understanding of how forest fires affect health in the present day and which populations are most vulnerable, and of how climate change could impact forest fires and thereby health and related vulnerabilities. Our findings would benefit efforts to manage forest fires, allow more targeted public health interventions, and aid effective allocation of resources, which is particularly important given the increased risk under climate change. The databases and methods developed would provide the research framework for studies of other environmental exposures, health outcomes, and climate change scenarios.