Department of City and Regional Planning, University of North Carolina, Chapel Hill, NC, USA.
Interdisciplinary Studies Department, Howard University, Washington, DC, USA; School of Environmental and Forest Sciences, University of Washington, Seattle, WA, USA.
Sci Total Environ. 2024 Jan 1;906:167834. doi: 10.1016/j.scitotenv.2023.167834. Epub 2023 Oct 14.
Wildland fire smoke risks are not uniformly distributed across people and places, and the most vulnerable communities are often disproportionately impacted. This study develops a county level community health vulnerability index (CHVI) for the Contiguous United States (CONUS) using three major vulnerability components: adaptive capacity, sensitivity, and exposure at the national and regional level. We first calculated sensitivity and adaptive capacity sub-indices using nine sensitivity and twenty adaptive capacity variables. These sub-indices were then combined with an exposure sub-index, which is based on the Community Multiscale Air Quality data (2008-2018), to develop CHVI. Finally, we conducted several analyses with the derived indices to: 1) explore associations between the level of fine particulate matter from wildland fires (fire-PM) and the sub-indices/CHVI; 2) measure the impact of fire-PM on the increase in the annual number of days with 12-35 μg/m (moderate) and >35 μg/m (at or above unhealthy for sensitive groups) based on the US EPA Air Quality Index categories, and 3) calculate population size in different deciles of the sub-indices/CHVI. This study has three main findings. First, we showed that the counties with higher daily fire-PM concentration tend to have lower adaptive capacity and higher sensitivity and vulnerability. Relatedly, the counties at high risk tended to experience a greater increase in the annual number of days with 12-35 μg/m and >35 μg/m than their counterparts. Second, we found that 16.1, 12.0, and 17.6 million people out of 332 million in CONUS reside in the counties in the lowest adaptive capacity decile, highest sensitivity decile, and highest vulnerability decile, respectively. Third, we identified that the US Northwest, California, and Southern regions tended to have higher vulnerability than others. Accurately identifying a community's vulnerability to wildfire smoke can help individuals, researchers, and policymakers better understand, prepare for, and respond to future wildland fire events.
野火烟雾风险在人群和地点之间的分布并不均匀，最脆弱的社区往往受到不成比例的影响。本研究使用三个主要脆弱性组成部分：适应能力、敏感性和国家和地区层面的暴露，为美国本土（CONUS）开发了一个县级社区健康脆弱性指数（CHVI）。我们首先使用九个敏感性和二十个适应性变量计算敏感性和适应能力子指数。然后，这些子指数与暴露子指数相结合，该指数基于社区多尺度空气质量数据（2008-2018 年），开发 CHVI。最后，我们使用派生指数进行了几项分析：1）探索野火产生的细颗粒物（fire-PM）水平与子指数/CHVI 之间的关联；2）根据美国环保署空气质量指数类别，衡量 fire-PM 对每年 12-35μg/m（中度）和 >35μg/m（对敏感人群不健康）天数增加的影响；3）计算不同子指数/CHVI 十分位数中的人口规模。本研究有三个主要发现。首先，我们表明，每日 fire-PM 浓度较高的县往往具有较低的适应能力和较高的敏感性和脆弱性。相关地，高风险的县经历的每年 12-35μg/m 和 >35μg/m 的天数增加幅度往往大于其对应县。其次，我们发现，在 CONUS 的 3.32 亿人口中，有 1610 万人、1200 万人和 1760 万人分别居住在适应性能力最低十分位数、敏感性最高十分位数和脆弱性最高十分位数的县。第三，我们发现美国西北部、加利福尼亚州和南部地区的脆弱性往往高于其他地区。准确识别社区对野火烟雾的脆弱性可以帮助个人、研究人员和决策者更好地了解、准备和应对未来的野火事件。
