Chen Dong, Billmire Michael, Loughner Christopher P, Bredder Allison, French Nancy H F, Kim Hyun Cheol, Loboda Tatiana V
Department of Geographical Sciences, University of Maryland, College Park, MD, USA.
Michigan Tech Research Institute, Michigan Technological University, Ann Arbor, MI, USA.
Sci Total Environ. 2023 Nov 10;898:165594. doi: 10.1016/j.scitotenv.2023.165594. Epub 2023 Jul 17.
Wildfire is a major disturbance agent in Arctic boreal and tundra ecosystems that emits large quantities of atmospheric pollutants, including PM. Under the substantial Arctic warming which is two to three times of global average, wildfire regimes in the high northern latitude regions are expected to intensify. This imposes a considerable threat to the health of the people residing in the Arctic regions. Alaska, as the northernmost state of the US, has a sizable rural population whose access to healthcare is greatly limited by a lack of transportation and telecommunication infrastructure and low accessibility. Unfortunately, there are only a few air quality monitoring stations across the state of Alaska, and the air quality of most remote Alaskan communities is not being systematically monitored, which hinders our understanding of the relationship between wildfire emissions and human health within these communities. Models simulating the dispersion of pollutants emitted by wildfires can be extremely valuable for providing spatially comprehensive air quality estimates in areas such as Alaska where the monitoring station network is sparse. In this study, we established a methodological framework that is based on an integration of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, the Wildland Fire Emissions Inventory System (WFEIS), and the Arctic-Boreal Vulnerability Experiment (ABoVE) Wildfire Date of Burning (WDoB) dataset, an Arctic-oriented fire product. Through our framework, daily gridded surface-level PM concentrations for the entire state of Alaska between 2001 and 2015 for which wildfires are responsible can be estimated. This product reveals the spatio-temporal patterns of the impacts of wildfires on the regional air quality in Alaska, which, in turn, offers a direct line of evidence indicating that wildfire is the dominant driver of PM concentrations over Alaska during the fire season. Additionally, it provides critical data inputs for research on understanding how wildfires affect human health which creates the basis for the development of effective and efficient mitigation efforts.
野火是北极针叶林和苔原生态系统中的一种主要干扰因素，会排放大量大气污染物，包括颗粒物。在北极大幅变暖（其速度是全球平均水平的两到三倍）的情况下，预计高北纬地区的野火活动将加剧。这对居住在北极地区的人们的健康构成了相当大的威胁。阿拉斯加作为美国最北部的州，有相当数量的农村人口，由于缺乏交通和电信基础设施以及可达性低，他们获得医疗保健的机会受到极大限制。不幸的是，阿拉斯加州仅有少数空气质量监测站，阿拉斯加大多数偏远社区的空气质量并未得到系统监测，这阻碍了我们对这些社区野火排放与人类健康之间关系的理解。模拟野火排放污染物扩散的模型对于在阿拉斯加等监测站网络稀疏的地区提供空间上全面的空气质量估计可能极具价值。在本研究中，我们建立了一个方法框架，该框架整合了混合单粒子拉格朗日积分轨迹（HYSPLIT）模型、野火排放清单系统（WFEIS）以及北极 - 北方脆弱性实验（ABoVE）野火燃烧日期（WDoB）数据集（一种面向北极的火灾产品）。通过我们的框架，可以估算出2001年至2015年阿拉斯加州全州范围内由野火导致的每日网格化地面颗粒物浓度。该产品揭示了野火对阿拉斯加区域空气质量影响的时空模式，这反过来又提供了直接证据，表明野火是火灾季节阿拉斯加颗粒物浓度的主要驱动因素。此外，它为理解野火如何影响人类健康的研究提供了关键数据输入，为制定有效且高效的缓解措施奠定了基础。
