Influence of uncertainties in burned area estimates on modeled wildland fire PM2.5 and ozone pollution in the contiguous US
Influence of uncertainties in burned area estimates on modeled wildland fire PM2.5 and ozone pollution in the contiguous US
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DOI：
10.1016/j.atmosenv.2018.08.020
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发表时间：
2018-10-01
影响因子：
5
通讯作者：
Beidler, James
中科院分区：
文献类型：
--
作者：
Koplitz, Shannon N.;Nolte, Christopher G.;Beidler, James
野火是细颗粒物（PM2.5）的主要来源，细颗粒物是全球对人类健康最有害的环境污染物之一。为了代表荒地火灾排放对大气成分的影响，区域和全球化学传输模型依赖于从燃烧面积（即火灾规模和位置）估计中得出的排放清单。虽然不同的方法估计每年烧毁面积同意在美国西部相当不错（在2002-2014年期间的大多数年份在20-30%），美国南部的估计可以相差超过五倍。燃烧面积的这些差异导致了火灾排放清单平台之间排放量的空间和时间分配的显著变化。在这项工作中，我们从三个不同的产品-美国环保署国家排放清单（NEI），NCAR火灾清单（FINN），和全球火灾排放数据库（GFED 4s）-社区多尺度空气质量（CMAQ）模型，以量化和表征美国（CONUS）邻近地区模拟PM和臭氧浓度的差异由于所使用的火灾排放清单。NEI是专门为美国开发的，而FINN和GFED 4在全球都有售。我们发现，NEI排放导致全国范围内模拟的年平均PM2.5（0.85 μ g m（-3））和4月至9月最大日8小时臭氧（0.28 ppb）与“无火”基线相比增加最多，其次是FINN（0.33 μ g m（-3）和0.22 ppb）和GFED 4s（0.12 μ g m（-3）和0.17 ppb）。在所有三个清单中，美国南部的荒地火灾污染的年平均增强最高（在某些地区超过4 μ g m（-3）和2 ppb），但在这些地区内显示出相当大的空间变异性。我们还研究了2011年期间五个单独火灾事件的代表性，发现在两个全球清单中，FINN再现了NEI建模的污染物浓度的剧烈变化，并在调查的每一个事件期间的地表观测中显示，与GFED 4s相比。了解美国火灾相关PM2.5和臭氧建模对燃烧面积估计方法的敏感性，将为未来评估国家和全球范围内当前和未来火灾活动对空气质量和人类健康的影响提供信息。
Wildland fires are a major source of fine particulate matter (PM2.5), one of the most harmful ambient pollutants for human health globally. To represent the influence of wildland fire emissions on atmospheric composition, regional and global chemical transport models rely on emission inventories developed from estimates of burned area (i.e. fire size and location). While different methods of estimating annual burned area agree reasonably well in the western U.S. (within 20-30% for most years during 2002-2014), estimates for the southern U.S. can vary by more than a factor of five. These differences in burned area lead to significant variability in the spatial and temporal allocation of emissions across fire emission inventory platforms. In this work, we implement wildland fire emission estimates for 2011 from three different products - the USEPA National Emission Inventory (NEI), the Fire Inventory of NCAR (FINN), and the Global Fire Emission Database (GFED4s) - into the Community Multiscale Air Quality (CMAQ) model to quantify and characterize differences in simulated PM and ozone concentrations across the contiguous U.S. (CONUS) due to the fire emission inventory used. The NEI is developed specifically for the U.S., while both FINN and GFED4s are available globally. We find that NEI emissions lead to the largest increases in modeled annual average PM2.5 (0.85 mu g m(-3)) and April-September maximum daily 8-h ozone (0.28 ppb) nationally compared to a "no fire" baseline, followed by FINN (0.33 mu g m(-3) and 0.22 ppb) and GFED4s (0.12 mu g m(-3) and 0.17 ppb). Annual mean enhancements in wildland fire pollution are highest in the southern U.S. across all three inventories (over 4 mu g m(-3) and 2 ppb in some areas), but show considerable spatial variability within these regions. We also examine the representation of five individual fire events during 2011 and find that of the two global inventories, FINN reproduces more of the acute changes in pollutant concentrations modeled with NEI and shown in surface observations during each of the episodes investigated compared to GFED4s. Understanding the sensitivity of modeling fire-related PM2.5 and ozone in the U.S. to burned area estimation approaches will inform future efforts to assess the implications of present and future fire activity for air quality and human health at national and global scales.