Global_Environmental_Research_Vol.27No.1
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A literature search through PubMed was conducted using the following terms: “biomass burning,” “forest fire,” “vegetation fire” and “wildfire.” This was used in combination with the terms “public health,” “health,” “morbidity” and “mortality.” To link the study to air pollution and modeling, the terms “air pollution,” “air quality,” and “modeling” were also used to gather studies that explored the connection between biomass burning, air pollution and public health impacts (both long- and short-term), through the use of atmospheric modeling methods. Any articles that did not attempt to establish links between health and air pollution from biomass burning through the use of atmospheric modeling methods were excluded (i.e., reviews, guidelines, perspectives, other systematic scoping the following data were extracted from the articles: authors, location, year conducted, health impact measured and atmospheric modeling technique used. 2. Methodology 3.1 Descriptive Statistics 3. Results and Discussion the research designs of future studies on atmospheric modeling and possible early warning systems. “atmospheric modeling,” reviews). After appropriate selection, The database search identified 197 papers. We then excluded five duplicates (i.e., papers identified by more than one search). We eliminated papers that did not meet the inclusion criteria by first screening the titles (42 papers excluded), by examining abstracts (72 papers excluded), and then by examining the full articles (21 papers excluded) (Fig. 1). The final review included 57 studies of human health impacts of biomass burning, which can be found in Annex 1. Review on Exposure Assessment of Biomass Burning Fig. 1 Article selection process following PRISMA. “model” The three main categories of air quality data collection included direct site monitors, satellite imaging (i.e., remote sensing) and air quality models (i.e., chemical transport models). More than half of these studies used a single approach (32/57 studies, 56.14%), while the rest employed a blended approach (25/57 studies, 43.86%), using at least two of the three data collection methods. Among the three, the majority of our reviewed articles (33/57 studies, 57.89%) used chemical transport models for their data collection, the most popular specific model being GEOS-Chem (Goddard followed by Earth Observing System-Chemistry), WRF-Chem and Forecasting- Chemistry). After chemical transport models, the next most commonly used data source was satellite imaging (30/57 studies, 52.63%), most popularly through MODIS (Moderate Resolution Imaging Spectroradiometer). The least commonly used data source was direct station monitors (20/57, 35.08%). There were 43 countries and regions included in this review. The studies spanned the continents of North America, South America, Europe, Asia and Australia and emphasized the health impacts of air pollution in densely populated urban regions, industrial zones and areas prone to wildfires. The focus of the studies was on areas in the global north in 75.44% of the studies (43/57 studies), with 39.53% focusing on the USA (17/43 studies), with California, then Colorado being the most studied states. This is likely due to richness of research infrastructure, funding opportunities, data availability, diverse range of (Weather Research 51

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