Global_Environmental_Research_Vol.27No.1
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· What are the existing current policies or measures for · What are the priority research and information needs that can better prepare managers, policymakers and the public to reach informed decisions related to the impacts of air pollution from vegetation fire events on human health? Table 1 Key terms and searches. Search Policies or measures to reduce air pollution from vegetation fire events Set 1 Set 2 Set 3 Set 4 Set 5 Set 6 Effects of air pollution from fire events and policies on human health Set 7 Set 8 Set 9 Key terms and searches 62 2.1 Literature Review 2. Methods prohibited burning in forest areas (Uttajug et al., 2022b). These measures have had beneficial impacts on air pollution concentrations (Yabueng et al., 2020) and health effects (Uttajug et al., 2022b). Previously, the studies reviewed have focused on the health effects of exposure to air pollution from vegetation fires (Cheong et al., 2019; Phung et al., 2022; Ramakreshnan et al., 2018), but none have demonstrated how policies on vegetation fire events affect air pollution and human health. The objective of this study was to review the literature on existing and current policies or measures against vegetation fire events and their effects on air pollution and human health in Thailand, as well as to integrate disparate information to address the following questions: reducing air pollution from vegetation fire events? Relevant publications were searched from electronic reference databases (Pubmed and Web of Science) using combinations of the key terms shown in Table 1. Only full-text original or research articles related to the research questions conducted in Thailand were included. Articles focusing on reviewing other articles were excluded. Due to the scarcity of articles on policy measures for reducing vegetation fires or air pollution from in Thailand, both peer-reviewed and non-peer-reviewed articles were included in this study. A search using the key terms of Set 6 (Table 1) was conducted to address the first research question. To address only epidemiological studies with implementation (Set 9) and without it (Set 8) were considered in this study. fires the second Regulation or abatement measure or campaign or law or ban or policy or control measure Air pollution or smoke haze Vegetation fire events or biomass burning or wildfire or bushfire or forest fire or fires Thailand or northern upper Thailand Publication year = 1990:2023 Set 1 and Set 2 and Set 3 and Set 4 and Set 5 Public health or health or morbidity or mortality or hospitalization or hospital visits or clinic visits Set 2 and Set 3 and Set 4 and Set 5 and Set 7 Set 6 and Set 7 question, research A. UTTAJUG 2.2 Data Integration and Analysis 2.2.1 Environmental Data 2.2.2 Mortalities Attributable to PM2.5 To evaluate the effectiveness of existing and current policies or measures against vegetation fire events, a report titled “Standard Operating Procedure for Northern Haze Response” (Pollution Control Department, 2019) was analyzed along with environmental and mortality information. The data were collected from 2012 to 2021 in UNT, which includes nine provinces: Chiang Mai, Chiang Rai, Phrea, Phayao, Mae Hong Son, Nan, Lamphun, Lampang and Tak. Daily concentrations of PM2.5 and PM10 (μg/m3) were obtained from background monitoring stations provided by the Pollution Control Department of Thailand. The data were gathered from two stations each for PM10 and PM2.5, all situated in Chiang Mai Province. This location was chosen as it is representative of the UNT, given the availability average concentrations of PM2.5 and PM10 were computed for each year. Fire hotspot data were obtained from NASA’s Fire Information for Resource Management Systems (FIRMS), which, in brief, detects fire hotspots at a resolution of 1 km by Terra and Aqua satellites. Daily fire hotspots were summed for UNT each year. The number of mortalities attributable to PM2.5 was estimated using UNT population data, the national mortality rate (https://data.worldbank.org/), concentration- response function (relative risk 1.004 (95% confidence interval: 1.001, 1.008), (Uttajug et al., 2023)) and background PM2.5 concentration. The health burden estimation method was documented in a previous study (Uttajug et al., 2022a). The estimation was performed for January to April, during which intensive burning occurs in this area. It was assumed that burning events mainly emitted elevated PM2.5 concentrations during these periods. historical of data. Daily

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