PM2.5 in household kitchens of Bhaktapur, Nepal, using four different cooking fuels
PM2.5 in household kitchens of Bhaktapur, Nepal, using four different cooking fuels
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DOI：
10.1016/j.atmosenv.2015.04.060
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发表时间：
2015-07-01
影响因子：
5
通讯作者：
Smith, Kirk R.
中科院分区：
文献类型：
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作者：
Pokhrel, Amod K.;Bates, Michael N.;Smith, Kirk R.
在研究家庭空气污染（HAP）对健康的影响时，由于缺乏负担得起的监测设备，往往无法收集实际的空气污染数据，因此不得不使用暴露指标，如所使用的烹饪燃料类型。其中最重要的污染物是细颗粒物（PM2.5），这可能是烟雾暴露风险的最佳单一指标。在这项研究中，我们部署了一种经济实惠且功能强大的设备，用于监测尼泊尔巴克塔普尔824户家庭的PM2.5。这些家庭使用的四种主要烹饪燃料的比例大致相等：电力（22%）、液化石油气（LPG）（29%）、煤油（23%）和生物质（26%）。使用光散射浊度计UCB-PATS（加州大学伯克利分校-颗粒和温度监测系统）测量厨房中的PM2.5浓度。调查了研究家庭中PM2.5浓度的主要影响因素。UCB-PATS结果与重量分析结果具有良好的相关性（R-2 = 0.84;对于所有燃料组合）。一年中所有季节的平均家庭PM2.5浓度为656（标准差：924）μ g/m3，来自生物质; 169（标准差：207）μ g/m3，来自煤油; 101（标准差：130）μ g/m3，来自液化石油气; 80（标准差：103）μ g/m3，来自电炉。在PM2.5测量的多元回归中，与电炉相比，使用液化石油气，煤油和生物质炉灶分别与室内PM2.5浓度增加65%（95%CI：38-95%），146%（103-200%）和733%（589 907%）。UCB-PATS在该领域表现良好。没有烟道的生物质燃料炉是PM2，5的最重要来源，其次是煤油，然后是液化石油气炉。室外PM2，5和季节影响室内PM2，5水平。结果支持谨慎使用廉价的光散射监测器监测HAP在发展中国家。(C)2015爱思唯尔有限公司版权所有。
In studies examining the health effects of household air pollution (HAP), lack of affordable monitoring devices often precludes collection of actual air pollution data, forcing use of exposure indicators, such as type of cooking fuel used. Among the most important pollutants is fine particulate matter (PM2.5), perhaps the best single indicator of risk from smoke exposure. In this study, we deployed an affordable and robust device to monitor PM2.5 in 824 households in Bhaktapur, Nepal. Four primary cooking fuels were used in roughly equal proportions in these households: electricity (22%), liquefied petroleum gas (LPG) (29%), kerosene (23%), and biomass (26%). PM2.5 concentrations were measured in the kitchens using a light-scattering nephelometer, the UCB-PATS (University of California, Berkeley-Particle and Temperature monitoring System). The major ptedictors of PM2.5 concentrations in study households were investigated. The UCB-PATS results were well correlated with the gravimetric results (R-2 = 0.84; for all fuels combined). The mean household PM2.5 concentrations across all seasons of the year were 656 (standard deviation (SD):924) mu g/m(3) from biomass; 169 (SD: 207) mu g/m(3) from kerosene; 101 (SD: 130) mu g/m(3) from LPG; and 80 (SD: 103) mu g/m(3) from electric stoves. In the multivariate regression of PM2.5 measures, compared with electric stoves, use of LPG, kerosene and biomass stoves were associated with increased indoor PM2.5 concentrations of 65% (95% CI: 38-95%), 146% (103-200%), and 733% (589 907%), respectively. The UCB-PATS performed well in the field. Biomass fuel stoves without flues were the most significant sources of PM2,5, followed by kerosene and then LPG stoves. Outdoor PM2,5, and season influenced indoor PM2,5 levels. Results support careful use of inexpensive light-scattering monitors for monitoring of HAP in developing countries. (C) 2015 Elsevier Ltd. All rights reserved.