Measuring and predicting personal and household Black Carbon levels from 88 communities in eight countries
| Autor: | Pure-Air study investigators, Jephat Chifamba, Rita Yusuf, Deepa Mohan, P V M Lakshmi, Johnna Otero, Matthew Shupler, Afreen Zaman Khan, Paul A. Camacho, Romaina Iqbal, Yen Li Chu, KG Jayachitra, Pamela Seron, Vivek Sagar, Sanjeev Nair, Aaron Birch, Maha Mustaha, Khawar Kazmi, Sumathy Rangarajan, Li Wei, Hu Bo, Tatenda Ncube, Maritza Perez-Mayorga, Kamala Rammohan, Prem Mony, Luis A. Salazar, Zhiguang Liu, Laura Heenan, Matthew Jeronimo, Nicolás Saavedra, Indu Mohan, Salim Yusuf, Brian Ncube, Nicola West, Karen Yeates, Maria Jose Oliveros, Perry Hystad, Ying Wang, Michael Brauer, R Khawaja, Fernando Lanas, Parthiban Kumar, Patricio Lopez-Jaramillo, Rajeev Gupta, Lap A. H. Tse |
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| Rok vydání: | 2021 |
| Předmět: |
Male
Rural Population Air Pollutants Environmental Engineering Light absorbance Air pollution Environmental Exposure medicine.disease_cause Pollution Reflectivity Carbon Geography Environmental health Stove Air Pollution Indoor medicine Environmental Chemistry Humans Female Particulate Matter Cooking Prospective Studies Waste Management and Disposal Environmental Monitoring |
| Zdroj: | The Science of the total environment. 818 |
| ISSN: | 1879-1026 |
| Popis: | Black Carbon (BC) is an important component of household air pollution (HAP) in low- and middle-income countries (LMICs), but levels and drivers of exposure are poorly understood. As part of the Prospective Urban and Rural Epidemiological (PURE) study, we analyzed 48-hour BC measurements for 1187 individual and 2242 household samples from 88 communities in 8 LMICs (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Light absorbance (10−5 m−1) of collected PM2.5 filters, a proxy for BC concentrations, was calculated via an image-based reflectance method. Surveys of household/personal characteristics and behaviors were collected after monitoring. The geometric mean (GM) of personal and household BC measures was 2.4 (3.3) and 3.5 (3.9)·10−5 m−1, respectively. The correlation between BC and PM2.5 was r = 0.76 for personal and r = 0.82 for household measures. A gradient of increasing BC concentrations was observed for cooking fuels: BC increased 53% (95%CI: 30, 79) for coal, 142% (95%CI: 117, 169) for wood, and 190% (95%CI: 149, 238) for other biomass, compared to gas. Each hour of cooking was associated with an increase in household (5%, 95%CI: 3, 7) and personal (5%, 95%CI: 2, 8) BC; having a window in the kitchen was associated with a decrease in household (−38%, 95%CI: −45, −30) and personal (−31%, 95%CI: −44, −15) BC; and cooking on a mud stove, compared to a clean stove, was associated with an increase in household (125%, 95%CI: 96, 160) and personal (117%, 95%CI: 71, 117) BC. Male participants only had slightly lower personal BC (−0.6%, 95%CI: −1, 0.0) compared to females. In multivariate models, we were able to explain 46–60% of household BC variation and 33–54% of personal BC variation. These data and models provide new information on exposure to BC in LMICs, which can be incorporated into future exposure assessments, health research, and policy surrounding HAP and BC. |
| Databáze: | OpenAIRE |
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