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There is a notable lack of continuous monitoring of air pollutants in the Global South, especially for measuring chemical composition, due to the high cost of regulatory monitors. Using our previously developed low-cost method to quantify black carbon (BC) in fine particulate matter (PM2.5) by analyzing reflected red light from ambient particle deposits on glass fiber filters, we estimated hourly ambient BC concentrations with filter tapes from beta attenuation monitors (BAMs). BC measurements obtained through this method were validated against a reference aethalometer between August 2 and 23, 2023 in Addis Ababa, Ethiopia, demonstrating a very strong agreement (R2 = 0.95 and slope = 0.97). We present hourly BC for three cities in sub-Saharan Africa (SSA) and one in North America: Abidjan (Côte d'Ivoire), Accra (Ghana), Addis Ababa (Ethiopia), and Pittsburgh (USA). The average BC concentrations for the measurement period at the Abidjan, Accra, Addis Ababa Central summer, Addis Ababa Central winter, Addis Ababa Jacros winter, and Pittsburgh sites were 3.85 µg/m3, 5.33 µg/m3, 5.63 µg/m3, 3.89 µg/m3, 9.14 µg/m3, and 0.52 µg/m3, respectively. BC made up 14-20% of PM2.5 mass in the SSA cities compared to only 5.6% in Pittsburgh. The hourly BC data at all sites (SSA and North America) show a pronounced diurnal pattern with prominent peaks during the morning and evening rush hours on workdays. A comparison between our measurements and the Goddard Earth Observing System Composition Forecast (GEOS-CF) estimates shows that the model performs well in predicting PM2.5 for most sites but struggles to predict BC at an hourly resolution. Adding more ground measurements could help evaluate and improve the performance of chemical transport models. Our method can potentially use existing BAM networks, such as BAMs at U.S. Embassies around the globe, to measure hourly BC concentrations. The PM2.5 composition data, thus acquired, can be crucial in identifying emission sources and help in effective policymaking in SSA.
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Poluentes Atmosféricos , Cidades , Monitoramento Ambiental , Material Particulado , Monitoramento Ambiental/métodos , Poluentes Atmosféricos/análise , Material Particulado/análise , África , Carbono/análise , Fuligem/análiseRESUMO
BACKGROUND: Indoor air pollution from biomass fuel is responsible for 50,320 annual deaths of children under-five year, accounting for 4.9% of the national burden of disease in Ethiopia. Acute respiratory infections are the leading cause of mortality among children in Ethiopia. There is limited research that has examined the association between the use of biomass fuel and acute respiratory infections among children. METHODS: A community based cross-sectional study was conducted during January to February 2012 among 422 households in the slum of Addis Ababa. Data were collected by using structured and pretested questionnaire. Odds ratio was done to determine association between independent variables and acute respiratory infections by using logistic regression analysis. Multivariate logistic regression was used to determine the presence of an association between biomass fuel use and acute respiratory infections after controlling for other confounding variables. RESULTS: Nearly 253 (60%) of children live in households that predominately used biomass fuel. The two weeks prevalence of acute respiratory infection was 23.9%. The odds ratios of acute respiratory infection were 2.97 (95% CI: 1.38-3.87) and 1.96 (95% CI: 0.78-4.89) in households using biomass fuel and kerosene, respectively, relative to cleaner fuels. CONCLUSION: There is an association between biomass fuel usage and acute respiratory infection in children. The relationship needs investigation which measure indoor air pollution and clinical measures of acute respiratory infection.
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Poluição do Ar em Ambientes Fechados/efeitos adversos , Biomassa , Infecções Respiratórias/epidemiologia , Doença Aguda , Criança , Estudos Transversais , Etiópia/epidemiologia , Feminino , Humanos , Lactente , Modelos Logísticos , Masculino , Áreas de Pobreza , Infecções Respiratórias/etiologia , Infecções Respiratórias/prevenção & controle , Inquéritos e QuestionáriosRESUMO
Global ground-level measurements of elements in ambient particulate matter (PM) can provide valuable information to understand the distribution of dust and trace elements, assess health impacts, and investigate emission sources. We use X-ray fluorescence spectroscopy to characterize the elemental composition of PM samples collected from 27 globally distributed sites in the Surface PARTiculate mAtter Network (SPARTAN) over 2019-2023. Consistent protocols are applied to collect all samples and analyze them at one central laboratory, which facilitates comparison across different sites. Multiple quality assurance measures are performed, including applying reference materials that resemble typical PM samples, acceptance testing, and routine quality control. Method detection limits and uncertainties are estimated. Concentrations of dust and trace element oxides (TEO) are determined from the elemental dataset. In addition to sites in arid regions, a moderately high mean dust concentration (6 µg/m3) in PM2.5 is also found in Dhaka (Bangladesh) along with a high average TEO level (6 µg/m3). High carcinogenic risk (>1 cancer case per 100000 adults) from airborne arsenic is observed in Dhaka (Bangladesh), Kanpur (India), and Hanoi (Vietnam). Industries of informal lead-acid battery and e-waste recycling as well as coal-fired brick kilns likely contribute to the elevated trace element concentrations found in Dhaka.
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Poor ventilation and polluting cooking fuels in low-income homes cause high exposure, yet relevant global studies are limited. We assessed exposure to in-kitchen particulate matter (PM2.5 and PM10) employing similar instrumentation in 60 low-income homes across 12 cities: Dhaka (Bangladesh); Chennai (India); Nanjing (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Akure (Nigeria); Blantyre (Malawi); Dar-es-Salaam (Tanzania) and Nairobi (Kenya). Exposure profiles of kitchen occupants showed that fuel, kitchen volume, cooking type and ventilation were the most prominent factors affecting in-kitchen exposure. Different cuisines resulted in varying cooking durations and disproportional exposures. Occupants in Dhaka, Nanjing, Dar-es-Salaam and Nairobi spent > 40% of their cooking time frying (the highest particle emitting cooking activity) compared with â¼ 68% of time spent boiling/stewing in Cairo, Sulaymaniyah and Akure. The highest average PM2.5 (PM10) concentrations were in Dhaka 185 ± 48 (220 ± 58) µg m-3 owing to small kitchen volume, extensive frying and prolonged cooking compared with the lowest in Medellín 10 ± 3 (14 ± 2) µg m-3. Dual ventilation (mechanical and natural) in Chennai, Cairo and Sulaymaniyah reduced average in-kitchen PM2.5 and PM10 by 2.3- and 1.8-times compared with natural ventilation (open doors) in Addis Ababa, Dar-es-Salam and Nairobi. Using charcoal during cooking (Addis Ababa, Blantyre and Nairobi) increased PM2.5 levels by 1.3- and 3.1-times compared with using natural gas (Nanjing, Medellin and Cairo) and LPG (Chennai, Sao Paulo and Sulaymaniyah), respectively. Smaller-volume kitchens (<15 m3; Dhaka and Nanjing) increased cooking exposure compared with their larger-volume counterparts (Medellin, Cairo and Sulaymaniyah). Potential exposure doses were highest for Asian, followed by African, Middle-eastern and South American homes. We recommend increased cooking exhaust extraction, cleaner fuels, awareness on improved cooking practices and minimising passive occupancy in kitchens to mitigate harmful cooking emissions.
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Poluentes Atmosféricos , Poluição do Ar em Ambientes Fechados , Aerossóis , Poluentes Atmosféricos/análise , Poluição do Ar em Ambientes Fechados/análise , Bangladesh , Brasil , Cidades , Culinária , Monitoramento Ambiental/métodos , Etiópia , Índia , Quênia , Material Particulado/análiseRESUMO
Real-time monitoring of fine particulate matter (PM2.5) concentrations and assessing the health impact are limited in Ethiopia. The objective of this study is to describe current levels of PM2.5 air pollution in Addis Ababa and examine temporal patterns and to consider the health impact of current PM2.5 exposure levels. METHODS: PM2.5 concentrations were measured using a centrally-located Beta Attenuator Monitor (BAM-1022) for 3 years (1 April 2017 to 31 March 2020), with data downloaded biweekly. Deaths attributable to current PM2.5 concentration levels were estimated using the AirQ+ tool. The daily average was estimated using hourly data. RESULTS: The daily mean (SD) PM2.5 concentration was 42.4 µg/m3 (15.98). Two daily extremes were observed: morning (high) and afternoon (low). Sundays had the lowest PM2.5 concentration, while Mondays to Thursdays saw a continuous increase; Fridays showed the highest concentration. Seasons showed marked variation, with the highest values during the wet season. Concentration spikes reflected periods of intensive fuel combustion. A total of 502 deaths (4.44%) were attributable to current air pollution levels referenced to the 35 µg/m3 WHO interim target annual level and 2,043 (17.7%) at the WHO 10 µg/m3 annual guideline. CONCLUSION: PM2.5 daily levels were 1.7 times higher than the WHO-recommended 24-hour guideline. The current annual mean PM2.5 concentration results in a substantial burden of attributable deaths compared to an annual mean of 10 µg/m3. The high PM2.5 level and its variability across days and seasons calls for citywide interventions to promote clean air.
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Car microenvironments significantly contribute to the daily pollution exposure of commuters, yet health and socioeconomic studies focused on in-car exposure are rare. This study aims to assess the relationship between air pollution levels and socioeconomic indicators (fuel prices, city-specific GDP, road density, the value of statistical life (VSL), health burden and economic losses resulting from exposure to fine particulate matter ≤2.5 µm; PM2.5) during car journeys in ten cities: Dhaka (Bangladesh); Chennai (India); Guangzhou (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Blantyre (Malawi); and Dar-es-Salaam (Tanzania). Data collected by portable laser particle counters were used to develop a proxy of car-user exposure profiles. Hotspots on all city routes displayed higher PM2.5 concentrations and disproportionately high inhaled doses. For instance, the time spent at the hotspots in Guangzhou and Addis Ababa was 26% and 28% of total trip time, but corresponded to 54% and 56%, respectively, of the total PM2.5 inhaled dose. With the exception of Guangzhou, all the cities showed a decrease in per cent length of hotspots with an increase in GDP and VSL. Exposure levels were independent of fuel prices in most cities. The largest health burden related to in-car PM2.5 exposure was estimated for Dar-es-Salam (81.6 ± 39.3 µg m-3), Blantyre (82.9 ± 44.0) and Dhaka (62.3 ± 32.0) with deaths per 100,000 of the car commuting population per year of 2.46 (2.28-2.63), 1.11 (0.97-1.26) and 1.10 (1.05-1.15), respectively. However, the modest health burden of 0.07 (0.06-0.08), 0.10 (0.09-0.12) and 0.02 (0.02-0.03) deaths per 100,000 of the car commuting population per year were estimated for Medellin (23 ± 13.7 µg m-3), São Paulo (25.6 ± 11.7) and Sulaymaniyah (22.4 ± 15.0), respectively. Lower GDP was found to be associated with higher economic losses due to health burdens caused by air pollution in most cities, indicating a socioeconomic discrepancy. This assessment of health and socioeconomic parameters associated with in-car PM2.5 exposure highlights the importance of implementing plausible solutions to make a positive impact on peoples' lives in these cities.
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Poluentes Atmosféricos , Poluição do Ar , Aerossóis , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Automóveis , Bangladesh , Brasil , Cidades , Exposição Ambiental , Etiópia , Índia , Material Particulado/análiseRESUMO
Cars are a commuting lifeline worldwide, despite contributing significantly to air pollution. This is the first global assessment on air pollution exposure in cars across ten cities: Dhaka (Bangladesh); Chennai (India); Guangzhou (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Blantyre (Malawi); and Dar-es-Salaam (Tanzania). Portable laser particle counters were used to develop a proxy of car-user exposure profiles and analyse the factors affecting particulate matter ≤2.5 µm (PM2.5; fine fraction) and ≤10 µm (PM2.5-10; coarse fraction). Measurements were carried out during morning, off- and evening-peak hours under windows-open and windows-closed (fan-on and recirculation) conditions on predefined routes. For all cities, PM2.5 and PM10 concentrations were highest during windows-open, followed by fan-on and recirculation. Compared with recirculation, PM2.5 and PM10 were higher by up to 589% (Blantyre) and 1020% (São Paulo), during windows-open and higher by up to 385% (São Paulo) and 390% (São Paulo) during fan-on, respectively. Coarse particles dominated the PM fraction during windows-open while fine particles dominated during fan-on and recirculation, indicating filter effectiveness in removing coarse particles and a need for filters that limit the ingress of fine particles. Spatial variation analysis during windows-open showed that pollution hotspots make up to a third of the total route-length. PM2.5 exposure for windows-open during off-peak hours was 91% and 40% less than morning and evening peak hours, respectively. Across cities, determinants of relatively high personal exposure doses included lower car speeds, temporally longer journeys, and higher in-car concentrations. It was also concluded that car-users in the least affluent cities experienced disproportionately higher in-car PM2.5 exposures. Cities were classified into three groups according to low, intermediate and high levels of PM exposure to car commuters, allowing to draw similarities and highlight best practices.
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BACKGROUND: The health effects of air pollution are generally global problems, but they have, since recently become issues of particular concern for developing countries. This review assessed the situation of air pollution and related health effects in the context of Ethiopia. METHODS: The materials reviewed in this publication are published scientific papers from online search engines, unpublished government reports and academic theses/dissertations. In addition, interview data obtained from authorities and experts involved in the management of air quality were analyzed, interpreted and reported in the article. RESULTS: Review of the few studies conducted in Ethiopia showed that average concentrations of PM2.5 reached as high as 280 µg/m3 for 24-hour measurements (range: 2,417-12,739 µg/m3). Indoor carbon monoxide (CO) levels were universally higher than regulatory limits for the United States and were found to be much higher among households using traditional stoves and solid biomass fuels. The use of traditional stoves and solid biomass fuels was reported in >95% of the households considered. High average levels of NO2 (97 ppb) were reported in a large longitudinal study. The ambient PM10 level was below the WHO guideline values in the majority of the samples. About 50% of the on-road CO samples taken from traffic roads in Addis Ababa were found to be less than the guideline values while the number of motor vehicles in Ethiopia is reported to be increasing by more than 9% per annum. There is a very limited air quality monitoring capacity in the country. The co-ordination between stakeholders in this regard is also inadequate. The limited evidence available on health effects of air pollution indicates that the prevalence of acute respiratory illness among children living in households using crude biomass fuels is significantly higher than the national average figures. CONCLUSION: The limited evidence reviewed and reported in this article indicates high levels of indoor air pollution and trends of worsening outdoor air pollution. This tentative conclusion carries with it the urgent need for more evidence-based research and capacity building in the areas of indoor and outdoor air pollution.