The highest levels of air pollution in the world now occur in developing country cities, where air pollution sources differ from high-income countries. We analyzed particulate matter (PM) chemical composition and estimated the contributions of various sources to particle pollution in poor and affluent neighborhoods of Accra, Ghana. Elements from earth's crust were most abundant during the seasonal Harmattan period between late December and late January when Saharan dust is carried to coastal West Africa. During Harmattan, crustal particles accounted for 55 µg m −3 (37%) of fine particle (PM 2.5 ) mass and 128 µg m −3 (42%) of PM 10 mass. Outside Harmattan, biomass combustion, which was associated with higher black carbon, potassium, and sulfur, accounted for between 10.6 and 21.3 µg m −3 of fine particle mass in different neighborhoods, with its contribution largest in the poorest neighborhood. Other sources were sea salt, vehicle emissions, tire and brake wear, road dust, and solid waste burning. Reducing air pollution in African cities requires policies related to energy, transportation and urban planning, and forestry and agriculture, with explicit attention to impacts of each strategy in poor communities. Such cross-sectoral integration requires emphasis on urban environment and urban poverty in the post-2015 Development Agenda.

Household air pollution in sub-Saharan Africa and other developing regions is an important cause of disease burden. Little is known about the chemical composition and sources of household air pollution in subSaharan Africa, and how they differ between rural and urban homes. We analyzed the chemical composition and sources of fine particles (PM 2.5 ) in household cooking areas of multiple neighborhoods in Accra, Ghana, and in peri-urban (Banjul) and rural (Basse) areas in The Gambia. In Accra, biomass burning accounted for 39−62% of total PM 2.5 mass in the cooking area in different neighborhoods; the absolute contributions were 10−45 μg/m 3 . Road dust and vehicle emissions comprised 12−33% of PM 2.5 mass. Solid waste burning was also a significant contributor to household PM 2.5 in a low-income neighborhood but not for those living in better-off areas. In Banjul and Basse, biomass burning was the single dominant source of cooking-area PM 2.5 , accounting for 74−87% of its total mass; the relative and absolute contributions of biomass smoke to PM 2.5 mass were larger in households that used firewood than in those using charcoal, reaching as high as 463 μg/m 3 in Basse homes that used firewood for cooking. Our findings demonstrate the need for policies that enhance access to cleaner fuels in both rural and urban areas, and for controlling traffic emissions in cities in sub-Saharan Africa.

22Atmospheric lead (Pb) concentrations in São Paulo city, Brazil, remain significant, despite the fact that leaded 23 gasoline has been phased out. The use of its isotope signature allows tracing emissions from increasing car 24 numbers, urban construction, and industrial emissions in this extremely populated area. High-precision and 25 accurate stable isotope ratio determinations using isotope dilution thermal ionization mass spectrometry (ID-26 TIMS) combined with particle induced X-ray emission (PIXE) and multivariate analysis were used to identify

, and is published here as part of a special grouping of papers from that conference. Several studies indicate that mortality and morbidity can be well correlated to atmospheric aerosol concentrations with aerodynamic diameter less than 2.5 µm (PM 2.5). In this work the PM 2.5 at Recife city was analyzed as part of a main research project (INAIRA) to evaluate the air pollution impact on human health in six Brazilian metropolitan areas. The average concentration, for 309 samples (24-hr), from June 2007 to July 2008, was 7.3 µg/m 3 , with an average of 1.1 µg/m 3 of black carbon. The elemental concentrations of samples were obtained by x-ray fluorescence. The concentrations were then used for characterizing the aerosol, and also were employed for receptor modelling to identify the major local sources of PM 2.5. Positive matrix factorization analysis indicated six main factors, with four being associated to soil dust, vehicles and sea spray, metallurgical activities, and biomass burning, while for a chlorine factor, and others related to S, Ca, Br, and Na, we could make no specific source association. Principal component analysis also indicated six dominant factors, with some specific characteristics. Four factors were associated to soil dust, vehicles, biomass burning, and sea spray, while for the two others, a chlorine-and copper-related factor and a nickel-related factor, it was not possible to do a specific source association. The association of the factors to the likely sources was possible thanks to meteorological analysis and sources information. Each model, although giving similar results, showed factors' peculiarities, especially for source apportionment. The observed PM 2.5 concentration levels were acceptable, notwithstanding the high urbanization of the metropolitan area, probably due to favorable conditions for air pollution dispersion. More than a valuable historical register, these results should be very important for the next analysis, which will correlate health data, PM 2.5 levels, and sources contributions in the context of the six studied Brazilian metropolises. Implications: The analysis of fine particulate matter (PM 2.5) in Recife city, Brazil, gave a significant picture of the local concentration and composition of this pollutant, which exhibits robust associations to adverse human health effects. Data from 1 year of sampling evaluated the seasonal variability and its connections with weather patterns. Source apportionment in this metropolitan area was obtained based in a combination of receptor models: principal component analysis (PCA)/chemical mass balance (CMB) and positive matrix factorization (PMF). These results give guidelines for local air pollution control actions, providing significant information for a health study in the context of establishing a new national air pollution protocol based on Brazilian cities data.

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