h i g h l i g h t sCombining deposition and dispersion helps designing urban vegetation related to air quality. The dilution of emissions with clean air from aloft is crucial; limit high urban vegetation. High concentrations of air pollutants increase deposition; vegetation should be close to the source. Air floating above, and not through, vegetation barriers is not filtered; decides barrier porosity. Differently designed vegetation catch different particle sizes. a b s t r a c tUrban vegetation affects air quality through influencing pollutant deposition and dispersion. Both processes are described by many existing models and experiments, on-site and in wind tunnels, focussing e.g. on urban street canyons and crossings or vegetation barriers adjacent to traffic sources. There is an urgent need for well-structured experimental data, including detailed empirical descriptions of parameters that are not the explicit focus of the study.This review revealed that design and choice of urban vegetation is crucial when using vegetation as an ecosystem service for air quality improvements. The reduced mixing in trafficked street canyons on adding large trees increases local air pollution levels, while low vegetation close to sources can improve air quality by increasing deposition. Filtration vegetation barriers have to be dense enough to offer large deposition surface area and porous enough to allow penetration, instead of deflection of the air stream above the barrier. The choice between tall or short and dense or sparse vegetation determines the effect on air pollution from different sources and different particle sizes.

Abstract. Aerosol emissions from vegetation fires have a large impact on air quality and climate. In this study, we use published experimental data and different fitting procedures to derive dynamic particle number and mass emission factors (EFPN, EFPM) related to the fuel type, burning conditions and the mass of dry fuel burned, as well as characteristic CO-referenced emission ratios (PN/CO, PM/CO). Moreover, we explore and characterize the variability of the particle size distribution of fresh smoke, which is typically dominated by a lognormal accumulation mode with count median diameter around 120 nm (depending on age, fuel and combustion efficiency), and its effect on the relationship between particle number and mass emission factors. For the particle number emission factor of vegetation fires, we found no dependence on fuel type and obtained the following parameterization as a function of modified combustion efficiency (MCE): EFPN=34×1015×(1−MCE) kg−1±1015 kg−1 with regard to dry fuel mass (d.m.). For the fine particle mass emission factors (EFPM) we obtained (86–85×MCE) g kg−1±3 g kg−1 as an average for all investigated fires; (93–90×MCE) g kg−1±4 g kg−1 for forest; (67–65×MCE) g kg−1±2 g kg−1 for savanna; (63–62×MCE) g kg−1±1 g kg−1 for grass. For the PN/CO emission ratio we obtained an average of (34±16) cm−3 ppb−1 exhibiting no systematic dependence on fuel type or combustion efficiency. The average PM/CO emission ratios were (0.09±0.04) g g−1 for all investigated fires; (0.13±0.05) g g−1 for forest; (0.08±0.03) g g−1 for savanna; and (0.07±0.03) g g−1 for grass. The results are consistent with each other, given that particles from forest fires are on average larger than those from savanna and grass fires. This assumption and the above parameterizations represent the current state of knowledge, but they are based on a rather limited amount of experimental data which should be complemented by further measurements. Nevertheless, the presented parameterizations appear sufficiently robust for exploring the influence of vegetation fires on aerosol particle number and mass concentrations in regional and global model studies.

Abstract. Aerosol emissions from vegetation fires have a large impact on air quality and climate. In this study, we use published experimental data and different fitting procedures to derive dynamic particle number and mass emission factors (EFPN, EFPM) related to the fuel type, burning conditions and the mass of dry fuel burned, as well as characteristic CO-referenced emission ratios (PN/CO, PM/CO). Moreover, we explore and characterize the variability of the particle size distribution of fresh smoke, which is typically dominated by a lognormal accumulation mode with count median diameter around 120 nm (depending on age, fuel and combustion efficiency), and its effect on the relationship between particle number and mass emission factors. For the particle number emission factor of vegetation fires, we found no dependence on fuel type and obtained the following parameterization as a function of modified combustion efficiency (MCE): EFPN=34·1015×(1-MCE) kg−1±1015 kg−1 with regard to dry fuel mass (d.m.). For the fine particle mass emission factors (EFPM) we obtained (86–85×MCE) g kg−1±3 g kg−1 as an average for all investigated fires; (93–90×MCE) g kg

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Abstract. Sources of airborne particulate matter and their seasonal variation in urban areas in Sub-Saharan Africa are poorly understood due to lack of long-term measurement data. In view of this, filter samples of airborne particulate matter (particle diameter ≤2.5 μm, PM2.5) were collected between May 2008 and April 2010 at two sites (urban background site and suburban site) within the Nairobi metropolitan area. A total of 780 samples were collected and analyzed for particulate mass, black carbon (BC) and 13 trace elements. The average PM2.5 concentration at the urban background site was 21±9.5 μg m−3, whereas the concentration at the suburban site was 13±7.3 μg m−3. The daily PM2.5 concentrations exceeded 25 μg m−3 (the World Health Organization 24 h guideline value) on 29% of the days at the urban background site and 7% of the days at the suburban site. At both sites, BC, Fe, S and Cl accounted for approximately 80% of all detected elements. Positive matrix factorization analysis identified five source factors that contribute to PM2.5 in Nairobi, namely traffic, mineral dust, industry, combustion and a mixed factor (composed of biomass burning, secondary aerosol and aged sea salt). Mineral dust and traffic factors were related to approximately 74% of PM2.5. The identified source factors exhibited seasonal variation, apart from the traffic factor, which was prominently consistent throughout the sampling period. Weekly variations were observed in all factors, with weekdays having higher concentrations than weekends. The results provide information that can be exploited for policy formulation and mitigation strategies to control air pollution in Sub-Saharan African cities.

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