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Tropospheric ozone (O-3) concentrations are observed to increase with temperature in urban and rural locations. We investigated the apparent temperature dependency of daytime ozone concentration in the Finnish boreal forest in summertime based on long-term measurements. We used statistical mixed effects models to separate the direct effects of temperature from other factors influencing this dependency, such as weather conditions, long-range transport of precursors, and concentration of various hydrocarbons. The apparent temperature dependency of 1.16 ppb ?(-1) based on a simple linear regression was reduced to 0.87 ppb ?(-1) within the canopy for summer daytime data after considering these factors. In addition, our results indicated that small oxygenated volatile organic compounds may play an important role in the temperature dependence of O-3 concentrations in this dataset from a low-NOx environment. Summertime observations and daytime data were selected for this analysis to focus on an environment that is significantly affected by biogenic emissions. Despite limitations due to selection of the data, these results highlight the importance of considering factors contributing to the apparent temperature dependence of the O-3 concentration. In addition, our results show that a mixed effects model achieves relatively good predictive accuracy for this dataset without explicitly calculating all processes involved in O-3 formation and removal.

A reliable assessment of the optical properties of atmospheric black carbon is of crucial importance for an accurate estimation of radiative forcing. In this study we investigated the spatio-temporal variability of the mass absorption cross-section (MAC) of atmospheric black carbon, defined as light absorption coefficient (σap) divided by elemental carbon mass concentration (mEC). σap and mEC have been monitored at supersites of the ACTRIS network for a minimum period of one year. The 9 rural background sites considered in this study cover southern Scandinavia, central Europe and the Mediterranean. σap was determined using filter based absorption photometers and mEC using a thermal-optical technique. Homogeneity of the data-set was ensured by harmonization of all involved methods and instruments during extensive intercomparison exercises at the European Center for Aerosol Calibration (ECAC). Annual mean values of σap at a wavelength of 637 nm vary between 0.66 and 1.3 Mm−1 in southern Scandinavia, 3.7–11 Mm−1 in Central Europe and the British Isles, and 2.3–2.8 Mm−1 in the Mediterranean. Annual mean values of mEC vary between 0.084 and 0.23 μg m−3 in southern Scandinavia, 0.28–1.1 in Central Europe and the British Isles, and 0.22–0.26 in the Mediterranean. Both σap and mEC in southern Scandinavia and Central Europe have a distinct seasonality with maxima during the cold season and minima during summer, whereas at the Mediterranean sites an opposite trend was observed. Annual mean MAC values were quite similar across all sites and the seasonal variability was small at most sites. Consequently, a MAC value of 10.0 m2 g−1 (geometric standard deviation = 1.33) at a wavelength of 637 nm can be considered to be representative of the mixed boundary layer at European background sites, where BC is expected to be internally mixed to a large extent. The observed spatial variability is rather small compared to the variability of values in previous literature, indicating that the harmonization efforts resulted in substantially increased precision of the reported MAC. However, absolute uncertainties of the reported MAC values remain as high as ± 30–70% due to the lack of appropriate reference methods and calibration materials. The mass ratio between elemental carbon and non-light-absorbing matter was used as a proxy for the thickness of coatings around the BC cores, in order to assess the influence of the mixing state on the MAC of BC. Indeed, the MAC was found to increase with increasing values of the coating thickness proxy. This provides evidence that coatings do increase the MAC of atmospheric BC to some extent, which is commonly referred to as lensing effect. © 2016 The Authors, The research leading to these results has received funding from the European Union Seventh Framework Programme (ACTRIS, FP7/2007-2013, grant agreement no. 262254 ). ACTRIS-2 is a European Project supported by the European Commission Horizon 2020 Research and Innovation Framework Programme (ACTRIS-2, H2020-INFRAIA-2014-2015, grant agreement no. 654109 ). This work was also supported by grants from Labex OSUG@2020 (PhD investissements d'avenir – ANR10 LABX56) and from the European Research Council (ERC-CoG 615922-BLACARAT). Appendix A.

This study asserts that the evaluation of pollution reduction strategies should be approached on the basis of health benefits. The framework presented could be used for decision making on the basis of cost effectiveness when the strategies are applied concurrently. Several vehicular pollution control strategies have been proposed in literature for effective management of urban air pollution. The effectiveness of these strategies has been mostly studied as a one at a time approach on the basis of change in pollution concentration. The adequacy and practicality of such an approach is studied in the present work. Also, the assessment of respective benefits of these strategies has been carried out when they are implemented simultaneously. An integrated model has been developed which can be used as a tool for optimal prioritization of various pollution management strategies. The model estimates health benefits associated with specific control strategies. ISC-AERMOD View has been used to provide the cause-effect relation between control options and change in ambient air quality. BenMAP, developed by U.S. EPA, has been applied for estimation of health and economic benefits associated with various management strategies. Valuation of health benefits has been done for impact indicators of premature mortality, hospital admissions and respiratory syndrome. An optimization model has been developed to maximize overall social benefits with determination of optimized percentage implementations for multiple strategies. The model has been applied for sub-urban region of Mumbai city for vehicular sector. Several control scenarios have been considered like revised emission standards, electric, CNG, LPG and hybrid vehicles. Reduction in concentration and resultant health benefits for the pollutants CO, NOx and particulate matter are estimated for different control scenarios. Finally, an optimization model has been applied to determine optimized percentage implementation of specific control strategies with maximization of social benefits, when these strategies are applied simultaneously. (c) 2012 Elsevier Ltd. All rights reserved.

There is evidence that long-range transport of natural and/or anthropogenic particles can have a negative impact on urban air quality. Certain European cities may fail to comply with the currently implemented 24-h PM (10) limit value due to the additional impact of remote sources of particles, which are not controllable at local level. For that reason, reliable methodologies identifying long-range transport patterns and quantifying their contribution to urban PM10 levels are required. In this study, a two-stage clustering methodology was developed and applied to back trajectories arriving in three European cities: Athens, Madrid and Birmingham, which experience large, moderate and small numbers of daily PM10 episodes, respectively. The atmospheric trajectories used in this analysis were computed with HYSPLIT model (NOAA) for a 3-year period. The two-stage cluster analysis has the advantage of providing highly disaggregated trajectory clusters, which proved to correspond to significantly different PM10 levels. In the case of Madrid and Birmingham, clusters of trajectories originating from North Africa and continental Europe, respectively, were strongly associated with the highest PM10 levels recorded in selected monitoring stations. In Athens, long-range transport patterns and trans-boundary influences were less evident, which highlighted the more substantial impact of local emission sources. Finally, two simple statistical indexes were proposed for assessing PM10 episodes associated with different clusters of trajectories. This study has established a practical methodology for examining the impact of long-range atmospheric transport on local air quality, without resorting to high resource-demanding source apportionment techniques. (c) 2007 Published by Elsevier Ltd. Atmospheric Environment

In-use, fuel-based motor vehicle emission factors were determined using measurements made in a highway tunnel in Pittsburgh, Pennsylvania. Concentrations Of PM2.5 mass, CO, CO2, and NO, were measured continuously. Filter-based measurements included PM2.5 mass, organic and elemental carbon (OC and EQ, inorganic ions and metals. Fuel-based emission factors for each pollutant were calculated using a fuel-carbon balance. The weekday traffic volume and fleet composition varied in a consistent diurnal pattern with the estimated fraction of fuel consumed by heavy-duty diesel ve ' hicle (HDDV) traffic ranging from 11% to 36%. The emission rate of most species showed a significant dependence on sample period. NOx, PM2.5, EC and OC emission factors were significantly larger during the early morning, truckdominated period. Emissions of particulate metals associated with brake wear (Cu, Sb, Ba and potentially Ga) were emitted at higher rates during the rush-hour period, which is characterized by slower, stop-and-go traffic. Emission rates of crustal elements (Fe, Ca, Mg, Li), Zn and Mn were highest during the early-morning period when there was more heavytruck traffic. A seasonal shift in average OC/EC ratio for the rush-hour period was observed; fall and summer OC/EC ratios are 1.0+0.6 and 0.26+0.06, respectively. Potential causes for this shift are increased partitioning of semi-volatile organic compounds into the gas phase during the summer months and/or effects of seasonal changes in fuel formulation. Emission factors for HDDV and light-duty vehicles (LDV) classes were estimated using a linear regression of emission factor as a function of fleet composition. The extrapolated emission factors generally agree with previously published measurements, though a substantial range in published values is noted. (c) 2006 Elsevier Ltd. All rights reserved.