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A large number of studies have shown much higher health effects of particulate matter (PM) during the warm compared to the cold season. In this paper we present the results of an experimental study carried out in an unoccupied test apartment with the aim of understanding the reasons behind the seasonal variations of the health effects due to ambient PM 2.5 exposure. Measurements included indoor and outdoor PM 2.5 mass and chemical composition as well as particle size distribution of ultrafine particles. Monitoring campaigns were carried out during summer and winter following a ventilation protocol developed to replicate typical occupant behaviour according to a questionnaire-based survey. Our findings showed that seasonal variation of the relationship between ambient and indoor mass concentrations cannot entirely explain the apparent difference in PM toxicity between seasons and size distribution and chemical composition of particles were identified as other possible causes of changes in the apparent PM toxicity. A marked decrease of ultrafine particles (<100 nm) passing from outdoors to indoors was observed during winter; this resulted in higher indoor exposure to nanoparticles (<50 nm) during summer. With regards to the chemical composition, a pooled analysis showed infiltration factors of chemical species similar to that obtained for PM 2.5 mass with values increasing from 0.73 during winter to 0.90 during summer and few deviations from the pooled estimates. In particular, significantly lower infiltration factors and sink effect were found for nitrates and ammonium during winter. In addition, a marked increase in the contribution of indoor and outdoor sulfates to the total mass was observed during summer. [ABSTRACT FROM AUTHOR]

This paper revisits the emission scenarios of the European Commission's 2005 Thematic Strategy on Air Pollution (TSAP) in light of today's knowledge. We review assumptions made in the past on the main drivers of emission changes, i.e., demographic trends, economic growth, changes in the energy intensity of GDP, fuel-switching, and application of dedicated emission control measures. Our analysis shows that for most of these drivers, actual trends have not matched initial expectations. Observed ammonia and sulfur emissions in European Union in 2010 were 10% to 20% lower than projected, while emissions of nitrogen oxides and particulate matter exceeded estimates by 8% to 15%. In general, a higher efficiency of dedicated emission controls compensated for a lower-than-expected decline in total energy consumption as well as a delay in the phase-out of coal. For 2020, updated projections anticipate lower sulfur and nitrogen oxide emissions than those under the 2005 baseline, whereby the degree to which these emissions are lower depends on what assumptions are made for emission controls and new vehicle standards. Projected levels of particulates are about 10% higher, while smaller differences emerge for other pollutants. New emission projections suggest that environmental targets established by the TSAP for the protection of human health, eutrophication and forest acidification will not be met without additional measures. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an evaluation of the European type-approval test procedure for evaporative emissions from passenger cars based on real-world mobility data. The study relies on two large databases of driving patterns from conventional fuel vehicles collected by means of on-board GPS systems in the Italian provinces of Modena and Firenze. Approximately 28,000 vehicles were monitored, corresponding to approximately 36millionkilometres over a period of one month. The driving pattern of each vehicle was processed to derive the relation between trip length and parking duration, and the rate of occurrence of parking events against multiple evaporative cycles, defined on the basis of the type-approval test procedure as 12-hour diurnal time windows. These results are used as input for an emission simulation model, which calculates the total evaporative emissions given the characteristics of the evaporative emission control system of the vehicle and the ambient temperature conditions. The results suggest that the evaporative emission control system, fitted to the vehicles from Euro 3 step and optimised for the current type-approval test procedure, could not efficiently work under real-world conditions, resulting in evaporative emissions well above the type-approval limit, especially for small size vehicles and warm climate conditions. This calls for a revision of the type-approval test procedure in order to address real-world evaporative emissions. [Copyright &y& Elsevier]

Abstract: Many countries are developing models to estimate N emissions in rivers as part of national-scale water quality assessments. Generally, models are applied with national databases, while at the regional scale, more detailed databases are sometimes available. This paper discusses pros and cons of developing regionalized models versus applying countrywide models. A case study is used to support the discussion. The model used, called Nutting-N (NUTrient Transfer modelING-Nitrogen), relies on a statistical approach linking nitrogen sources and watershed land and river characteristics and aims to evaluate the risk of water bodies failing to reach quality objectives defined by national and federal policies. After calibration and evaluation at the national scale (France), the predictive quality of the model was compared with two regionalized models in a crystalline massif (Brittany, western France, 27,000km2) and in a sedimentary basin (Seine, Paris basin, 78,000km2), where detailed regional databases are available. The national-scale model provided robust predictions in most conditions encountered in France (efficiency=0.69). Terrestrial retention was related mainly to specific runoff, and its median value was estimated at 49% of the N surplus, whereas median river retention represented 18% of incoming N discharge. Regionalizing the model generally improved goodness-of-fit, as the root mean squared error was reduced by 6–24%. However, precision of parameter estimates degraded when too few monitoring basins were available or when variability in land and river characteristics was too low in the calibration dataset. Hence, regional-scale models should be advocated only after the trade-off between improvement of fit and degradation of parameter estimates is examined. [Copyright &y& Elsevier]

Abstract: Receptor models are useful tools to identify sources of a specific pollutant and to estimate the quantitative contributions of each source based on environmental data. This paper reports on similarities and differences in results achieved when testing three receptor models for estimating the sources of polycyclic aromatic hydrocarbons (PAHs) in soils from Huanghuai Plain, China. The three tested models are Principal Component Analysis with Multiple Linear Regression (PCA-MLR), Positive Matrix Factorization (PMF) and Unmix. Overall source contributions as well as modeled ∑PAHs concentrations compared well among models. All three models apportioned three common PAH sources: wood/biomass burning, fossil fuel combustion and traffic emission, which contributed on average 27.7%, 53.0% and 19.3% by PCA-MLR, 36.9%, 27.2% and 16.3% by PMF, and 47.8%, 21.1% and 18.3% by Unmix to the total sum of PAHs (∑PAHs), respectively. Moreover, the spatial evolution of the common sources were well correlated among models (r=0.83–0.99, p <0.001). In addition, the PMF and Unmix models allowed segregating an additional source from the fossil fuel combustion source, with 19.6% and 11.8% contributions to ∑PAHs, respectively. The current findings further validate that different receptor models provide divergent source profiles, which are mainly attributed to both the model itself and/or the underlying dataset. It is therefore generally recommended to apply multiple techniques to determine the source apportionment in order to minimize individual-method weaknesses and thereby to strengthen the conclusion. [Copyright &y& Elsevier]