Modelling the air quality benefits of EU climate mitigation policies using two different PM2.5-related health impact methodologies.

The EU, seeking to be a global leader in the fight against climate change, is moving ahead with ambitious policies to mitigate greenhouse gases emissions. In this context, the Fit for 55 package (FF55) is a set of proposals to revise and update EU legislation, to ensure that policies are in line with the climate goals of cutting emissions by at least 55% by 2030. Whilst these policies are designed for climate purposes, they will have positive side-effects (co-benefits) on air quality. Separately, additional policies are also in place to reduce emissions of related air pollutants and to improve air quality concentrations on EU territory. In this work, through a modelling study, we analyse the benefits of these policies via the health benefits arising from the resulting reductions in yearly average PM2.5 concentrations. Results are analysed by assessing and comparing morbidity and mortality impacts as computed using both the HRAPIE (Health risks of air pollution in Europe, WHO, as implemented in the CaRBonH model) and the GBD (Global Burden of Disease, as implemented in FASST-GBD model) approaches. Even when considering the uncertainty and variability in the results obtained using the two approaches, it is clear that EU policies can bring health and economic benefit in EU, with several Billions of Euro of benefits both in terms of morbidity and mortality indicators.

Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas.

This work presents the results of a PM2.5 source apportionment study conducted in urban background sites from 16 European and Asian countries. For some Eastern Europe and Central Asia cities this was the first time that quantitative information on pollution source contributions to ambient particulate matter (PM) has been performed. More than 2200 filters were sampled and analyzed by X-Ray Fluorescence (XRF), Particle-Induced X-Ray Emission (PIXE), and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) to measure the concentrations of chemical elements in fine particles. Samples were also analyzed for the contents of black carbon, elemental carbon, organic carbon, and water-soluble ions. The Positive Matrix Factorization receptor model (EPA PMF 5.0) was used to characterize similarities and heterogeneities in PM2.5 sources and respective contributions in the cities that the number of collected samples exceeded 75. At the end source apportionment was performed in 11 out of the 16 participating cities. Nine major sources were identified to have contributed to PM2.5: biomass burning, secondary sulfates, traffic, fuel oil combustion, industry, coal combustion, soil, salt and "other sources". From the averages of sources contributions, considering 11 cities 16% of PM2.5 was attributed to biomass burning, 15% to secondary sulfates, 13% to traffic, 12% to soil, 8.0% to fuel oil combustion, 5.5% to coal combustion, 1.9% to salt, 0.8% to industry emissions, 5.1% to "other sources" and 23% to unaccounted mass. Characteristic seasonal patterns were identified for each PM2.5 source. Biomass burning in all cities, coal combustion in Krakow/POL, and oil combustion in Belgrade/SRB and Banja Luka/BIH increased in Winter due to the impact of domestic heating, whereas in most cities secondary sulfates reached higher levels in Summer as a consequence of the enhanced photochemical activity. During high pollution days the largest sources of fine particles were biomass burning, traffic and secondary sulfates.

Representativeness of an air quality monitoring station for PM2.5 and source apportionment over a small urban domain.

In this study, PM2.5 concentrations together with the water-soluble ionic compounds and total elements were simultaneously measured at 16 sites in the city of Varese located in Northern Italy within a domain of 2 × 2 km2. The center point of this domain consisted of an existing urban air quality monitoring station. The representativeness of the monitoring station for PM2.5 mass and chemical composition was estimated using a methodology relying on statistical/geostatistical analyses. Source apportionment by means of the Chemical Mass Balance (CMB) receptor model was also performed to evaluate the spatial distribution of source contribution throughout the domain. Very high soluble fraction was found for Cd, Sb, K and V, indicating the anthropogenic origin of those elements. The geostatistical analysis/mapping showed that the monitoring station captured the spatial variation of PM2.5 and most of the anthropogenic originated elements, e.g., As, Cd and V, whereas it did not captured the spatial patterns of the ones originated from both natural and anthropogenic sources, e.g., Na, Ni, Pb, K, Zn, Fe, Cr, and Ti. The CMB source contribution estimations in the monitoring station were at least 25% different from many sites of the domain for PM2.5. The significant spatial variation in concentrations and source contribution estimates showed that the monitoring station could not be considered representative for the air quality monitoring studies with exposure assessment and source apportionment purposes in Varese.

Source apportionment to support air quality planning: Strengths and weaknesses of existing approaches.

Information on the origin of pollution constitutes an essential step of air quality management as it helps identifying measures to control air pollution. In this work, we review the most widely used source-apportionment methods for air quality management. Using theoretical and real-case datasets we study the differences among these methods and explain why they result in very different conclusions to support air quality planning. These differences are a consequence of the intrinsic assumptions that underpin the different methodologies and determine/limit their range of applicability. We show that ignoring their underlying assumptions is a risk for efficient/successful air quality management as these methods are sometimes used beyond their scope and range of applicability. The simplest approach based on increments (incremental approach) is often not suitable to support air quality planning. Contributions obtained through mass-transfer methods (receptor models or tagging approaches built in air quality models) are appropriate to support planning but only for specific pollutants. Impacts obtained via "brute-force" methods are the best suited but it is important to assess carefully their application range to make sure they reproduce correctly the prevailing chemical regimes.

Sources and geographic origin of particulate matter in urban areas of the Danube macro-region: The cases of Zagreb (Croatia), Budapest (Hungary) and Sofia (Bulgaria).

The contribution of main PM pollution sources and their geographic origin in three urban sites of the Danube macro-region (Zagreb, Budapest and Sofia) were determined by combining receptor and Lagrangian models. The source contribution estimates were obtained with the Positive Matrix Factorization (PMF) receptor model and the results were further examined using local wind data and backward trajectories obtained with FLEXPART. Potential Source Contribution Function (PSCF) analysis was applied to identify the geographical source areas for the PM sources subject to long-range transport. Gas-to-particle transformation processes and primary emissions from biomass burning are the most important contributors to PM in the studied sites followed by re-suspension of soil (crustal material) and traffic. These four sources can be considered typical of the Danube macro-region because they were identified in all the studied locations. Long-range transport was observed of: a) sulphate-enriched aged aerosols, deriving from SO2 emissions in combustion processes in the Balkans and Eastern Europe and b) dust from the Saharan and Karakum deserts. The study highlights that PM pollution in the studied urban areas of the Danube macro-region is the result of both local sources and long-range transport from both EU and no-EU areas.

Why air quality in the Alps remains a matter of concern. The impact of organic pollutants in the alpine area.

In the middle of Europe, the Alps form a geographical and meteorological trap for atmospheric pollutants including volatile and semi-volatile organic compounds emitted in the surrounding lowlands. This is due to their barrier effects, high precipitation rates, and low ambient temperatures. Also the pollutants emitted in the cities inside the Alps spread in the region depending on orographic and meteorological conditions. Although a number of studies on the distribution and effect of pollutants in the Alps has been published, comprehensive information on potential hazards, and ways to improve this sensible environment are lacking. This opinion paper is the result of a discussion during the Winterseminar of the AlpsBioCluster project in Munich. It summarizes the current literature and presents some case studies on local pollution sources in the Alps, and the possibility of using biomonitoring techniques to assess critical pollution loads and distributions.

A comparison of Alpine emissions to forest soil and spruce needle loads for persistent organic pollutants (POPs).

The project MONARPOP analysed the concentrations of semivolatile organic compounds (SVOCs) in two important sink compartments, needles of Norway spruce (Picea abies [L.] Karst.) and forest soil from 40 remote Alpine forest sites in Austria, Germany, Italy, Slovenia and Switzerland. In the present study the load of PCDD/F, PCB, PBDE, PAH, HCB, HCH and DDT in the Alps calculated on the basis of measured data are compared with their estimated emissions in the Alpine region. It comes out that the masses of the studied pollutants stored in the forests are higher than the corresponding emissions in the Alpine area indicating that the Alps are a sink for POPs advected from surrounding areas. It is assumed that local emissions of PCDD/F and PAH deriving from biomass burning are probably underestimated and that the pool of these pollutants in the forests represents the accumulation over some decades.