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As a particular form of biomass burning (BB), domesticheating with firewood is a major source of fine dust inthe cold season. Understanding its impact on air qualityrequires reliable aerosol source apportionment andassessment of prevailing loss processes. Further, to establisheffective mitigation policies, it is necessary toaccurately quantify the contribution of local vs. remotesources to the aerosol burden. To this end, source-receptormodelling is employed, such as chemical massbalance or Lagrangian techniques, to calculate concentrationsof the BB specific tracer in aerosol, levoglucosan(Fine et al. 2002, Chunmao et al. 2019). In the lastdecades, it has been shown that combining stable isotoperatios with concentration measurements allows forseparating the impact of chemical degradation fromchanges linked to source strength or atmospherictransport. Based on that, Gensch et al. (2018) developeda numerical approach, comparing stable carbonisotopic ratio and concentration measurements withback trajectory analyses by the Lagrangian particle dispersionmodel FLEXPART (https://www.flexpart.eu/) toinvestigate chemical aging processes in BB aerosol.In the present study, stable carbon isotopes were implementedin the full dispersed output of FLEXPART byexplicitly tracking of the levoglucosan fraction containing13C. Further, sensitivity studies were carried out toexamine the simulation responses to the uncertaintiesof the governing atmospheric processes described inFLEXPART and thus, to determine the model performancefor given conditions. Finally, the set of selectedmodelling routines were applied in a case study with thegoal to assess the contribution of local vs. remotesources of biomass burning emissions from residentialheating to the particulate matter sampled at twomeasurement stations of the North Rhine-WestphaliaEnvironmental Agency, LANUV. Thereby, the measuredlevoglucosan concentration and isotopic composition in50 selected aerosol samples taken at an urbanbackground station in Mülheim-Styrum and at a ruralbackground station in the Eifel, in the cold seasons of2015 - 2017 were compared with the model results.The simulations indicate that the biggest fraction of thesampled aerosol is 1 to 2 days old. Chemical aging, alsolimited by low mean OH concentrations in the cold season,has thus a minor influence on the observedlevoglucosan concentration and δ13C (Fig. 1). Theexperimental data, interpreted as a two end-membermixing series between low-concentration/isotopicallyheavyback-ground and high-concentration/isotopicallylightfresh emissions, support the model outcome,showing similar isotopic ratios for the two constituents.The high variability in the observed δ13C implies that thelocal levoglucosan emissions are characterized by verydifferent isotopic ratios in the range of -25.3 to -21.4 %(Fig. 1 in Pdf). These values are in good agreement withprevious studies on levoglucosan source specificisotopic composition in BB aerosol (Sang et al. 2012).These findings demonstrate that the aerosol burdenfrom residential heating in living areas is of local originand thus, mitigation is possible through reduction oflocal emissions. In this work we show that combiningLagrangian modelling with isotope ratios is valuable toobtain additional insight in source apportionment.There is, though, a need for a better isotopic descriptionof sources. Moreover, studies investigating long rangetransport of BB aerosol from large-scale fires in the dryseason are essential to examine the role of aging amongother loss processes.Fine, P.M., Cass, G.R. and Simoneit, B.R.T. (2002) J. Geophys.Res., [Atmos.], doi 10.1029/2001jd000661Chunmao, Z., Yugo, K., et al. (2019) Environ. Pollut., doi10.1016/j.envpol.2019.01.003Gensch, I., Sang, X.F., et al. (2018) Environ. Sci.&Tech.,doi 10.1021/acs.est.8b03054Sang, X.F., Gensch, I., et al. (2012) Environ. Sci.&Tech.,doi 10.1021/ es204094v

Background: Recent epidemiological studies investigating the modifying effect of air temperature in ozone-mortality associations lack consensus as how to adjust for nonlinear and lagged temperature effect in addition to including an interaction term. Methods: We evaluated the influence of temperature confounding control on temperature-stratified ozone-mortality risks in a time series setting in eight European cities and 86 US cities, respectively. To investigate potential residual confounding, we additionally incorporated next day's ozone in models with differing temperature control. Results: Using only a categorical variable for temperature or only controlling nonlinear effect of low temperatures yielded highly significant ozone effects at high temperatures but also significant residual confounding in both regions. Adjustment for nonlinear effect of temperature, especially high temperatures, substantially reduced ozone effects at high temperatures and residual confounding. Conclusions: Inadequate control for confounding by air temperature leads to residual confounding and an overestimation of the temperature-modifying effect in studies of ozone-related mortality. © 2018 The Authors. Published by Wolters Kluwer Health

Background: Epidemiologic evidence on the association between short-term exposure to ultrafine particles and mortality is weak, due to the lack of routine measurements of these particles and standardized multicenter studies. We investigated the relationship between ultrafine particles and particulate matter (PM) and daily mortality in eight European urban areas. Methods: We collected daily data on nonaccidental and cardiorespiratory mortality, particle number concentrations (as proxy for ultrafine particle number concentration), fine and coarse PM, gases and meteorologic parameters in eight urban areas of Finland, Sweden, Denmark, Germany, Italy, Spain, and Greece, between 1999 and 2013. We applied city-specific time-series Poisson regression models and pooled them with random-effects meta-analysis. Results: We estimated a weak, delayed association between particle number concentration and nonaccidental mortality, with mortality increasing by approximately 0.35% per 10,000 particles/cm 3 increases in particle number concentration occurring 5 to 7 days before death. A similar pattern was found for cause-specific mortality. Estimates decreased after adjustment for fine particles (PM 2.5) or nitrogen dioxide (NO 2). The stronger association found between particle number concentration and mortality in the warmer season (1.14% increase) became null after adjustment for other pollutants. Conclusions: We found weak evidence of an association between daily ultrafine particles and mortality. Further studies are required with standardized protocols for ultrafine particle data collection in multiple European cities over extended study periods. © 2016 Wolters Kluwer Health, Inc. All rights reserved.

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements.We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning.PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10.Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM. © 2015 Elsevier Ltd.

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM 2.5) explaining on average between 67 and 79% of the concentration variance (R2) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R2 ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R2 under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE. © 2013 American Chemical Society.

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM2.5, PM2.5 absorbance, PM10, and PMcoarse were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R2) was 71% for PM2.5 (range across study areas 35-94%). Model R2 was higher for PM2.5 absorbance (median 89%, range 56-97%) and lower for PMcoarse (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R2 was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R2 results were on average 8-11% lower than model R2. Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE. © 2012 American Chemical Society.

The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates relationships between long-term exposure to outdoor air pollution and health using cohort studies across Europe. This paper analyses the spatial variation of PM2.5, PM2.5 absorbance, PM10 and PMcoarse concentrations between and within 20 study areas across Europe.We measured NO2, NOx, PM2.5, PM2.5 absorbance and PM10 between October 2008 and April 2011 using standardized methods. PMcoarse was determined as the difference between PM10 and PM2.5. In each of the twenty study areas, we selected twenty PM monitoring sites to represent the variability in important air quality predictors, including population density, traffic intensity and altitude. Each site was monitored over three 14-day periods spread over a year, using Harvard impactors. Results for each site were averaged after correcting for temporal variation using data obtained from a reference site, which was operated year-round.Substantial concentration differences were observed between and within study areas. Concentrations for all components were higher in Southern Europe than in Western and Northern Europe, but the pattern differed per component with the highest average PM2.5 concentrations found in Turin and the highest PMcoarse in Heraklion. Street/urban background concentration ratios for PMcoarse (mean ratio 1.42) were as large as for PM2.5 absorbance (mean ratio 1.38) and higher than those for PM2.5 (1.14) and PM10 (1.23), documenting the importance of non-tailpipe emissions. Correlations between components varied between areas, but were generally high between NO2 and PM2.5 absorbance (average R2 = 0.80). Correlations between PM2.5 and PMcoarse were lower (average R2 = 0.39). Despite high correlations, concentration ratios between components varied, e.g. the NO2/PM2.5 ratio varied between 0.67 and 3.06.In conclusion, substantial variability was found in spatial patterns of PM2.5, PM2.5 absorbance, PM10 and PMcoarse. The highly standardized measurement of particle concentrations across Europe will contribute to a consistent assessment of health effects across Europe. © 2012 Elsevier Ltd.

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The identification of sources is one of the prerequisites for the implementation of the Air Quality Directive (AQD). It provides scientific support to the development and periodic revision of air quality plans and short term action plans and to the quantification of categories with special status like long range transport, natural sources and winter road salting and sanding. The suitability of receptor models (RM) for the apportionment of pollutant sources in the implementa-tion of the AQD is testified by the amount of published studies in 2005 and 2010 in correspondence with the entry into force of new provisions for PM10 and PM2,5, respectively. In recent years, Member States were requested to provide official estimations of source contribution to the Commission like the quantification of natural sources in 2006 and PM10 time extension reports in 2009 (Fragkou et al., 2011). These experiences have shown that al-though this kind of methodology is used by about 60 % of the European experts involved in source apportion-ment there is a considerable variability in the methodo-logical approaches and adopted tools. Furthermore, there are critical steps that require strict quality assurance standards and skilled practitioners (e.g. identification of the appropriate number of sources). In order to foster harmonization in this field, the JRC has promoted a number of interconnected initiatives linked to FAIRMODE. One of those was to set up a group of experts with skills in different areas to assess RM methodologies and propose common criteria and procedures for source apportionment studies. The infor-mation collected was summarized in a document which is intended to serve as a basis for a common Receptor Model Technical Protocol (RMTP). The RMTP is addressed to different kinds of us-ers: Policy makers and managers interested in the output of RMs for development of mitigation measures, air quality experts and scientists unfamiliar with these tech-niques, and RM practitioners involved in the model ex-ecution and interpretation of results. In order to address such heterogeneous readership the document was designed to be accessible at different levels. The RMTP is organized in three sections : an introduction to present the methodology to the unskilled reader, illustrating its capabilities and recom-mending when and how to use it ; a core section concerning the most common RM methodologies for source apportionment with in-depth analysis boxes for more experienced readers. The section is structured in 13 chapters following, as a check list, the logical steps to accomplish a source apportionment study. The first chapters deal with preliminary activities like the evaluation of the study area, collection of exist-ing information and experimental design. In the follow-ing chapters data collection and data treatment are dis-cussed. The section includes also chapters regarding spe-cific aspects of widely used methodologies like CMB, Factor Analysis, and PMF. The evaluation of test per-formance and reporting are discussed in the last part of this section ; the third section of the document was conceived to give an insight on the capabilities and the possible future trends in RM methodology. It consists of four chapters dealing with advanced, innovative techniques for which ready- to-use tools are already available or under development : trajectory analysis combined with RM, constrained and expanded models, AMS data processing, and the aethalometer model. The document includes a number of annexes to provide additional and practical information on specific topics, and examples.

The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates long-term effects of exposure to air pollution on human health in Europe. This paper documents the spatial variation of measured NO2 and NOx concentrations between and within 36 ESCAPE study areas across Europe.In all study areas NO2 and NOx were measured using standardized methods between October 2008 and April 2011. On average, 41 sites were selected per study area, including regional and urban background as well as street sites. The measurements were conducted in three different seasons, using Ogawa badges. Average concentrations for each site were calculated after adjustment for temporal variation using data obtained from a routine monitor background site.Substantial spatial variability was found in NO2 and NOx concentrations between and within study areas; 40% of the overall NO2 variance was attributable to the variability between study areas and 60% to variability within study areas. The corresponding values for NOx were 30% and 70%. The within-area spatial variability was mostly determined by differences between street and urban background concentrations. The street/urban background concentration ratio for NO2 varied between 1.09 and 3.16 across areas. The highest median concentrations were observed in Southern Europe, the lowest in Northern Europe.In conclusion, we found significant contrasts in annual average NO2 and NOx concentrations between and especially within 36 study areas across Europe. Epidemiological long-term studies should therefore consider different approaches for better characterization of the intra-urban contrasts, either by increasing of the number of monitors or by modelling. © 2012 Elsevier Ltd.