Characterization and apportionment of carbonaceous aerosol emission factors from light-duty and heavy-duty vehicle fleets in Maharashtra, India.

This study aims to investigate the characteristics of carbonaceous aerosols and estimate emission factor (EF) based on roadway tunnel measurements, from two distinct vehicular fleets: an all light-duty vehicle (LDV) fleet, and a mixed fleet of 80% LDV and 20% heavy-duty vehicle (HDV). Carbonaceous content (organic carbon: OC and elemental carbon: EC) in total fine particles (PM2.5) accounted for 41% ± 6.8% in LDV fleet and 48% ± 7.2% in mixed fleet. While higher volatile OC dominated in the LDV fleet emissions, in mixed fleet, lower volatile OC and EC emissions dominated due to the presence of higher HDV and super-emitter (SE) fractions which led to significantly higher optically active absorbing aerosols. Reconstructed HDV fleet EF was higher than LDV fleet by 36 times (PM2.5), 19 times (OC) and 51 times (EC). Our findings emphasize the significance of implementing vehicle inspection and maintenance programs, coupled with decarbonization of HDVs to mitigate on-road vehicular emissions in India.

Chemical and oxidative properties of fine particulate matter from near-road traffic sources.

The toxicity associated with the fine particulate matter (PM2.5) has not been well studied, particularly in relation to the emissions from on-road vehicles and other sources in low- and middle-income countries such as India. Thus, a study was conducted to examine the oxidative potential (OP) of PM2.5 at a roadside (RS) site with heavy vehicular traffic and an urban background (BG) site in Mumbai using the dithiothreitol (DTT) assay. Simultaneous gravimetric PM2.5 was measured at both sites and characterized for carbonaceous constituents and water-soluble trace elements and metals. Results depicted higher PM2.5, elemental carbon (EC), and organic carbon (OC) concentrations on the RS than BG (by a factor of 1.7, 4.6, and 1.2, respectively), while BG had higher water-soluble organic carbon (WSOC) levels (by a factor of 1.4) and a higher WSOC to OC ratio (86%), likely due to the dominance of secondary aerosol formation. In contrast, the measured OPDTTv at RS (8.9 ± 5.5 nmol/min/m3) and BG (8.1 ± 6.4 nmol/min/m3) sites were similar. However, OPDTTv at BG was higher during the afternoon, suggesting the influence of photochemical transformation on measured OPDTTv at BG. At RS, OC and redox-active metals (Cu, Zn, Mn, and Fe) were significantly associated with measured OP (p < 0.05), while at BG, WSOC was most strongly associated (p < 0.05). The coefficient of divergence (COD) for PM2.5, its chemical species, and OPDTTv was >0.2, indicating spatial heterogeneity between the sites, and differences in emission sources and toxicity. The estimated hazard index (HI) was not associated with OPDTTv, indicating that current PM2.5 mass regulations may not adequately capture the health effects of PM2.5. The study highlights the need for further studies examining PM2.5 toxicity and developing toxicity-based air quality regulations.

Reassessing the availability of crop residue as a bioenergy resource in India: A field-survey based study.

Second-generation bioenergy, a carbon neutral or negative renewable resource, is crucial to achieving India's net-zero emission targets. Crop residues are being targeted as a bioenergy resource as they are otherwise burned on-field, leading to significant pollutant emissions. But estimating their bioenergy potential is problematic because of broad assumptions about their surplus fractions. Here, we use comprehensive surveys and multivariate regression models to estimate the bioenergy potential of surplus crop residues in India. These are with high sub-national and crop disaggregation that can facilitate the development of efficient supply chain mechanisms for its widespread usage. The estimated potential for 2019 of 1313 PJ can increase the present bioenergy installed capacity by 82% but is likely insufficient alone to meet India's bioenergy targets. The shortage of crop residue for bioenergy, combined with the sustainability concerns raised by previous studies, imply a need to reassess the strategy for the use of this resource.

On-road vehicular emission characterization from the road-tunnel measurements in India: Morphology, emission factors, and sources.

In India, there is very limited data on vehicular emission characterization in real-world driving conditions and the contribution of non-exhaust vehicular emissions to ambient particulate matter (PM) is still unanswered. Furthermore, there are no real-world emission factors (EFs) for the PM constituents. Thus, this study aims to characterize the trace elements and metals, and black carbon (BC) in PM2.5 and PM10 from the light-duty vehicles (LDVs) and mixed vehicular fleet with significant contribution of heavy-duty vehicles (HDVs) through road-tunnel measurements. Real-world EFs were estimated for the measured PM chemical constituents. Further, source apportionment was carried out to find the plausible sources and their contribution to total PM2.5 and PM10 road traffic emissions. Air pollutant and traffic measurements were conducted at two roadway tunnels: Eastern Freeway tunnel (FT; only LDVs) and Kamshet-I tunnel (KT; 80% LDVs & 20% HDVs) in Mumbai, India covering both peak and off-peak traffic hours. Major elements (Al, Ca, Fe, K, Mg, and Na) constitute 90─93% of total measured elemental concentrations in both PM2.5 and PM10 road traffic emissions. Overall, the elemental concentrations were higher for the HDV-dominant fleet than the LDV-fleet for both PM2.5 and PM10. Similarly, BC was higher for the HDV-dominant fleet which is corroborated by the morphological analysis. The measured BC, trace elements and metals EFs in this study were higher than those reported than previous road tunnel studies with similar vehicle composition indicating the presence of high-emitting vehicles in this study. The dominant proportion of PM2.5 road traffic emissions was from the tailpipe (52%) followed by brake wear (30%) and vehicular driven resuspended road dust (18%). Whilst, resuspended road dust (63%) was identified as the major source of PM10 traffic emissions followed by vehicular exhaust (28%) and brake wear (9%). With the potential increase in the share of electric and hybrid vehicles in the vehicular fleet, the relative contribution of non-exhaust emissions to the airborne PM will be more significant. Hence, there is an imminent need to regulate non-exhaust vehicular emissions.

Chemical characteristics and oxidative potential of indoor and outdoor PM2.5 in densely populated urban slums.

A significant proportion of population in metropolitan cities in India live in slums which are highly dense and crowded informal housing settlements with poor environmental conditions including high exposure to air pollution. Recent studies report that toxicity is induced by oxidative processes, mediated by the water-soluble PM chemical components leading to reactive oxygen species production thereby causing inflammatory disorders. Hence, for the first time, this study assessed the chemical characteristics and oxidative potential (OP) of indoor and outdoor PM2.5 in two slums in Mumbai, India. Daily gravimetric PM2.5 was measured in ∼40 homes each in a low- and a high-traffic slum and analysed for 18 water-soluble elements and organic carbon (WSOC). Subsequently, OP was assessed through the Dithiothreitol (DTT) assay. Average WSOC was similar in indoor and outdoor environments while the water-soluble concentrations of total elements ranged 4.5-6.5 µg/m3 indoors and 6.4-19.2 µg/m3 outdoors, with S, Ca, K, Na and Zn being the most abundant elements. Spatial distributions of indoor concentrations were influenced by outdoor sources such as local traffic emissions for Cd, Fe, Al and Zn. The influence of outdoor-origin particles was enhanced in homes reporting high air exchange rates. OP was higher outdoors than indoors in both low-traffic slum (0.04-0.51 nmol min-1m-3 outdoors and 0.02-0.38 nmol min-1m-3 indoors) and high-traffic slum (0.03-1.06 nmol min-1m-3 outdoors and 0.04-0.77 nmol min-1m-3 indoors). Outdoor and indoor OP was also more influenced by outdoor road dust showing significant correlation with tracer elements Cu and Al (r ≥ 0.45; p < 0.05). Similar to OP, the non-carcinogenic health risk associated with indoor PM2.5 were also higher in high-traffic slum (Hazard Index, HI = 1.60) than in low-traffic slum (HI = 0.43). Overall, this study shows that the indoor PM2.5 and its chemical constituents in Mumbai slums are primarily of outdoor origin with higher toxicity and non-carcinogenic health risk in high-traffic slums.

1H NMR structural signatures of source and atmospheric organic aerosols in India.

Organic aerosols (OA) play significant roles in several atmospheric processes and adversely impact human health. This study examines the key structural units present in water- and methanol-soluble organic carbon (WSOC, MSOC) fraction of OA from emission sources (traffic and biomass cooking) and an urban background location in India. Proton nuclear magnetic resonance (1H NMR) spectroscopy was employed to assess the distribution of non-exchangeable proton structural groups of the OAs. Organic carbon, elemental carbon, black carbon, and water-soluble organic carbon (WSOC) analyses were also conducted. The 1H NMR analysis corroborated that the WSOC and MSOC fractions hold similar 1H structural groups; however, they differ in their relative distribution and absolute concentrations across the ambient locations and source emissions. The relative contribution of the proton structural groups to OA was in the order C-H > H-C-C=> H-C-O > Ar-H. The aliphatic concentration was lower in the morning tunnel entry aerosols when compared to other tunnel aerosols, whereas the unsaturated structures (H-C-C= ) were present in all the tunnel aerosols within a range of 47.2-62.3 µmol/m3. The aromatic groups were the maximum in the firewood aerosols, about 1.4 and 3.7 times higher than the crop residue and the mixed fuel aerosols, respectively. The total functional groups, i.e., the sum of all the observed groups, significantly correlated with C-H (r = 0.96) and WSOC (r = 0.7), suggesting the higher contribution of aliphatic groups in the WSOC fraction. WSOC examined in this study fits well in the established 1H NMR source identification fingerprints of urban aerosols. However, biomass cooking aerosols do not fit the established biomass burning organic aerosols (BBOAs) boundaries, exhibiting a smaller relative contribution of carbon-oxygen double bonds and a less oxidised character than open-field burning. Our results provide essential insights into the nature of urban atmospheric, near-traffic and biomass cooking OAs in India.

Inequalities in occupational exposures among people using popular commute modes.

Several recent studies have looked into the differences in air qualities inside popular commute modes. The impact of daily commuting patterns and work-related trips on inhalation doses, however, are not investigated. The purpose of this study is to quantify the variation in air pollutants within popular commute modes in Mumbai, India, and to estimate the variation in exposure as a result of occupational or work-related trips across different sub-groups. Real-time pollutants, both gaseous and particulate matters (PM), were measured on a pre-defined route during rush and non-rush hours on buses, cars, auto-rickshaws, sub-urban trains, and motorbikes through several trips (N = 98). Household surveys were conducted to estimate the exposures of different occupational subgroups (cab-driver, auto-rickshaw drivers, delivery persons) and people commuting to their offices daily. Participants (N = 800) from various socioeconomic backgrounds in the city were asked about their job categories, work-activity patterns, and work-related commute trips. Mass concentrations of particles in different size ranges (PM1, PM2.5, and PM10) were substantially higher (p < 0.05) inside auto-rickshaws (44.6 µg/m3, 84.7 µg/m3, and 138.3 µg/m3) compared to other modes. Inside cars, gaseous pollutants such as carbon monoxide (CO) and total volatile organic compounds (TVOC) were significantly higher (p < 0.05). Although both gaseous and particulate concentrations were lower (p < 0.05) inside buses, bus-commuters were found to be highly exposed to the pollutants due to the extended trip time (∼1.2 times longer than other modes) and driving conditions. Office commuters inhale a large fraction of their daily doses (25-30%) during their work-related travel. Occupational sub-groups, on the other hand, inhale ∼90% of the pollutants during their work. In a day, an auto-rickshaw driver inhales 10-15% more (p < 0.05) pollutants than cab driver or delivery personnel. Therefore, this study highlights the inequalities in occupational exposure as a combined effect of in-cabin air qualities and commute patterns due to occupational obligations.

Spatial and seasonal variation of outdoor BC and PM2.5 in densely populated urban slums.

A large proportion of residents in urban centers of low- and middle-income countries live in low-socioeconomic neighborhoods called "slums" characterized by low-cost housings of high population density, poor ventilation, and likely poor air quality. This study provides the first quantitative assessment of spatial and seasonal variation of outdoor BC and PM2.5 concentrations in several densely populated slums of Mumbai, India. Mobile outdoor real-time BC and PM2.5 monitoring was conducted along pre-designed monitoring routes in seven slums in Mumbai during the summer (May-June 2015 and May 2016) and repeated in four of them during the winter (February 2016). The measurements were repeated on the routes during different hours and days to account for the temporal variability of air pollution (nsummer = 80 trips; nwinter = 48 trips). PM2.5 exhibited homogenous distribution inside each slum (coefficient of divergence (COD) = 0.11-0.23), while BC varied significantly showing increasing concentrations with proximity to major roads (COD = 0.26-0.64). BC/PM2.5 ratio, an indicator of impact of traffic emissions, was higher along major roads of all slums (14-43%) and minor roads and alleys of high-traffic slums (10-17%) while lowest along alleys and minor roads of low-traffic slums (7-11%). Comparison of pollutant concentrations among major roads revealed the dominant effect of emissions from heavy-duty vehicles and traffic congestion. Significantly high concentrations were observed during winter season compared with summer for both PM2.5 (125 ± 46 µg m-3 in winter and 41 ± 25 µg m-3 in summer) and BC (12 ± 6 µg m-3 in winter and 7 ± 6 µg m-3 in summer). The results of this study indicate that slum residents in Mumbai and similar slums around the world are at a higher risk of traffic-related air pollution, with risk being more severe in winters due to poorer dispersion conditions. Our findings suggest that targeted mitigation strategies to reduce vehicular emissions, especially in high-traffic slums, would yield required benefits.Graphical abstract.

Clinical, Epidemiological and Experimental Approaches to Assess Adverse Health Outcomes of Indoor Biomass Smoke Exposure: Conclusions from An Indo-Swedish Workshop in Mysuru, January 2020.

This report summarizes the outcome of a workshop held in Mysuru, India in January 2020 addressing the adverse health effects of exposure to biomass smoke (BMS). The aim of the workshop was to identify uncertainties and gaps in knowledge and possible methods to address them in the Mysuru study on Determinants of Health in Rural Adults (MUDHRA) cohort. Specific aims were to discuss the possibility to improve and introduce new screening methods for exposure and effect, logistic limitations and other potential obstacles, and plausible strategies to overcome these in future studies. Field visits were included in the workshop prior to discussing these issues. The workshop concluded that multi-disciplinary approaches to perform: (a) indoor and personalized exposure assessment; (b) clinical and epidemiological field studies among children, adolescents, and adults; (c) controlled exposure experiments using physiologically relevant in vitro and in vivo models to understand molecular patho-mechanisms are warranted to dissect BMS-induced adverse health effects. It was perceived that assessment of dietary exposure (like phytochemical index) may serve as an important indicator for understanding potential protective mechanisms. Well trained field teams and close collaboration with the participating hospital were identified as the key requirements to successfully carry out the study objectives.

Origin and properties of soluble brown carbon in freshly emitted and aged ambient aerosols over an urban site in India.

This work investigates the absorption properties of soluble brown carbon (BrC), extracted in methanol and water, from ambient aerosol (PM10) samples, collected over an urban background site in Mumbai, India. The diurnal variability was investigated in samples collected in the morning (7-11 a.m.) and afternoon (12-4 p.m.) periods. Absorption properties of BrC (in the 300-600-nm wavelength range) were measured in filter extracts of water-soluble organic carbon (WSOC) and methanol-soluble organic carbon (MSOC). WSOC and MSOC accounted for on average 52% and 77%, respectively, of the measured OC, potentially indicating unextracted BrC and rendering these values the lower bound. Compared with afternoon samples, the morning samples of MSOC and WSOC had increased BrC concentrations and absorption coefficients (babs365; 40%-65%). The correlation between babs365 and EC, ns-K+, and NO3- in the morning samples indicated contributions from primary sources, including both biomass and vehicular sources. The decreased babs365 in the afternoon samples was partly explained by mixing layer dilution, accompanied by a reduction in the concentrations of primary aerosol constituents. Furthermore, in the afternoon samples, 1HNMR spectroscopy revealed the presence of more oxidized functional groups and significantly higher OC/EC and WSOC/OC ratios, indicating the greater aging of afternoon aerosol. The MAC365 (m2gC-1) for both WSOC and MSOC extracts decreased significantly by 20%-34% in the afternoon samples compared with the morning samples, indicating degradation in the absorption properties of the particles and potentially a change in the constituent BrC chromophores.

Development of land use regression models for nitrogen dioxide, ultrafine particles, lung deposited surface area, and four other markers of particulate matter pollution in the Swiss SAPALDIA regions.

BACKGROUND: Land Use Regression (LUR) is a popular method to explain and predict spatial contrasts in air pollution concentrations, but LUR models for ultrafine particles, such as particle number concentration (PNC) are especially scarce. Moreover, no models have been previously presented for the lung deposited surface area (LDSA) of ultrafine particles. The additional value of ultrafine particle metrics has not been well investigated due to lack of exposure measurements and models. METHODS: Air pollution measurements were performed in 2011 and 2012 in the eight areas of the Swiss SAPALDIA study at up to 40 sites per area for NO2 and at 20 sites in four areas for markers of particulate air pollution. We developed multi-area LUR models for biannual average concentrations of PM2.5, PM2.5 absorbance, PM10, PMcoarse, PNC and LDSA, as well as alpine, non-alpine and study area specific models for NO2, using predictor variables which were available at a national level. Models were validated using leave-one-out cross-validation, as well as independent external validation with routine monitoring data. RESULTS: Model explained variance (R(2)) was moderate for the various PM mass fractions PM2.5 (0.57), PM10 (0.63) and PMcoarse (0.45), and was high for PM2.5 absorbance (0.81), PNC (0.87) and LDSA (0.91). Study-area specific LUR models for NO2 (R(2) range 0.52-0.89) outperformed combined-area alpine (R (2) = 0.53) and non-alpine (R (2) = 0.65) models in terms of both cross-validation and independent external validation, and were better able to account for between-area variability. Predictor variables related to traffic and national dispersion model estimates were important predictors. CONCLUSIONS: LUR models for all pollutants captured spatial variability of long-term average concentrations, performed adequately in validation, and could be successfully applied to the SAPALDIA cohort. Dispersion model predictions or area indicators served well to capture the between area variance. For NO2, applying study-area specific models was preferable over applying combined-area alpine/non-alpine models. Correlations between pollutants were higher in the model predictions than in the measurements, so it will remain challenging to disentangle their health effects.

Spatial variation of PM elemental composition between and within 20 European study areas--Results of the ESCAPE project.

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.

Long-term effects of elemental composition of particulate matter on inflammatory blood markers in European cohorts.

BACKGROUND: Epidemiological studies have associated long-term exposure to ambient particulate matter with increased mortality from cardiovascular and respiratory disorders. Systemic inflammation is a plausible biological mechanism behind this association. However, it is unclear how the chemical composition of PM affects inflammatory responses. OBJECTIVES: To investigate the association between long-term exposure to elemental components of PM and the inflammatory blood markers high-sensitivity C-reactive protein (hsCRP) and fibrinogen as part of the European ESCAPE and TRANSPHORM multi-center projects. METHODS: In total, 21,558 hsCRP measurements and 17,428 fibrinogen measurements from cross-sections of five and four cohort studies were available, respectively. Residential long-term concentrations of particulate matter <10µm (PM10) and <2.5µm (PM2.5) in diameter and selected elemental components (copper, iron, potassium, nickel, sulfur, silicon, vanadium, zinc) were estimated based on land-use regression models. Associations between components and inflammatory markers were estimated using linear regression models for each cohort separately. Cohort-specific results were combined using random effects meta-analysis. As a sensitivity analysis the models were additionally adjusted for PM mass. RESULTS: A 5ng/m(3) increase in PM2.5 copper and a 500ng/m(3) increase in PM10 iron were associated with a 6.3% [0.7; 12.3%] and 3.6% [0.3; 7.1%] increase in hsCRP, respectively. These associations between components and fibrinogen were slightly weaker. A 10ng/m(3) increase in PM2.5 zinc was associated with a 1.2% [0.1; 2.4%] increase in fibrinogen; confidence intervals widened when additionally adjusting for PM2.5. CONCLUSIONS: Long-term exposure to transition metals within ambient particulate matter, originating from traffic and industry, may be related to chronic systemic inflammation providing a link to long-term health effects of particulate matter.

Modeling indoor air pollution of outdoor origin in homes of SAPALDIA subjects in Switzerland.

Given the shrinking spatial contrasts in outdoor air pollution in Switzerland and the trends toward tightly insulated buildings, the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) needs to understand to what extent outdoor air pollution remains a determinant for residential indoor exposure. The objectives of this paper are to identify determining factors for indoor air pollution concentrations of particulate matter (PM), ultrafine particles in the size range from 15 to 300nm, black smoke measured as light absorbance of PM (PMabsorbance) and nitrogen dioxide (NO2) and to develop predictive indoor models for SAPALDIA. Multivariable regression models were developed based on indoor and outdoor measurements among homes of selected SAPALDIA participants in three urban (Basel, Geneva, Lugano) and one rural region (Wald ZH) in Switzerland, various home characteristics and reported indoor sources such as cooking. Outdoor levels of air pollutants were important predictors for indoor air pollutants, except for the coarse particle fraction. The fractions of outdoor concentrations infiltrating indoors were between 30% and 66%, the highest one was observed for PMabsorbance. A modifying effect of open windows was found for NO2 and the ultrafine particle number concentration. Cooking was associated with increased particle and NO2 levels. This study shows that outdoor air pollution remains an important determinant of residential indoor air pollution in Switzerland.

Land use regression models for crustal and traffic-related PM2.5 constituents in four areas of the SAPALDIA study.

Many studies have documented adverse health effects of long-term exposure to fine particulate matter (PM2.5), but there is still limited knowledge regarding the causal relationship between specific sources of PM2.5 and such health effects. The spatial variability of PM2.5 constituents and sources, as a exposure assessment strategy for investigating source contributions to health effects, has been little explored so far. Between 2011 and 2012, three measurement campaigns of PM and nitrogen dioxide (NO2) were performed in 80 sites across four areas of the Swiss Study on Air Pollution and Lung and heart Diseases in Adults (SAPALDIA). Reflectance analysis and energy dispersive X-ray fluorescence (XRF) were performed on PM2.5 filter samples to estimate light absorbance and trace element concentrations, respectively. Three air pollution source factors were identified using principal-component factor analysis: vehicular, crustal, and long-range transport. Land use regression (LUR) models were developed for temporally-adjusted scores of each factor, combining the four study areas. Model performance was assessed using two cross-validation methods. Model explained variance was high for the vehicular factor (R(2)=0.76), moderate for the crustal factor (R(2)=0.46), and low for the long-range transport factor (R(2)=0.19). The cross-validation methods suggested that models for the vehicular and crustal factors moderately accounted for both the between and within-area variability, and therefore can be applied to the four study areas to estimate long-term exposures within the SAPALDIA study population. The combination of source apportionment techniques and LUR modelling may help in identifying air pollution sources and disentangling their contribution to observed health effects in epidemiologic studies.

Ambient ultrafine particle levels at residential and reference sites in urban and rural Switzerland.

Although there is evidence that ultrafine particles (UFP) do affect human health there are currently no legal ambient standards. The main reasons are the absence of spatially resolved exposure data to investigate long-term health effects and the challenge of defining representative reference sites for monitoring given the high dependence of UFP on proximity to sources. The objectives of this study were to evaluate the spatial distribution of UFP in four areas of the Swiss Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) and to investigate the representativeness of routine air monitoring stations for residential sites in these areas. Repeated UFP measurements during three seasons have been conducted at a total of 80 residential sites and four area specific reference sites over a median duration of 7 days. Arithmetic mean residential PNC scattered around the median of 10,800 particles/cm(3) (interquartile range [IQR] = 7800 particles/cm(3)). Spatial within area contrasts (90th/10th percentile ratios) were around two; increased contrasts were observed during weekday rush-hours. Temporal UFP patterns were comparable at reference and residential sites in all areas. Our data show that central monitoring sites can represent residential conditions when locations are well chosen with respect to the local sources--namely traffic. For epidemiological research, locally resolved spatial models are needed to estimate individuals' long-term exposures to UFP of outdoor origin at home, during commute and at work.

Differences in indoor versus outdoor concentrations of ultrafine particles, PM2.5, PMabsorbance and NO2 in Swiss homes.

Indoor air quality is a growing concern as we spend the majority of time indoors and as new buildings are increasingly airtight for energy saving purposes. For a better understanding of residential indoor air pollution in Switzerland we conducted repeated 1-2-week-long indoor and outdoor measurements of particle number concentrations (PNC), particulate matter (PM), light absorbance of PM2.5 (PMabsorbance) and nitrogen dioxide (NO2). Residents of all homes were enrolled in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA). Indoor levels were comparable in urban areas and generally low in rural homes. Average indoor levels were 7800 particles/cm(3) (interquartile range=7200); 8.7 µg/m(3) (6.5) PM2.5 and 10.2 µg/m(3) (11.2) NO2. All pollutants showed large variability of indoor/outdoor ratios between sites. We observed similar diurnal patterns for indoor and outdoor PNC. Nevertheless, the correlation of average indoor and outdoor PNC between sites as well as longitudinal indoor/outdoor correlations within sites were low. Our results show that a careful evaluation of home characteristics is needed when estimating indoor exposure to pollutants with outdoor origin.

Application of land use regression modelling to assess the spatial distribution of road traffic noise in three European cities.

Noise prediction models and noise maps are used to estimate the exposure to road traffic noise, but their availability and the quality of the noise estimates is sometimes limited. This paper explores the application of land use regression (LUR) modelling to assess the long-term intraurban spatial variability of road traffic noise in three European cities. Short-term measurements of road traffic noise taken in Basel, Switzerland (n=60), Girona, Spain (n=40), and Grenoble, France (n=41), were used to develop two LUR models: (a) a "GIS-only" model, which considered only predictor variables derived with Geographic Information Systems; and (b) a "Best" model, which in addition considered the variables collected while visiting the measurement sites. Both noise measurements and noise estimates from LUR models were compared with noise estimates from standard noise models developed for each city by the local authorities. Model performance (adjusted R(2)) was 0.66-0.87 for "GIS-only" models, and 0.70-0.89 for "Best" models. Short-term noise measurements showed a high correlation (r=0.62-0.78) with noise estimates from the standard noise models. LUR noise estimates did not show any systematic differences in the spatial patterns when compared with those from standard noise models. LUR modelling with accurate GIS source data can be a promising tool for noise exposure assessment with applications in epidemiological studies.

Adult lung function and long-term air pollution exposure. ESCAPE: a multicentre cohort study and meta-analysis.

The chronic impact of ambient air pollutants on lung function in adults is not fully understood. The objective of this study was to investigate the association of long-term exposure to ambient air pollution with lung function in adult participants from five cohorts in the European Study of Cohorts for Air Pollution Effects (ESCAPE). Residential exposure to nitrogen oxides (NO2, NOx) and particulate matter (PM) was modelled and traffic indicators were assessed in a standardised manner. The spirometric parameters forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) from 7613 subjects were considered as outcomes. Cohort-specific results were combined using meta-analysis. We did not observe an association of air pollution with longitudinal change in lung function, but we observed that a 10 µg·m(-3) increase in NO2 exposure was associated with lower levels of FEV1 (-14.0 mL, 95% CI -25.8 to -2.1) and FVC (-14.9 mL, 95% CI -28.7 to -1.1). An increase of 10 µg·m(-3) in PM10, but not other PM metrics (PM2.5, coarse fraction of PM, PM absorbance), was associated with a lower level of FEV1 (-44.6 mL, 95% CI -85.4 to -3.8) and FVC (-59.0 mL, 95% CI -112.3 to -5.6). The associations were particularly strong in obese persons. This study adds to the evidence for an adverse association of ambient air pollution with lung function in adults at very low levels in Europe.

The relevance of commuter and work/school exposure in an epidemiological study on traffic-related air pollution.

Exposure during transport and at non-residential locations is ignored in most epidemiological studies of traffic-related air pollution. We investigated the impact of separately estimating NO2 long-term outdoor exposures at home, work/school, and while commuting on the association between this marker of exposure and potential health outcomes. We used spatially and temporally resolved commuter route data and model-based NO2 estimates of a population sample in Basel, Switzerland, to assign individual NO2-exposure estimates of increasing complexity, namely (1) home outdoor concentration; (2) time-weighted home and work/school concentrations; and (3) time-weighted concentration incorporating home, work/school and commute. On the basis of their covariance structure, we estimated the expectable relative differences in the regression slopes between a quantitative health outcome and our measures of individual NO2 exposure using a standard measurement error model. The traditional use of home outdoor NO2 alone indicated a 12% (95% CI: 11-14%) underestimation of related health effects as compared with integrating both home and work/school outdoor concentrations. Mean contribution of commuting to total weekly exposure was small (3.2%; range 0.1-13.5%). Thus, ignoring commute in the total population may not significantly underestimate health effects as compared with the model combining home and work/school. For individuals commuting between Basel-City and Basel-Country, ignoring commute may produce, however, a significant attenuation bias of 4% (95% CI: 4-5%). Our results illustrate the importance of including work/school locations in assessments of long-term exposures to traffic-related air pollutants such as NO2. Information on individuals' commuting behavior may further improve exposure estimates, especially for subjects having lengthy commutes along major transportation routes.