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Background: The South Durban (SD) area of Durban, South Africa, has a history of air pollution issues due to the juxtaposition of low-income communities with industrial areas. This study used measurements of oxides of nitrogen (NO x ) to develop a land use regression (LUR) model to explain the spatial variation of air pollution concentrations in this area., Methods: Ambient NO x was measured over two two-week sampling periods at 32 sites using Ogawa badges. Following the ESCAPE approach, an annual adjusted average was calculated for these results and regressed against pre-selected geographic predictor variables in a multivariate regression model. The LUR model was then applied to predict the NO x exposure of a sample of pregnant women living in South Durban., Results: Measured NO x levels ranged from 22.3-50.9μg/m 3 with a median of 36μg/m 3 . The model developed accounts for 73% of the variance in ambient NO x measurements using three input variables (length of minor roads within a 1000m radius, length of major roads within a 300m radius, and area of open space within a 1000m radius). Model cross validation yielded a R 2 of 0.59. Subsequent participant exposure estimates indicated exposure to ambient NO x ranged from 19.9-53.2μg/m 3 , with a mean of 39μg/m 3 ., Discussion and Conclusion: This is the first study to develop a land use regression model that predicts ambient concentrations of NO x in a South African context. The findings of this study indicate that the participants in the South Durban are exposed to high levels of NO x that can be attributed mainly to traffic., (Copyright © 2017 Elsevier B.V. All rights reserved.)

In this Beijing Indoor Air Purifier StudY (BIAPSY), we conducted a randomized crossover intervention trial in a panel of 35 non-smoking senior participants with free-living, with and without chronic obstructive pulmonary disease (COPD). Portable air filtration units were randomly allocated to active-(filter in) for 2weeks and sham-mode (filter out) for 2weeks in the households. We examined the differences in indoor air pollutant concentrations in 20 study homes and a suite of cardio-respiratory biomarker levels in study participants between filtration modes, with and without adjustment for potential confounders. Following active filtration, we observed significant reductions from 60±45 to 24±15μg/m 3 in ten-day averages of indoor PM 2.5 and reductions from 3.87±1.65 to 1.81±1.19m -1 .10 -5 in ten-day averages of indoor BC, compared to sham-mode filtration. The major components of indoor PM 2.5 , including water soluble organics, NO 3 - , SO 4 2- and K 2+ , Pb 2+ and K + , were also reduced significantly by 42% to 63%. However, following active filtration, we only observed significant reductions on systemic inflammation measured as of IL-8 at 58.59% (95% CI: -76.31, -27.64) in the total group of participants and 70.04% (95% CI: -83.05, -47.05) in the subset of COPD patients, with adjustments. We were not able to detect improvements on lung function, blood pressure, and heart rate variability, following short-term intervention of two-week active air filtration. In conclusion, our results showed that indoor air filtration produced clear improvement on indoor air quality, but no demonstrable changes in the cardio-respiratory outcomes of study interest observed in the seniors living with real-world air pollution exposures., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Recently, short-term monitoring campaigns have been carried out to investigate the spatial variation of air pollutants within cities. Typically, such campaigns are based on short-term measurements at relatively large numbers of locations. It is largely unknown how well these studies capture the spatial variation of long term average concentrations. The aim of this study was to evaluate the within-site temporal and between-site spatial variation of the concentration of ultrafine particles (UFPs) and black carbon (BC) in a short-term monitoring campaign. In Amsterdam and Rotterdam (the Netherlands) measurements of number counts of particles larger than 10nm as a surrogate for UFP and BC were performed at 80 sites per city. Each site was measured in three different seasons of 2013 (winter, spring, summer). Sites were selected from busy urban streets, urban background, regional background and near highways, waterways and green areas, to obtain sufficient spatial contrast. Continuous measurements were performed for 30 min per site between 9 and 16 h to avoid traffic spikes of the rush hour. Concentrations were simultaneously measured at a reference site to correct for temporal variation. We calculated within- and between-site variance components reflecting temporal and spatial variations. Variance ratios were compared with previous campaigns with longer sampling durations per sample (24h to 14 days). The within-site variance was 2.17 and 2.44 times higher than the between-site variance for UFP and BC, respectively. In two previous studies based upon longer sampling duration much smaller variance ratios were found (0.31 and 0.09 for UFP and BC). Correction for temporal variation from a reference site was less effective for the short-term monitoring campaign compared to the campaigns with longer duration. Concentrations of BC and UFP were on average 1.6 and 1.5 times higher at urban street compared to urban background sites. No significant differences between the other site types and urban background were found. The high within to between-site concentration variances may result in the loss of precision and low explained variance when average concentrations from short-term campaigns are used to develop land use regression models., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Relatively little is known about long term effects of wood smoke on population health. A wood combustion marker - levoglucosan - was measured using a standardized sampling and measurement method in four European study areas (Oslo, The Netherlands, Munich/Augsburg, Catalonia) to assess within and between study area spatial variation. Levoglucosan was analyzed in addition to: PM2.5, PM2.5 absorbance, PM10, polycyclic aromatic hydrocarbons (PAH), nitrogen oxides (NOx), elemental and organic carbon (EC/OC), hopanes, steranes and elemental composition. Measurements were conducted at street, urban and regional background sites. Three two-week samples were taken per site and the annual average concentrations of pollutants were calculated using continuous measurements at one background reference site. Land use regression (LUR) models were developed to explain the spatial variation of levoglucosan. Much larger within than between study area contrast in levoglucosan concentration was found. Spatial variation patterns differed from other measured pollutants: PM2.5, NOx and EC. Levoglucosan had the highest spatial correlation with ΣPAH (r=0.65) and the lowest with traffic markers - NOx, Σhopanes/steranes (r=-0.22). Levoglucosan concentrations in the cold (heating) period were between 3 and 20 times higher compared to the warm period. The contribution of wood-smoke calculated based on levoglucosan measurements and previous European emission data to OC and PM2.5 mass was 13 to 28% and 3 to 9% respectively in the full year. Larger contributions were calculated for the cold period. The median model R(2) of the LUR models was 60%. The LUR models included population and natural land related variables. In conclusion, substantial spatial variability was found in levoglucosan concentrations within study areas. Wood smoke contributed substantially to especially wintertime PM2.5 OC and mass. The low to moderate correlation with PM2.5 mass and traffic markers offers the potential to assess health effects of wood smoke separate from traffic-related air pollution., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Background and Aims: Land use regression (LUR) models predict spatial variation of ambient concentrations, but little is known about the validity in predicting personal exposures. In this study, the association of LUR modeled concentrations of PM2.5 components with measured personal concentrations was determined. The elements of interest were copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V) and zinc (Zn)., Methods: In Helsinki (Finland), Utrecht (the Netherlands) and Barcelona (Spain) five participants from urban background, five from suburban background and five from busy street sites were selected in each city (15 participants per city). Outdoor, indoor and personal 96-hour PM2.5 samples were collected by the participants over periods of two weeks in three different seasons (winter, summer and spring/autumn) and the overall average was calculated. Elemental composition was measured by ED-XRF spectrometry. The LUR models for the average ambient concentrations of each element were developed by the ESCAPE project., Results: LUR models predicted the within-city variation of average outdoor Cu and Fe concentrations moderately well (range in R(2) 27-67% for Cu and 24-54% for Fe). The outdoor concentrations of the other elements were not well predicted. The LUR modeled concentration only significantly correlated with measured personal Fe exposure in Utrecht and Ni and V in Helsinki. The LUR model predictions did not correlate with measured personal Cu exposure. After excluding observations with an indoor/outdoor ratio of >1.5, modeled Cu outdoor concentrations correlated with indoor concentrations in Helsinki and Utrecht and personal concentrations in Utrecht. The LUR model predictions were associated with measured outdoor, indoor and personal concentrations for all elements when the data for the three cities was pooled., Conclusions: Within-city modeled variation of elemental composition of PM2.5 did not predict measured variation in personal exposure well., (Copyright © 2014. Published by Elsevier B.V.)

Epidemiological studies often use nitrogen dioxide (NO2) or proximity to roads to characterize exposure to more health-relevant pollutants (e.g., fine particles or black carbon aerosol) in vehicle exhaust. Due to the introduction of diesel-soot filters, particle-to-NO2 ratios may have decreased, but little information is available about these ratios over time. Our study aim was to evaluate the change in particle-to-NO2 ratios between 1999 and 2009. We compared data collected during measurement campaigns in 1999 and 2009 from Munich, the Netherlands, and Stockholm. Traffic-impacted and urban and regional background sites were studied during each campaign. The same pollutants were measured in each campaign (mass concentration of particles ≤ 2.5 microns in diameter (PM2.5), PM2.5 absorbance (a marker for black carbon), and NO2) using the same methods except for NO2: Palmes tubes were used in 1999 and Ogawa badges in 2009. Both NO2 methods were validated against side-by-side chemiluminescence measurements. The levels of PM2.5 absorbance and PM2.5 were significantly lower (p<0.05) in 2009 at traffic and urban background sites in Stockholm, but only slightly lower in Munich and the Netherlands. In contrast, NO2 levels were not significantly different in the three areas in 2009 compared to 1999. Statistically-significant decreases between 1999 and 2009 pollutant ratios in the Netherlands (PM2.5 absorbance/NO2 and PM2.5/NO2) and in Stockholm (PM2.5 absorbance/NO2 and PM2.5 absorbance/PM2.5) were observed. Smaller decreases in these ratios were observed in Munich. The contrast between traffic and urban background locations was larger in 2009 than 1999 for NO2, whereas it was smaller for PM2.5 absorbance and PM2.5. The lower PM2.5 absorbance/NO2 and PM2.5/NO2 ratios in 2009 is likely explained by the introduction of oxidative particle filters for diesel vehicles that reduce particles but produce NO2. The changed contrasts may affect estimates of health effects related to NO2 as a marker of proximity to roads., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Background: Evaluations of the effectiveness of air pollution policy interventions are scarce. This study investigated air pollution at street level before and after implementation of local traffic policies including low emission zones (LEZ) directed at heavy duty vehicles (trucks) in five Dutch cities., Methods: Measurements of PM(10), PM(2.5), 'soot', NO(2), NO(x), and elemental composition of PM(10) and PM(2.5) were conducted simultaneously at eight streets, six urban background locations and four suburban background locations before (2008) and two years after implementation of the policies (2010). The four suburban locations were selected as control locations to account for generic air pollution trends and weather differences., Results: All pollutant concentrations were lower in 2010 than in 2008. For traffic-related pollutants including 'soot' and NO(x) and elemental composition (Cr, Cu, Fe) the decrease did not differ significantly between the intervention locations and the suburban control locations. Only for PM(2.5) reductions were considerably larger at urban streets (30%) and urban background locations (27%) than at the matching suburban control locations (20%). In one urban street where traffic intensity was reduced with 50%, 'soot', NO(x) and NO(2) concentrations were reduced substantially more (41, 36 and 25%) than at the corresponding suburban control location (22, 14 and 7%)., Conclusion: With the exception of one urban street where traffic flows were drastically reduced, the local traffic policies including LEZ were too modest to produce significant decreases in traffic-related air pollution concentrations., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Recent interest has focused on the health effects of ultrafine particles because of the documented toxicity and the larger concentration contrast near motorways of UFP than for PM10 or PM2.5. There are only few studies that have measured UFP at inner-city streets simultaneously with other PM components. The aim of this study was to compare the contrast of UFP, PM(10) and soot measured simultaneously at 3 inner-city locations, namely a moderately busy street (15,000 vehicles/day), a city and a suburban background location. Simultaneously, measurements of particle number concentrations (PNC), PM(10) and soot have been conducted on three locations in and around Utrecht, a medium-sized city in the Netherlands for 20 weekdays in autumn 2008. Measurements were done for 6-h during afternoon and early evening. The mean PNC at the street location was more than 3 times higher than at the two background locations. The contrast was similar for soot concentrations. In PM(10) concentrations less contrast was found, namely 1.8 times. Mean PNC concentrations were poorly correlated with PM(10) and soot. At the street location, high temporal variation of PNC concentrations occurred within each sampling day, probably related to variations in traffic volumes, high-emission individual vehicles and wind direction. Temporal variation was smaller at the two background locations. Occasional unexplained short-term peaks occurred at the suburban background location. A relatively high correlation between PNC minute values at the two background locations was found, pointing to similar area-wide sources. Typically low correlations were found with the street locations, consistent with the dominant impact of local traffic. A large contrast between two background locations and a moderately busy urban street location was found for PNC and soot, comparable to previous studies of much busier motorways. Temporal variation of PNC was higher at the street location and uncorrelated with background variations., (Copyright 2010 Elsevier B.V. All rights reserved.)

In order to estimate the spatial variation within well-defined study areas, nitrogen dioxide was measured with diffusion samplers (Palmes tube) in 40-42 sites each in Germany (Munich), the Netherlands and Sweden (Stockholm County). Each site was measured over four 2-week periods during 1 year (spring 1999 to summer 2000). In each country, one reference site was measured during all periods and the results were used to adjust for seasonal variability, to improve the estimates of the annual average. Comparisons between the chemiluminescence method (European reference method) and Palmes tube measurement indicated a good agreement in Germany (with a ratio of 1.0 for Palmes tube/chemiluminescence) but underestimation for Palmes tube measurement in the Netherlands and Sweden (0.8 for both countries). The r2 values were between 0.86 and 0.90 for all three countries. The annual average values for NO2 for different sampling sites were between 15.9 and 50.6 (mean 28.8 microg/m3) in Germany, between 12.1 and 50.8 (mean 28.9 microg/m3) in the Netherlands and between 6.1 and 44.7 (mean 18.5 microg/m3) in Sweden. Comparing spatial variation between similar sites in the three countries, we did not find any significant differences between annual average levels for urban traffic sites. In Sweden, annual average levels in urban background and suburban backgrounds sites were about 8 microg/m3 lower than comparable sites in Germany and the Netherlands. Comparing site types within each country only urban traffic sites and suburban background sites differed in Germany. In the Netherlands and Sweden, the urban traffic sites differed from all other sites and in Sweden also the urban background sites differed from the other background sites. The observed contribution from local traffic was similar in the Netherlands and Sweden (10 and 8 microg/m3, corresponding to 26-27% of the NO2 concentration found in the urban traffic sites). In Germany, the contribution from local traffic was only 3 microg/m3, corresponding to 9% of the NO2 concentration found in the urban traffic sites. The spatial variation was substantially larger for NO2 than the variation for PM2.5 and similar to PM2.5 absorbance, measured in the same locations.