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Previous studies consistently showed an association between fine atmospheric particulate matter (PM 2.5 ) and cardiovascular diseases. Concerns about adverse health effects of ultrafine particles (UFP) are growing but long-term studies are still scarce. In this study, we examined the association between long-term exposure to ambient air pollutants and blood biomarkers of inflammation and coagulation, including fibrinogen, high-sensitivity C-reactive protein (hs-CRP), serum amyloid A (SAA) adiponectin and interleukin-6 (IL-6), measured in the German KORA-S4 cohort study (1999-2001). IL-6 was available for older participants only, who were therefore considered as a subsample. Annual mean concentrations of UFP (as particle number concentration), particulate matter in different particles sizes (PM 10 , PM coarse , PM 2.5 , PM 2.5 absorbance), ozone (O 3 ), and nitrogen oxides (NO 2 , NO X ) were estimated by land-use regression models and assigned to participants' home addresses. We performed a multiple linear regression between each pollutant and each biomarker with adjustment for confounders. Per 1 interquartile range (IQR, 1945 particles/cm 3 ) increase of UFP, fibrinogen increased by 0.70 % (0.04; 1.37) and hs-CRP increased by 3.16 % (-0.52; 6.98). Adiponectin decreased by -2.53 % (-4.78; -0.24) per 1 IQR (1.4 μg/m 3 ) increase of PM 2.5 . Besides, PM 2.5 was associated with increased IL-6 in the subsample. In conclusion, we observed that long-term exposure to air pollutants, including both fine and ultrafine particles, was associated with higher concentrations of pro-inflammatory and lower concentrations of an anti-inflammatory blood biomarkers, which is consistent with an increased risk for cardiovascular disease observed for long-term exposure to air pollutants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Epidemiological studies investigating the association between daily particle exposure and health effects are frequently based on a single monitoring site located in an urban background. Using a central site in epidemiological time-series studies has been established based on the premises of low spatial variability of particles within the areas of interest and hence the adequacy of the central sites to monitor the exposure. This is true to a large extent in relation to larger particles (PM 2.5 , PM 10 ) that are typically monitored and regulated. However, the distribution of ultrafine particles (UFP), which in cities predominantly originate from traffic, is heterogeneous. With increasing pressure to improve the epidemiology of UFP, an important question to ask is, whether central site monitoring is representative of community exposure to this size fraction of particulate matter; addressing this question is the aim of this paper. To achieve this aim, we measured personal exposure to UFP, expressed as particle number concentration (PNC), using Philips Aerasense Nanotracers (NT) carried by the participants of the study, and condensation particle counters (CPC) or scanning mobility particle sizers (SMPS) at central fixed-site monitoring stations. The measurements were conducted at three locations in Brisbane (Australia), Cassino (Italy) and Accra (Ghana). We then used paired t-tests to compare the average personal and average fixed-site PNC measured over the same 24-h, and hourly, periods. We found that, at all three locations, the 24-h average fixed-site PNC was no different to the personal PNC, when averaged over the study period and all the participants. However, the corresponding hourly averages were significantly different at certain times of the day. These were generally times spent commuting and during cooking and eating at home. Our analysis of the data obtained in Brisbane, showed that maximum personal exposure occurred in the home microenvironment during morning breakfast and evening dinner time. The main source of PNC for personal exposure was from the home-microenvironment. We conclude that the 24-h average PNC from the central-site can be used to estimate the 24-h average personal exposure for a community. However, the hourly average PNC from the central site cannot consistently be used to estimate hourly average personal exposure, mainly because they are affected by very different sources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Epigenetic mechanisms may underlie air pollution-health outcome associations. We estimated gaseous air pollutant-DNA methylation (DNAm) associations using twelve subpopulations within Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) cohorts (n = 8397; mean age 61.3 years; 83% female; 46% African-American, 46% European-American, 8% Hispanic/Latino). We used geocoded participant address-specific mean ambient carbon monoxide (CO), nitrogen oxides (NO 2 ; NOx), ozone (O 3 ), and sulfur dioxide (SO 2 ) concentrations estimated over the 2-, 7-, 28-, and 365-day periods before collection of blood samples used to generate Illumina 450 k array leukocyte DNAm measurements. We estimated methylome-wide, subpopulation- and race/ethnicity-stratified pollutant-DNAm associations in multi-level, linear mixed-effects models adjusted for sociodemographic, behavioral, meteorological, and technical covariates. We combined stratum-specific estimates in inverse variance-weighted meta-analyses and characterized significant associations (false discovery rate; FDR<0.05) at Cytosine-phosphate-Guanine (CpG) sites without among-strata heterogeneity (P Cochran's Q  > 0.05). We attempted replication in the Cooperative Health Research in Region of Augsburg (KORA) study and Normative Aging Study (NAS). We observed a -0.3 (95% CI: -0.4, -0.2) unit decrease in percent DNAm per interquartile range (IQR, 7.3 ppb) increase in 28-day mean NO 2 concentration at cg01885635 (chromosome 3; regulatory region 290 bp upstream from ZNF621; FDR = 0.03). At intragenic sites cg21849932 (chromosome 20; LIME1; intron 3) and cg05353869 (chromosome 11; KLHL35; exon 2), we observed a -0.3 (95% CI: -0.4, -0.2) unit decrease (FDR = 0.04) and a 1.2 (95% CI: 0.7, 1.7) unit increase (FDR = 0.04), respectively, in percent DNAm per IQR (17.6 ppb) increase in 7-day mean ozone concentration. Results were not fully replicated in KORA and NAS. We identified three CpG sites potentially susceptible to gaseous air pollution-induced DNAm changes near genes relevant for cardiovascular and lung disease. Further harmonized investigations with a range of gaseous pollutants and averaging durations are needed to determine the effect of gaseous air pollutants on DNA methylation and ultimately gene expression., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Objective: to study the sources contributing to quasi-ultrafine particle (UFP) organic carbon and the spatial temporal variability of the sources., Method: 24h quasi-UFP (particulate matter <0.36μm in this study) was sampled at a reference site continuously and at one of 5 other sites (T1, T2, T3, T4 and B1) in parallel in Augsburg, Germany from April 11th, 2014 to February 22nd, 2015, attempting to conduct 2-week campaigns at each site in 3 different seasons. Positive matrix factorization (PMF) was applied to measured organic tracers for source apportionment analyses. Pearson correlation coefficient r and coefficient of divergence (COD) were calculated to investigate spatial temporal variation of source contributions., Result: 5 sources were identified comprising biomass burning (BB), traffic emissions (Traffic), biogenic secondary organic aerosol (bioSOA), isoprene originated secondary organic aerosol (isoSOA) and biomass burning related secondary organic aerosol (bbSOA). In general, good temporal correlation and uniform distribution within the study area are found for bioSOA and bbSOA, probably resulting from regional formation/transport. Lower temporal correlation and spatial heterogeneity of isoSOA were found at the city background site with local influence from green space and less traffic impact. BB demonstrated very good temporal correlation, but higher contributions at sites influenced by local residential heating emissions were observed. Traffic showed the least seasonality and lower correlation over time among the sources. However, it demonstrated low spatial heterogeneity of absolute contribution, and only a few days of elevated contribution was found at T3 when wind came directly from the street nearby., Conclusion: temporal correlation and spatial variability of sources contributing to the organic fraction of quasi-UFP vary among sites and source types and show source-specific characteristics. Therefore, caution should be taken when using one monitor site measurement to assess human exposure in health effect studies of quasi-UFP., (Copyright © 2018 Elsevier B.V. All rights reserved.)

To investigate the organic composition and their sources of very fine atmospheric particulate matter (PM), size-segregated PM was sampled using rotating drum impactor (RDI) in series with a sequential filter sampler in Augsburg, Germany, from April 2014 to February 2015. Organic speciation analysis and organic carbon/elemental carbon (OC/EC) analysis was performed for the smallest size fraction PM 0.36 (PM<360nm). Different OC fractions were determined by thermal optical EC/OC analyzer, and OC2, OC3 and OC4 refer to OC fractions that were derived at 280, 480 and 580°C, respectively. Positive matrix factorization (PMF) analysis was applied for source apportionment study. PMF resolved 5 sources including biogenic dominated secondary organic aerosol (bioSOA), isoprene dominated SOA (isoSOA), traffic, biomass burning (BB) and biomass burning originated SOA (bbSOA). On annual average, PMF results indicate the largest contribution of biogenic originated SOA (bioSOA plus isoSOA) to OC, followed by traffic and then BB related sources (BB plus bbSOA). Traffic was found to be associated with the smallest particles; whereas bioSOA and BB are associated with larger particles. Secondary organic marker compounds from biogenic precursors, OC2, OC3 and bioSOA, isoSOA source factors show summer maximum. Polycyclic aromatic hydrocarbons (PAHs), biomass burning markers, OC4 and BB, bbSOA source factors show winter maximum. Hopanes and the traffic source factor show little seasonal variation. Summer peaks of OC3 and OC2 are well modeled by PMF and are attributed mainly to biogenic SOA. OC4 was generally poorly modeled due to lack of characteristic low volatile markers. Summer maxima of biogenic SOA related compounds and source factors are positively correlated with temperature, global radiation, O 3 concentration and mixing layer height (MLH). Winter maxima of BB related compounds and source factors are negatively correlated with temperature and MLH; whereas positively correlated with NO 2 level., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Air pollution, traffic noise and noise annoyance are suggested to be associated with hypertension and blood pressure (BP); however, the evidence remains inconsistent. Our study examined the long-term associations of modeled and self-reported measures of air pollution and traffic noise on prevalent hypertension and BP. We analyzed cross-sectional data from 2552 participants aged 31-72years from the KORA F4 (2006-2008) study conducted in the region of Augsburg, Germany. Land-use regression models were used to estimate residential long-term exposure to particulate matter <2.5μm (PM 2.5 ), soot content of PM 2.5 (PM 2.5 abs) and nitrogen dioxide (NO 2 ). Road traffic noise levels at the facade of the dwellings were estimated for the participants' residences. Participants filled-in a questionnaire on noise annoyance and heavy traffic passing their residence. Linear and logistic regression models adjusting for confounders were used to assess the association between exposure measures and hypertension and BP. An interquartile increase in annual mean PM 2.5 (1μg/m 3 ) was significantly associated with 15% higher prevalence of hypertension, without (95% CI: 2.5; 28.0%) and with (95% CI: 0.7; 30.8%) adjustment for traffic noise. Diastolic blood pressure (DBP) was associated with air pollutants and traffic noise with percent increases in mean of 0.7 (95% CI: 0.2; 1.2), 0.6 (95% CI: 0.1; 1.1) and 0.3 (95% CI: 0.0; 0.7) for an interquartile increase in PM 2.5 (1μg/m 3 ) and PM 2.5 abs (0.2∗10 -5 /m), and 5dB(A) increase in 24-hour road traffic noise, respectively. Associations of PM 2.5 abs and NO 2 with hypertension or DBP were stronger in men and diabetic individuals. No clear associations were seen with systolic BP or noise annoyance. In conclusion, self-reported measures of air pollution or noise did not perform better than the objective measures. Our findings provide further evidence for a link between air pollution, noise and cardiovascular disease and indicate a stronger association for men and diabetic individuals., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Important health relevance has been suggested for ultrafine particles (UFP) and ozone, but studies on long-term effects are scarce, mainly due to the lack of appropriate spatial exposure models. We designed a measurement campaign to develop land use regression (LUR) models to predict the spatial variability focusing on particle number concentration (PNC) as indicator for UFP, ozone and several other air pollutants in the Augsburg region, Southern Germany. Three bi-weekly measurements of PNC, ozone, particulate matter (PM 10 , PM 2.5 ), soot (PM 2.5 abs) and nitrogen oxides (NO x , NO 2 ) were performed at 20 sites in 2014/15. Annual average concentration were calculated and temporally adjusted by measurements from a continuous background station. As geographic predictors we offered several traffic and land use variables, altitude, population and building density. Models were validated using leave-one-out cross-validation. Adjusted model explained variance (R 2 ) was high for PNC and ozone (0.89 and 0.88). Cross-validation adjusted R 2 was slightly lower (0.82 and 0.81) but still indicated a very good fit. LUR models for other pollutants performed well with adjusted R 2 between 0.68 (PM coarse ) and 0.94 (NO 2 ). Contrary to previous studies, ozone showed a moderate correlation with NO 2 (Pearson's r=-0.26). PNC was moderately correlated with ozone and PM 2.5 , but highly correlated with NO x (r=0.91). For PNC and NO x , LUR models comprised similar predictors and future epidemiological analyses evaluating health effects need to consider these similarities., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Background and Aims: Epidemiological studies have shown adverse effects of ambient air pollutants on health with inflammation and oxidative stress playing an important role. We examine the association between blood biomarkers of inflammation and coagulation and physical attributes of particulate matter which are not routinely measured such as particle length or surface area concentration and apparent density of PM., Methods: Between 3/2007 and 12/2008 187 non-smoking individuals with type 2 diabetes mellitus (T2D) or impaired glucose tolerance (IGT) were examined within the framework of the KORA Study in Augsburg, Germany. In addition, we selected 87 participants with a potential genetic predisposition on detoxifying and inflammatory pathways. This was defined by the null polymorphism for glutathione S-transferase M1 in combination with a certain single nucleotide polymorphism on the C-reactive protein (CRP) gene (rs1205) or the fibrinogen gene (rs1800790). Participants had blood drawn up to seven different times, resulting in 1765 blood samples. Air pollutants were collected at a central measurement station and individual 24-h averages calculated. Associations between air pollutants and high sensitivity CRP, myeloperoxidase (MPO), interleukin (IL)-6 and fibrinogen were analysed using additive mixed models., Results: For the panel with genetic susceptibility, increases were seen for CRP and MPO with most attributes, specifically particle length and active surface concentration. The %change of geometric mean and 95% confidence intervals for the 5-day average exposure for CRP and MPO were 34.6% [21.8;48.8] and 8.3% [3.2;13.6] per interquartile range increase of particle length concentration and 29.8% [15.9;45.3] and 10.4 [4.4;16.7] for active surface area. Results for the panel of T2D and IGT and the other blood biomarkers were less conclusive., Conclusions: Particle length concentration and active surface concentration showed strong positive associations with blood biomarkers reflecting inflammation. These air pollution metrics might reflect harmful aerosol properties better than particulate mass or number concentration. They might therefore be important for epidemiological studies., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Risk assessment studies often ignore within-city variations of air pollutants. Our objective was to quantify the risk associated with fine particulate matter (PM2.5) exposure in 2 urban areas using fine-scale air pollution modeling and to characterize how this risk varied according to social deprivation. In Grenoble and Lyon areas (0.4 and 1.2 million inhabitants, respectively) in 2012, PM2.5 exposure was estimated on a 10×10m grid by coupling a dispersion model to population density. Outcomes were mortality, lung cancer and term low birth weight incidences. Cases attributable to air pollution were estimated overall and stratifying areas according to the European Deprivation Index (EDI), taking 10µg/m(3) yearly average as reference (counterfactual) level. Estimations were repeated assuming spatial homogeneity of air pollutants within urban area. Median PM2.5 levels were 18.1 and 19.6μg/m(3) in Grenoble and Lyon urban areas, respectively, corresponding to 114 (5.1% of total, 95% confidence interval, CI, 3.2-7.0%) and 491 non-accidental deaths (6.0% of total, 95% CI 3.7-8.3%) attributable to long-term exposure to PM2.5, respectively. Attributable term low birth weight cases represented 23.6% of total cases (9.0-37.1%) in Grenoble and 27.6% of cases (10.7-42.6%) in Lyon. In Grenoble, 6.8% of incident lung cancer cases were attributable to air pollution (95% CI 3.1-10.1%). Risk was lower by 8 to 20% when estimating exposure through background stations. Risk was highest in neighborhoods with intermediate to higher social deprivation. Risk assessment studies relying on background stations to estimate air pollution levels may underestimate the attributable risk., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: The link between particulate air pollution and cardiovascular (CVD) mortality has been investigated. However, there is little direct evidence that reduction measures which decrease particulate air pollution would lead to a reduction in CVD mortality., Objectives: In Beijing, China, air quality improvement strategies were developed and actions were taken before and during the 2008 Olympic and Paralympic Games. Taking advantage of this opportunity, the aim of the study was to assess the effects of changes in particulate air pollution before (May 20-July 20, 2008), during (August 1-September 20, 2008) and after (October 1-December 1, 2008) the Olympics period., Methods: Concentrations of air pollution, meteorology and CVD death counts were obtained from official networks and monitoring sites located on the Peking University campus. Air pollution effects with lags of 0-4 days as well as of the 5-day average on cause-specific CVD mortality were investigated for the complete study period (May 20-December 1, 2008) using Quasi-Poisson regression models. Different gender and age subgroups were taken into account. Additionally, effect modification by air mass origin was investigated. In a second step, air pollution effects were estimated for the three specific periods by including an interaction term in the models., Results: We observed large concentration decreases in all measured air pollutants during the unique pollution intervention for the Beijing 2008 Olympics. For the whole period, adverse effects of particulate air pollution were observed on CVD mortality with a 1-day delay as well as for the 5-day average exposure, e.g. an 8.8% (95%CI: 2.7-15.2%) increase in CVD mortality with an interquartile range increase in ultrafine particles. The effects were more pronounced in females, the elderly and for cerebrovascular deaths, but not modified by air mass origin. The specific sub-period analysis results suggested that the risks of CVD mortality were lowest during the Olympic Games where strongest reduction measures have been applied., Conclusions: The results indicated that the reduction of air pollution due to air quality control measures led to a decreased risk of CVD mortality in Beijing. Our findings provide new insight into efforts to reduce ambient air pollution., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Background: Numerous studies showed that chronic noise exposure modeled through noise mapping is associated with adverse health effects. However, knowledge about real individual noise exposure, emitted by several sources, is limited., Objectives: To explain the variation in individual daytime noise exposure regarding different microenvironments, activities and individual characteristics., Materials and Methods: In a repeated measures study in Augsburg, Germany (March 2007-December 2008), 109 individuals participated in 305 individual noise measurements with a mean duration of 5.5h. Whereabouts and activities were recorded in a diary. One-minute averages of A-weighted equivalent continuous sound pressure levels (Leq) were determined. We used mixed additive models to elucidate the variation of Leq by diary-based information, baseline characteristics and time-invariant variables like long-term noise exposure., Results: Overall noise levels were highly variable (median: 64 dB(A); range: 37-105 dB(A)). Highest noise levels were measured in traffic during bicycling (69 dB(A); 49-97 dB(A)) and lowest while resting at home (54 dB(A); 37-94 dB(A)). Nearly all diary-based information as well as physical activity, sex and age-group had significant influences on individual noise. In an additional analysis restricted to times spent at the residences, long-term noise exposure did not improve the model fit., Conclusions: Individual exposures to day-time noise were moderate to high and showed high variations in different microenvironments except when being in traffic. Individual noise levels were greatly determined by personal activities but also seemed to depend on environmental noise levels., (Copyright © 2015 Elsevier Inc. 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.)

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: Although short-term exposure to ambient particulate matter has increasingly been linked with cardiovascular diseases, it is not quite clear how physical characteristics of particles, such as particle size may be responsible for the association. This study aimed at investigating whether daily changes in number or mass concentrations of accurately size-segregated particles in the range of 3nm-10μm are associated with daily cardiovascular emergency room visits in Beijing, China., Methods: Cardiovascular emergency room visit counts, particle size distribution data, and meteorological data were collected from Mar. 2004 to Dec. 2006. Particle size distribution data was used to calculate particle number concentration in different size fractions, which were then converted to particle mass concentration assuming spherical particles. We applied a time-series analysis approach. We evaluated lagged associations between cardiovascular emergency room visits and particulate number and mass concentration using distributed lag non-linear models up to lag 10. We calculated percentage changes of cardiovascular emergency room visits, together with 95% confidence intervals (CI), in association with an interquartile range (IQR, difference between the third and first quartile) increase of 11-day or 2-day moving average number or mass concentration of particulate matter within each size fraction, assuming linear effects. We put interaction terms between season and 11-day or 2-day average particulate concentration in the models to estimate the modification of the particle effects by season., Results: We observed delayed associations between number concentration of ultrafine particles and cardiovascular emergency room visits, mainly from lag 4 to lag 10, mostly contributed by 10-30nm and 30-50nm particles. An IQR (9040cm(-3)) increase in 11-day average number concentration of ultrafine particles was associated with a 7.2% (1.1-13.7%) increase in total, and a 7.9% (0.5-15.9%) increase in severe cardiovascular emergency room visits. The delayed effects of particulate mass concentration were small. Regarding immediate effects, 2-day average number concentration of Aitken mode (30-100nm) particles had strongest effects. An IQR (2269cm(-3)) increase in 2-day average number concentration of 30-50nm particles led to a 2.4% (-1.5-6.5%) increase in total, and a 1.7% (-2.9-6.5%) increase in severe cardiovascular emergency room visits. The immediate effects of mass concentration came mainly from 1000-2500nm particles. An IQR (11.7μgm(-3)) increase in 2-day average mass concentration of 1000-2500nm particles led to an around 2.4% (0.4-4.4%) increase in total, and a 1.7% (-0.8-4.2%) increase in severe cardiovascular emergency room visits. The lagged effect curves of number and mass concentrations of 100-300nm particles or 300-1000nm particles were quite similar, indicating that using particulate number or mass concentrations seemed not to affect the cardiovascular effect (of particles within one size fraction). The effects of number concentration of ultrafine particles, sub-micrometer particles (3-1000nm) and 10-30nm particles were substantially higher in winter comparing with in summer., Conclusions: Elevated concentration levels of sub-micrometer particles were associated with increased cardiovascular morbidity. Ultrafine particles showed delayed effects, while accumulation mode (100-1000nm) particles showed immediate effects. Using number or mass concentrations did not affect the particle effects., (Copyright © 2012 Elsevier Inc. All rights reserved.)

The success of epidemiological studies depends on the use of appropriate exposure variables. The purpose of this study is to extract a relatively small selection of variables characterizing ambient particulate matter from a large measurement data set. The original data set comprised a total of 96 particulate matter variables that have been continuously measured since 2004 at an urban background aerosol monitoring site in the city of Augsburg, Germany. Many of the original variables were derived from measured particle size distribution (PSD) across the particle diameter range 3 nm to 10 μm, including size-segregated particle number concentration, particle length concentration, particle surface concentration and particle mass concentration. The data set was complemented by integral aerosol variables. These variables were measured by independent instruments, including black carbon, sulfate, particle active surface concentration and particle length concentration. It is obvious that such a large number of measured variables cannot be used in health effect analyses simultaneously. The aim of this study is a pre-screening and a selection of the key variables that will be used as input in forthcoming epidemiological studies. In this study, we present two methods of parameter selection and apply them to data from a two-year period from 2007 to 2008. We used the agglomerative hierarchical cluster method to find groups of similar variables. In total, we selected 15 key variables from 9 clusters which are recommended for epidemiological analyses. We also applied a two-dimensional visualization technique called "heatmap" analysis to the Spearman correlation matrix. 12 key variables were selected using this method. Moreover, the positive matrix factorization (PMF) method was applied to the PSD data to characterize the possible particle sources. Correlations between the variables and PMF factors were used to interpret the meaning of the cluster and the heatmap analyses., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Background: Epidemiological studies have shown associations between particulate matter (PM) and heart rate variability (HRV)., Objectives: We investigated the effects of air pollution on the root mean square of successive differences (RMSSD) and the standard deviation of normal-to-normal intervals (SDNN) and effect modifications by single nucleotide polymorphisms (SNP)., Methods: Between March 2007 and December 2008 207 ECG recordings comprising 1153 1 h-intervals were measured in 61 individuals with type 2 diabetes or impaired glucose tolerance (IGT) from Augsburg, Germany. Associations between 1 h-averages of air pollutants (PM, sulphate, black carbon, and ultrafine particles) and ECG parameters were analyzed using additive mixed models. Genotypes of 139 SNPs supposed to be involved in cardiac rhythm were identified in the literature. Using regression trees for longitudinal data, SNPs associated with ECG parameters were determined and included as potential air pollution effect modifiers., Results: We observed concurrent and lagged decreases in SDNN by about 2-5% in association with all air pollutants, especially in participants with at least one minor allele of rs332229. Increases in PM<2.5 μm (PM(2.5)) were associated with 4 h-lagged decreases of -6.6% [95%-confidence interval:-10.6;-2.6%] and -13.0% [-20.7;-5.1%] in SDNN in individuals with one or two minor alleles. We observed a -7.2% [-12.2;-1.8%] reduction in RMSSD associated with concurrent increases in PM(2.5.) Individuals with at least one minor allele of rs2096767 or at most one minor allele of rs2745967 exhibited stronger PM(2.5) effects., Conclusions: We identified a genetic predisposition in persons with diabetes or IGT making them potentially more susceptible to air pollutants with regard to changes in HRV., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Background: While the link between particulate matter and cardiovascular mortality is well established, it is not fully investigated and understood which properties of the aerosol might be responsible for the health effects, especially in polluted mega-city areas., Objectives: Our goal was to explore the association between daily cardiovascular mortality and different particle metrics in the sub-micrometer range in Beijing, China., Methods: We obtained daily counts of cause-specific cardiovascular deaths in the Beijing urban area for the period March 2004 to August 2005. Concurrently, continuous measurements of particle number size distributions were performed. Particle number concentrations (NC) between 0.003 μm and 0.8 μm were converted to particle mass and surface area concentrations assuming spherical particles. Semi-parametric Poisson regression models adjusting for trend, seasonality, day of the week, and meteorology were used to estimate immediate, delayed and cumulative particle effects. Additionally, effect modification by air mass origin was investigated., Results: We observed associations between daily cardiovascular mortality and particle NC for a 2-days delay. Moreover, nearly all particle metrics showed 2-days delayed associations with ischemic heart disease mortality. The strongest association was found for particle NC in the size range 0.03-0.1 μm (7.1% increase in daily mortality with a 95%-confidence interval of 2.9%-11.5%, per an increase of 6250 particles/cm3). Results for surface and mass concentrations with a lag of two days indicated effect modification by air mass origin, whereas effects of particle NC were not modified., Conclusions: Results show an elevated risk of cardiovascular mortality in Beijing from short-term exposure to particulate air pollution in the sub-micrometer range. Results also indicate that locally produced smaller particles and regionally transported particles may exhibit different effects in Beijing., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Epidemiological studies on health effects of outdoor air pollution are largely based on a single monitoring site to estimate the exposure of people living in urban areas. For such an approach two aspects are important: the temporal correlation and the spatial variation of the absolute levels of concentrations measured at different sites in an urban area. Whereas many studies have shown small spatial variability of fine particles in urban areas, little is known on how well a single monitoring station could represent the temporal and spatial variation of ultrafine particles across urban areas. In our study we investigated the temporal and spatial variation of particle number concentration (PNC) at four background sites in Augsburg, Germany. Two of them were influenced by traffic, one was placed in the outskirts of the city. The average PNC levels at two urban background sites with traffic impact were 16,943 cm(-3) and 20,702 cm(-3), respectively, compared to 11,656 cm(-3) at the urban background site without traffic impact (ratio 1.5 to 1.8). The Spearman correlation coefficients between the monitoring sites were high (r>0.80). The pronounced differences in absolute PNC levels suggest that the use of a single monitoring station in long-term epidemiological studies must be insufficient to attribute accurate exposure levels of PNC to all study subjects. On the other hand, the high temporal correlations of PNC across the city area of Augsburg implicate that in epidemiological time-series studies the use of one single ambient monitoring site is an adequate approach for characterizing exposure to ultrafine particles.

Particle size distribution data collected between September 1997 and August 2001 in Erfurt, Germany were used to investigate the sources of ambient particulate matter by positive matrix factorization (PMF). A total of 29,313 hourly averaged particle size distribution measurements covering the size range of 0.01 to 3.0 microm were included in the analysis. The particle number concentrations (cm(-3)) for the 9 channels in the ultrafine range, and mass concentrations (ng m(-3)) for the 41 size bins in the accumulation mode and particle up to 3 microm in aerodynamic diameter were used in the PMF. The analysis was performed separately for each season. Additional analyses were performed including calculations of the correlations of factor contributions with gaseous pollutants (O(3), NO, NO(2), CO and SO(2)) and particle composition data (sulfate, organic carbon and elemental carbon), estimating the contributions of each factor to the total number and mass concentration, identifying the directional locations of the sources using the conditional probability function, and examining the diurnal patterns of factor scores. These results were used to assist in the interpretation of the factors. Five factors representing particles from airborne soil, ultrafine particles from local traffic, secondary aerosols from local fuel combustion, particles from remote traffic sources, and secondary aerosols from multiple sources were identified in all seasons.

Ambient particulate air pollution has been associated with altered cardiac function and systemic inflammation. We reported repolarization changes and variations in markers of inflammation in association with ambient particulate exposure in a panel of male coronary artery disease (CAD) patients. The objective of this analysis was to identify the specific sources associated with these effects. A panel of male CAD patients participated in 12 clinical visits in Erfurt, Germany. We used 56 patients' 5min ECG recordings for the analysis of repolarization parameters QT interval and T wave amplitude, and 57 patients' plasma samples to determine the biomarkers von Willebrand factor (vWF) and C-reactive protein (CRP). Linear and logistic regression models were used to analyze the associations between five particle source factors (airborne soil, local traffic-related ultrafine particles, combustion-generated aerosols, diesel traffic-related particles, and secondary aerosols) and these health parameters adjusting for trend, weekday and meteorological variables. An increase in QT interval and a decrease in T wave amplitude were observed in association with traffic-related particles exposure during 0-23h before the ECG recordings. The inflammatory marker vWF increased in association with both traffic-related particles and combustion-generated aerosols at different exposure lags. All source particles had positive associations with CRP levels above the 90th percentile (8.5mg/l). These results suggest that traffic-related and combustion-generated particles show stronger adverse health impact with regard to cardiac effects, and that particles from different sources induce an acute phase response in these patients.

Source apportionment of urban fine particle mass (PM(2.5)) was performed from data collected during 1998-1999 in Amsterdam (The Netherlands), Erfurt (Germany) and Helsinki (Finland), using principal component analysis (PCA) and multiple linear regression. Six source categories of PM(2.5) were identified in Amsterdam. They were traffic-related particles (30% of the average PM(2.5)), secondary particles (34%), crustal material (7%), oil combustion (11%), industrial and incineration processes (9%), and sea salt (2%). The unidentified PM(2.5) fraction was 7% on the average. In Erfurt, four source categories were extracted with some difficulties in interpretation of source profiles. They were combustion emissions related to traffic (32%), secondary PM (32%), crustal material (21%) and industrial processes (8%). In Erfurt, 3% of PM(2.5) remained unidentified. Air pollution data and source apportionment results from the two Central European cities were compared to previously published results from Helsinki, where about 80% of average PM(2.5) was attributed to transboundary air pollution and particles from traffic and other regional combustion sources. Our results indicate that secondary particles and local combustion processes (mainly traffic) were the most important source categories in all cities; their impact on the average PM(2.5) was almost equal in Amsterdam and Erfurt whereas, in Helsinki, secondary particles made up for as much as half of the total average PM(2.5).

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.

We present the first results of a source apportionment for the urban aerosol in Erfurt, Germany, for the period 1995-1998. The analysis is based on data of particle number concentrations (0.01-2.5 microm; mean 1.8 x 10(4) cm(-3), continuous), the concentration of the ambient gases SO(2), NO, NO(2) and CO (continuous), particle mass less than 2.5 microm (PM(2.5)) and less than 10 microm (PM(10)) (Harvard Impactor sampling, mean PM(2.5) 26.3 micro/m(3), mean PM(10) 38.2 microg/m(3)) and the size fractionated concentrations of 19 elements (impactor sampling 0.05-1.62 microm, PIXE analysis). We determined: (a) the correlations between (i) the 1- and 24-h average concentrations of the gaseous pollutants and the particle number as well as the particle mass concentration and (ii) between the 24-h elemental concentrations; (b) Crustal Enrichment Factors for the PIXE elements using Si as reference element; and (c) the diurnal pattern of the measured pollutants on weekdays and on weekends. The highly correlated PIXE elements Si, Al, Ti and Ca having low enrichment factors were identified as soil elements. The strong correlation of particle number concentrations with NO, which is considered to be typically emitted by traffic, and the striking similarity of their diurnal variation suggest that a sizable fraction of the particle number concentration is associated with emission from vehicles. Besides NO and particle number concentrations other pollutants such as NO(2), CO as well as the elements Zn and Cu were strongly correlated and appear to reflect motor vehicle traffic. Sulfur could be a tracer for coal combustion, however, it was not correlated with any of the quoted elements. Highly correlated elements V and Ni have similar enrichment factors and are considered as tracers for oil combustion.

A comparison, based on the regression of 32 daily mean PM25 aerosol loadings determined by a tapered element oscillating microbalance (TEOM) and by a Harvard impactor (HI), is reported for the ambient aerosol of Erfurt (Germany). The PM2.5 concentrations measured by the TEOM were systematically lower then those obtained by the HI. The ratio of the means TEOM/HI was 0.74 and the regression equation is TEOM = 0.69 x HI + 0.071. This result is consistent with reports elsewhere suggesting that semi-volatile aerosol material is lost from the heated sample filter on the TEOM. To verify this assertion, a heating system was developed for the HI which was able to keep the HI sample filter at 50+/-1 degrees C. After the implementation of this heating system, no systematically differences were observed between the TEOM and the heated HI system. The ratio of means was 1.06 and the regression equation TEOM = 1.10 x HI - 0.668. Because the measured levels of ammonium nitrate were very low in Erfurt, we concluded that other compounds like semi-volatile organics were responsible for the loss of particulate material at 50 degrees C.

Here we report indoor and outdoor concentrations of NO2 for Erfurt and Hamburg and assess the contribution of the most important indoor sources (e.g. the presence of gas cooking ranges, smoking) and outdoor sources (traffic exhaust emissions). We examined the relative contribution of the different sources of NO2 to the total indoor NO2 levels in Erfurt and Hamburg. NO2 indoor concentrations in Hamburg were slightly higher than those in Erfurt (i.e. living room: 15 microg m(-3) for Erfurt and 17 microg m(-3) for Hamburg). A linear regression model including the variables, place of residence, season and outdoor NO2 levels, location of the home within the city, housing and occupant characteristics accounted for 38% of the NO2 variance. The most important predictors of indoor NO2 concentrations were gas in cooking followed by other characteristics, such as ventilation or outdoor NO2 level. Residences in which gas was used for cooking, or in which occupants smoked, had substantially higher indoor NO2 concentrations (41 or 18% increase, respectively). An increase in the outdoor NO2 concentration from the 25th to the 75th-percentile (17 microg m(-3)) was associated with a 33% increase in the living room NO2 concentration. Multiple regression analysis for both cities separately illustrated that use of gas for cooking was the major indoor source of NO2. This variable caused a similar increase in the indoor NO2 levels in each city (43% in Erfurt and 47% in Hamburg). However, outdoor sources of NO2 (motor vehicle traffic) contributed more to indoor NO2 levels in Hamburg than in Erfurt.