Quality control and quality assurance for particle size distribution measurements at an urban monitoring station in Augsburg, Germany

Levels and drivers of urban black carbon and health risk assessment during pre- and COVID19 lockdown in Augsburg, Germany

This study aimed to evaluate the levels and phenomenology of equivalent black carbon (eBC) at the city center of Augsburg, Germany (01/2018 to 12/2020). Furthermore, the potential health risk of eBC based on equivalent numbers of passively smoked cigarettes (PSC) was also evaluated, with special emphasis on the impact caused by the COVID19 lockdown restriction measures. As it could be expected, peak concentrations of eBC were commonly recorded in morning (06:00-8:00 LT) and night (19:00-22:00 LT) in all seasons, coinciding with traffic rush hours and atmospheric stagnation. The variability of eBC was highly influenced by diurnal variations in traffic and meteorology (air temperature (T), mixing-layer height (MLH), wind speed (WS)) across days and seasons. Furthermore, a marked "weekend effect" was evidenced, with an average eBC decrease of ∼35% due to lower traffic flow. During the COVID19 lockdown period, an average ∼60% reduction of the traffic flow resulted in ∼30% eBC decrease, as the health risks of eBC exposure was markedly reduced during this period. The implementation of a multilinear regression analysis allowed to explain for 53% of the variability in measured eBC, indicating that the several factors (e.g., traffic and meteorology) may contribute simultaneously to this proportion. Overall, this study will provide valuable input to the policy makers to mitigate eBC pollutant and its adverse effect on environment and human health.

Investigation of COVID-19-related lockdowns on the air pollution changes in augsburg in 2020, Germany

The COVID-19 pandemic in Germany in 2020 brought many regulations to impede its transmission such as lockdown. Hence, in this study, we compared the annual air pollutants (CO, NO, NO₂, O₃, PM₁₀, PM_2.5, and BC) in Augsburg in 2020 to the record data in 2010-2019. The annual air pollutants in 2020 were significantly (p < 0.001) lower than that in 2010-2019 except O₃, which was significantly (p = 0.02) higher than that in 2010-2019. In a depth perspective, we explored how lockdown impacted air pollutants in Augsburg. We simulated air pollutants based on the meteorological data, traffic density, and weekday and weekend/holiday by using four different models (i.e. Random Forest, K-nearest Neighbors, Linear Regression, and Lasso Regression). According to the best fitting effects, Random Forest was used to predict air pollutants during two lockdown periods (16/03/2020-19/04/2020, 1st lockdown and 02/11/2020-31/12/2020, 2nd lockdown) to explore how lockdown measures impacted air pollutants. Compared to the predicted values, the measured CO, NO₂, and BC significantly reduced 18.21%, 21.75%, and 48.92% in the 1st lockdown as well as 7.67%, 32.28%, and 79.08% in the 2nd lockdown. It could be owing to the reduction of traffic and industrial activities. O₃ significantly increased 15.62% in the 1st lockdown but decreased 40.39% in the 2nd lockdown, which may have relations with the fluctuations the NO titration effect and photochemistry effect. PM₁₀ and PM_2.5 were significantly increased 18.23% an 10.06% in the 1st lockdown but reduced 34.37% and 30.62% in the 2nd lockdown, which could be owing to their complex generation mechanisms.

Spatiotemporal Characteristics and Driving Factors of Black Carbon in Augsburg, Germany: Combination of Mobile Monitoring and Street View Images

The study investigates the spatial pattern of black carbon (BC) at a high spatial resolution in Augsburg, Germany. Sixty two walks were performed to assess the concentrations of equivalent black carbon (eBC), ultraviolet particulate matter (UVPM), and equivalent brown carbon (eBrC) in different seasons and at different times of the day with a mobile platform (i.e., trolley). Along with BC measurements, images of street microenvironments were recorded. Meteorological parameters, including temperature, relative humidity, and wind speed, were monitored. The BC concentrations showed significant spatial heterogeneity and diurnal variations peaking in the morning and at night. The highest BC concentrations were observed near dense traffic. The correlations between BC and street views (buildings, roads, cars, and vegetation) were weak but highly significant. Moreover, meteorological factors also influenced the BC concentration. A model based on street view images and meteorological data was developed to examine the driving factors of the spatial variability of BC concentrations at a higher spatial resolution as different microenvironments based on traffic density. The best results were obtained for UVPM and eBC (71 and 70% explained variability). eBrC (53%), to which other sources besides road traffic can also make significant contributions, is modeled less well.

Hourly Exposure to Ultrafine Particle Metrics and the Onset of Myocardial Infarction in Augsburg, Germany

BACKGROUND

Epidemiological evidence on the health effects of ultrafine particles (UFP) remains insufficient to infer a causal relationship that is largely due to different size ranges and exposure metrics examined across studies. Moreover, evidence regarding the association between UFP and cardiovascular disease at a sub-daily timescale is lacking.

OBJECTIVE

We investigated the relationship between different particle metrics, including particle number (PNC), length (PLC), and surface area (PSC) concentrations, and myocardial infarction (MI) at an hourly timescale.

METHODS

We collected hourly air pollution and meteorological data from fixed urban background monitoring sites and hourly nonfatal MI cases from a MI registry in Augsburg, Germany, during 2005-2015. We conducted a time-stratified case-crossover analysis with conditional logistic regression to estimate the association between hourly particle metrics and MI cases, adjusted for air temperature and relative humidity. We also examined the independent effects of a certain particle metric in two-pollutant models by adjusting for copollutants, including particulate matter (PM) with an aerodynamic diameter of ≤10μm or 2.5μm (PM10 and PM2.5, respectively), nitrogen dioxide, ozone, and black carbon.

RESULTS

Overall, a total of 5,898 cases of nonfatal MI cases were recorded. Exploratory analyses showed similar associations across particle metrics in the first 6-12 h. For example, interquartile range increases in PNC within the size range of 10-100 nm, PLC, and PSC were associated with an increase of MI 6 h later by 3.27% [95% confidence interval (CI): 0.27, 6.37], 5.71% (95% CI: 1.79, 9.77), and 5.84% (95% CI: 1.04, 10.87), respectively. Positive, albeit imprecise, associations were observed for PNC within the size range of 10-30 nm and 100-500 nm. Effect estimates for PLC and PSC remained similar after adjustment for PM and gaseous pollutants.

CONCLUSIONS

Transient exposure to particle number, length, and surface area concentrations or other potentially related exposures may trigger the onset of nonfatal myocardial infraction. https://doi.org/10.1289/EHP5478.

Comparison of methods for converting Dylos particle number concentrations to PM2.5 mass concentrations

The aim of this study was to (a) develop a method for converting particle number concentrations (PNC) obtained by Dylos to PM2.5 mass concentrations, (b) compare this conversion with similar methods available in the literature, and (c) compare Dylos PM2.5 obtained using all available conversion methods with gravimetric samples. Data were collected in multiple residences in three European countries using the Dylos and an Aerodynamic Particle Sizer (APS, TSI) in the Netherlands or an optical particle counter (OPC, GRIMM) in Greece. Two statistical fitted curves were developed based on Dylos PNC and either an APS or an OPC particle mass concentrations (PMC). In addition, at the homes of 16 volunteers (UK and Netherlands), Dylos measurements were collected along with gravimetric samples. The Dylos PNC were transformed to PMC using all the fitted curves obtained during this study (and three found in the literature) and were compared with gravimetric samples. The method developed in the present study using an OPC showed the highest correlation (Pearson (R) = 0.63, Concordance (ρ_c ) = 0.61) with gravimetric data. The other methods resulted in an underestimation of PMC compared to gravimetric measurements (R = 0.65-0.55, ρ_c  = 0.51-0.24). In conclusion, estimation of PM2.5 concentrations using the Dylos is acceptable for indicative purposes.

Organic speciation of ambient quasi-ultrafine particulate matter (PM0.36) in Augsburg, Germany: Seasonal variability and source apportionment

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, O₃ 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 NO₂ level.

Land use regression modeling of ultrafine particles, ozone, nitrogen oxides and markers of particulate matter pollution in Augsburg, Germany

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 (PM₁₀, PM_2.5), soot (PM_2.5abs) and nitrogen oxides (NO_x, NO₂) 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 (R²) was high for PNC and ozone (0.89 and 0.88). Cross-validation adjusted R² was slightly lower (0.82 and 0.81) but still indicated a very good fit. LUR models for other pollutants performed well with adjusted R² between 0.68 (PM_coarse) and 0.94 (NO₂). Contrary to previous studies, ozone showed a moderate correlation with NO₂ (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.

Association of novel metrics of particulate matter with vascular markers of inflammation and coagulation in susceptible populations -results from a panel study

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.

Genome-Wide Analysis of DNA Methylation and Fine Particulate Matter Air Pollution in Three Study Populations: KORA F3, KORA F4, and the Normative Aging Study

BACKGROUND

Epidemiological studies have reported associations between particulate matter (PM) concentrations and cancer and respiratory and cardiovascular diseases. DNA methylation has been identified as a possible link but so far it has only been analyzed in candidate sites.

OBJECTIVES

We studied the association between DNA methylation and short- and mid-term air pollution exposure using genome-wide data and identified potential biological pathways for additional investigation.

METHODS

We collected whole blood samples from three independent studies-KORA F3 (2004-2005) and F4 (2006-2008) in Germany, and the Normative Aging Study (1999-2007) in the United States-and measured genome-wide DNA methylation proportions with the Illumina 450k BeadChip. PM concentration was measured daily at fixed monitoring stations and three different trailing averages were considered and regressed against DNA methylation: 2-day, 7-day and 28-day. Meta-analysis was performed to pool the study-specific results.

RESULTS

Random-effect meta-analysis revealed 12 CpG (cytosine-guanine dinucleotide) sites as associated with PM concentration (1 for 2-day average, 1 for 7-day, and 10 for 28-day) at a genome-wide Bonferroni significance level (p ≤ 7.5E-8); 9 out of these 12 sites expressed increased methylation. Through estimation of I2 for homogeneity assessment across the studies, 4 of these sites (annotated in NSMAF, C1orf212, MSGN1, NXN) showed p > 0.05 and I2 < 0.5: the site from the 7-day average results and 3 for the 28-day average. Applying false discovery rate, p-value < 0.05 was observed in 8 and 1,819 additional CpGs at 7- and 28-day average PM2.5 exposure respectively.

CONCLUSION

The PM-related CpG sites found in our study suggest novel plausible systemic pathways linking ambient PM exposure to adverse health effect through variations in DNA methylation.

CITATION

Panni T, Mehta AJ, Schwartz JD, Baccarelli AA, Just AC, Wolf K, Wahl S, Cyrys J, Kunze S, Strauch K, Waldenberger M, Peters A. 2016. A genome-wide analysis of DNA methylation and fine particulate matter air pollution in three study populations: KORA F3, KORA F4, and the Normative Aging Study. Environ Health Perspect 124:983-990; http://dx.doi.org/10.1289/ehp.1509966.

Semi-continuous sampling of health relevant atmospheric particle subfractions for chemical speciation using a rotating drum impactor in series with sequential filter sampler

To achieve unattended continuous long-term (eg., 1 week) sampling of size-segregated 24-h ambient particulate matter (PM), a sampling strategy of a modified 3-stage rotating drum impactor (RDI) in series with a sequential filter sampler was introduced and verified in a field campaign. Before the field sampling, lab experiment was conducted to test the collection efficiency of the third stage of the RDI using the quartz-fiber filter (QFF) as the substrate. The measured value is 0.36 μm, which is larger than the nominal value 0.1 μm. A fast direct analysis of organic species in all size fractions (<0.36, 0.36-1, 1-2.4, and 2.4-10 μm) of 24-h ambient samples was done using in situ derivatization thermal desorption gas chromatography time-of-flight mass spectrometry (IDTD-GC-TOFMS). A few secondary originated polar markers (dicarboxylic acids, cis-pinonic acid, etc.) were introduced and evaluated using this method for the first time and quantified simultaneously with polycyclic aromatic hydrocarbons (PAH) in the filter samples (<0.36 μm). For the other RDI strip samples (0.36-1, 1-2.4, and 2.4-10 μm), PAH and levoglucosan were quantified. The comparability of two such sampler sets was verified with respect to the PM collection profile of the two RDIs as well as measured concentration of chemical compounds in each sampled size fraction, so that a future epidemiological study on the relationship between the finest PM/its chemical composition and health outcome could be carried out through parallel sampling at two sites. The internal correlations between the size-segregated organic compounds are discussed. Besides, the correlations between the size-segregated organic species and size-segregated particulate number concentration (PNC) as well as meteorological parameter are discussed as well.

Personal exposure to ultrafine particles: Two-level statistical modeling of background exposure and time-activity patterns during three seasons

Personal exposure to air pollution is associated with time- and location-specific factors including indoor and outdoor air pollution, meteorology and time activities. Our investigation aims at the description and identification of factors determining personal exposure to particle number concentration (PNC) in everyday situations. Ten volunteers recorded their personal exposure to PNC and kept an activity diary in three different seasons besides stationary measurements of ambient air pollution and meteorology. Background exposure to PNC was modelled using the most predictive variables. In a second step, the effects of the activities were calculated adjusted for the background exposure. The average personal PNC level was highest in winter and was three times higher than the mean stationary PNC level while staying indoors and two times higher while staying outdoors. Personal indoor PNC levels were significantly increased during the use of candles, cooking and the occurrence of smell of food. High stationary outdoor PNC levels and low dew point temperatures were associated with increased personal outdoor PNC levels. Times spent in public transport were associated with lower personal PNC levels than other times spent in transportation. Personal PNC levels in everyday situations exhibited a large variability because of seasonal, microenvironment-specific and activity-specific influences.

Elevated particle number concentrations induce immediate changes in heart rate variability: a panel study in individuals with impaired glucose metabolism or diabetes

BACKGROUND

The health effects of short-term exposure to ambient ultrafine particles in micro-environments are still under investigation.

METHODS

Sixty-four individuals with type 2 diabetes and impaired glucose tolerance recorded ambulatory electrocardiograms over five to six hours on 191 occasions in a panel study in Augsburg, Germany. Personal exposure to particle number concentrations (PNC) was monitored for each individual on 5-minute basis concurrently and particulate matter with an aerodynamic diameter<2.5 μm (PM2.5) was acquired from a central monitoring site on an hourly basis.

RESULTS

More than 11,000 5-minute intervals were available for heart rate and measures of heart rate variability including SDNN (standard deviation of NN intervals). A concurrent decrease in 5-minute SDNN of -0.56% (95% confidence limits (CI): -1.02%; -0.09%) and a 5-minute delayed increase in heart rate of 0.23 % (95% CI: 0.11%; 0.36%) was observed with an increase in personal PNC of 16,000 per cm3 in additive mixed models. Models evaluating the association of concurrent 5-minute personal PNC and of 1-hour PM2.5 showed independent effects on SDNN.

CONCLUSION

The data suggest that freshly emitted ultrafine particles and aged fine particulate matter are both associated with changes in cardiac function in individuals with type 2 diabetes and impaired glucose tolerance in urban areas.

Personal day-time exposure to ultrafine particles in different microenvironments

In order to assess the personal exposure to ultrafine particles (UFP) during individual day-time activities and to investigate the impact of different microenvironments on exposure, we measured personal exposure to particle number concentrations (PNC), a surrogate for UFP, among 112 non-smoking participants in Augsburg, Germany over a nearly two-year period from March 2007 to December 2008. We obtained 337 personal PNC measurements from 112 participants together with dairies of their activities and locations. The measurements lasted on average 5.5h and contained on average 330 observations. In addition, ambient PNC were measured at an urban background stationary monitoring site. Personal PNC were highly variable between measurements (IQR of mean: 11780-24650cm(-3)) and also within a single measurement. Outdoor personal PNC in traffic environments were about two times higher than in non-traffic environments. Higher indoor personal PNC were associated with activities like cooking, being in a bistro or exposure to passive smoking. Overall, personal and stationary PNC were weakly to moderately correlated (r<0.41). Personal PNC were much higher than stationary PNC in traffic (ratio: 1.5), when shopping (ratio: 2.4), and indoors with water vapor (ratio: 2.5). Additive mixed models were applied to predict personal PNC by participants' activities and locations. Traffic microenvironments were significant determinants for outdoor personal PNC. Being in a bistro, passive smoking, and cooking contributed significantly to an increased indoor personal PNC.

Impact of atmospheric boundary layer depth variability and wind reversal on the diurnal variability of aerosol concentration at a valley site

The development of the atmospheric boundary layer (ABL) plays a key role in affecting the variability of atmospheric constituents such as aerosols, greenhouse gases, water vapor, and ozone. In general, the concentration of any tracers within the ABL varies due to the changes in the mixing volume (i.e. ABL depth). In this study, we investigate the impact on the near-surface aerosol concentration in a valley site of 1) the boundary layer dilution due to vertical mixing and 2) changes in the wind patterns. We use a data set obtained during a 10-day field campaign in which a number of remote sensing and in-situ instruments were deployed, including a ground-based aerosol lidar system for monitoring of the ABL top height (zi), a particle counter to determine the number concentration of aerosol particles at eight different size ranges, and tower-based standard meteorological instruments. Results show a clearly visible decreasing trend of the mean daytime zi from 2900 m AGL (above ground level) to 2200 m AGL during a three-day period which resulted in increased near-surface pollutant concentrations. An inverse relationship exists between the zi and the fine fraction (0.3-0.7 μm) accumulation mode particles (AMP) on some days due to the dilution effect in a well-mixed ABL. These days are characterized by the absence of daytime upvalley winds and the presence of northwesterly synoptic-driven winds. In contrast, on the days with an onset of an upvalley wind circulation after the morning transition, the wind-driven local transport mechanism outweighs the ABL-dilution effect in determining the variability of AMP concentration. The interplay between the ABL depth evolution and the onset of the upvalley wind during the morning transition period significantly governs the air quality in a valley and could be an important component in the studies of mountain meteorology and air quality.

Short-term effects of air temperature on blood pressure and pulse pressure in potentially susceptible individuals

BACKGROUND

Only few epidemiological studies have investigated the association between air temperature and blood pressure (BP) or pulse pressure (PP), with inconsistent findings. We examined whether short-term changes in air temperature were associated with changes in BP or PP in three different populations.

METHODS

Between March 2007 and December 2008, 371 systolic and diastolic BP measurements were collected in 30 individuals with type-2 diabetes mellitus (T2D), 30 persons with impaired glucose tolerance and 42 healthy individuals without a metabolic disorder from Augsburg, Germany. Hourly means of ambient meteorological data were obtained from a fixed measurement station. Personal temperature measurements were conducted using data loggers. Temperature effects were evaluated using additive mixed models adjusting for time trend and relative humidity.

RESULTS

Decreases in air temperature were associated with an increase in systolic BP, diastolic BP and PP in individuals with T2D. For example, a 1°C decrease in ambient temperature was associated with an immediate increase in systolic BP of 1.0 mmHg (95%-confidence interval: [0.5;1.4]mmHg). Effects of personally measured air temperature were similar. Temperature effects were modified by age, body mass index, gender, antihypertensive medication and whereabouts, such as being indoors.

CONCLUSIONS

We observed associations between decreases in air temperature and increases in BP as well as PP in persons with T2D indicating that these people might be potentially more susceptible to changes in air temperature. Our findings may provide a hypothesis for a mechanism between air temperature decreases and short-term increases of cardiovascular events.

Selection of key ambient particulate variables for epidemiological studies - applying cluster and heatmap analyses as tools for data reduction

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.

Cardiovascular and inflammatory effects of intratracheally instilled ambient dust from Augsburg, Germany, in spontaneously hypertensive rats (SHRs)

Rationale

Several epidemiological studies associated exposure to increased levels of particulate matter in Augsburg, Germany with cardiovascular mortality and morbidity. To elucidate the mechanisms of cardiovascular impairments we investigated the cardiopulmonary responses in spontaneously hypertensive rats (SHR), a model for human cardiovascular diseases, following intratracheal instillation of dust samples from Augsburg.

Methods

250 μg, 500 μg and 1000 μg of fine ambient particles (aerodynamic diameter <2.5 μm, PM_2.5-AB) collected from an urban background site in Augsburg during September and October 2006 (PM_2.5 18.2 μg/m³, 10,802 particles/cm³) were instilled in 12 months old SHRs to assess the inflammatory response in bronchoalveolar lavage fluid (BALF), blood, lung and heart tissues 1 and 3 days post instillation. Radio-telemetric analysis was performed to investigate the cardiovascular responses following instillation of particles at the highest dosage based on the inflammatory response observed.

Results

Exposure to 1000 μg of PM_2.5-AB was associated with a delayed increase in delta mean blood pressure (ΔmBP) during 2^nd-4^th day after instillation (10.0 ± 4.0 vs. -3.9 ± 2.6 mmHg) and reduced heart rate (HR) on the 3^rd day post instillation (325.1 ± 8.8 vs. 348.9 ± 12.5 bpm). BALF cell differential and inflammatory markers (osteopontin, interleukin-6, C-reactive protein, and macrophage inflammatory protein-2) from pulmonary and systemic level were significantly induced, mostly in a dose-dependent way. Protein analysis of various markers indicate that PM_2.5-AB instillation results in an activation of endothelin system (endothelin1), renin-angiotensin system (angiotensin converting enzyme) and also coagulation system (tissue factor, plasminogen activator inhibitor-1) in pulmonary and cardiac tissues during the same time period when alternation in ΔmBP and HR have been detected.

Conclusions

Our data suggests that high concentrations of PM_2.5-AB exposure triggers low grade PM mediated inflammatory effects in the lungs but disturbs vascular homeostasis in pulmonary tissues and on a systemic level by affecting the renin angiotensin system, the endothelin system and the coagulation cascade. These findings are indicative for promotion of endothelial dysfunction, atherosclerotic lesions, and thrombogeneis and, thus, provide plausible evidence that susceptible-predisposed individuals may develop acute cardiac events like myocardial infarction when repeatedly exposed to high pollution episodes as observed in epidemiological studies in Augsburg, Germany.

Surgical smoke and ultrafine particles

Background

Electrocautery, laser tissue ablation, and ultrasonic scalpel tissue dissection all generate a 'surgical smoke' containing ultrafine (<100 nm) and accumulation mode particles (< 1 μm). Epidemiological and toxicological studies have shown that exposure to particulate air pollution is associated with adverse cardiovascular and respiratory health effects.

Methods

To measure the amount of generated particulates in 'surgical smoke' during different surgical procedures and to quantify the particle number concentration for operation room personnel a condensation particle counter (CPC, model 3007, TSI Inc.) was applied.

Results

Electro-cauterization and argon plasma tissue coagulation induced the production of very high number concentration (> 100000 cm^-3) of particles in the diameter range of 10 nm to 1 μm. The peak concentration was confined to the immediate local surrounding of the production side. In the presence of a very efficient air conditioning system the increment and decrement of ultrafine particle occurrence was a matter of seconds, with accumulation of lower particle number concentrations in the operation room for only a few minutes.

Conclusion

Our investigation showed a short term very high exposure to ultrafine particles for surgeons and close assisting operating personnel – alternating with longer periods of low exposure.