Interlab comparison of elemental analysis for low ambient urban PM2.5 levels

Indoor and ambient black carbon and fine particulate matter associations with blood biomarkers in COPD patients

BACKGROUND

Systemic inflammation contributes to cardiovascular risk and chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between systemic inflammation and exposure to ambient fine particulate matter (PM ≤ 2.5 μm diameter; PM2.5), and black carbon (BC), a PM2.5 component attributable to traffic and other sources of combustion, infiltrating indoors are not well described.

METHODS

Between 2012 and 2017, COPD patients completed in-home air sampling over one-week intervals, up to four times (seasonally), followed by measurement of plasma biomarkers of systemic inflammation, C-reactive protein (CRP) and interleukin-6 (IL-6), and endothelial activation, soluble vascular adhesion molecule-1 (sVCAM-1). Ambient PM2.5, BC and sulfur were measured at a central site. The ratio of indoor/ambient sulfur in PM2.5, a surrogate for fine particle infiltration, was used to estimate indoor BC and PM2.5 of ambient origin. Linear mixed effects regression with a random intercept for each participant was used to assess associations between indoor and indoor of ambient origin PM2.5 and BC with each biomarker.

RESULTS

144 participants resulting in 482 observations were included in the analysis. There were significant positive associations between indoor BC and indoor BC of ambient origin with CRP [%-increase per interquartile range (IQR);95 % CI (13.2 %;5.2-21.8 and 11.4 %;1.7-22.1, respectively)]. Associations with indoor PM2.5 and indoor PM2.5 of ambient origin were weaker. There were no associations with IL-6 or sVCAM-1.

CONCLUSIONS

In homes of patients with COPD without major sources of combustion, indoor BC is mainly attributable to the infiltration of ambient sources of combustion indoors. Indoor BC of ambient origin is associated with increases in systemic inflammation in patients with COPD, even when staying indoors.

Indoor (residential) and ambient particulate matter associations with urinary oxidative stress biomarkers in a COPD cohort

OBJECTIVES

Oxidative stress contributes to chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between indoor (residential) exposure to particulate matter ≤2.5 μm in diameter (PM2.5) and one of its components, black carbon (BC), and oxidative stress are ill-defined.

METHODS

Between 2012 and 2017, 140 patients with COPD completed in-home air sampling over one week intervals, followed by collection of urine samples to measure oxidative stress biomarkers, malondialdehyde (MDA), a marker of lipid peroxidation, and 8-hydroxy-2' -deoxyguanosine (8-OHdG), a marker of oxidative DNA damage. Ambient (central site) BC and PM2.5 were measured, and the ratio of indoor/ambient sulfur in PM2.5, a surrogate for residential ventilation and particle infiltration, was used to estimate indoor BC and PM2.5 of outdoor origin. Mixed effects linear regression models with a participant-specific random intercept were used to assess associations with oxidative biomarkers, adjusting for personal characteristics.

RESULTS

There were positive associations (% increase per IQR; 95 % CI) of directly measured indoor BC with total MDA (6.96; 1.54, 12.69) and 8-OHdG (4.18; -0.67, 9.27), and similar associations with both indoor BC of outdoor origin and ambient BC. There were no associations with directly measured indoor PM2.5, but there were positive associations between indoor PM2.5 of outdoor origin and total MDA (5.40; -0.91, 12.11) and 8-OHdG (8.02; 2.14, 14.25).

CONCLUSIONS

In homes with few indoor combustion sources, directly measured indoor BC, estimates of indoor BC and PM2.5 of outdoor origin, and ambient BC, were positively associated with urinary biomarkers of oxidative stress. This suggests that the infiltration of particulate matter from outdoor sources, attributable to traffic and other sources of combustion, promotes oxidative stress in COPD patients.

Improved indoor air quality during desert dust storms: The impact of the MEDEA exposure-reduction strategies

Desert dust storms (DDS) are natural events that impact not only populations close to the emission sources but also populations many kilometers away. Countries located across the main dust sources, including countries in the Eastern Mediterranean, are highly affected by DDS. In addition, climate change is expanding arid areas exacerbating DDS events. Currently, there are no intervention measures with proven, quantified exposure reduction to desert dust particles. As part of the wider "MEDEA" project, co-funded by LIFE 2016 Programme, we examined the effectiveness of an indoor exposure-reduction intervention (i.e., decrease home ventilation during DDS events and continuous use of air purifier during DDS and non-DDS days) across homes and/or classrooms of schoolchildren with asthma and adults with atrial fibrillation in Cyprus and Crete-Greece. Participants were randomized to a control or intervention groups, including an indoor intervention group with exposure reduction measures and the use of air purifiers. Particle sampling, PM₁₀ and PM_2.5, was conducted in participants' homes and/or classrooms, between 2019 and 2022, during DDS-free weeks and during DDS days for as long as the event lasted. In indoor and outdoor PM₁₀ and PM_2.5 samples, mass and content in main and trace elements was determined. Indoor PM_2.5 and PM₁₀ mass concentrations, adjusting for premise type and dust conditions, were significantly lower in the indoor intervention group compared to the control group (PM_{2.5-intervention}/PM_2.5-control = 0.57, 95% CI: 0.47, 0.70; PM_{10-intervention}/PM_10-control = 0.59, 95% CI: 0.49, 0.71). In addition, the PM_2.5 and PM₁₀ particles of outdoor origin were significantly lower in the intervention vs. the control group (PM_2.5 infiltration intervention-to-control ratio: 0.49, 95% CI: 0.42, 0.58; PM₁₀ infiltration intervention-to-control ratio: 0.68, 95% CI: 0.52, 0.89). Our findings suggest that the use of air purifiers alongside decreased ventilation measures is an effective protective measure that reduces significantly indoor exposure to particles during DDS and non-DDS in high-risk population groups.

PM2.5 elemental composition in indoor residential environments and co-exposure effects on respiratory health in an industrial area

This study aimed to identify and characterise indoor sources of particulate matter (PM) in domestic environments. 74 inhabited apartments located in the urban area of Gela (Sicily, Italy), close to a refinery, and in three villages of the hinterland were evaluated, in real-world conditions, for the elemental composition of PM_2.5. The samples were collected simultaneously inside and outside each apartment for 48 h. In addition, two of the apartments were simultaneously studied for four weeks. The elemental composition of PM_2.5 was determined by applying a chemical fractionation procedure followed by inductively-coupled plasma spectrometry analysis, with both optical emission and mass detection. The extractable, more bio-accessible fraction (_ext), and the mineralised residual fraction (_res) of each element were determined, thus increasing the selectivity of elements as source tracers. Indoor air in the considered apartments was affected by both outdoor pollution and specific indoor emission sources. The behaviour of each source was studied in detail, identifying a reliable tracer: Ti_res for soil, As_ext for industrial sources, V_ext for heavy oil combustion, Ce for cigarette smoking and Mo for the use of vacuum dust cleaners. As_ext and V_ext showed an excellent infiltration capacity, while the concentration of Ti_res was affected by a low infiltration capacity and by the contribution of particles re-suspension caused by the residents' movements. In the case of Ce and Mo, indoor concentrations were much higher than outdoor with a high variability among the apartments, due to the inhabitants' habits concerning cigarette smoke and use of electric appliances. To test the overall effect of the concomitant exposure to the identified sources on Wh12 M and on DDA, a WQS analysis was conducted. Cigarette smoking and heavily oil combustion driven the Wh12 M odds increase, while the DDA odds increase was mainly driven by heavily oil combustion and the use of vacuum dust cleaners.

Comparison of the Concentrations of Heavy Metals in PM2.5 Analyzed in Three Different Global Research Institutions Using X-ray Fluorescence

This inter-lab study aimed to evaluate the comparability of heavy metal concentrations in the same samples using three X-ray fluorescence spectrometers (XRFs) in three different global re-search institutions, namely a collaboration lab between Soonchunhyang University (Asan, Korea). and PAN (a branch of Malvern PANalytical, Seoul, Korea), RTI (Research Triangle Institute, NC, U.S.A), and Aerosol laboratory in Harvard University, Boston, U.S.A. Indoor air filter samples were collected from 8 homes using 3 filters in each household (n = 24) of individuals with asthma, and the same filter samples were sequentially analyzed separately in the collaboration lab Soonchunhyang-PAN, Harvard University, and RTI. Results showed the detection rates of most heavy metals (n = 25 metals) across the three institutions to be approximately 90%. Of the 25 metals, 16 showed coefficient of determination (R²) 0.7 or higher (10 components had 0.9 or higher) implying high correlation among institutions. Therefore, this study demonstrated XRF as a useful device, ensuring reproducibility and compatibility in the measurement of heavy metals in PM2.5, collected from indoor air filters of asthmatics’ residents.

A statistic comparison of multi-element analysis of low atmospheric fine particles (PM2.5) using different spectroscopy techniques

Over the past few decades, the metal elements (MEs) in atmospheric particles have aroused great attention. Some well-established techniques have been used to measure particle-bound MEs. However, each method has its own advantages and disadvantages in terms of complexity, accuracy, and specific elements of interest. In this study, the performances of inductively coupled plasma-optical emission spectrometry (ICP-OES) and total reflection X-ray fluorescence spectroscopy (TXRF) were evaluated for quality control to analyze data accuracy and precision. The statistic methods (Deming regression and significance testing) were applied for intercomparison between ICP-OES and TXRF measurements for same low-loading PM_2.5 samples in Weizhou Island. The results from the replicate analysis of standard filters (SRM 2783) and field filters samples indicated that 10 MEs (K, Ca, V, Cr, Mn, Fe, Ni, Cu, Zn, and Pb) showed good accuracies and precision for both techniques. The higher accuracy tended to the higher precision in the MEs analysis process. In addition, the interlab comparisons illustrated that V and Mn all had good agreements between ICP-OES and TXRF. The measurements of K, Cu and Zn were more reliable by TXRF analysis for low-loading PM_2.5. ICP-OES was more accurate for the determinations for Ca, Cr, Ni and Pb, owing to the overlapping spectral lines and low sensitivity during TXRF analysis. The measurements of Fe, influenced by low-loading PM_2.5, were not able to determine which instrument could obtain more reliable results. These conclusions could provide reference information to choose suitable instrument for the determination of MEs in low-loading PM_2.5 samples.

Non-nutritive suck and airborne metal exposures among Puerto Rican infants

Air pollution has been shown to impact multiple measures of neurodevelopment in young children. Its effects on particularly vulnerable populations, such as ethnic minorities, however, is less studied. To address this gap in the literature, we assess the associations between infant non-nutritive suck (NNS), an early indicator of central nervous system integrity, and air pollution exposures in Puerto Rico. Among infants aged 0-3 months enrolled in the Center for Research on Early Childhood Exposure and Development (CRECE) cohort from 2017 to 2019, we examined associations between exposure to fine particulate matter (PM_2.5) and its components on infant NNS in Puerto Rico. NNS was assessed using a pacifier attached to a pressure transducer, allowing for real-time visualization of NNS amplitude, frequency, duration, cycles/burst, cycles/min and bursts/min. These data were linked to 9-month average prenatal concentrations of PM_2.5 and components, measured at three community monitoring sites. We used linear regression to examine the PM_2.5-NNS association in single pollutant models, controlling for infant sex, maternal age, gestational age, and season of birth in base and additionally for household smoke exposure, age at testing, and NNS duration in full models. Among 198 infants, the average NNS amplitude and burst duration was 17.1 cmH₂O and 6.1 s, respectively. Decreased NNS amplitude was consistently and significantly associated with 9-month average exposure to sulfur (-1.026 ± 0.507), zinc (-1.091 ± 0.503), copper (-1.096 ± 0.535) vanadium (-1.157 ± 0.537), and nickel (-1.530 ± 0.501). Decrements in NNS frequency were associated with sulfur exposure (0.036 ± 0.018), but not other examined PM components. Our findings provide new evidence that prenatal maternal exposure to specific PM components are associated with impaired neurodevelopment in Puerto Rican infants soon after birth.

Sources of indoor PM2.5 gross α and β activities measured in 340 homes

Particle radioactivity (PR) exposure has been linked to adverse health effects. PR refers to the presence of α- and β-emitting radioisotopes attached to fine particulate matter (PM_2.5). This study investigated sources contributing to indoor PM_2.5 gross α- and β-radioactivity levels. We measured activity from long-lived radon progeny radionuclides from archived PM_2.5 samples collected in 340 homes in Massachusetts during the period 2006-2010. We analyzed the data using linear mixed effects models and positive matrix factorization (PMF) analysis. Indoor PM_2.5 gross α-activity levels were correlated with sulfur (S), iron (Fe), bromine (Br), vanadium (V), sodium (Na), lead (Pb), potassium (K), calcium (Ca), silicon (Si), zinc (Zn), arsenic (As), titanium (Ti), radon (²²²Rn) and black carbon (BC) concentrations (p <0.05). Indoor PM_2.5 β-activity was correlated with S, As, antimony (Sb), Pb, Br and BC. We identified four indoor PM_2.5 sources: outdoor air pollution (62%), salt aerosol source (14%), fireworks and environmental tobacco smoke (7%) and indoor mixed dust (17%). Outdoor air pollution was the most significant contributor to indoor PM_2.5 α- and β-activity levels. The contributions of this source were during the summer months and when windows were open. Indoor mixed dust was also found to contribute to PM_2.5 α-activity. PM_2.5 α-activity was further associated with radon during winter months, showing radon's important role as an indoor source of ionizing radiation.

Trace element mass fractions in road dust as a function of distance from road

Road dust particles play an important role in atmospheric pollution and are associated with adverse human health effects. Traffic emissions are a major source of particles in road dust. However, there has been limited information about the relationship between distance from road and traffic-related elements levels in road dust. We investigated the relationships between proximity to the nearest major roadway and trace element mass fractions in PM₁₀ and PM_2.5 re-suspended from the road surface, based on measurements at three different distance ranges. We found that mass fractions of Ba, Cu, Zr, Zn, Cl, Co, Cr, Ca, Ti in PM₁₀ road dust as well as Zr, Cu, Cl, Zn, Cr, Ti, Mn, Ca, Ni, and Fe in PM_2.5 road dust, significantly decreased with distance from major road. Most of these elements are associated with road traffic emissions, including both tailpipe and non-tailpipe emissions. The decrease rates differed among elements due to differences in local traffic contributions. The decreases for elements which are mainly associated with non-tailpipe traffic emissions (e.g., Ba, Zr) were more dramatic. Our results indicate that traffic emissions, especially non-tailpipe emissions, contribute substantially to road dust, suggesting the need for control strategies for non-tailpipe emissions. Implications: We investigated the relationships between road proximity with trace element mass fractions in PM10 and PM2.5 re-suspended from the road surface. We observed significant decrease of traffic-related elements in PM10 and PM2.5 road dust with log distance from major road. We also found that the mass fractions for elements, which mainly come from traffic decrease more sharply compared to elements which come from both traffic and other sources. Our results indicate that traffic emissions contribute substantially to road dust, and imply that the distance to major road can be used as a proxy for ambient exposure.

Measurements of Gross α- and β-Activities of Archived PM2.5 and PM10 Teflon Filter Samples

The adverse effects of ambient particulate matter (PM) on human health have been well demonstrated, but the underlying properties responsible for its toxicity are still unclear. We hypothesized that particulate radioactivity, which is due to the attachment of radioactive nuclides on particle surfaces, may be responsible for part of PM toxicity. We measured the gross α- and β-activities for daily PM_2.5 and PM₁₀ filters collected at the Harvard Supersite in downtown Boston from 2005 to 2006 and calculated the radioactivities at the time of air sampling retrospectively based on a previously established formula. We examined the relationship between different radioactivities and compared our measurements to those measured at the Boston EPA RadNet Station. The results showed that the majority of PM₁₀ radioactivity is associated with that of PM_2.5 samples for both α-activity (98%) and β-activity (83%). A strong linear relationship was observed between the α- and β-activities for both PM_2.5 [slope = 0.47 (±0.03); p-value < 0.0001] and PM₁₀ [slope = 0.46 (±0.09); p-value < 0.0001] samples. Measurements at the Harvard Supersite and at EPA RadNet sites are highly correlated for both α-activities [slope = 0.17 (±0.02), p-value < 0.0001] and β-activities [slope = 0.30 (±0.05), p-value < 0.0001]. Additionally, we identified several significant predictors for PM_2.5 α-activities. This novel method we developed to measure α- and β-activities from archived filters will make it possible to assess the retrospective particle radioactivity exposure for future epidemiological studies.

Long-term impact of PM2.5 mass and sulfur reductions on ultrafine particle trends in Boston, MA from 1999 to 2018

Ultrafine particles (UFPs) pose a human health risk as they can penetrate deep into the respiratory system. The Harvard supersite in Boston, MA provides one of the longest time series of UFP concentrations. This study examined the hypothesis that long-term reductions in PM_2.5 mass and sulfur have influenced UFP trends by limiting the ability of UFPs to coagulate onto the accumulation mode via polydisperse coagulation with larger particles. The study used Generalized Additive Models (GAMs) to assess whether changes in PM_2.5 mass and sulfur concentrations resulted in smaller than expected (assuming no change in PM_2.5 mass or sulfur) decreases in daily UFP trends over the 20-year period from 1999 to 2018. The impact of PM_2.5 mass and sulfur changes were represented as UFP penalties. Bootstrapping was applied to calculate standard errors for the different trend and penalty estimates. Results showed that PM_2.5 mass and sulfur concentrations declined significantly over the study period. The analysis found an estimated 7.3% (95% CI: 3.5, 11.1%) UFP penalty due to long-term PM_2.5 mass trends, and a 9.9% (95% CI: 6.2, 13.7%) UFP penalty due to long-term sulfur trends. Findings from this study suggest that future UFP control efforts should account for the role of PM_2.5 mass and sulfur changes.

IMPLICATIONS

Using one of the longest available time series of UFP concentrations (1999 to 2018), this study examined the hypothesis that long-term trends of PM_2.5 mass and sulfur concentrations have an impact on UFP trends. We found that PM_2.5 mass and sulfur reductions had a small but significant impact, i.e., penalty, on UFP trends. Improved understanding of the impact of PM_2.5 mass and sulfur concentrations on UFP trends can inform future air quality control efforts.

Indoor Particle Alpha Radioactivity Origins in Occupied Homes

Exposure to radioactivity inside homes potentially poses severe health risks which can be exacerbated by the interaction between radioactive particles and fine indoor particles; in particular, the presence of α particles are a key risk factor. Hence, in this study, particle radioactivity was concurrently measured in the family rooms and basements of 26 homes to assess its concentrations and identify its sources, both indoors and outdoors, across two seasons. The levels of radon, air ions, and particle radioactivity, which included short- and long-lived α-activity (SLA and LLA, respectively), varied greatly but were substantially higher in the basements. Also, particle radioactivity-as well as PM_2.5 and sulfur concentrations-were lower during the heating season. SLA was associated with radon, which was consistently of indoor origin, whereas LLA was more strongly related to the sulfur measured in indoor PM_2.5, which is a proxy of outdoor infiltration. A regression model adjusted for sulfur and SLA also indicated a predominance of outdoor sources, likely due to the short residence time of indoor particles. Our results suggest that radiation in homes originates from both the decay of indoor radon and the infiltration of outdoor radioactivity.

Classroom indoor PM2.5 sources and exposures in inner-city schools

Children spend over 6 h a day in schools and have higher asthma morbidity from school environmental exposures. The present study aims to determine indoor and outdoor possible sources affecting indoor PM_2.5 in classrooms. Weeklong indoor PM_2.5 samples were collected from 32 inner-city schools from a Northeastern U.S. community during three seasons (fall, winter and spring) during the years 2009 to 2013. Concurrently, daily outdoor PM_2.5 samples were taken at a central monitoring site located at a median distance of 4974 m (range 1065-11,592 m) from the schools. Classroom indoor concentrations of PM_2.5 (an average of 5.2 μg/m³) were lower than outdoors (an average of 6.5 μg/m³), and these averages were in the lower range compared to the findings in other schools' studies. The USEPA PMF model was applied to the PM_2.5 components measured simultaneously from classroom indoor and outdoor to estimate the source apportionment. The major sources (contributions) identified across all seasons of indoor PM_2.5 were secondary pollution (41%) and motor vehicles (17%), followed by Calcium (Ca)-rich particles (12%), biomass burning (15%), soil dust (6%), and marine aerosols (4%). Likewise, the major sources of outdoor PM_2.5 across all seasons were secondary pollution (41%) and motor vehicles (26%), followed by biomass burning (17%), soil dust (7%), road dust (3%), and marine aerosols (1%). Secondary pollution was the greatest contributor to indoor and outdoor PM_2.5 over all three seasons, with the highest contribution during spring with 53% to indoor PM_2.5 and 45% to outdoor PM_2.5. Lower contributions of this source during fall and winter are most likely attributed to less infiltration indoors. In contrast, the indoor contribution of motor vehicles source was highest in the fall (29%) and winter (25%), which was presumably categorized by a local source. From the relationship between indoor-to-outdoor sulfur ratios and each source contribution, we also estimated the local and regional influence on indoor PM_2.5 concentration. Overall, the observed differences to indoor PM_2.5 are related to seasonality, and the distinct characteristics and behavior of each classroom/school.

Elemental and Mineralogical Composition of the Western Andean Snow (18°S-41°S)

The snowpack is an important source of water for many Andean communities. Because of its importance, elemental and mineralogical composition analysis of the Andean snow is a worthwhile effort. In this study, we conducted a chemical composition analysis (major and trace elements, mineralogy, and chemical enrichment) of surface snow sampled at 21 sites across a transect of about 2,500 km in the Chilean Andes (18–41°S). Our results enabled us to identify five depositional environments: (i) sites 1–3 (in the Atacama Desert, 18–26°S) with relatively high concentrations of metals, high abundance of quartz and low presence of arsenates, (ii) sites 4–8 (in northern Chile, 29–32°S) with relatively high abundance of quartz and low presence of metals and arsenates, (iii) sites 9–12 (in central Chile, 33–35°S) with anthropogenic enrichment of metals, relatively high values of quartz and low abundance of arsenates, (iv) sites 13–14 (also in central Chile, 35–37°S) with relatively high values of quartz and low presence of metals and arsenates, and v) sites 15–21 (in southern Chile, 37–41°S) with relatively high abundance of arsenates and low presence of metals and quartz. We found significant anthropogenic enrichment at sites close to Santiago (a major city of 6 million inhabitants) and in the Atacama Desert (that hosts several major copper mines).

Lead in Air in Bangladesh: Exposure in a Rural Community with Elevated Blood Lead Concentrations among Young Children

Previous evaluations of a birth cohort in the Munshiganj District of Bangladesh had found that over 85% of 397 children aged 2⁻3 years had blood lead concentrations above the United States Centers for Disease Control and Prevention's reference level of 5 μg/dL. Studies in urban areas of Bangladesh have found elevated levels of lead in the air due to industries and remaining contamination from the historic use of leaded gasoline. Sources of lead in rural areas of Bangladesh remain unknown. We conducted air sampling in both residential and industrial sites in Munshiganj to determine whether children are exposed to elevated lead concentrations in the air and study the association between the children's blood lead levels and sampled air lead concentrations. Residential and industrial air samples in Munshiganj were found to have elevated lead concentrations (mean 1.22 μg/m³) but were not found to be associated with the observed blood lead concentrations. Lead in air is an important environmental health exposure risk to the for children in Munshiganj, and further research may shed light on specific sources to inform exposure prevention and mitigation programs.

Modeling indoor particulate exposures in inner-city school classrooms

Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed effects linear models were used to determine the relationships between indoor PM2.5 (particulate matter) and black carbon (BC), and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor-outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM2.5 and BC in 199 samples from 136 classrooms (30 school buildings) were compared with those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: (1) there are important PM2.5 sources in classrooms; (2) the penetration of outdoor PM2.5 particles varies by school and (3) the site-specific outside PM2.5 levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (out of sample correlations: PM2.5: r2=0.68, BC; r2=0.61). Our results suggest that PM2.5 has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available.

Nicotine, aerosol particles, carbonyls and volatile organic compounds in tobacco- and menthol-flavored e-cigarettes

BACKGROUND

We aimed to assess the content of electronic cigarette (EC) emissions for five groups of potentially toxic compounds that are known to be present in tobacco smoke: nicotine, particles, carbonyls, volatile organic compounds (VOCs), and trace elements by flavor and puffing time.

METHODS

We used ECs containing a common nicotine strength (1.8%) and the most popular flavors, tobacco and menthol. An automatic multiple smoking machine was used to generate EC aerosols under controlled conditions. Using a dilution chamber, we targeted nicotine concentrations similar to that of exposure in a general indoor environment. The selected toxic compounds were extracted from EC aerosols into a solid or liquid phase and analyzed with chromatographic and spectroscopic methods.

RESULTS

We found that EC aerosols contained toxic compounds including nicotine, fine and nanoparticles, carbonyls, and some toxic VOCs such as benzene and toluene. Higher mass and number concentrations of aerosol particles were generated from tobacco-flavored ECs than from menthol-flavored ECs.

CONCLUSION

We found that diluted machine-generated EC aerosols contain some pollutants. These findings are limited by the small number of ECs tested and the conditions of testing. More comprehensive research on EC exposure extending to more brands and flavor compounds is warranted.

Intra-urban biomonitoring: Source apportionment using tree barks to identify air pollution sources

It is of great interest to evaluate if there is a relationship between possible sources and trace elements using biomonitoring techniques. In this study, tree bark samples of 171 trees were collected using a biomonitoring technique in the inner city of São Paulo. The trace elements (Al, Ba, Ca, Cl, Cu, Fe, K, Mg, Mn, Na, P, Rb, S, Sr and Zn) were determined by the energy dispersive X-ray fluorescence (EDXRF) spectrometry. The Principal Component Analysis (PCA) was applied to identify the plausible sources associated with tree bark measurements. The greatest source was vehicle-induced non-tailpipe emissions derived mainly from brakes and tires wear-out and road dust resuspension (characterized with Al, Ba, Cu, Fe, Mn and Zn), which was explained by 27.1% of the variance, followed by cement (14.8%), sea salt (11.6%) and biomass burning (10%), and fossil fuel combustion (9.8%). We also verified that the elements related to vehicular emission showed different concentrations at different sites of the same street, which might be helpful for a new street classification according to the emission source. The spatial distribution maps of element concentrations were obtained to evaluate the different levels of pollution in streets and avenues. Results indicated that biomonitoring techniques using tree bark can be applied to evaluate dispersion of air pollution and provide reliable data for the further epidemiological studies.

Composition and sources of fine and coarse particles collected during 2002-2010 in Boston, MA

Identifying the sources, composition, and temporal variability of fine (PM2.5) and coarse (PM2.5-10) particles is a crucial component in understanding particulate matter (PM) toxicity and establishing proper PM regulations. In this study, a Harvard Impactor was used to collect daily integrated fine and coarse particle samples every third day for 9 years at a single site in Boston, MA. In total, 1,960 filters were analyzed for elements, black carbon (BC), and total PM mass. Positive Matrix Factorization (PMF) was used to identify source types and quantify their contributions to ambient PM2.5 and PM2.5-10. BC and 17 elements were identified as the main constituents in our samples. Results showed that BC, S, and Pb were associated exclusively with the fine particle mode, while 84% of V and 79% of Ni were associated with this mode. Elements mostly found in the coarse mode, over 80%, included Ca, Mn (road dust), and Cl (sea salt). PMF identified six source types for PM2.5 and three source types for PM2.5-10. Source types for PM2.5 included regional pollution, motor vehicles, sea salt, crustal/road dust, oil combustion, and wood burning. Regional pollution contributed the most, accounting for 48% of total PM2.5 mass, followed by motor vehicles (21%) and wood burning (19%). Source types for PM2.5-10 included crustal/road dust (62%), motor vehicles (22%), and sea salt (16%). A linear decrease in PM concentrations with time was observed for both fine (-5.2%/yr) and coarse (-3.6%/yr) particles. The fine-mode trend was mostly related to oil combustion and regional pollution contributions. Average PM2.5 concentrations peaked in summer (10.4 µg/m3), while PM2.5-10 concentrations were lower and demonstrated little seasonal variability. The findings of this study show that PM2.5 is decreasing more sharply than PM2.5-10 over time. This suggests the increasing importance of PM2.5-10 and traffic-related sources for PM exposure and future policies.

IMPLICATIONS

Although many studies have examined fine and coarse particle composition and sources, few studies have used concurrent measurements of these two fractions. Our analysis suggests that fine and coarse particles exhibit distinct compositions and sources. With better knowledge of the compositional and source differences between these two PM fractions, better decisions can be made about PM regulations. Further, such information is valuable in enabling epidemiologists to understand the ensuing health implications of PM exposure.