Spatial variations of levoglucosan in four European study areas

Development of Spatio-Temporal Land Use Regression Models for Fine Particulate Matter and Wood-Burning Tracers in Temuco, Chile

Biomass burning is common in much of the world, and in some areas, residential wood-burning has increased. However, air pollution resulting from biomass burning is an important public health problem. A sampling campaign was carried out between May 2017 and July 2018 in over 64 sites in four sessions, to develop a spatio-temporal land use regression (LUR) model for fine particulate matter (PM) and wood-burning tracers levoglucosan and soluble potassium (Ksol) in a city heavily impacted by wood-burning. The mean (sd) was 46.5 (37.4) μg m-3 for PM2.5, 0.607 (0.538) μg m-3 for levoglucosan, and 0.635 (0.489) μg m-3 for Ksol. LUR models for PM2.5, levoglucosan, and Ksol had a satisfactory performance (LOSOCV R2), explaining 88.8%, 87.4%, and 87.3% of the total variance, respectively. All models included sociodemographic predictors consistent with the pattern of use of wood-burning in homes. The models were applied to predict concentrations surfaces and to estimate exposures for an epidemiological study.

Key factors for abating particulate matter in a highly industrialized area in N Spain: Fugitive emissions and secondary aerosol precursors

In highly industrialized areas, abating particulate matter (PM) is complex owing to the variety of emission sources with different chemical profiles that may mix in the atmosphere. Gijón-an industrial city in northern Spain-was selected as a case study to better understand the key emission sources and improve air quality in highly industrialized areas. Accordingly, the trends of various air quality indicators (PM10, PM2.5, SO2, NO2, and O3) during the past decade (2010-2019) were analyzed. Additionally, the inorganic and organic PM10 compositions were analyzed for source apportionment studies and to assess the impact of COVID-19 restrictions on PM10 levels. The results revealed that over the past decade, PM10 concentrations decreased, whereas PM2.5 concentrations dominated by secondary inorganic aerosols (SIA) remained relatively constant. Notably, during the COVID-19 lockdown, the PM10 concentration increased by 9.1%, primarily owing to an increase in regional SIA (>65%) due to specific meteorological conditions that favor the formation of secondary PM from gaseous precursors. Overall, eight key PM10 sources were identified: "industrial fugitive PM resuspension" (FPM, 28% of mean PM10 concentration), "aged sea spray" (SSp, 16%), "secondary nitrate" (SN, 15%), "local diffuse source" (LPM, 12%), "solid fuel combustion" (SFC, 7.8%), "biomass burning" (BB, 7.4%), "secondary sulphate" (SSu, 6.0%), and "sinter" (SIN, 4.5%). The PM10 concentration in Gijón is significantly influenced by the integrated steel industry (FPM, SFC, and SIN; 41% of PM10) and fugitive primary PM emissions were the main source (FPM and LPM; 40%). To reduce PM10 and PM2.5 concentrations, industrial fugitive emissions, which are currently poorly regulated, and SIA precursors must be abated. This study provides a methodological approach that combines trend analysis, chemical speciation, and source apportionment for assessing pollution abatement strategies in industrialized areas with a complex mix of emission sources.

Carbonaceous Aerosols in Contrasting Atmospheric Environments in Greek Cities: Evaluation of the EC-tracer Methods for Secondary Organic Carbon Estimation

This study examines the carbonaceous-aerosol characteristics at three contrasting urban environments in Greece (Ioannina, Athens, and Heraklion), on the basis of 12 h sampling during winter (January to February 2013), aiming to explore the inter-site differences in atmospheric composition and carbonaceous-aerosol characteristics and sources. The winter-average organic carbon (OC) and elemental carbon (EC) concentrations in Ioannina were found to be 28.50 and 4.33 µg m−3, respectively, much higher than those in Heraklion (3.86 µg m−3 for OC and 2.29 µg m−3 for EC) and Athens (7.63 µg m−3 for OC and 2.44 µg m−3 for EC). The winter OC/EC ratio in Ioannina (6.53) was found to be almost three times that in Heraklion (2.03), indicating a larger impact of wood combustion, especially during the night, whereas in Heraklion, emissions from biomass burning were found to be less intense. Estimations of primary and secondary organic carbon (POC and SOC) using the EC-tracer method, and specifically its minimum R-squared (MRS) variant, revealed large differences between the sites, with a prevalence of POC (67–80%) in Ioannina and Athens and with a larger SOC fraction (53%) in Heraklion. SOC estimates were also obtained using the 5% and 25% percentiles of the OC/EC data to determine the (OC/EC)pri, leading to results contrasting to the MRS approach in Ioannina (70–74% for SOC). Although the MRS method provides generally more robust results, it may significantly underestimate SOC levels in environments highly burdened by biomass burning, as the fast-oxidized semi-volatile OC associated with combustion sources is classified in POC. Further analysis in Athens revealed that the difference in SOC estimates between the 5% percentile and MRS methods coincided with the semi-volatile oxygenated organic aerosol as quantified by aerosol mass spectrometry. Finally, the OC/Kbb+ ratio was used as tracer for decomposition of the POC into fossil-fuel and biomass-burning components, indicating the prevalence of biomass-burning POC, especially in Ioannina (77%).

Spatial Patterns in Rush-Hour vs. Work-Week Diesel-Related Pollution across a Downtown Core

Despite advances in monitoring and modelling of intra-urban variation in multiple pollutants, few studies have attempted to separate spatial patterns by time of day, or incorporated organic tracers into spatial monitoring studies. Due to varying emissions sources from diesel and gasoline vehicular traffic, as well as within-day temporal variation in source mix and intensity (e.g., rush-hours vs. full-day measures), accurately assessing diesel-related air pollution within an urban core can be challenging. We allocated 24 sampling sites across downtown Pittsburgh, Pennsylvania (2.8 km²) to capture fine-scale variation in diesel-related pollutants, and to compare these patterns by sampling interval (i.e., “rush-hours” vs. “work-week” concentrations), and by season. Using geographic information system (GIS)-based methods, we allocated sampling sites to capture spatial variation in key traffic-related pollution sources (i.e., truck, bus, overall traffic densities). Programmable monitors were used to collect integrated work-week and rush-hour samples of fine particulate matter (PM_2.5), black carbon (BC), trace elements, and diesel-related organics (polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes), in summer and winter 2014. Land use regression (LUR) models were created for PM_2.5, BC, total elemental carbon (EC), total organic carbon (OC), elemental (Al, Ca, Fe), and organic constituents (total PAHs, total hopanes), and compared by sampling interval and season. We hypothesized higher pollution concentrations and greater spatial contrast in rush-hour, compared to full work-week samples, with variation by season and pollutant. Rush-hour sampling produced slightly higher total PM_2.5 and BC concentrations in both seasons, compared to work-week sampling, but no evident difference in spatial patterns. We also found substantial spatial variability in most trace elements and organic compounds, with comparable spatial patterns using both sampling paradigms. Overall, we found higher concentrations of traffic-related trace elements and organic compounds in rush-hour samples, and higher concentrations of coal-related elements (e.g., As, Se) in work-week samples. Mean bus density was the strongest LUR predictor in most models, in both seasons, under each sampling paradigm. Within each season and constituent, the bus-related terms explained similar proportions of variance in the rush-hour and work-week samples. Rush-hour and work-week LUR models explained similar proportions of spatial variation in pollutants, suggesting that the majority of emissions may be produced during rush-hour traffic across downtown. Results suggest that rush-hour emissions may predominantly shape overall spatial variance in diesel-related pollutants.

Source Characterization and Exposure Modeling of Gas-Phase Polycyclic Aromatic Hydrocarbon (PAH) Concentrations in Southern California

Airborne exposures to polycyclic aromatic hydrocarbons (PAHs) are associated with adverse health outcomes. Because personal air measurements of PAHs are labor intensive and costly, spatial PAH exposure models are useful for epidemiological studies. However, few studies provide adequate spatial coverage to reflect intra-urban variability of ambient PAHs. In this study, we collected 39-40 weekly gas-phase PAH samples in southern California twice in summer and twice in winter, 2009, in order to characterize PAH source contributions and develop spatial models that can estimate gas-phase PAH concentrations at a high resolution. A spatial mixed regression model was constructed, including such variables as roadway, traffic, land-use, vegetation index, commercial cooking facilities, meteorology, and population density. Cross validation of the model resulted in an R² of 0.66 for summer and 0.77 for winter. Results showed higher total PAH concentrations in winter. Pyrogenic sources, such as fossil fuels and diesel exhaust, were the most dominant contributors to total PAHs. PAH sources varied by season, with a higher fossil fuel and wood burning contribution in winter. Spatial autocorrelation accounted for a substantial amount of the variance in total PAH concentrations for both winter (56%) and summer (19%). In summer, other key variables explaining the variance included meteorological factors (9%), population density (15%), and roadway length (21%). In winter, the variance was also explained by traffic density (16%). In this study, source characterization confirmed the dominance of traffic and other fossil fuel sources to total measured gas-phase PAH concentrations while a spatial exposure model identified key predictors of PAH concentrations. Gas-phase PAH source characterization and exposure estimation is of high utility to epidemiologist and policy makers interested in understanding the health impacts of gas-phase PAHs and strategies to reduce emissions.

Methods for Assessing Long-Term Exposures to Outdoor Air Pollutants

Purpose of Review

Epidemiological studies of health effects of long-term exposure to outdoor air pollution rely on different exposure assessment methods. This review discusses widely used methods with a special focus on new developments.

Recent Findings

New data and study designs have been applied, including satellite measurements of fine particles and nitrogen dioxide (NO₂). The methods to apply satellite data for epidemiological studies are improving rapidly and have already contributed significantly to national-, continental- and global-scale models. Spatiotemporal models have been developed allowing more detailed temporal resolution compared to spatial models. The development of hybrid models combining dispersion models, satellite observations, land use and surface monitoring has improved models substantially. Mobile monitoring designs to develop models for long-term UFP exposure have been conducted.

Summary

Methods to assess long-term exposure to outdoor air pollution have improved significantly over the past decade. Application of satellite data and mobile monitoring designs is promising new methods.

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.

Toxicity of Urban PM10 and Relation with Tracers of Biomass Burning

The chemical composition of particles varies with space and time and depends on emission sources, atmospheric chemistry and weather conditions. Evidence suggesting that particles differ in toxicity depending on their chemical composition is growing. This in vitro study investigated the biological effects of PM₁₀ in relation to PM-associated chemicals. PM₁₀ was sampled in ambient air at an urban traffic site (Borgerhout) and a rural background location (Houtem) in Flanders (Belgium). To characterize the toxic potential of PM₁₀, airway epithelial cells (Beas-2B cells) were exposed to particles in vitro. Different endpoints were studied including cell damage and death (cell viability) and the induction of interleukin-8 (IL-8). The mutagenic capacity was assessed using the Ames II Mutagenicity Test. The endotoxin levels in the collected samples were analyzed and the oxidative potential (OP) of PM₁₀ particles was evaluated by electron paramagnetic resonance (EPR) spectroscopy. Chemical characteristics of PM₁₀ included tracers for biomass burning (levoglucosan, mannosan and galactosan), elemental and organic carbon (EC/OC) and polycyclic aromatic hydrocarbons (PAHs). Most samples displayed dose-dependent cytotoxicity and IL-8 induction. Spatial and temporal differences in PM₁₀ toxicity were seen. PM₁₀ collected at the urban site was characterized by increased pro-inflammatory and mutagenic activity as well as higher OP and elevated endotoxin levels compared to the background area. Reduced cell viability (−0.46 < r_s < −0.35, p < 0.01) and IL-8 induction (−0.62 < r_s < −0.67, p < 0.01) were associated with all markers for biomass burning, levoglucosan, mannosan and galactosan. Furthermore, direct and indirect mutagenicity were associated with tracers for biomass burning, OC, EC and PAHs. Multiple regression analyses showed levoglucosan to explain 16% and 28% of the variance in direct and indirect mutagenicity, respectively. Markers for biomass burning were associated with altered cellular responses and increased mutagenic activity. These findings may indicate a role of biomass burning in the observed adverse health effect of particulate matter.

Residential Coal Combustion as a Source of Levoglucosan in China

Levoglucosan (LG) has been widely identified as a specific marker for biomass burning (BB) sources and frequently utilized in estimating the BB contribution to atmospheric fine particles all over the world. However, this study provides direct evidence to show that coal combustion (CC) is also a source of LG, especially in the wintertime in Northern China, based on both source testing and ambient measurement. Our results show that low-temperature residential CC could emit LG with emission factors (EF) ranging from 0.3 to 15.9 mg kg^-1. Ratios of LG to its isomers, mannosan and galactosan, differ between CC and BB emissions, and the wintertime ratios in Beijing ambient PM_2.5 and source-specific tracers including carbon isotopic signatures all indicated a significant contribution from CC to ambient levoglucosan in winter in Beijing. The results suggest that LG cannot be used as a distinct source marker for biomass burning in special cases such as some cities in the northern China, where coal is still widely used in the residential and industrial sectors. Biomass burning sources could be overestimated, although such an over-estimation could vary spatially and temporally.

Effects of long-term exposure to particulate matter and metal components on mortality in the Rome longitudinal study

BACKGROUND

The effect of long-term exposure to metal components in particulate matter on mortality are still controversial.

OBJECTIVES

To study the association between long-term exposure to PM₁₀, PM_2.5, PM_2.5 absorbance, particulate matter components (copper, iron, zinc, sulfur, silicon, potassium, nickel, and vanadium) and non-accidental, cardiovascular (CVD), and ischemic heart disease (IHD) mortality.

METHODS

All 30+ year olds from the Rome Longitudinal Study were followed for vital status from October 2001 until December 2010. We used land use regression models to estimate annual average concentrations at residences and Cox models to estimate the associations between pollutants and cause-specific mortality, adjusting for individual and contextual characteristics. Hazard ratios (HRs) were expressed per increments equal to the 5^th-95^th percentile range of each pollutant distribution.

RESULTS

We analyzed 1,249,108 residents and found strong associations between all exposure indicators and mortality. We observed higher mortality risk with increasing exposure to PM_2.5 absorbance (HR=1.05; 95% CI: 1.03-1.06) and to tracers of non-tailpipe traffic emissions such as tire and brake wear (Cu, Fe, and Zn); for PM_2.5Zn, we found HR=1.06 (95% CI: 1.04-1.08) for non-accidental mortality, HR=1.07 (95% CI: 1.04-1.10) for CVD, and HR=1.11 (95% CI: 1.06-1.16) for IHD mortality. With increasing levels of nickel in PM₁₀, we found HR=1.07 (95% CI: 1.05-1.09) for non-accidental mortality, HR=1.08 (95% CI: 1.05-1.11) for CVD, and HR=1.13 (95% CI: 1.08-1.18) for IHD mortality. Results were robust when we adjusted for PM mass and for cardiovascular mortality when we adjusted for NO₂.

CONCLUSIONS

In addition to vehicular exhaust pollutants, PM related to non-tailpipe emissions and mixed oil burning/industry plays an important role in mortality.

Spatial and temporal variability of carbonaceous aerosols: Assessing the impact of biomass burning in the urban environment

Biomass burning (BB) is a significant source of atmospheric particles in many parts of the world. Whereas many studies have demonstrated the importance of BB emissions in central and northern Europe, especially in rural areas, its impact in urban air quality of southern European countries has been sparsely investigated. In this study, highly time resolved multi-wavelength absorption coefficients together with levoglucosan (BB tracer) mass concentrations were combined to apportion carbonaceous aerosol sources. The Aethalometer model takes advantage of the different spectral behavior of BB and fossil fuel (FF) combustion aerosols. The model was found to be more sensitive to the assumed value of the aerosol Ångström exponent (AAE) for FF (AAE_ff) than to the AAE for BB (AAE_bb). As result of various sensitivity tests the model was optimized with AAE_ff=1.1 and AAE_bb=2. The Aethalometer model and levoglucosan tracer estimates were in good agreement. The Aethalometer model was further applied to data from three sites in Granada urban area to evaluate the spatial variation of CM_ff and CM_bb (carbonaceous matter from FF or BB origin, respectively) concentrations within the city. The results showed that CM_bb was lower in the city centre while it has an unexpected profound impact on the CM levels measured in the suburbs (about 40%). Analysis of BB tracers with respect to wind speed suggested that BB was dominated by sources outside the city, to the west in a rural area. Distinguishing whether it corresponds to agricultural waste burning or with biomass burning for domestic heating was not possible. This study also shows that although traffic restrictions measures contribute to reduce carbonaceous concentrations, the extent of the reduction is very local. Other sources such as BB, which can contribute to CM as much as traffic emissions, should be targeted to reduce air pollution.

Systematic identification and prioritization of communities impacted by residential woodsmoke in British Columbia, Canada

Residential woodsmoke is an under-regulated source of fine particulate matter (PM_2.5), often surpassing mobile and industrial emissions in rural communities in North America and elsewhere. In the province of British Columbia (BC), Canada, many municipalities are hesitant to adopt stricter regulations for residential wood burning without empirical evidence that smoke is affecting local air quality. The objective of this study was to develop a retrospective algorithm that uses 1-h PM_2.5 concentrations and daily temperature data to identify smoky days in order to prioritise communities by smoke impacts. Levoglucosan measurements from one of the smokiest communities were used to establish the most informative values for three algorithmic parameters: the daily standard deviation of 1-h PM_2.5 measurements; the daily mean temperature; and the daytime-to-nighttime ratio of PM_2.5 concentrations. Alternate parameterizations were tested in 45 sensitivity analyses. Using the most informative parameter values on the most recent two years of data for each community, the number of smoky days ranged from 5 to 277. Heat maps visualizing seasonal and diurnal variation in PM_2.5 concentrations showed clear differences between the higher- and lower-ranked communities. Some communities were sensitive to one or more of the parameters, but the overall rankings were consistent across the 45 analyses. This information will allow stakeholder agencies to work with local governments on implementing appropriate intervention strategies for the most smoke-impacted communities.

Mutagenicity and Pollutant Emission Factors of Solid-Fuel Cookstoves: Comparison with Other Combustion Sources

BACKGROUND

Emissions from solid fuels used for cooking cause ~4 million premature deaths per year. Advanced solid-fuel cookstoves are a potential solution, but they should be assessed by appropriate performance indicators, including biological effects.

OBJECTIVE

We evaluated two categories of solid-fuel cookstoves for eight pollutant and four mutagenicity emission factors, correlated the mutagenicity emission factors, and compared them to those of other combustion emissions.

METHODS

We burned red oak in a 3-stone fire (TSF), a natural-draft stove (NDS), and a forced-draft stove (FDS), and we combusted propane as a liquified petroleum gas control fuel. We determined emission factors based on useful energy (megajoules delivered, MJd) for carbon monoxide, nitrogen oxides (NOx), black carbon, methane, total hydrocarbons, 32 polycyclic aromatic hydrocarbons, PM2.5, levoglucosan (a wood-smoke marker), and mutagenicity in Salmonella.

RESULTS

With the exception of NOx, the emission factors per MJd were highly correlated (r ≥ 0.97); the correlation for NOx with the other emission factors was 0.58-0.76. Excluding NOx, the NDS and FDS reduced the emission factors an average of 68 and 92%, respectively, relative to the TSF. Nevertheless, the mutagenicity emission factor based on fuel energy used (MJthermal) for the most efficient stove (FDS) was between those of a large diesel bus engine and a small diesel generator.

CONCLUSIONS

Both mutagenicity and pollutant emission factors may be informative for characterizing cookstove performance. However, mutagenicity emission factors may be especially useful for characterizing potential health effects and should be evaluated in relation to health outcomes in future research. An FDS operated as intended by the manufacturer is safer than a TSF, but without adequate ventilation, it will still result in poor indoor air quality.

CITATION

Mutlu E, Warren SH, Ebersviller SM, Kooter IM, Schmid JE, Dye JA, Linak WP, Gilmour MI, Jetter JJ, Higuchi M, DeMarini DM. 2016. Mutagenicity and pollutant emission factors of solid-fuel cookstoves: comparison with other combustion sources. Environ Health Perspect 124:974-982; http://dx.doi.org/10.1289/ehp.1509852.

Size-distribution of airborne polycyclic aromatic hydrocarbons and other organic source markers in the surroundings of a cement plant powered with alternative fuels

The distributions of polycyclic aromatic hydrocarbons (PAHs) and molecular tracer organic compounds for biomass combustion, traffic emissions, soil dust, and secondary aerosol processing have been studied in three fractions of ambient air particulate matter (PM10, 2.5, and 1) collected in the vicinity of a cement plant. PAH concentrations were used to estimate the carcinogenic risks in humans. Combustion related compounds, including PAHs, and those from secondary aerosol processing, predominated in the finest (PM<1) fraction, while saccharides related to organic soil dust predominated in the coarse fraction (2.5<PM<10). The molecular markers of biomass combustion were found in high concentrations, indicating the influence of biomass burning on PM. Most predominant PAHs were five and six rings species, related to a PAH profile characteristic of urban-industrial environments. The concentrations of benzo[a]pyrene varied between 0.2 and 1.0ng/m(3), which is close but lower than the annual limit value of 1ng/m(3) established by law. Exposure and inhalation carcinogenic risks from total PAHs were below the EPA threshold of acceptable risk (1·10(-6)).