Neighborhood-Scale Spatial Models of Diesel Exhaust Concentration Profile Using 1-Nitropyrene and Other Nitroarenes

Leveraging low-cost sensors to predict nitrogen dioxide for epidemiologic exposure assessment

BACKGROUND

Statistical models of air pollution enable intra-urban characterization of pollutant concentrations, benefiting exposure assessment for environmental epidemiology. The new generation of low-cost sensors facilitate the deployment of dense monitoring networks and can potentially be used to improve intra-urban models of air pollution.

OBJECTIVE

Develop and evaluate a spatiotemporal model for nitrogen dioxide (NO2) in the Puget Sound region of WA, USA for the Adult Changes in Thought Air Pollution (ACT-AP) study and assess the contribution of low-cost sensor data to the model's performance through cross-validation.

METHODS

We developed a spatiotemporal NO2 model for the study region incorporating data from 11 agency locations, 364 supplementary monitoring locations, and 117 low-cost sensor (LCS) locations for the 1996-2020 time period. Model features included long-term time trends and dimension-reduced land use regression. We evaluated the contribution of LCS network data by comparing models fit with and without sensor data using cross-validated (CV) summary performance statistics.

RESULTS

The best performing model had one time trend and geographic covariates summarized into three partial least squares components. The model, fit with LCS data, performed as well as other recent studies (agency cross-validation: CV- root mean square error (RMSE) = 2.5 ppb NO2; CV- coefficient of determination (R 2 ) = 0.85). Predictions of NO2 concentrations developed with LCS were higher at residential locations compared to a model without LCS, especially in recent years. While LCS did not provide a strong performance gain at agency sites (CV-RMSE = 2.8 ppb NO2; CV-R 2  = 0.82 without LCS), at residential locations, the improvement was substantial, with RMSE = 3.8 ppb NO2 andR 2  = 0.08 (without LCS), compared to CV-RMSE = 2.8 ppb NO2 and CV-R 2  = 0.51 (with LCS).

IMPACT

We developed a spatiotemporal model for nitrogen dioxide (NO2) pollution in Washington's Puget Sound region for epidemiologic exposure assessment for the Adult Changes in Thought Air Pollution study. We examined the impact of including low-cost sensor data in the NO2 model and found the additional spatial information the sensors provided predicted NO2 concentrations that were higher than without low-cost sensors, particularly in recent years. We did not observe a clear, substantial improvement in cross-validation performance over a similar model fit without low-cost sensor data; however, the prediction improvement with low-cost sensors at residential locations was substantial. The performance gains from low-cost sensors may have been attenuated due to spatial information provided by other supplementary monitoring data.

The East Bay Diesel Exposure Project: a biomonitoring study of parents and their children in heavily impacted communities

BACKGROUND

Diesel exhaust (DE) exposures pose concerns for serious health effects, including asthma and lung cancer, in California communities burdened by multiple stressors.

OBJECTIVE

To evaluate DE exposures in disproportionately impacted communities using biomonitoring and compare results for adults and children within and between families.

METHODS

We recruited 40 families in the San Francisco East Bay area. Two metabolites of 1-nitropyrene (1-NP), a marker for DE exposures, were measured in urine samples from parent-child pairs. For 25 families, we collected single-day spot urine samples during two sampling rounds separated by an average of four months. For the 15 other families, we collected daily spot urine samples over four consecutive days during the two sampling rounds. We also measured 1-NP in household dust and indoor air. Associations between urinary metabolite levels and participant demographics, season, and 1-NP levels in dust and air were evaluated.

RESULTS

At least one 1-NP metabolite was present in 96.6% of the urine samples. Detection frequencies for 1-NP in dust and indoor air were 97% and 74%, respectively. Results from random effect models indicated that levels of the 1-NP metabolite 6-hydroxy-1-nitropyrene (6-OHNP) were significantly higher in parents compared with their children (p-value = 0.005). Urinary 1-NP metabolite levels were generally higher during the fall and winter months. Within-subject variability was higher than between-subject variability (~60% of total variance versus ~40%, respectively), indicating high short-term temporal variability.

IMPACT

Biomonitoring, coupled with air monitoring, improves understanding of hyperlocal air pollution impacts. Results from these studies will inform the design of effective exposure mitigation strategies in disproportionately affected communities.

Evaluation of Orthotrichum lyellii moss as a biomonitor of diesel exhaust

Exhaust from diesel combustion engines is an important contributor to urban air pollution and poses significant risk to human health. Diesel exhaust contains a chemical class known as nitrated polycyclic aromatic hydrocarbons (nitro-PAHs) and is enriched in 1-nitropyrene (1-NP), which has the potential to serve as a marker of diesel exhaust. The isomeric nitro-PAHs 2-nitropyrene (2-NP) and 2-nitrofluoranthene (2-NFL) are secondary pollutants arising from photochemical oxidation of pyrene and fluoranthene, respectively. Like other important air toxics, there is not extensive monitoring of nitro-PAHs, leading to gaps in knowledge about relative exposures and urban hotspots. Epiphytic moss absorbs water, nutrients, and pollutants from the atmosphere and may hold potential as an effective biomonitor for nitro-PAHs. In this study we investigate the suitability of Orthotrichum lyellii as a biomonitor of diesel exhaust by analyzing samples of the moss for 1-NP, 2-NP, and 2-NFL in the Seattle, WA metropolitan area. Samples were collected from rural parks, urban parks, residential, and commercial/industrial areas (N = 22 locations) and exhibited increasing concentrations across these land types. Sampling and laboratory method performance varied by nitro-PAH, but was generally good. We observed moderate to moderately strong correlation between 1-NP and select geographic variables, including summer normalized difference vegetation index (NDVI) within 250 m (r = -0.88, R2 = 0.77), percent impervious surface within 50 m (r = 0.83, R2 = 0.70), percent high development land use within 500 m (r = 0.77, R2 = 0.60), and distance to nearest secondary and connecting road (r = -0.75, R2 = 0.56). The relationships between 2-NP and 2-NFL and the geographic variables were generally weaker. Our results suggest O. lyellii is a promising biomonitor of diesel exhaust, specifically for 1-NP. To our knowledge this pilot study is the first to evaluate using moss concentrations of nitro-PAHs as biomonitors of diesel exhaust.

1-Nitropyrene disrupts testicular steroidogenesis via oxidative stress-evoked PERK-eIF2α pathway

Our previous study showed 1-Nitropyrene (1-NP) exposure disrupted testicular testosterone synthesis in mouse, but the exact mechanism needs further investigation. The present research found 4-phenylbutyric acid (4-PBA), an endoplasmic reticulum (ER) stress inhibitor, recovered 1-NP-induced ER stress and testosterone synthases reduction in TM3 cells. GSK2606414, a protein kinase-like ER kinase (PERK) kinase inhibitor, attenuated 1-NP-induced PERK-eukaryotic translation initiation factor 2α (eIF2α) signaling activation and downregulation of steroidogenic proteins in TM3 cells. Both 4-PBA and GSK2606414 attenuated 1-NP-induced steroidogenesis disruption in TM3 cells. Further studies used N-Acetyl-L-cysteine (NAC) as a classical antioxidant to explore whether oxidative stress-activated ER stress mediated 1-NP-induced testosterone synthases reduction and steroidogenesis disruption in TM3 cells and mouse testes. The results showed NAC pretreatment mitigated oxidative stress, and subsequently attenuated ER stress, particularly PERK-eIF2α signaling activation, and downregulation of testosterone synthases in 1-NP-treated TM3 cells. More importantly, NAC extenuated 1-NP-induced testosterone synthesis in vitro and in vivo. The current work indicated that oxidative stress-caused ER stress, particularly PERK-eIF2α pathway activation, mediates 1-NP-downregulated steroidogenic proteins and steroidogenesis disruption in TM3 cells and mouse testes. Significantly, the current study provides a theoretical basis and demonstrates the experimental evidence for the potential application of antioxidant, such as NAC, in public health prevention, particularly in 1-NP-induced endocrine disorder.

Chitosan-supported metal nanocatalysts for the reduction of nitroaromatics

The second most abundant natural polymer in the earth's crust is chitosan (CS). The unique physical, chemical, structural, and mechanical features of this natural polymer have led to its increased application in a variety of fields such as medicine, catalysis, removal of pollutants, etc. To eliminate various pollutants, it is preferable to employ natural compounds as their use aids the removal of contaminants from the environment. Consequently, employing CS to eliminate contaminants is a viable choice. For this aim, CS can be applied as a template and support for metal nanoparticles (MNPs) and prevent the accumulation of MNPs as well as a reducing and stabilizing agent for the fabrication of MNPs. Among the pollutants present in nature, nitro compounds are an important and wide category of biological pollutants. 4-Nitrophenol (4-NP) is one of the nitro pollutants. There are different ways for the removal of 4-NP, but the best and most effective method for this purpose is the application of a metallic catalyst and a reducing agent. In this review, we report the recent developments regarding CS-supported metallic (nano)catalysts for the reduction of nitroaromatics such as nitrophenols, nitroaniline compounds, nitrobenzene, etc. in the presence of reducing agents. The metals investigated in this study include Ag, Au, Ni, Cu, Ru, Pt, Pd, etc.

Emissions and light absorption of PM2.5-bound nitrated aromatic compounds from on-road vehicle fleets

Vehicle emissions are an important source of nitrated aromatic compounds (NACs) in particulate size smaller 2.5 μm (PM_2.5), which adversely affect human health and biodiversity, especially in urban areas. In this study, filter-based PM_2.5 samples were collected during October 14-19, 2019, in a busy urban tunnel (approximately 35,000 vehicles per day) in south China to identify PM_2.5-bound NACs. Among them, 2,8-dinitrodibenzothiophene, 3-nitrodibenzofuran and 2-nitrodibenzothiophene were the most abundant nitrated polycyclic aromatic hydrocarbons (NPAHs), while 2-methyl-4-nitrophenol, 2,4-dinitrophenol, 3-methyl-4-nitrophenol and 4-nitrophenol were the most abundant nitrophenols (NPs). The observed mean fleet emission factors (EFs) of NPAHs and NPs were 2.2 ± 2.1 and 7.7 ± 4.1 μg km^-1, and were 2.9 ± 2.7 and 10.2 ± 5.4 μg km^-1 if excluding electric and liquefied petroleum gas vehicles, respectively. Regression analysis revealed that diesel vehicles (DVs) had NPAH-EFs (55.3 ± 5.3 μg km^-1) approximately 180 times higher than gasoline vehicles (GVs) (0.3 ± 0.2 μg km^-1), and NP-EFs (120.6 ± 25.8 μg km^-1) approximately 30 times higher than GVs (4.1 ± 0.2 μg km^-1), and thus 89% NPAH emissions and 56% NP emissions from the onroad fleets were contributed by DVs although DVs only accounted for 3.3% in the fleets. Methanol solution-based light absorption measurements demonstrated that the mean incremental light absorption for methanol-soluble brown carbon at 365 nm was 6.8 ± 2.2 Mm^-1, of which the 44 detected NACs only contributed about 1%. The mean EF of the 7 toxic NACs was approximately 3% that of the 16 priority PAHs; However, their benzo(a)pyrene toxic equivalence quotients (TEQ_BaP) could reach over 25% that of the PAHs. Moreover, 6-nitrochrysene mainly from DVs contributed 93% of the total TEQ_BaP of the NACs. This study demonstrated that enhancing DV emission control in urban areas could benefit the reduction of exposure to air toxins such as 6-nitrochrysene.

Mitochondrial ROS-mediated ribosome stalling and GCN2 activation are partially involved in 1-nitropyrene-induced steroidogenic inhibition in testes

In the past 50 years, testosterone (T) level in men has declined gradually. In this research, we discovered that acute exposure to 1-nitropyrene (1-NP), an environmental stressor from polluted atmosphere, reduced T contents by downregulating steroidogenic proteins in mouse testes and Leydig cells. Acute 1-NP exposure caused GCN2 activation and eIF2α phosphorylation, a marker of integrated stress, in mouse testes and Leydig cells. GCN2iB, a selective GCN2 kinase inhibitor, and siGCN2, the GCN2-targeted short interfering RNA, attenuated 1-NP-induced reduction of steroidogenic proteins in Leydig cells. Mechanistically, mitochondrial membrane potential was reduced and ATP5A, UQCRC2, SDHB and NDUFB8, four OXPHOS subunits, were reduced in 1-NP-exposed Leydig cells. Cellular mitochondrial respiration was inhibited and ATP production was reduced. Moreover, mitochondrial reactive oxygen species (ROS) were elevated in 1-NP-exposed Leydig cells. The interaction between GCN2 and uL10, a marker of ribosome stalling, was observed in 1-NP-exposed Leydig cells. MitoQ, a mitochondria-targeted antioxidant, attenuated1-NP-evoked ATP depletion and ribosome stalling in Leydig cells. Moreover, MitoQ suppressed 1-NP-caused GCN2 activation and eIF2α phosphorylation in Leydig cells. In addition, MitoQ alleviated 1-NP-induced steroidogenic inhibition in mouse testes. In conclusion, mitochondrial ROS-mediated ribosome stalling and GCN2 activation are partially involved in environmental stress-induced steroidogenic inhibition in testes.

Spatial predictors of heavy metal concentrations in epiphytic moss samples in Seattle, WA

The use of bio-indicators is an emerging, cost-effective alternative approach to identifying air pollution and assessing the need for additional air monitoring. This community science project explores the use of moss samples as bio-indicators of the distribution of metal air particulates in two residential neighborhoods of the industrial Duwamish Valley located in Seattle, WA (USA). We applied geographically weighted regression to data from 61 youth-collected samples to assess the location-specific area-level spatial predictors of the concentrations of 25 elements with focus on five heavy metals of concern due to health and environmental considerations. Spatial predictors included traffic volume, industrial land uses, major roadways, the airport, dirt roads, the Duwamish River, impervious surfaces, tree canopy cover, and sociodemographics. Traffic volume surrounding sample locations was the most consistent positive predictor of increasing heavy metal concentration. Greater distance from the heavy-industry corridor surrounding the Duwamish River predicted lower concentrations of all metals, with statistically significant associations for chromium and lead in some areas. As the distance from dirt roads increased, the concentration of arsenic and chromium decreased significantly. Percent tree canopy within 200 m of sample locations was a significant protective factor for cadmium concentrations. In addition, percent people of color was significantly positively associated with increasing lead, chromium and nickel concentrations. Our findings underscore the potential influence of heavy industry and mobile sources on heavy metal concentrations, the buffering potential of trees in local environments, and persistent opportunity to improve environmental justice.

A Spatiotemporal Prediction Model for Black Carbon in the Denver Metropolitan Area, 2009-2020

Studies on health effects of air pollution from local sources require exposure assessments that capture spatial and temporal trends. To facilitate intraurban studies in Denver, Colorado, we developed a spatiotemporal prediction model for black carbon (BC). To inform our model, we collected more than 700 weekly BC samples using personal air samplers from 2018 to 2020. The model incorporated spatial and spatiotemporal predictors and smoothed time trends to generate point-level weekly predictions of BC concentrations for the years 2009-2020. Our results indicate that our model reliably predicted weekly BC concentrations across the region during the year in which we collected data. We achieved a 10-fold cross-validation R² of 0.83 and a root-mean-square error of 0.15 μg/m³ for weekly BC concentrations predicted at our sampling locations. Predicted concentrations displayed expected temporal trends, with the highest concentrations predicted during winter months. Thus, our prediction model improves on typical land use regression models that generally only capture spatial gradients. However, our model is limited by a lack of long-term BC monitoring data for full validation of historical predictions. BC predictions from the weekly spatiotemporal model will be used in traffic-related air pollution exposure-disease associations more precisely than previous models for the region have allowed.

One-year measurements of secondary organic aerosol (SOA) markers in the Paris region (France): Concentrations, gas/particle partitioning and SOA source apportionment

Twenty-five biogenic and anthropogenic secondary organic aerosol (SOA) markers have been measured over a one-year period in both gaseous and PM₁₀ phases in the Paris region (France). Seasonal and chemical patterns were similar to those previously observed in Europe, but significantly different from the ones observed in America and Asia due to dissimilarities in source precursor emissions. Nitroaromatic compounds showed higher concentrations in winter due to larger emissions of their precursors originating from biomass combustion used for residential heating purposes. Among the biogenic markers, only isoprene SOA marker concentrations increased in summer while pinene SOA markers did not display any clear seasonal trend. The measured SOA markers, usually considered as semi-volatiles, were mainly associated to the particulate phase, except for the nitrophenols and nitroguaiacols, and their gas/particle partitioning (GPP) showed a low temperature and OM concentrations dependency. An evaluation of their GPP with thermodynamic model predictions suggested that apart from equilibrium partitioning between organic phase and air, the GPP of the markers is affected by processes suppressing volatility from a mixed organic and inorganic phase, such as enhanced dissolution in aerosol aqueous phase and non-equilibrium conditions. SOA marker concentrations were used to apportion secondary organic carbon (SOC) sources applying both, an improved version of the SOA-tracer method and positive matrix factorization (PMF) Total SOC estimations agreed very well between both models, except in summer and during a highly processed Springtime PM pollution event in which systematic underestimation by the SOA tracer method was evidenced. As a first approach, the SOA-tracer method could provide a reliable estimation of the average SOC concentrations, but it is limited due to the lack of markers for aged SOA together with missing SOA/SOC conversion fractions for several sources.

Modeling the Formation, Degradation, and Spatiotemporal Distribution of 2-Nitrofluoranthene and 2-Nitropyrene in the Global Atmosphere

Polycyclic aromatic hydrocarbons (PAHs) are common atmospheric pollutants and known to cause adverse health effects. Nitrated PAHs (NPAHs) are formed in combustion activities and by nitration of PAHs in the atmosphere and may be equally or more toxic, but their spatial and temporal distribution in the atmosphere is not well characterized. Using the global EMAC model with atmospheric chemistry and surface compartments coupled, we investigate the formation, abundance, and fate of two secondarily formed NPAHs, 2-nitrofluoranthene (2-NFLT) and 2-nitropyrene (2-NPYR). The default reactivity scenario, the model with the simplest interpretation of parameters from the literature, tends to overestimate both absolute concentrations and NPAH/PAH ratios at observational sites. Sensitivity scenarios indicate that NO₂-dependent NPAH formation leads to better agreement between measured and predicted NPAH concentrations and that photodegradation is the most important loss process of 2-NFLT and 2-NPYR. The highest concentrations of 2-NFLT and 2-NPYR are found in regions with strong PAH emissions, but because of continued secondary formation from the PAH precursors, these two NPAHs are predicted to be spread across the globe.

Toward Environmental Justice in Civic Science: Youth Performance and Experience Measuring Air Pollution Using Moss as a Bio-Indicator in Industrial-Adjacent Neighborhoods

This article reports on an interdisciplinary evaluation of the pilot phase of a community-driven civic science project. The project investigates the distribution of heavy metals in air pollution using moss growing on street trees as a bio-indicator in two industrial-adjacent neighborhoods in Seattle, Washington (USA). One goal of the ongoing project is to meaningfully engage local urban youths (eighth to twelfth grade) in the scientific process as civic scientists, and teach them about environmental health, environmental justice, and urban forestry concepts in a place-based, urban-oriented environmental research project. We describe the collaborative context in which our project developed, evaluate the quality of youth-collected data through analysis of replicate samples, and assess participants’ learning, career interests, and overall appraisal of the pilot. Our results indicate that youth scientists collected usable samples (with acceptable precision among repeated samples), learned project content (with statistically significant increases in scores of test-style survey questions; p = 0.002), and appraised their engagement favorably (with 69% of participants reporting they liked the project). We observed few changes in career interests, however. We discuss our intention to use these preliminary insights to further our community-driven education, research, and action model to address environmental injustices.

Long-term 1-nitropyrene exposure induces endoplasmic reticulum stress and inhibits steroidogenesis in mice testes

1-Nitropyrene (1-NP) is a representative nitro-polycyclic aromatic hydrocarbon from diesel exhaust. Recently, we found that maternal 1-NP exposure caused fetal growth retardation and disturbed cognitive development in adolescent female offspring. To investigate long-term 1-NP exposure on spermatogenesis and steroidogenesis, male mice were exposed to 1-NP (1.0 mg/kg/day) by gavage for 70 days. There was no significant difference on relative testicular weight, number of testicular apoptotic cells and epididymal sperm count between 1-NP-exposed mice and controls. Although long-term 1-NP exposure did not influence number of Leydig cells, steroidogenic genes and enzymes, including STAR, P450scc, P45017α and 17β-HD, were downregulated in 1-NP-expoed mouse testes. Correspondingly, serum and testicular testosterone (T) levels were reduced in 1-NP-exposed mice. Additional experiment showed that testicular GRP78 mRNA and protein were upregulated by 1-NP. Testicular phospho-IRE1α and sliced xbp-1 mRNA, a downstream molecule of IRE1α, were elevated in 1-NP-exposed mice. Testicular phospho-PERK and phospho-eIF2α, a downstream molecule of PERK pathway, were increased in 1-NP-exposed mice. Testicular NOX4, a subunit of NAPDH oxidase, and HO-1, MDA, two oxidative stress markers, were increased in 1-NP-exposed mice. Testicular GSH and GSH/GSSG were decreased in 1-NP-exposed mice. These results suggest that long-term 1-NP exposure induces reactive oxygen species-evoked ER stress and disrupts steroidogenesis in mouse testes.

Speciation of organic fractions does matter for aerosol source apportionment. Part 3: Combining off-line and on-line measurements

The present study proposes an advanced methodology to refine the source apportionment of organic aerosol (OA). This methodology is based on the combination of offline and online datasets in a single Positive Matrix Factorization (PMF) analysis using the multilinear engine (ME-2) algorithm and a customized time synchronization procedure. It has been applied to data from measurements conducted in the Paris region (France) during a PM pollution event in March 2015. Measurements included OA ACSM (Aerosol Chemical Speciation Monitor) mass spectra and specific primary and secondary organic molecular markers from PM₁₀ filters on their original time resolution (30 min for ACSM and 4 h for PM₁₀ filters). Comparison with the conventional PMF analysis of the ACSM OA dataset (PMF-ACSM) showed very good agreement for the discrimination between primary and secondary OA fractions with about 75% of the OA mass of secondary origin. Furthermore, the use of the combined datasets allowed the deconvolution of 3 primary OA (POA) factors and 7 secondary OA (SOA) factors. A clear identification of the source/origin of 54% of the total SOA mass could be achieved thanks to specific molecular markers. Specifically, 28% of that fraction was linked to combustion sources (biomass burning and traffic emissions). A clear identification of primary traffic OA was also obtained using the PMF-combined analysis while PMF-ACSM only gave a proxy for this OA source in the form of total hydrocarbon-like OA (HOA) mass concentrations. In addition, the primary biomass burning-related OA source was explained by two OA factors, BBOA and OPOA-like BBOA. This new approach has showed undeniable advantages over the conventional approaches by providing valuable insights into the processes involved in SOA formation and their sources. However, the origins of highly oxidized SOA could not be fully identified due to the lack of specific molecular markers for such aged SOA.

Evaluation of 1-Nitropyrene as a Surrogate Measure for Diesel Exhaust

We investigated the viability of particle bound 1-nitropyrene (1-NP) air concentration measurements as a surrogate of diesel exhaust (DE) exposure, as compared with industry-standard elemental carbon (EC) and total carbon (TC) measurements. Personal exposures are reported for 18 employees at a large underground metal mine during four different monitoring campaigns. Full-shift personal air exposure sampling was conducted using a Mine Safety and Health Administration (MSHA) compliant diesel particulate matter (DPM) impactor cassette downstream of a GS-1 cyclone pre-selector. Each DPM filter element was analyzed for EC and organic carbon (OC) using NIOSH Method 5040. After EC and OC analysis, the remaining portion of each DPM filter was analyzed for 1-NP using liquid chromatography tandem mass spectrometry (LC/MS/MS). We observed high correlations between the quantiles of 1-NP and EC exposures across 10 different work shift task groups (r = 0.87 to 0.96), and a linear relationship with a slope between 6.0 to 6.9 pg 1-NP per µg EC. However, correlation between 1-NP and EC was weak (r =0.34) for the 91 individual sample pairs due to low EC concentrations and possible heterogeneity of DE composition. While both 1-NP and EC differentiated between high and low exposure groups categorized by job location, measurements of 1-NP, but not EC further differentiated between specific job activities. Repeated measurements on individual subjects verified the relationship between 1-NP and EC and demonstrated substantial within-subject variability in exposure. The detection limit of TC air concentration ranged between 18 and 28 µg m-3 and was limited by OC contamination of the quartz filters in the MSHA compliant DPM samplers.

Separating spatial patterns in pollution attributable to woodsmoke and other sources, during daytime and nighttime hours, in Christchurch, New Zealand

During winter nights, woodsmoke may be a predominant source of air pollution, even in cities with many sources. Since two major earthquakes resulted in major structural damage in 2010 and 2011, reliance on woodburning for home heating has increased substantially in Christchurch, New Zealand (NZ), along with intensive construction/demolition activities. Further, because NZ is a relatively isolated western country, it offers the unique opportunity to disentangle multiple source impacts in the absence of long-range transport pollution. Finally, although many spatial saturation studies have been published, and levoglucosan is an established tracer for woodburning emissions, few studies have monitored multiple sites simultaneously for this or other organic constituents, with the ability to distinguish spatial patterns for daytime vs. nighttime hours, in complex urban settings. We captured seven-day integrated samples of PM_2.5, and elemental and organic tracers of woodsmoke and diesel emissions, during "daytime" (7 a.m. - 5:30 p.m.) and "nighttime" (7 p.m. - 5:30 a.m.) hours, at nine sites across commercial and residential areas, over three weeks in early winter (May 2014). At a subset of six sites, we also sampled during hypothesized "peak" woodburning hours (7 p.m. - 12 a.m.), to differentiate emissions during "active" residential woodburning, vs. overnight smouldering. Concentrations of PM_2.5 were, on average, were twice as high during nighttime than daytime [µ = 18.4 (SD = 6.13) vs. 9.21 (SD = 6.13) µg/m³], with much greater differences in woodsmoke tracers (i.e., levoglucosan [µ = 1.83 (SD = 0.82) vs. 0.34 (SD = 0.17) µg/m³], potassium) and indicators of treated- or painted-wood burning (e.g., arsenic, lead). Only nitrogen dioxide, calcium, iron, and manganese (tracers of vehicular emissions) were higher during daytime. Levoglucosan and most PAHs were higher during "active" woodburning, vs. overnight smouldering. Our time-stratified spatial saturation detected strong spatial variability throughout the study area, which distinctly differed during daytime vs. night time hours, and quantified the substantial contribution of woodsmoke to overnight spatial variation in PM_2.5 across Christchurch. Daytime vs. nighttime differences were greater than those observed across sites. Traffic, especially diesel, contributed substantially to daytime NO₂ and spatial gradients in non-woodsmoke constituents.

A hybrid kriging/land-use regression model to assess PM2.5 spatial-temporal variability

Proximate pollutant data can provide information for land-use predictors in LUR models, when coupled with spatial interpolation of ambient pollutant measurements, may provide better pollutant predictions. This study applies a hybrid kriging/LUR model to assess the spatial-temporal variability of PM_2.5 for Taiwan. Using PM_2.5 concentrations at 71 EPA monitoring stations from 2006 to 2011, pollutant gradient surfaces were spatially interpolated using a leave-one-out ordinary kriging method based on "n-1" observations. The predicted concentration level of the targeted site was then extracted from the generated kriging map and adopted as a variable in LUR modelling. Annual and monthly resolutions of LUR models were developed to assess the effects by incorporating kriging-based estimates into pollutant predictions. The R² obtained from conventional LUR procedures was 0.66 and 0.70 for annual and monthly models, respectively, whereas models using the hybrid approach showed better explanatory power (R² of annual model: 0.85; R² of monthly model: 0.88). Moreover, kriging-based PM_2.5 estimates were the most important factor in the resultant models according to the dominant partial R² of 0.82 and 0.7 in monthly and yearly models. Cross-validation and external data verification showed similar results, demonstrating robustness of the proposed approach. Using governmental pollutant observations is usually publicly available for most areas, this method provides an efficient mean to better assess PM_2.5 spatial-temporal variations and predicts levels for nonmonitored areas.

Personal Exposure to PM2.5 Black Carbon and Aerosol Oxidative Potential using an Automated Microenvironmental Aerosol Sampler (AMAS)

Traditional methods for measuring personal exposure to fine particulate matter (PM2.5) are cumbersome and lack spatiotemporal resolution; methods that are time-resolved are limited to a single species/component of PM. To address these limitations, we developed an automated microenvironmental aerosol sampler (AMAS), capable of resolving personal exposure by microenvironment. The AMAS is a wearable device that uses a GPS sensor algorithm in conjunction with a custom valve manifold to sample PM2.5 onto distinct filter channels to evaluate home, school, and other (e.g., outdoors, in transit, etc.) exposures. Pilot testing was conducted in Fresno, CA where 25 high-school participants ( n = 37 sampling events) wore an AMAS for 48-h periods in November 2016. Data from 20 (54%) of the 48-h samples collected by participants were deemed valid and the filters were analyzed for PM2.5 black carbon (BC) using light transmissometry and aerosol oxidative potential (OP) using the dithiothreitol (DTT) assay. The amount of inhaled PM2.5 was calculated for each microenvironment to evaluate the health risks associated with exposure. On average, the estimated amount of inhaled PM2.5 BC (μg day-1) and OP [(μM min-1) day-1] was greatest at home, owing to the proportion of time spent within that microenvironment. Validation of the AMAS demonstrated good relative precision (8.7% among collocated instruments) and a mean absolute error of 22% for BC and 33% for OP when compared to a traditional personal sampling instrument. This work demonstrates the feasibility of new technology designed to quantify personal exposure to PM2.5 species within distinct microenvironments.

Speciation of organic fractions does matter for aerosol source apportionment. Part 2: Intensive short-term campaign in the Paris area (France)

The present study aimed at performing PM₁₀ source apportionment, using positive matrix factorization (PMF), based on filter samples collected every 4h at a sub-urban station in the Paris region (France) during a PM pollution event in March 2015 (PM₁₀>50μgm^-3 for several consecutive days). The PMF model allowed to deconvolve 11 source factors. The use of specific primary and secondary organic molecular markers favoured the determination of common sources such as biomass burning and primary traffic emissions, as well as 2 specific biogenic SOA (marine+isoprene) and 3 anthropogenic SOA (nitro-PAHs+oxy-PAHs+phenolic compounds oxidation) factors. This study is probably the first one to report the use of methylnitrocatechol isomers as well as 1-nitropyrene to apportion secondary OA linked to biomass burning emissions and primary traffic emissions, respectively. Secondary organic carbon (SOC) fractions were found to account for 47% of the total OC. The use of organic molecular markers allowed the identification of 41% of the total SOC composed of anthropogenic SOA (namely, oxy-PAHs, nitro-PAHs and phenolic compounds oxidation, representing 15%, 9%, 11% of the total OC, respectively) and biogenic SOA (marine+isoprene) (6% in total). Results obtained also showed that 35% of the total SOC originated from anthropogenic sources and especially PAH SOA (oxy-PAHs+nitro-PAHs), accounting for 24% of the total SOC, highlighting its significant contribution in urban influenced environments. Anthropogenic SOA related to nitro-PAHs and phenolic compounds exhibited a clear diurnal pattern with high concentrations during the night indicating the prominent role of night-time chemistry but with different chemical processes involved.

Hemoglobin Adducts and Urinary Metabolites of Arylamines and Nitroarenes

Arylamines and nitroarenes are intermediates in the production of pharmaceuticals, dyes, pesticides, and plastics and are important environmental and occupational pollutants. N-Hydroxyarylamines are the toxic common intermediates of arylamines and nitroarenes. N-Hydroxyarylamines and their derivatives can form adducts with hemoglobin (Hb-adducts), albumin, DNA, and tissue proteins in a dose-dependent manner. Most of the arylamine Hb-adducts are labile and undergo hydrolysis in vitro, by mild acid or base, to form the arylamines. According to current knowledge of arylamine adduct-formation, the hydrolyzable fraction is derived from the reaction products of the arylnitroso derivatives that yield arylsulfinamide adducts with cysteine. Hb-adducts are markers for the bioavailability of N-hydroxyarylamines. Hb-adducts of arylamines and nitroarenes have been used for many biomonitoring studies for over 30 years. Hb-adducts reflect the exposure history of the last four months. Biomonitoring of urinary metabolites is a less invasive process than biomonitoring blood protein adducts, and urinary metabolites have served as short-lived biomarkers of exposure to these hazardous chemicals. However, in case of intermittent exposure, urinary metabolites may not be detected, and subjects may be misclassified as nonexposed. Arylamines and nitroarenes and/or their metabolites have been measured in urine, especially to monitor the exposure of workers. This review summarizes the results of human biomonitoring studies involving urinary metabolites and Hb-adducts of arylamines and nitroarenes. In addition, studies about the relationship between Hb-adducts and diseases are summarized.

Development of a QuEChERS-Based Method for Determination of Carcinogenic 2-Nitrofluorene and 1-Nitropyrene in Rice Grains and Vegetables: A Comparative Study with Benzo[a]pyrene

Nitrated polycyclic aromatic hydrocarbons (nitro-PAHs) are ubiquitous environmental pollutants attracting increasing attention because of their potent mutagenicity to humans. Previous studies of nitro-PAHs focused on investigating their formation mechanisms and detecting them in atmospheric environment; however, few studies have reported their occurrence in food samples, and regulations on nitro-PAHs are still lacking. We report in this study the development and application of a quick, easy, cheap, effective, rugged, and safe (QuEChERS) method for determination of nitro-PAHs in rice and vegetable samples. Analysis of the collected samples by the validated method revealed 1-nitropyrene and 2-nitrofluorene were widespread food contaminants. A comparative study with benzo[a]pyrene, the commonly used marker for PAH exposure, showed that carcinogenic nitro-PAHs existed in rice and vegetables at similar concentrations. Dietary exposure risk, which was estimated based on the surveillance data, suggested 3.28-5.03 ng/kg/day of nitro-PAHs exposure for Hong Kong citizens from rice grains and vegetables.

Ambient Air Quality Measurements from a Continuously Moving Mobile Platform: Estimation of Area-Wide, Fuel-Based, Mobile Source Emission Factors Using Absolute Principal Component Scores

We have applied the absolute principal component scores (APCS) receptor model to on-road, background-adjusted measurements of NOx, CO, CO₂, black carbon (BC), and particle number (PN) obtained from a continuously moving platform deployed over nine afternoon sampling periods in Seattle, WA. Two Varimax-rotated principal component features described 75% of the overall variance of the observations. A heavy-duty vehicle feature was correlated with black carbon and particle number, whereas a light-duty feature was correlated with CO and CO₂. NO_x had moderate correlation with both features. The bootstrapped APCS model predictions were used to estimate area-wide, average fuel-based emission factors and their respective 95% confidence limits. The average emission factors for NOx, CO, BC and PN (14.8, 18.9, 0.40 g/kg, and 4.3×10¹⁵ particles/kg for heavy duty vehicles, and 3.2, 22.4, 0.016 g/kg, and 0.19×10¹⁵ particles/kg for light-duty vehicles, respectively) are consistent with previous estimates based on remote sensing, vehicle chase studies, and recent dynamometer tests. Information on the spatial distribution of the concentrations contributed by these two vehicle categories relative to background during the sampling period was also obtained.

Spatial variation in diesel-related elemental and organic PM2.5 components during workweek hours across a downtown core

Capturing intra-urban variation in diesel-related pollution exposures remains a challenge, given its complex chemical mix, and relatively few well-characterized ambient-air tracers for the multiple diesel sources in densely-populated urban areas. To capture fine-scale spatial resolution (50×50m grid cells) in diesel-related pollution, we used geographic information systems (GIS) to systematically allocate 36 sampling sites across downtown Pittsburgh, PA, USA (2.8km²), cross-stratifying to disentangle source impacts (i.e., truck density, bus route frequency, total traffic density). For buses, outbound and inbound trips per week were summed by route and a kernel density was calculated across sites. Programmable monitors collected fine particulate matter (PM_2.5) samples specific to workweek hours (Monday-Friday, 7 am-7 pm), summer and winter 2013. Integrated filters were analyzed for black carbon (BC), elemental carbon (EC), organic carbon (OC), elemental constituents, and diesel-related organic compounds [i.e., polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes]. To our knowledge, no studies have collected this suite of pollutants with such high sampling density, with the ability to capture spatial patterns during specific hours of interest. We hypothesized that we would find substantial spatial variation for each pollutant and significant associations with key sources (e.g. diesel and gasoline vehicles), with higher concentrations near the center of this small downtown core. Using a forward stepwise approach, we developed seasonal land use regression (LUR) models for PM_2.5, BC, total EC, OC, PAHs, hopanes, steranes, aluminum (Al), calcium (Ca), and iron (Fe). Within this small domain, greater concentration differences were observed in most pollutants across sites, on average, than between seasons. Higher PM_2.5 and BC concentrations were found in the downtown core compared to the boundaries. PAHs, hopanes, and steranes displayed different spatial patterning across the study area by constituent. Most LUR models suggested a strong influence of bus-related emissions on pollution gradients. Buses were more dominant predictors compared to truck and vehicular traffic for several pollutants. Overall, we found substantial variation in diesel-related concentrations in a very small downtown area, which varied across elemental and organic components.

Assessment of regional air quality by a concentration-dependent Pollution Permeation Index

Although air quality monitoring networks have been greatly improved, interpreting their expanding data in both simple and efficient ways remains challenging. Therefore, needed are new analytical methods. We developed such a method based on the comparison of pollutant concentrations between target and circum areas (circum comparison for short), and tested its applications by assessing the air pollution in Jing-Jin-Ji, Yangtze River Delta, Pearl River Delta and Cheng-Yu, China during 2015. We found the circum comparison can instantly judge whether a city is a pollution permeation donor or a pollution permeation receptor by a Pollution Permeation Index (PPI). Furthermore, a PPI-related estimated concentration (original concentration plus halved average concentration difference) can be used to identify some overestimations and underestimations. Besides, it can help explain pollution process (e.g., Beijing’s PM_2.5 maybe largely promoted by non-local SO₂) though not aiming at it. Moreover, it is applicable to any region, easy-to-handle, and able to boost more new analytical methods. These advantages, despite its disadvantages in considering the whole process jointly influenced by complex physical and chemical factors, demonstrate that the PPI based circum comparison can be efficiently used in assessing air pollution by yielding instructive results, without the absolute need for complex operations.

On-road traffic emissions of polycyclic aromatic hydrocarbons and their oxy- and nitro- derivative compounds measured in road tunnel environments

Vehicular emissions are a key source of polycyclic aromatic compounds (PACs), including polycyclic aromatic hydrocarbons (PAHs) and their oxygenated (OPAH) and nitrated (NPAH) derivatives, in the urban environment. Road tunnels are a useful environment for the characterisation of on-road vehicular emissions, providing a realistic traffic fleet and a lack of direct sunlight, chemical reactivity and non-traffic sources. In the present investigation the concentrations of selected PAHs, OPAHs and NPAHs have been measured in the Parc des Princes Tunnel in Paris (PdPT, France), and at the Queensway Road Tunnel and an urban background site in Birmingham (QT, U.K). A higher proportion of semi-volatile (3-4 ring) PAH, OPAH and NPAH compounds are associated with the particulate phase compared with samples from the ambient environment. A large (~85%) decline in total PAH concentrations is observed between 1992 and 2012 measurements in QT. This is attributed primarily to the introduction of catalytic converters in the U.K as well as increasingly stringent EU vehicle emissions legislation. In contrast, NPAH concentrations measured in 2012 are similar to those measured in 1996. This observation, in addition to an increased proportion of (Phe+Flt+Pyr) in the observed PAH burden in the tunnel, is attributed to the increased number of diesel passenger vehicles in the U.K during this period. Except for OPAHs, comparable PAH and NPAH concentrations are observed in both investigated tunnels (QT and PdP). Significant differences are shown for specific substances between PAC chemical profiles in relation with the national traffic fleet differences (33% diesel passenger cars in U.K. vs 69% in France and up to 80% taking into account all vehicle categories). The dominating and sole contribution of 1-Nitropyrene observed in the PdPT NPAH profile strengthens the promising use of this compound as a diesel exhaust marker for PM source apportionment studies.