Perinatal exposure to traffic related air pollutants and the risk of infection in the first six months of life: a cohort study from a low-middle income country.

OBJECTIVE: There is limited study from low-and-middle income countries on the effect of perinatal exposure to air pollution and the risk of infection in infant. We assessed the association between perinatal exposure to traffic related air pollution and the risk of infection in infant during their first six months of life. METHODS: A prospective cohort study was performed in Jakarta, March 2016-September 2020 among 298 mother-infant pairs. PM2.5, soot, NOx, and NO2 concentrations were assessed using land use regression models (LUR) at individual level. Repeated interviewer-administered questionnaires were used to obtain data on infection at 1, 2, 4 and 6 months of age. The infections were categorized as upper respiratory tract (runny nose, cough, wheezing or shortness of breath), lower respiratory tract (pneumonia, bronchiolitis) or gastrointestinal tract infection. Logistic regression models adjusted for covariates were used to assess the association between perinatal exposure to air pollution and the risk of infection in the first six months of life. RESULTS: The average concentrations of PM2.5 and NO2 were much higher than the WHO recommended levels. Upper respiratory tract infections (URTI) were much more common in the first six months of life than diagnosed lower respiratory tract or gastro-intestinal infections (35.6%, 3.5% and 5.8% respectively). Perinatal exposure to PM2.5 and soot suggested increase cumulative risk of upper respiratory tract infection (URTI) in the first 6 months of life per IQR increase with adjusted OR of 1.50 (95% CI 0.91; 2.47) and 1.14 (95% CI 0.79; 1.64), respectively. Soot was significantly associated with the risk of URTI at 4-6 months age interval (aOR of 1.45, 95%CI 1.02; 2.09). All air pollutants were also positively associated with lower respiratory tract infection, but all CIs include unity because of relatively small samples. Adjusted odds ratios for gastrointestinal infections were close to unity. CONCLUSION: Our study adds to the evidence that perinatal exposure to fine particles is associated with respiratory tract infection in infants in a low-middle income country.

Harnessing AI to unmask Copenhagen's invisible air pollutants: A study on three ultrafine particle metrics.

Ultrafine particles (UFPs) are airborne particles with a diameter of less than 100 nm. They are emitted from various sources, such as traffic, combustion, and industrial processes, and can have adverse effects on human health. Long-term mean ambient average particle size (APS) in the UFP range varies over space within cities, with locations near UFP sources having typically smaller APS. Spatial models for lung deposited surface area (LDSA) within urban areas are limited and currently there is no model for APS in any European city. We collected particle number concentration (PNC), LDSA, and APS data over one-year monitoring campaign from May 2021 to May 2022 across 27 locations and estimated annual mean in Copenhagen, Denmark, and obtained additionally annual mean PNC data from 6 state-owned continuous monitors. We developed 94 predictor variables, and machine learning models (random forest and bagged tree) were developed for PNC, LDSA, and APS. The annual mean PNC, LDSA, and APS were, respectively, 5523 pt/cm3, 12.0 µm2/cm3, and 46.1 nm. The final R2 values by random forest (RF) model were 0.93 for PNC, 0.88 for LDSA, and 0.85 for APS. The 10-fold, repeated 10-times cross-validation R2 values were 0.65, 0.67, and 0.60 for PNC, LDSA, and APS, respectively. The root mean square error for final RF models were 296 pt/cm3, 0.48 µm2/cm3, and 1.60 nm for PNC, LDSA, and APS, respectively. Traffic-related variables, such as length of major roads within buffers 100-150 m and distance to streets with various speed limits were amongst the highly-ranked predictors for our models. Overall, our ML models achieved high R2 values and low errors, providing insights into UFP exposure in a European city where average PNC is quite low. These hyperlocal predictions can be used to study health effects of UFPs in the Danish Capital.

Urinary Amino-PAHs in relation to diesel engine emissions and urinary mutagenicity.

Diesel exhaust has long been of health concern due to established toxicity including carcinogenicity in humans. However, the precise components of diesel engine emissions that drive carcinogenesis are still unclear. Limited work has suggested that nitrated polycyclic aromatic hydrocarbons (NPAHs) such as 1-nitropyrene and 2-nitrofluorene may be more abundant in diesel exhaust. The present study aimed to examine whether urinary amino metabolites of these NPAHs were associated with high levels of diesel engine emissions and urinary mutagenicity in a group of highly exposed workers including both smokers and nonsmokers. Spot urine samples were collected immediately following a standard work shift from each of the 54 diesel engine testers and 55 non-tester controls for the analysis of five amino metabolites of NPAHs, and cotinine (a biomarker of tobacco smoke exposure) using liquid chromatography-mass spectrometry. An overnight urine sample was collected in a subgroup of non-smoking participants for mutagenicity analysis using strain YG1041 in the Salmonella (Ames) mutagenicity assay. Personal exposure to fine particles (PM2.5) and more-diesel-specific constituents (elemental carbon and soot) was assessed for the engine testers by measuring breathing-zone concentrations repeatedly over several full work shifts. Results showed that it was 12.8 times more likely to detect 1-aminopyrene and 2.9 times more likely to detect 2-aminofluorene in the engine testers than in unexposed controls. Urinary concentrations of 1-aminopyrene were significantly higher in engine testers (p < 0.001), and strongly correlated with soot and elemental carbon exposure as well as mutagenicity tested in strain YG1041 with metabolic activation (p < 0.001). Smoking did not affect 1-aminopyrene concentrations and 1-aminopyrene relationships with diesel exposure. In contrast, both engine emissions and smoking affected 2-aminofluorene concentrations. The results confirm that urinary 1-aminopyrene may serve as an exposure biomarker for diesel engine emissions and associated mutagenicity.

Alterations to biomarkers related to long-term exposure to diesel exhaust at concentrations below occupational exposure limits in the European Union and the USA.

BACKGROUND: We previously found that occupational exposure to diesel engine exhaust (DEE) was associated with alterations to 19 biomarkers that potentially reflect the mechanisms of carcinogenesis. Whether DEE is associated with biological alterations at concentrations under existing or recommended occupational exposure limits (OELs) is unclear. METHODS: In a cross-sectional study of 54 factory workers exposed long-term to DEE and 55 unexposed controls, we reanalysed the 19 previously identified biomarkers. Multivariable linear regression was used to compare biomarker levels between DEE-exposed versus unexposed subjects and to assess elemental carbon (EC) exposure-response relationships, adjusted for age and smoking status. We analysed each biomarker at EC concentrations below the US Mine Safety and Health Administration (MSHA) OEL (<106 µg/m3), below the European Union (EU) OEL (<50 µg/m3) and below the American Conference of Governmental Industrial Hygienists (ACGIH) recommendation (<20 µg/m3). RESULTS: Below the MSHA OEL, 17 biomarkers were altered between DEE-exposed workers and unexposed controls. Below the EU OEL, DEE-exposed workers had elevated lymphocytes (p=9E-03, false discovery rate (FDR)=0.04), CD4+ count (p=0.02, FDR=0.05), CD8+ count (p=5E-03, FDR=0.03) and miR-92a-3p (p=0.02, FDR=0.05), and nasal turbinate gene expression (first principal component: p=1E-06, FDR=2E-05), as well as decreased C-reactive protein (p=0.02, FDR=0.05), macrophage inflammatory protein-1ß (p=0.04, FDR=0.09), miR-423-3p (p=0.04, FDR=0.09) and miR-122-5p (p=2E-03, FDR=0.02). Even at EC concentrations under the ACGIH recommendation, we found some evidence of exposure-response relationships for miR-423-3p (ptrend=0.01, FDR=0.19) and gene expression (ptrend=0.02, FDR=0.19). CONCLUSIONS: DEE exposure under existing or recommended OELs may be associated with biomarkers reflective of cancer-related processes, including inflammatory/immune response.

The effect of exposure to traffic related air pollutants in pregnancy on birth anthropometry: a cohort study in a heavily polluted low-middle income country.

BACKGROUND: Ambient air pollution has been recognized as one of the most important environmental health threats. Exposure in early life may affect pregnancy outcomes and the health of the offspring. The main objective of our study was to assess the association between prenatal exposure to traffic related air pollutants during pregnancy on birth weight and length. Second, to evaluate the association between prenatal exposure to traffic related air pollutants and the risk of low birth weight (LBW). METHODS: Three hundred forty mother-infant pairs were included in this prospective cohort study performed in Jakarta, March 2016-September 2020. Exposure to outdoor PM2.5, soot, NOx, and NO2 was assessed by land use regression (LUR) models at individual level. Multiple linear regression models were built to evaluate the association between air pollutants with birth weight (BW) and birth length (BL). Logistic regression was used to assess the risk of low birth weight (LBW) associated with all air pollutants. RESULTS: The average PM2.5 concentration was almost eight times higher than the current WHO guideline and the NO2 level was three times higher. Soot and NOx were significantly associated with reduced birth length. Birth length was reduced by - 3.83 mm (95% CI -6.91; - 0.75) for every IQR (0.74 × 10- 5 per m) increase of soot, and reduced by - 2.82 mm (95% CI -5.33;-0.30) for every IQR (4.68 µg/m3) increase of NOx. Outdoor air pollutants were not significantly associated with reduced birth weight nor the risk of LBW. CONCLUSION: Exposure to soot and NOx during pregnancy was associated with reduced birth length. Associations between exposure to all air pollutants with birth weight and the risk of LBW were less convincing.

Occupational exposure to diesel engine exhaust and serum levels of microRNAs in a cross-sectional molecular epidemiology study in China.

Diesel engine exhaust (DEE) is an established lung carcinogen, but the biological mechanisms of diesel-induced lung carcinogenesis are not well understood. MicroRNAs (miRNAs) are small noncoding RNAs that play a potentially important role in regulating gene expression related to lung cancer. We conducted a cross-sectional molecular epidemiology study to evaluate whether serum levels of miRNAs are altered in healthy workers occupationally exposed to DEE compared to unexposed controls. We conducted a two-stage study, first measuring 405 miRNAs in a pilot study of six DEE-exposed workers exposed and six controls. In the second stage, 44 selected miRNAs were measured using the Fireplex circulating miRNA assay that profiles miRNAs directly from biofluids of 45 workers exposed to a range of DEE (Elemental Carbon (EC), median, range: 47.7, 6.1-79.7 µg/m3 ) and 46 controls. The relationship between exposure to DEE and EC with miRNA levels was analyzed using linear regression adjusted for potential confounders. Serum levels of four miRNAs were significantly lower (miR-191-5p, miR-93-5p, miR-423-3p, miR-122-5p) and one miRNA was significantly higher (miR-92a-3p) in DEE exposed workers compared to controls. Of these miRNAs, miR-191-5p (ptrend  = .001, FDR = 0.04) and miR-93-5p (ptrend  = .009, FDR = 0.18) showed evidence of an inverse exposure-response with increasing EC levels. Our findings suggest that occupational exposure to DEE may affect circulating miRNAs implicated in biological processes related to carcinogenesis, including immune function.

Association between diesel exhaust exposure and mitochondrial DNA methylation.

OBJECTIVES: Diesel exhaust is an established human carcinogen, however the mechanisms by which it leads to cancer development are not fully understood. Mitochondrial dysfunction is an established contributor to carcinogenesis. Recent studies have improved our understanding of the role played by epigenetic modifications in the mitochondrial genome on tumorigenesis. In this study, we aim to evaluate the association between diesel engine exhaust (DEE) exposure with mitochondrial DNA (mtDNA) methylation levels in workers exposed to DEE. METHODS: The study population consisted of 53 male workers employed at a diesel engine manufacturing facility in Northern China who were routinely exposed to diesel exhaust in their occupational setting, as well as 55 unexposed male control workers from other unrelated factories in the same geographic area. Exposure to DEE, elemental carbon, organic carbon, and particulate matter (PM2.5) were assessed. mtDNA methylation for CpG sites (CpGs) from seven mitochondrial genes (D-Loop, MT-RNR1, MT-CO2, MT-CO3, MT-ATP6, MT-ATP8, MT-ND5) was measured in blood samples. Linear regression models were used to estimate the associations between DEE, elemental carbon, organic carbon and PM2.5 exposures with mtDNA methylation levels, adjusting for potential confounders. RESULTS: DEE exposure was associated with decreased MT-ATP6 (difference = -35.6%, P-value = 0.019) and MT-ATP8 methylation (difference = -30%, P-value = 0.029) compared to unexposed controls. Exposures to elemental carbon, organic carbon, and PM2.5 were also significantly and inversely associated with methylation in MT-ATP6 and MT-ATP8 genes (all P-values < 0.05). CONCLUSIONS: Our findings suggest that DEE exposure perturbs mtDNA methylation, which may be of importance for tumorigenesis.

Hyperlocal variation of nitrogen dioxide, black carbon, and ultrafine particles measured with Google Street View cars in Amsterdam and Copenhagen.

Hyperlocal air quality maps are becoming increasingly common, as they provide useful insights into the spatial variation and sources of air pollutants. In this study, we produced several high-resolution concentration maps to assess the spatial differences of three traffic-related pollutants, Nitrogen dioxide (NO2), Black Carbon (BC) and Ultrafine Particles (UFP), in Amsterdam, the Netherlands, and Copenhagen, Denmark. All maps were based on a mixed-effect model approach by using state-of-the-art mobile measurements conducted by Google Street View (GSV) cars, during October 2018 - March 2020, and Land-use Regression (LUR) models based on several land-use and traffic predictor variables. We then explored the concentration ratio between the different normalised pollutants to understand possible contributing sources to the observed hyperlocal variations. The maps developed in this work reflect, (i) expected elevated pollution concentrations along busy roads, and (ii) similar concentration patterns on specific road types, e.g., motorways, for both cities. In the ratio maps, we observed a clear pattern of elevated concentrations of UFP near the airport in both cities, compared to BC and NO2. This is the first study to produce hyperlocal maps for BC and UFP using high-quality mobile measurements. These maps are important for policymakers and health-effect studies, trying to disentangle individual effects of key air pollutants of interest (e.g., UFP).

Exposure to diesel engine exhaust and alterations to the Cys34/Lys525 adductome of human serum albumin.

We investigated whether exposure to carcinogenic diesel engine exhaust (DEE) was associated with altered adduct levels in human serum albumin (HSA) residues. Nano-liquid chromatography-high resolution mass spectrometry (nLC-HRMS) was used to measure adducts of Cys34 and Lys525 residues in plasma samples from 54 diesel engine factory workers and 55 unexposed controls. An untargeted adductomics and bioinformatics pipeline was used to find signatures of Cys34/Lys525 adductome modifications. To identify adducts that were altered between DEE-exposed and unexposed participants, we used an ensemble feature selection approach that ranks and combines findings from linear regression and penalized logistic regression, then aggregates the important findings with those determined by random forest. We detected 40 Cys34 and 9 Lys525 adducts. Among these findings, we found evidence that 6 Cys34 adducts were altered between DEE-exposed and unexposed participants (i.e., 841.75, 851.76, 856.10, 860.77, 870.43, and 913.45). These adducts were biologically related to antioxidant activity.

Mixed-Effects Modeling Framework for Amsterdam and Copenhagen for Outdoor NO2 Concentrations Using Measurements Sampled with Google Street View Cars.

High-resolution air quality (AQ) maps based on street-by-street measurements have become possible through large-scale mobile measurement campaigns. Such campaigns have produced data-only maps and have been used to produce empirical models [i.e., land use regression (LUR) models]. Assuming that all road segments are measured, we developed a mixed model framework that predicts concentrations by an LUR model, while allowing road segments to deviate from the LUR prediction based on between-segment variation as a random effect. We used Google Street View cars, equipped with high-quality AQ instruments, and measured the concentration of NO2 on every street in Amsterdam (n = 46.664) and Copenhagen (n = 28.499) on average seven times over the course of 9 and 16 months, respectively. We compared the data-only mapping, LUR, and mixed model estimates with measurements from passive samplers (n = 82) and predictions from dispersion models in the same time window as mobile monitoring. In Amsterdam, mixed model estimates correlated rs (Spearman correlation) = 0.85 with external measurements, whereas the data-only approach and LUR model estimates correlated rs = 0.74 and 0.75, respectively. Mixed model estimates also correlated higher rs = 0.65 with the deterministic model predictions compared to the data-only (rs = 0.50) and LUR model (rs = 0.61). In Copenhagen, mixed model estimates correlated rs = 0.51 with external model predictions compared to rs = 0.45 and rs = 0.50 for data-only and LUR model, respectively. Correlation increased for 97 locations (rs = 0.65) with more detailed traffic information. This means that the mixed model approach is able to combine the strength of data-only mapping (to show hyperlocal variation) and LUR models by shrinking uncertain concentrations toward the model output.

Short-term associations between barbecue fumes and respiratory health in young adults.

BACKGROUND: Epidemiological studies have associated biomass combustion with (respiratory) morbidity and mortality, primarily in indoor settings. Barbecuing results in high outdoor air pollution exposures, but the health effects are unknown. OBJECTIVE: The objective was to investigate short-term changes in respiratory health in healthy adults, associated with exposure to barbecue fumes. METHODS: 16 healthy, adult volunteers were exposed to barbecue smoke in outdoor air in rest during 1.5 h, using a repeated-measures design. Major air pollutants were monitored on-site, including particulate matter <2.5 µm (PM2.5), particle number concentrations (PNC) and black- and brown carbon. At the same place and time-of-day, subjects participated in a control session, during which they were not exposed to barbecue smoke. Before and immediately after all sessions lung function was measured. Before, immediately after, 4- and 18 h post-sessions nasal expression levels of interleukin (IL)-8, IL6 and Tumor Necrosis Factor alpha (TNFα) were determined in nasal swabs, using quantitative polymerase chain reaction. Associations between major air pollutants, lung function and inflammatory markers were assessed using mixed linear regression models. RESULTS: High PM2.5 levels and PNCs were observed during barbecue sessions, with averages ranging from 553 to 1062 µg/m3 and 109,000-463,000 pt/cm3, respectively. Average black- and brown carbon levels ranged between 4.1-13.0 and 5.0-16.2 µg/m3. A 1000 µg/m3 increase in PM2.5 was associated with 2.37 (0.97, 4.67) and 2.21 (0.98, 5.00) times higher expression of IL8, immediately- and 18 h after exposure. No associations were found between air pollutants and lung function, or the expression of IL6 or TNFα. DISCUSSION: Short-term exposure to air pollutants emitted from barbecuing was associated with a mild respiratory response in healthy young adults, including prolonged increase in nasal IL8 without a change in lung function and other measured inflammatory markers. The results might indicate prolonged respiratory inflammation, due to short-term exposure to barbecue fumes.

Proteomic analysis of serum in workers exposed to diesel engine exhaust.

Diesel engine exhaust (DEE) is classified as a Group 1 human carcinogen. Using a targeted proteomics approach, we aimed to identify proteins associated with DEE and characterize these markers to understand the mechanisms of DEE-induced carcinogenicity. In this cross-sectional molecular epidemiology study, we measured elemental carbon (EC) using a personal air monitor and quantified 1317 targeted proteins in the serum using the SOMAScan assay (SOMALogic) among 19 diesel exposed factory workers and 19 unexposed controls. We used linear regressions to identify proteins associated with DEE and examined their exposure-response relationship across levels of EC using linear trend tests. We further examined pathway enrichment of DEE-related proteins using MetaCore. Occupational exposure to DEE was associated with altered levels of 22 serum proteins (permutation p < .01). Of these, 13 proteins (CXCL11, HAPLN1, FLT4, CD40LG, PES1, IGHE.IGK..IGL, TNFSF9, PGD, NAGK, CCL25, CCL4L1, PDXK, and PLA2G1B) showed an exposure-response relationship with EC (p trend < .01), with serum levels of all but PLA2G1B declining with increasing air levels of EC. For instance, C-X-C Motif Chemokine Ligand 11 (CXCL11) showed the most significant association with DEE (ß = -0.25; permutation p = .00004), where mean serum levels were 4121.1, 2356.7, and 2298.8 relative fluorescent units among the unexposed, lower exposed (median, range : 56.9, 40.2-62.1 µg/m3 EC), and higher exposed (median, range of EC: 72.9, 66.9-107.7 µg/m3 EC) groups, respectively (p trend = .0005). Pathway analysis suggested that these proteins are enriched in pathways related to inflammation and immune regulation. Our study suggests that DEE exposure is associated with altered serum proteins, which play a role in inflammation and immune regulation.

Household air pollution from, and fuel efficiency of, different coal types following local cooking practices in Xuanwei, China.

The domestic combustion of smoky (bituminous) coal in the Chinese counties of Xuanwei and Fuyuan, are responsible for some of the highest rates of lung cancer in the world. Cancer rates vary between coal producing regions (deposits) in the area, with coals from Laibin exhibiting particularly high risks and smokeless (anthracite) coal exhibiting lower risks. However, little information is available on the specific burning characteristics of coals from throughout the area. We conducted an extensive controlled burning experiment using coal from multiple deposits in either a traditional firepit or ventilated stove, accompanied by a detailed examination of time-weighted and real-time size-aggregated particle concentrations. Smoky coal caused higher particle concentrations of all sizes than smokeless coal, with variations observed by geological source. Virtually all particle emissions were in the PM2.5 fraction (98% - mass based), and 75% and 46% were in the PM1 and PM0.3 fraction respectively. Real-time concentrations of PM1 and PM0.1 peaked after coal was added and declined afterwards. Ventilation reduced particle concentrations by up to 15-fold and increased the coal burning rate by 1.9-fold. These findings may provide valuable insight for reducing exposure and adverse health effects associated with domestic coal combustion.

Occupational and environmental exposure to SARS-CoV-2 in and around infected mink farms.

OBJECTIVE: Unprecedented SARS-CoV-2 infections in farmed minks raised immediate concerns regarding transmission to humans and initiated intensive environmental investigations to assess occupational and environmental exposure. METHODS: Air sampling was performed at infected Dutch mink farms, at farm premises and at nearby residential sites. A range of other environmental samples were collected from minks' housing units, including bedding materials. SARS-CoV-2 RNA was analysed in all samples by quantitative PCR. RESULTS: Inside the farms, considerable levels of SARS-CoV-2 RNA were found in airborne dust, especially in personal inhalable dust samples (approximately 1000-10 000 copies/m3). Most of the settling dust samples tested positive for SARS-CoV-2 RNA (82%, 75 of 92). SARS-CoV-2 RNA was not detected in outdoor air samples, except for those collected near the entrance of the most recently infected farm. Many samples of minks' housing units and surfaces contained SARS-CoV-2 RNA. CONCLUSIONS: Infected mink farms can be highly contaminated with SARS-CoV-2 RNA. This warns of occupational exposure, which was substantiated by considerable SARS-CoV-2 RNA concentrations in personal air samples. Dispersion of SARS-CoV-2 to outdoor air was found to be limited and SARS-CoV-2 RNA was not detected in air samples collected beyond farm premises, implying a negligible risk of environmental exposure to nearby communities. Our occupational and environmental risk assessment is in line with whole genome sequencing analyses showing mink-to-human transmission among farm workers, but no indications of direct zoonotic transmission events to nearby communities.

Elevated urinary mutagenicity among those exposed to bituminous coal combustion emissions or diesel engine exhaust.

Urinary mutagenicity reflects systemic exposure to complex mixtures of genotoxic/carcinogenic agents and is linked to tumor development. Coal combustion emissions (CCE) and diesel engine exhaust (DEE) are associated with cancers of the lung and other sites, but their influence on urinary mutagenicity is unclear. We investigated associations between exposure to CCE or DEE and urinary mutagenicity. In two separate cross-sectional studies of nonsmokers, organic extracts of urine were evaluated for mutagenicity levels using strain YG1041 in the Salmonella (Ames) mutagenicity assay. First, we compared levels among 10 female bituminous (smoky) coal users from Laibin, Xuanwei, China, and 10 female anthracite (smokeless) coal users. We estimated exposure-response relationships using indoor air concentrations of two carcinogens in CCE relevant to lung cancer, 5-methylchrysene (5MC), and benzo[a]pyrene (B[a]P). Second, we compared levels among 20 highly exposed male diesel factory workers and 15 unexposed male controls; we evaluated exposure-response relationships using elemental carbon (EC) as a DEE-surrogate. Age-adjusted linear regression was used to estimate associations. Laibin smoky coal users had significantly higher average urinary mutagenicity levels compared to smokeless coal users (28.4 ± 14.0 SD vs. 0.9 ± 2.8 SD rev/ml-eq, p = 2 × 10-5 ) and a significant exposure-response relationship with 5MC (p = 7 × 10-4 ). DEE-exposed workers had significantly higher urinary mutagenicity levels compared to unexposed controls (13.0 ± 10.1 SD vs. 5.6 ± 4.4 SD rev/ml-eq, p = .02) and a significant exposure-response relationship with EC (p-trend = 2 × 10-3 ). Exposure to CCE and DEE is associated with urinary mutagenicity, suggesting systemic exposure to mutagens, potentially contributing to cancer risk and development at various sites.

Elevated Alu retroelement copy number among workers exposed to diesel engine exhaust.

BACKGROUND: Millions of workers worldwide are exposed to diesel engine exhaust (DEE), a known genotoxic carcinogen. Alu retroelements are repetitive DNA sequences that can multiply and compromise genomic stability. There is some evidence linking altered Alu repeats to cancer and elevated mortality risks. However, whether Alu repeats are influenced by environmental pollutants is unexplored. In an occupational setting with high DEE exposure levels, we investigated associations with Alu repeat copy number. METHODS: A cross-sectional study of 54 male DEE-exposed workers from an engine testing facility and a comparison group of 55 male unexposed controls was conducted in China. Personal air samples were assessed for elemental carbon, a DEE surrogate, using NIOSH Method 5040. Quantitative PCR (qPCR) was used to measure Alu repeat copy number relative to albumin (Alb) single-gene copy number in leucocyte DNA. The unitless Alu/Alb ratio reflects the average quantity of Alu repeats per cell. Linear regression models adjusted for age and smoking status were used to estimate relations between DEE-exposed workers versus unexposed controls, DEE tertiles (6.1-39.0, 39.1-54.5 and 54.6-107.7 µg/m3) and Alu/Alb ratio. RESULTS: DEE-exposed workers had a higher average Alu/Alb ratio than the unexposed controls (p=0.03). Further, we found a positive exposure-response relationship (p=0.02). The Alu/Alb ratio was highest among workers exposed to the top tertile of DEE versus the unexposed controls (1.12±0.08 SD vs 1.06±0.07 SD, p=0.01). CONCLUSION: Our findings suggest that DEE exposure may contribute to genomic instability. Further investigations of environmental pollutants, Alu copy number and carcinogenesis are warranted.

A hybrid air pollution / land use regression model for predicting air pollution concentrations in Durban, South Africa.

The objective of this paper was to incorporate source-meteorological interaction information from two commonly employed atmospheric dispersion models into the land use regression technique for predicting ambient nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter (PM10). The study was undertaken across two regions in Durban, South Africa, one with a high industrial profile and a nearby harbour, and the other with a primarily commercial and residential profile. Multiple hybrid models were developed by integrating air pollution dispersion modelling predictions for source specific NO2, SO2, and PM10 concentrations into LUR models following the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to characterise exposure, in Durban. Industrial point sources, ship emissions, domestic fuel burning, and vehicle emissions were key emission sources. Standard linear regression was used to develop annual, summer and winter hybrid models to predict air pollutant concentrations. Higher levels of NO2 and SO2 were predicted in south Durban as compared to north Durban as these are industrial related pollutants. Slightly higher levels of PM10 were predicted in north Durban as compared to south Durban and can be attributed to either traffic, bush burning or domestic fuel burning. The hybrid NO2 models for annual, summer and winter explained 60%, 58% and 63%, respectively, of the variance with traffic, population and harbour being identified as important predictors. The SO2 models were less robust with lower R2 annual (44%), summer (53%) and winter (46%), in which industrial and traffic variables emerged as important predictors. The R2 for PM10 models ranged from 80% to 85% with population and urban land use type emerging as predictor variables.

Spatial and Spatiotemporal Variability of Regional Background Ultrafine Particle Concentrations in the Netherlands.

Studies of the health effects of ultrafine particles (UFPs) in large nationwide cohorts are currently hampered by a lack of knowledge about spatial and spatiotemporal variations in regional background UFPs. We measured the UFP (10-300 nm) at 20 regional background locations (3 × 2 weeks) across the Netherlands and a reference site continuously over a total period of 14 months in 2016-2017. We compared the overall averages for each site and used kriging to create a regional background spatial map of the Netherlands. Spatiotemporal variability was analyzed by correlating time-series of 2 and 24 h average concentrations. The overall average measured UFP concentrations at the 20 locations ranged from 3814 to 7070 particles/cm3. We found the spatial correlation in the UFP concentrations up to 180 km and clear differences between the north and the more populated southern parts of the country. The average temporal correlation between 2 and 24 h average UFP concentrations was 0.50 (IQR: 0.36-0.61) and 0.58 (IQR: 0.44-0.75), respectively. Temporal correlation declined weakly with a distance between sites, from 0.58 for sites within 80 km of each other to 0.47 for sites farther away. The substantial spatial variation in the regional background UFP concentrations suggests that regional variation may contribute importantly to exposure contrast in nationwide health studies of UFP.

Harbor and Intra-City Drivers of Air Pollution: Findings from a Land Use Regression Model, Durban, South Africa.

Multiple land use regression models (LUR) were developed for different air pollutants to characterize exposure, in the Durban metropolitan area, South Africa. Based on the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology, concentrations of particulate matter (PM10 and PM2.5), sulphur dioxide (SO2), and nitrogen dioxide (NO2) were measured over a 1-year period, at 41 sites, with Ogawa Badges and 21 sites with PM Monitors. Sampling was undertaken in two regions of the city of Durban, South Africa, one with high levels of heavy industry as well as a harbor, and the other small-scale business activity. Air pollution concentrations showed a clear seasonal trend with higher concentrations being measured during winter (25.8, 4.2, 50.4, and 20.9 µg/m3 for NO2, SO2, PM10, and PM2.5, respectively) as compared to summer (10.5, 2.8, 20.5, and 8.5 µg/m3 for NO2, SO2, PM10, and PM2.5, respectively). Furthermore, higher levels of NO2 and SO2 were measured in south Durban as compared to north Durban as these are industrial related pollutants, while higher levels of PM were measured in north Durban as compared to south Durban and can be attributed to either traffic or domestic fuel burning. The LUR NO2 models for annual, summer, and winter explained 56%, 41%, and 63% of the variance with elevation, traffic, population, and Harbor being identified as important predictors. The SO2 models were less robust with lower R2 annual (37%), summer (46%), and winter (46%) with industrial and traffic variables being important predictors. The R2 for PM10 models ranged from 52% to 80% while for PM2.5 models this range was 61-76% with traffic, elevation, population, and urban land use type emerging as predictor variables. While these results demonstrate the influence of industrial and traffic emissions on air pollution concentrations, our study highlighted the importance of a Harbor variable, which may serve as a proxy for NO2 concentrations suggesting the presence of not only ship emissions, but also other sources such as heavy duty motor vehicles associated with the port activities.

Cardiovascular benefits of short-term indoor air filtration intervention in elderly living in Beijing: An extended analysis of BIAPSY study.

BACKGROUND: Adverse cardiovascular effects associated with air pollution exposure have been widely demonstrated. However, inconsistent cardiovascular responses were observed from reducing indoor air pollution exposure. We aimed to assess whether short-term air filtration intervention could benefit cardiovascular health in elderly living in high pollution area. METHODS: A randomized crossover intervention study of short-term indoor air filtration intervention on cardiovascular health was conducted among 35 non-smoking elderly participants living in Beijing in the winter of 2013, as part of Beijing Indoor Air Purifier StudY (BIAPSY). Portable air filtration units were randomly allocated to active filtration for 2 weeks and sham filtration for 2 weeks in the households. Twelve-hour daytime ambulatory heart rate variability (HRV) and blood pressure (ABP) were measured during active and sham filtration. Concurrently, real-time indoor and outdoor particulate matter with diameter less than 2.5 µm (PM2.5) and indoor black carbon (BC) concentrations were measured. We applied generalized additive mixed models to evaluate the associations of 1- to 10-h moving average (MA) exposures of indoor PM2.5 and BC with HRV and ABP indices, and to explore whether these associations could be modified by air filtration. RESULTS: We observed decreases of 34.8% in indoor PM2.5 and 35.3% in indoor BC concentrations during active filtration. Indoor PM2.5 and BC exposures were significantly associated with reduced HRV and increased ABP indices, and greater changes were observed during sham filtration. In specific, each 10 µg/m3 increase in indoor PM2.5 at MA8-h was associated with a significant reduction of 1.34% (95% CI: -2.42, -0.26) in SDNN during sham filtration, compared with a non-significant reduction of 0.81% (95% CI: -6.00, 4.68) during active filtration (Pinter< 0.001). Each 1 µg/m3 increase in indoor BC at MA8-h was associated with a significant increase of 2.41% (95% CI: 0.38, 4.47) in SBP during sham filtration, compared with a non-significant increase of -1.09% (95% CI: -4.06, 1.96) during active filtration (Pinter = 0.135). Nonlinear inverse exposure-response relationships of indoor air pollution exposures with predicted HRV and ABP indices also confirmed some cardiovascular benefits of short-term air filtration intervention. CONCLUSIONS: Our results suggested that short-term indoor air filtration intervention can be of some cardiovascular benefits in elderly living with high pollution episodes.