Dataset Information

Combining Measurements from Mobile Monitoring and a Reference Site To Develop Models of Ambient Ultrafine Particle Number Concentration at Residences.

ABSTRACT: Significant spatial and temporal variation in ultrafine particle (UFP; <100 nm in diameter) concentrations creates challenges in developing predictive models for epidemiological investigations. We compared the performance of land-use regression models built by combining mobile and stationary measurements (hybrid model) with a regression model built using mobile measurements only (mobile model) in Chelsea and Boston, MA (USA). In each study area, particle number concentration (PNC; a proxy for UFP) was measured at a stationary reference site and with a mobile laboratory driven along a fixed route during an ∼1-year monitoring period. In comparing PNC measured at 20 residences and PNC estimates from hybrid and mobile models, the hybrid model showed higher Pearson correlations of natural log-transformed PNC ( r = 0.73 vs 0.51 in Chelsea; r = 0.74 vs 0.47 in Boston) and lower root-mean-square error in Chelsea (0.61 vs 0.72) but no benefit in Boston (0.72 vs 0.71). All models overpredicted log-transformed PNC by 3-6% at residences, yet the hybrid model reduced the standard deviation of the residuals by 15% in Chelsea and 31% in Boston with better tracking of overnight decreases in PNC. Overall, the hybrid model considerably outperformed the mobile model and could offer reduced exposure error for UFP epidemiology.

SUBMITTER: Simon MC

PROVIDER: S-EPMC8371457 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Combining Measurements from Mobile Monitoring and a Reference Site To Develop Models of Ambient Ultrafine Particle Number Concentration at Residences.

Simon Matthew C MC Patton Allison P AP Naumova Elena N EN Levy Jonathan I JI Kumar Prashant P Brugge Doug D Durant John L JL

Environmental science & technology 20180525 12

Significant spatial and temporal variation in ultrafine particle (UFP; <100 nm in diameter) concentrations creates challenges in developing predictive models for epidemiological investigations. We compared the performance of land-use regression models built by combining mobile and stationary measurements (hybrid model) with a regression model built using mobile measurements only (mobile model) in Chelsea and Boston, MA (USA). In each study area, particle number concentration (PNC; a proxy for UF ...[more]

PMID: 29762018

Similar Datasets

Project description:Ultrafine particles (UFP; aerodynamic diameter < 0.1 micrometers) are a ubiquitous exposure in the urban environment and are elevated near highways. Most epidemiological studies of UFP health effects use central site monitoring data, which may misclassify exposure. Our aims were to: (1) examine the relationship between distant and proximate monitoring sites and their ability to predict hourly UFP concentration measured at residences in an urban community with a major interstate highway and; (2) determine if meteorology and proximity to traffic improve explanatory power. Short-term (1 - 3 weeks) residential monitoring of UFP concentration was conducted at 18 homes. Long-term monitoring was conducted at two near-highway monitoring sites and a central site. We created models of outdoor residential UFP concentration based on concentrations at the near-highway site, at the central site, at both sites together and without fixed sites. UFP concentration at residential sites was more highly correlated with those at a near-highway site than a central site. In regression models of each site alone, a 10% increase in UFP concentration at a near-highway site was associated with a 6% (95% CI: 6%, 7%) increase at residences while a 10% increase in UFP concentration at the central site was associated with a 3% (95% CI: 2%, 3%) increase at residences. A model including both sites showed minimal change in the magnitude of the association between the near-highway site and the residences, but the estimated association with UFP concentration at the central site was substantially attenuated. These associations remained after adjustment for other significant predictors of residential UFP concentration, including distance from highway, wind speed, wind direction, highway traffic volume and precipitation. The use of a central site as an estimate of personal exposure for populations near local emissions of traffic-related air pollutants may result in exposure misclassification.

Project description:BackgroundThe metabolomic signatures of short- and long-term exposure to PM2.5 have been reported and linked to inflammation and oxidative stress. However, little is known about the relative contribution of the specific PM2.5 species (hence sources) that drive these metabolomic signatures.ObjectivesWe aimed to determine the relative contribution of the different species of PM2.5 exposure to the perturbed metabolic pathways related to changes in the plasma metabolome.MethodsWe performed mass-spectrometry based metabolomic profiling of plasma samples among men from the Normative Aging Study to identify metabolic pathways associated with PM2.5 species. The exposure windows included short-term (one, seven-, and thirty-day moving average) and long-term (one year moving average). We used linear mixed-effect regression with subject-specific intercepts while simultaneously adjusting for PM2.5, NO2, O3, temperature, relative humidity, and covariates and correcting for multiple testing. We also used independent component analysis (ICA) to examine the relative contribution of patterns of PM2.5 species.ResultsBetween 2000 and 2016, 456 men provided 648 blood samples, in which 1158 metabolites were quantified. We chose 305 metabolites for the short-term and 288 metabolites for the long-term exposure in this analysis that were significantly associated (p-value < 0.01) with PM2.5 to include in our PM2.5 species analysis. On average, men were 75.0 years old and their body mass index was 27.7 kg/m2. Only 3% were current smokers. In the adjusted models, ultrafine particles (UFPs) were the most significant species of short-term PM2.5 exposure followed by nickel, vanadium, potassium, silicon, and aluminum. Black carbon, vanadium, zinc, nickel, iron, copper, and selenium were the significant species of long-term PM2.5 exposure. We identified several metabolic pathways perturbed with PM2.5 species including glycerophospholipid, sphingolipid, and glutathione. These pathways are involved in inflammation, oxidative stress, immunity, and nucleic acid damage and repair. Results were overlapped with the ICA.ConclusionsWe identified several significant perturbed plasma metabolites and metabolic pathways associated with exposure to PM2.5 species. These species are associated with traffic, fuel oil, and wood smoke. This is the largest study to report a metabolomic signature of PM2.5 species' exposure and the first to use ICA.

Project description:Epidemiology studies have linked exposure to pollutant particles to increased cardiovascular mortality and morbidity, however, the mechanism remains unknown. In this study, we hypothesized that the ultrafine fraction of ambient pollutant particles would cause endothelial cells dysfunction. We profiled gene expression of human pulmonary artery endothelial cells (HPAEC) exposed to ultrafine Chapel Hill particles (UFP) (100μg/ml) or vehicle for 4h with Affymetrix HG U133 Plus 2.0 chips (N = 4 each). Using an unpaired t-test (p <0.01, 5% false discovery rate) we found 426 unique genes to be differentially expressed with 320 upregulated genes and 106 downregulated genes. Among these genes, we noted upregulation of genes related to coagulation-inflammation circuitry including tissue factor (F3), coagulation factor II receptor-like 2 (F2RL2, PAR3), interleukin (IL)-6 and IL-8. Upregulation of these genes were independently confirmed by RT-PCR and/or protein release. Genes related to the CXC chemokine family that have been implicated in the pathogenesis of vascular disease were upregulated, including MCP-1 (2.60 fold), IL-8 (2.47 fold), CXCL1 (1.41 fold), CXCL2 (1.95 fold), CXCL3 (2.28 fold) and CXCR4 (1.30 fold). In addition, genes related to clotting independent signaling of F3 were also differentially expressed, including FOS, JUN and NFKBIA. Treatment of HPAEC with UFP for 16 hours increased the release of IL6 and IL8 by 1.9-fold and 1.8-fold respectively. Pretreatment of HPAEC with a blocking antibody against F3 attenuated IL6 and IL8 release by 30% and 70% respectively. Thus using gene profiling, we uncovered that UFP may induce vascular endothelial cells to express genes related to clotting and angiogenesis. These results provide a novel hypothesis that PM may cause cardiovascular adverse health effects via induction of tissue factor in vascular endothelial cells which then triggers clotting dependent and independent downstream signaling. Keywords: particle treatment

Dataset Information

Combining Measurements from Mobile Monitoring and a Reference Site To Develop Models of Ambient Ultrafine Particle Number Concentration at Residences.

Publications

Combining Measurements from Mobile Monitoring and a Reference Site To Develop Models of Ambient Ultrafine Particle Number Concentration at Residences.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets