Traffic-related Air Pollution and Lung Cancer Incidence: The California Multiethnic Cohort Study.

Rationale: Although the contribution of air pollution to lung cancer risk is well characterized, few studies have been conducted in racially, ethnically, and socioeconomically diverse populations. Objectives: To examine the association between traffic-related air pollution and risk of lung cancer in a racially, ethnically, and socioeconomically diverse cohort. Methods: Among 97,288 California participants of the Multiethnic Cohort Study, we used Cox proportional hazards regression to examine associations between time-varying traffic-related air pollutants (gaseous and particulate matter pollutants and regional benzene) and lung cancer risk (n = 2,796 cases; average follow-up = 17 yr), adjusting for demographics, lifetime smoking, occupation, neighborhood socioeconomic status (nSES), and lifestyle factors. Subgroup analyses were conducted for race, ethnicity, nSES, and other factors. Measurements and Main Results: Among all participants, lung cancer risk was positively associated with nitrogen oxide (hazard ratio [HR], 1.15 per 50 ppb; 95% confidence interval [CI], 0.99-1.33), nitrogen dioxide (HR, 1.12 per 20 ppb; 95% CI, 0.95-1.32), fine particulate matter with aerodynamic diameter <2.5 µm (HR, 1.20 per 10 µg/m3; 95% CI, 1.01-1.43), carbon monoxide (HR, 1.29 per 1,000 ppb; 95% CI, 0.99-1.67), and regional benzene (HR, 1.17 per 1 ppb; 95% CI, 1.02-1.34) exposures. These patterns of associations were driven by associations among African American and Latino American groups. There was no formal evidence for heterogeneity of effects by nSES (P heterogeneity > 0.21), although participants residing in low-SES neighborhoods had increased lung cancer risk associated with nitrogen oxides, and no association was observed among those in high-SES neighborhoods. Conclusions: These findings in a large multiethnic population reflect an association between lung cancer and the mixture of traffic-related air pollution and not a particular individual pollutant. They are consistent with the adverse effects of air pollution that have been described in less racially, ethnically, and socioeconomically diverse populations. Our results also suggest an increased risk of lung cancer among those residing in low-SES neighborhoods.

Substantial Near-Field Air Quality Improvements at a General Aviation Airport Following a Runway Shortening.

Santa Monica Airport (SMO), a general aviation airport in Southern California, recently shortened its only runway by 225 m at both ends to limit jet aircraft operations. We evaluated the resulting changes in aviation activity and air quality by measuring particle number (PN), black carbon (BC), and lead (Pb) concentrations, before and after the runway was shortened at two near-airfield locations including a residential site. Postshortening, there was a 50% decrease in total operations, driven mostly by the greater than 80% decrease in jet operations; however, there was no significant change in piston engine aircraft operations (which use leaded fuel). We measured greater than 75%, 30%, and 75% reductions in the concentrations of PN, BC, and Pb, respectively, after the runway was shortened, largely due to enhanced dispersion resulting from the increased distance to the newly shortened runway. Overall, the runway shortening improved air quality in nearby areas such that airport impacts were comparable to or lower than impacts from other sources such as vehicular traffic. Until aviation fuel becomes completely unleaded, runway shortening or relocating operations away from the edge abutting residential areas may be the most effective environmental impact mitigation strategy for general aviation airports situated adjacent to residential areas.

Predicting Fine Spatial Scale Traffic Noise Using Mobile Measurements and Machine Learning.

Environmental noise has been associated with a variety of health endpoints including cardiovascular disease, sleep disturbance, depression, and psychosocial stress. Most population noise exposure comes from vehicular traffic, which produces fine-scale spatial variability that is difficult to characterize using traditional fixed-site measurement techniques. To address this challenge, we collected A-weighted, equivalent noise (LAeq in decibels, dB) data on hour-long foot journeys around 16 locations throughout Long Beach, California and trained four machine learning models, linear regression, random forest, extreme gradient boosting, and a neural network, to predict noise with 20 m resolution. Input variables to the models included traffic metrics, road network features, meteorological conditions, and land use type. Among all machine learning models, extreme gradient boosting had the best results in validation tests (leave-one-route-out R2 = 0.71, root mean square error (RMSE) of 4.54 dB; 5-fold R2 = 0.96, RMSE of 1.8 dB). Local traffic volume was the most important predictor of noise; road features, land use, and meteorology including humidity, temperature, and wind speed also contributed. We show that a novel, on-foot mobile noise measurement method coupled with machine learning approaches enables highly accurate prediction of small-scale spatial patterns in traffic-related noise over a mixed-use urban area.

Impacts of Aviation Emissions on Near-Airport Residential Air Quality.

Impacts of aviation emissions on air quality in and around residences near airports remain underexamined. We measured gases (CO, CO2, NO, and NO2) and particles (black carbon, particle-bound aromatic hydrocarbons, fine particulate matter (PM2.5), and ultrafine particles (reported using particle number concentrations (PNC) as a proxy)) continuously for 1 month at a residence near the Logan International Airport, Boston. The residence was located under a flight trajectory of the most utilized runway configuration. We found that when the residence was downwind of the airport, the concentrations of all gaseous and particulate pollutants (except PM2.5) were 1.1- to 4.8-fold higher than when the residence was not downwind of the airport. Controlling for runway usage and meteorology, the impacts were highest during overhead landing operations: average PNC was 7.5-fold higher from overhead landings versus takeoffs on the closest runway. Infiltration of aviation-origin emissions resulted in indoor PNC that were comparable to ambient concentrations measured locally on roadways and near highways. In addition, ambient NO2 concentrations at the residence exceeded those measured at regulatory monitoring sites in the area including near-road monitors. Our results highlight the need for further characterization of outdoor and indoor impacts of aviation emissions at the neighborhood scale to more accurately estimate residential exposures.

The role of traffic noise on the association between air pollution and children's lung function.

Although it has been shown that traffic-related air pollution adversely affects children's lung function, few studies have examined the influence of traffic noise on this association, despite both sharing a common source. Estimates of noise exposure (Ldn, dB), and freeway and non-freeway emission concentrations of oxides of nitrogen (NOx, ppb) were spatially assigned to children in Southern California who were tested for forced vital capacity (FVC, n=1345), forced expiratory volume in 1s, (FEV1, n=1332), and asthma. The associations between traffic-related NOx and these outcomes, with and without adjustment for noise, were examined using mixed effects models. Adjustment for noise strengthened the association between NOx and reduced lung function. A 14.5mL (95% CI -40.0, 11.0mL) decrease in FVC per interquartile range (13.6 ppb) in freeway NOx was strengthened to a 34.6mL decrease after including a non-linear function of noise (95% CI -66.3, -2.78mL). Similarly, a 6.54mL decrease in FEV1 (95% CI -28.3, 15.3mL) was strengthened to a 21.1mL decrease (95% CI -47.6, 5.51) per interquartile range in freeway NOx. Our results indicate that where possible, noise should be included in epidemiological studies of the association between traffic-related air pollution on lung function. Without taking noise into account, the detrimental effects of traffic-related pollution may be underestimated.

Ultrafine particle size as a tracer for aircraft turbine emissions.

Ultrafine particle number (UFPN) and size distributions, black carbon, and nitrogen dioxide concentrations were measured downwind of two of the busiest airports in the world, Los Angeles International Airport (LAX) and Hartsfield-Jackson International Airport (ATL - Atlanta, GA) using a mobile monitoring platform. Transects were located between 5 km and 10 km from the ATL and LAX airports. In addition, measurements were taken at 43 additional urban neighborhood locations in each city and on freeways. We found a 3-5 fold increase in UFPN concentrations in transects under the landing approach path to both airports relative to surrounding urban areas with similar ground traffic characteristics. The latter UFPN concentrations measured were distinct in size distributional properties from both freeways and across urban neighborhoods, clearly indicating different sources. Elevated concentrations of Black Carbon (BC) and NO2 were also observed on airport transects, and the corresponding pattern of elevated BC was consistent with the observed excess UFPN concentrations relative to other urban locations.

A Novel Wireless Wearable Volatile Organic Compound (VOC) Monitoring Device with Disposable Sensors.

A novel portable wireless volatile organic compound (VOC) monitoring device with disposable sensors is presented. The device is miniaturized, light, easy-to-use, and cost-effective. Different field tests have been carried out to identify the operational, analytical, and functional performance of the device and its sensors. The device was compared to a commercial photo-ionization detector, gas chromatography-mass spectrometry, and carbon monoxide detector. In addition, environmental operational conditions, such as barometric change, temperature change and wind conditions were also tested to evaluate the device performance. The multiple comparisons and tests indicate that the proposed VOC device is adequate to characterize personal exposure in many real-world scenarios and is applicable for personal daily use.

Inflammatory response of monocytes to ambient particles varies by highway proximity.

Epidemiological studies have demonstrated associations of chronic respiratory disease with near-roadway pollutant exposure, effects that were independent of those of regional air pollutants. However, there has been limited study of the potential mechanisms for near-roadway effects. Therefore, we examined the in vitro effect of respirable particulate matter (PM) collected adjacent to a major Los Angeles freeway and at an urban background location. PM was collected on filters during two consecutive 15-day periods. Oxidative stress and inflammatory response (intracellular reactive oxygen species [ROS], IL-1ß, IL-6, IL-8, and TNF-α) to PM aqueous extract was assessed in THP-1 cells, a model for evaluating monocyte/macrophage lineage cell responses. The near-roadway PM induced statistically significantly higher levels of IL-6, IL-8, and TNF-α (P < 0.01) and a near significant increase in IL-1ß (P = 0.06) but did not induce ROS activity (P = 0.17). The contrast between urban background and near-roadway PM-induced inflammatory cytokines was similar in magnitude to that corresponding to temporal differences between the two collection periods. PM-induced proinflammatory protein expression was attenuated by antioxidant pretreatment, and PM stimulation enhanced the activity of protein kinases, including extracellular signal-regulated kinase and c-Jun N-terminal kinase. Pretreatment of THP-1 cells with kinase inhibitors reduced PM-induced proinflammatory mediator expression. The proinflammatory response was also reduced by pretreatment with polymyxin B, suggesting a role for endotoxin. However, the patterns of PM-induced protein kinase response and the attenuation of inflammatory responses by antioxidant or polymyxin B pretreatment did not vary between near-roadway and urban background locations. We conclude that near-roadway PM produced greater inflammatory response than urban background PM, a finding consistent with emerging epidemiologic findings, but these differences were not explained by PM endotoxin content or by MAPK pathways. Nevertheless, THP-1 cells may be a model for the development of biologically relevant metrics of long-term spatial variation in exposure for study of chronic disease.

Emissions from an international airport increase particle number concentrations 4-fold at 10 km downwind.

We measured the spatial pattern of particle number (PN) concentrations downwind from the Los Angeles International Airport (LAX) with an instrumented vehicle that enabled us to cover larger areas than allowed by traditional stationary measurements. LAX emissions adversely impacted air quality much farther than reported in previous airport studies. We measured at least a 2-fold increase in PN concentrations over unimpacted baseline PN concentrations during most hours of the day in an area of about 60 km(2) that extended to 16 km (10 miles) downwind and a 4- to 5-fold increase to 8-10 km (5-6 miles) downwind. Locations of maximum PN concentrations were aligned to eastern, downwind jet trajectories during prevailing westerly winds and to 8 km downwind concentrations exceeded 75 000 particles/cm(3), more than the average freeway PN concentration in Los Angeles. During infrequent northerly winds, the impact area remained large but shifted to south of the airport. The freeway length that would cause an impact equivalent to that measured in this study (i.e., PN concentration increases weighted by the area impacted) was estimated to be 280-790 km. The total freeway length in Los Angeles is 1500 km. These results suggest that airport emissions are a major source of PN in Los Angeles that are of the same general magnitude as the entire urban freeway network. They also indicate that the air quality impact areas of major airports may have been seriously underestimated.

Determinants of the Spatial Distributions of Elemental Carbon and Particulate Matter in Eight Southern Californian Communities.

Emerging evidence indicates that near-roadway pollution (NRP) in ambient air has adverse health effects. However, specific components of the NRP mixture responsible for these effects have not been established. A major limitation for health studies is the lack of exposure models that estimate NRP components observed in epidemiological studies over fine spatial scale of tens to hundreds of meters. In this study, exposure models were developed for fine-scale variation in biologically relevant elemental carbon (EC). Measurements of particulate matter (PM) and EC less than 2.5 µm in aerodynamic diameter (EC2.5) and of PM and EC of nanoscale size less than 0.2 µm were made at up to 29 locations in each of eight Southern California Children's Health Study communities. Regression-based prediction models were developed using a guided forward selection process to identify traffic variables and other pollutant sources, community physical characteristics and land use as predictors of PM and EC variation in each community. A combined eight-community model including only CALINE4 near-roadway dispersion-estimated vehicular emissions accounting for distance, distance-weighted traffic volume, and meteorology, explained 51% of the EC0.2 variability. Community-specific models identified additional predictors in some communities; however, in most communities the correlation between predicted concentrations from the eight-community model and observed concentrations stratified by community were similar to those for the community-specific models. EC2.5 could be predicted as well as EC0.2. EC2.5 estimated from CALINE4 and population density explained 53% of the within-community variation. Exposure prediction was further improved after accounting for between-community heterogeneity of CALINE4 effects associated with average distance to Pacific Ocean shoreline (to 61% for EC0.2) and for regional NOx pollution (to 57% for EC2.5). PM fine spatial scale variation was poorly predicted in both size fractions. In conclusion, models of exposure that include traffic measures such as CALINE4 can provide useful estimates for EC0.2 and EC2.5 on a spatial scale appropriate for health studies of NRP in selected Southern California communities.

Spatial Variation in Particulate Matter Components over a Large Urban Area.

To characterize exposures to particulate matter (PM) and its components, we performed a large sampling study of small-scale spatial variation in size-resolved particle mass and composition. PM was collected in size ranges of < 0.2, 0.2-to-2.5, and 2.5-to-10 µm on a scale of 100s to 1000s of meters to capture local sources. Within each of eight Southern California communities, up to 29 locations were sampled for rotating, month-long integrated periods at two different times of the year, six months apart, from Nov 2008 through Dec 2009. Additional sampling was conducted at each community's regional monitoring station to provide temporal coverage over the sampling campaign duration. Residential sampling locations were selected based on a novel design stratified by high- and low-predicted traffic emissions and locations over- and under-predicted from previous dispersion model and sampling comparisons. Primary vehicle emissions constituents, such as elemental carbon (EC), showed much stronger patterns of association with traffic than pollutants with significant secondary formation, such as PM2.5 or water soluble organic carbon. Associations were also stronger during cooler times of the year (Oct through Mar). Primary pollutants also showed greater within-community spatial variation compared to pollutants with secondary formation contributions. For example, the average cool-season community mean and standard deviation (SD) for EC were 1.1 and 0.17 µg/m3, respectively, giving a coefficient of variation (CV) of 18%. For PM2.5, average mean and SD were 14 and 1.3 µg/m3, respectively, with a CV of 9%. We conclude that within-community spatial differences are important for accurate exposure assessment of traffic-related pollutants.

Estimating near-roadway air pollution from multi-frequency noise measurements.

Air pollution is a major environmental problem and its monitoring is essential for regulatory purposes, policy making, and protecting public health. However, dense networks of air quality monitoring equipment are prohibitively expensive due to equipment costs, labor requirements, and infrastructure needs. As a result, alternative lower-cost methods that reliably determine air quality levels near potent pollution sources such as freeways are desirable. We present an approach that couples noise frequency measurements with machine learning to estimate near-roadway particulate matter (PM2.5), nitrogen dioxide (NO2), and black carbon (BC) at 1-min temporal resolution. The models were based on data collected by co-located noise and air quality instruments near a busy freeway in Long Beach, California. Model performance was excellent for all three pollutants, e.g., NO2 predictions yielded Pearson's R = 0.87 with a root mean square error of 7.2 ppb; this error represents about 10 % of total morning rush hour concentrations. Among the best air pollutant predictors were noise frequencies at 40 Hz, 500 Hz, and 800 Hz, and meteorology, particularly wind direction. Overall, our method potentially provides a cost-effective and efficient approach to estimating and/or supplementing near-road air pollutant concentrations in urban areas at high temporal resolution.

Association between Airport Ultrafine Particles and Lung Cancer Risk: The Multiethnic Cohort Study.

BACKGROUND: Ultrafine particles (UFP) are unregulated air pollutants abundant in aviation exhaust. Emerging evidence suggests that UFPs may impact lung health due to their high surface area-to-mass ratio and deep penetration into airways. This study aimed to assess long-term exposure to airport-related UFPs and lung cancer incidence in a multiethnic population in Los Angeles County. METHODS: Within the California Multiethnic Cohort, we examined the association between long-term exposure to airport-related UFPs and lung cancer incidence. Multivariable Cox proportional hazards regression models were used to estimate the effect of UFP exposure on lung cancer incidence. Subgroup analyses by demographics, histology and smoking status were conducted. RESULTS: Airport-related UFP exposure was not associated with lung cancer risk [per one IGR HR, 1.01; 95% confidence interval (CI), 0.97-1.05] overall and across race/ethnicity. A suggestive positive association was observed between a one IQR increase in UFP exposure and lung squamous cell carcinoma (SCC) risk (HR, 1.08; 95% CI, 1.00-1.17) with a Phet for histology = 0.05. Positive associations were observed in 5-year lag analysis for SCC (HR, 1.12; 95% CI, CI, 1.02-1.22) and large cell carcinoma risk (HR, 1.23; 95% CI, 1.01-1.49) with a Phet for histology = 0.01. CONCLUSIONS: This large prospective cohort analysis suggests a potential association between airport-related UFP exposure and specific lung histologies. The findings align with research indicating that UFPs found in aviation exhaust may induce inflammatory and oxidative injury leading to SCC. IMPACT: These results highlight the potential role of airport-related UFP exposure in the development of lung SCC.

Inflammatory cytokine response to ambient particles varies due to field collection procedures.

In vitro assays of biological activity induced by particulate matter (PM) are a tool for investigating mechanisms of PM health effects. They have potential application to exposure assessment in chronic disease epidemiology. However, there has been little reporting of the impact of real-world PM collection techniques on assay results. Therefore, we examined the effect of sampling duration and postsampling delays in freezing on PM-induced biological activity. Duplicate samples of respirable ambient Los Angeles PM were collected on polyurethane foam filters during 17 days and during three contemporaneous consecutive shorter periods. After collection, one duplicate was stored at ambient temperature for 24 hours before freezing; the other was frozen immediately. Cytokine response (IL-1ß, IL-6, IL-8, and TNF-α) to PM aqueous extract was assessed in THP-1 cells, a model for evaluating monocyte/macrophage lineage cell responses. There was consistent 3- to 4-fold variation in PM-induced cytokine levels across the three collection intervals. Compared with levels induced by PM pooled across the three periods, continuously collected PM-induced levels were reduced by 25% (IL-6) to 39% (IL-8). The pattern of cytokine gene expression response was similar. Cytokine level variation by time to freezing was not statistically significant. PM-induced inflammatory response varied substantially over a weekly time scale. We conclude that long PM sampling interval induced less activity than the average of equivalent shorter consecutive sampling intervals. Time to freezing was less important. Implications for development of metrics of long-term spatial variation in biological exposure metrics for study of chronic disease merit further investigation.

Modeling the concentrations of on-road air pollutants in southern California.

High concentrations of air pollutants on roadways, relative to ambient concentrations, contribute significantly to total personal exposure. Estimation of these exposures requires measurements or prediction of roadway concentrations. Our study develops, compares, and evaluates linear regression and nonlinear generalized additive models (GAMs) to estimate on-road concentrations of four key air pollutants, particle-bound polycyclic aromatic hydrocarbons (PB-PAH), particle number count (PNC), nitrogen oxides (NOx), and particulate matter with diameter <2.5 µm (PM2.5) using traffic, meteorology, and elevation variables. Critical predictors included wind speed and direction for all the pollutants, traffic-related variables for PB-PAH, PNC, and NOx, and air temperatures and relative humidity for PM2.5. GAMs explained 50%, 55%, 46%, and 71% of the variance for log or square-root transformed concentrations of PB-PAH, PNC, NOx, and PM2.5, respectively, an improvement of 5% to over 15% over the linear models. Accounting for temporal autocorrelation in the GAMs further improved the prediction, explaining 57-89% of the variance. We concluded that traffic and meteorological data are good predictors in estimating on-road traffic-related air pollutant concentrations and GAMs perform better for nonlinear variables, such as meteorological parameters.

Disparities in greenspace associated with sleep duration among adolescent children in Southern California.

More than half of adolescent children do not get the recommended 8 hours of sleep necessary for optimal growth and development. In adults, several studies have evaluated effects of urban stressors including lack of greenspace, air pollution, noise, nighttime light, and psychosocial stress on sleep duration. Little is known about these effects in adolescents, however, it is known that these exposures vary by socioeconomic status (SES). We evaluated the association between several environmental exposures and sleep in adolescent children in Southern California. Methods: In 2010, a total of 1476 Southern California Children's Health Study (CHS) participants in grades 9 and 10 (mean age, 13.4 years; SD, 0.6) completed a questionnaire including topics on sleep and psychosocial stress. Exposures to greenspace, artificial light at night (ALAN), nighttime noise, and air pollution were estimated at each child's residential address, and SES was characterized by maternal education. Odds ratios and 95% confidence intervals (95% CIs) for sleep outcomes were estimated by environmental exposure, adjusting for age, sex, race/ethnicity, home secondhand smoke, and SES. Results: An interquartile range (IQR) increase in greenspace decreased the odds of not sleeping at least 8 hours (odds ratio [OR], 0.86 [95% CI, 0.71, 1.05]). This association was significantly protective in low SES participants (OR, 0.77 [95% CI, 0.60, 0.98]) but not for those with high SES (OR, 1.16 [95%CI, 0.80, 1.70]), interaction P = 0.03. Stress mediated 18.4% of the association among low SES participants. Conclusions: Residing in urban neighborhoods of greater greenness was associated with improved sleep duration among children of low SES but not higher SES. These findings support the importance of widely reported disparities in exposure and access to greenspace in socioeconomically disadvantaged populations.

Particulate matter, traffic-related air pollutants, and circulating C-reactive protein levels: The Multiethnic Cohort Study.

Inhaled particles and gases can harm health by promoting chronic inflammation in the body. Few studies have investigated the relationship between outdoor air pollution and inflammation by race and ethnicity, socioeconomic status, and lifestyle risk factors. We examined associations of particulate matter (PM) and other markers of traffic-related air pollution with circulating levels of C-reactive protein (CRP), a biomarker of systemic inflammation. CRP was measured from blood samples obtained in 1994-2016 from 7,860 California residents participating in the Multiethnic Cohort (MEC) Study. Exposure to PM (aerodynamic diameter ≤2.5 µm [PM2.5], ≤10 µm [PM10], and between 2.5 and 10 µm [PM10-2.5]), nitrogen oxides (NOx, including nitrogen dioxide [NO2]), carbon monoxide (CO), ground-level ozone (O3), and benzene averaged over one or twelve months before blood draw were estimated based on participants' addresses. Percent change in geometric mean CRP levels and 95% confidence intervals (CI) per standard concentration increase of each pollutant were estimated using multivariable generalized linear regression. Among 4,305 females (55%) and 3,555 males (45%) (mean age 68.1 [SD 7.5] years at blood draw), CRP levels increased with 12-month exposure to PM10 (11.0%, 95% CI: 4.2%, 18.2% per 10 µg/m3), PM10-2.5 (12.4%, 95% CI: 1.4%, 24.5% per 10 µg/m3), NOx (10.4%, 95% CI: 2.2%, 19.2% per 50 ppb), and benzene (2.9%, 95% CI: 1.1%, 4.6% per 1 ppb). In subgroup analyses, these associations were observed in Latino participants, those who lived in low socioeconomic neighborhoods, overweight or obese participants, and never or former smokers. No consistent patterns were found for 1-month pollutant exposures. This investigation identified associations of primarily traffic-related air pollutants, including PM, NOx, and benzene, with CRP in a multiethnic population. The diversity of the MEC across demographic, socioeconomic, and lifestyle factors allowed us to explore the generalizability of the effects of air pollution on inflammation across subgroups.

Glutathione-S-transferase M1 regulation of diesel exhaust particle-induced pro-inflammatory mediator expression in normal human bronchial epithelial cells.

BACKGROUND: Diesel exhaust particles (DEP) contribute substantially to ambient particulate matter (PM) air pollution in urban areas. Inhalation of PM has been associated with increased incidence of lung disease in susceptible populations. We have demonstrated that the glutathione S-transferase M1 (GSTM1) null genotype could aggravate DEP-induced airway inflammation in human subjects. Given the critical role airway epithelial cells play in the pathogenesis of airway inflammation, we established the GSTM1 deficiency condition in primary bronchial epithelial cells from human volunteers with GSTM1 sufficient genotype (GSTM1+) using GSTM1 shRNA to determine whether GSTM1 deficiency could exaggerate DEP-induced expression of interleukin-8 (IL-8) and IL-1ß proteins. Furthermore, the mechanisms underlying GSTM1 regulation of DEP-induced IL-8 and IL-1ß expression were also investigated. METHODS: IL-8 and IL-1ß protein levels were measured using enzyme-linked immunosorbent assay. GSTM1 deficiency in primary human bronchial epithelial cells was achieved using lentiviral GSTM1 shRNA particles and verified using real-time polymerase chain reaction and immunoblotting. Intracellular reactive oxygen species (ROS) production was evaluated using flow cytometry. Phosphorylation of protein kinases was detected using immunoblotting. RESULTS: Exposure of primary human bronchial epithelial cells (GSTM1+) to 25-100 µg/ml DEP for 24 h significantly increased IL-8 and IL-1ß protein expression. Knockdown of GSTM1 in these cells further elevated DEP-induced IL-8 and IL-1ß expression, implying that GSTM1 deficiency aggravated DEP-induced pro-inflammatory response. DEP stimulation induced the phosphorylation of extracellular signal-regulated kinase (ERK) and Akt, the downstream kinase of phosphoinositide 3-kinase (PI3K), in GSTM1+ bronchial epithelial cells. Pharmacological inhibition of ERK kinase and PI3K activity blocked DEP-induced IL-8 and IL-1ß expression. DEP-induced ERK and Akt phosphorylation could be increased by GSTM1 knockdown. In addition, pretreatment of HBEC with the antioxidant N-acetyl cysteine significantly inhibited DEP-induced ERK and Akt phosphorylation, and subsequent IL-8 and IL-1ß expression. CONCLUSION: GSTM1 regulates DEP-induced IL-8 and IL-1ß expression in primary human bronchial epithelial cells by modulation of ROS, ERK and Akt signaling.

Ultrafine particle size distributions near freeways: Effects of differing wind directions on exposure.

High ambient ultrafine particle (UFP) concentrations may play an important role in the adverse health effects associated with living near busy roadways. However, UFP size distributions change rapidly as vehicle emissions dilute and age. These size changes can influence UFP lung deposition rates and dose because deposition in the respiratory system is a strong function of particle size. Few studies to date have measured and characterized changes in near-road UFP size distributions in real-time, thus missing transient variations in size distribution due to short-term fluctuations in wind speed, direction, or particle dynamics. In this study we measured important wind direction effects on near-freeway UFP size distributions and gradients using a mobile platform with 5-s time resolution. Compared to more commonly measured perpendicular (downwind) conditions, parallel wind conditions appeared to promote formation of broader and larger size distributions of roughly one-half the particle concentration. Particles during more parallel wind conditions also changed less in size with downwind distance and the fraction of lung-deposited particle number was calculated to be 15% lower than for downwind conditions, giving a combined decrease of about 60%. In addition, a multivariate analysis of several variables found meteorology, particularly wind direction and temperature, to be important in predicting UFP concentrations within 150 m of a freeway (R2 = 0.46, p = 0.014).

Observation of Elevated Air Pollutant Concentrations in a Residential Neighborhood of Los Angeles California Using a Mobile Platform.

We observed elevated air pollutant concentrations, especially of ultrafine particles (UFP), black carbon (BC) and NO, across the residential neighborhood of the Boyle Heights Community (BH) of Los Angeles, California. Using an electric vehicle mobile platform equipped with fast response instruments, real-time air pollutant concentrations were measured in BH in spring and summer of 2008. Pollutant concentrations varied significantly in the two seasons, on different days, and by time of day, with an overall average UFP concentration in the residential areas of ~33 000 cm-3. The averaged UFP, BC, and NO concentrations measured on Soto St, a major surface street in BH, were 57 000 cm-3, 5.1 µg m-3, and 67 ppb, respectively. Concentrations of UFP across the residential areas in BH were nearly uniform spatially, in contrast to other areas in the greater metropolitan area of Los Angeles where UFP concentrations exhibit strong gradients downwind of roadways. We attribute this "UFP cloud" to high traffic volumes, including heavy duty diesel trucks on the freeways which surround and traverse BH, and substantial numbers of high-emitting vehicles (HEVs) on the surface streets traversing BH. Additionally, the high density of stop signs and lights and short block lengths, requiring frequent accelerations of vehicles, may contribute. The data also support a role for photochemical production of UFP in the afternoon. UFP concentration peaks (5 s average) of up to 9 million particles cm-3 were also observed immediately behind HEVs when they accelerated from stop lights in the BH neighborhood and areas immediately adjacent. Although encounters with HEV during mornings accounted for only about 6% and 17% of time spent monitoring residential areas and major surface streets, HEV contributed to about 28% and 53% of total ultrafine particles measured on the route, respectively. The observation of elevated pollutant number concentrations across the Boyle Heights community highlights how multiple factors combine to create high pollutant levels, and has important human exposure assessment implications, including the potential utility of our data as inputs to epidemiological studies.