SciCombinator

Discover the most talked about and latest scientific content & concepts.

Journal: Atmospheric environment (Oxford, England : 1994)

0

Commuting in automobiles can contribute substantially to total traffic-related air pollution (TRAP) exposure, yet measuring commuting exposures for studies of health outcomes remains challenging. To estimate real-world TRAP exposures, we developed and evaluated the robustness of a scripted drive protocol on the NJ Turnpike and local roads between April 2007 and October 2014. Study participants were driven in a car with closed windows and open vents during morning rush hours on 190 days. Real-time measurements of PM2.5, PNC, CO, and BC, and integrated samples of NO2, were made in the car cabin. Exposure measures included in-vehicle concentrations on the NJ Turnpike and local roads and the differences and ratios of these concentrations. Median in-cabin concentrations were 11 μg/m(3) PM2.5, 40 000 particles/cm(3), 0.3 ppm CO, 4 μg/m(3) BC, and 20.6 ppb NO2. In-cabin concentrations on the NJ Turnpike were higher than in-cabin concentrations on local roads by a factor of 1.4 for PM2.5, 3.5 for PNC, 1.0 for CO, and 4 for BC. Median concentrations of NO2 for full rides were 2.4 times higher than ambient concentrations. Results were generally robust relative to season, traffic congestion, ventilation setting, and study year, except for PNC and PM2.5, which had secular and seasonal trends. Ratios of concentrations were more stable than differences or absolute concentrations. Scripted drives can be used for generating reasonably consistent in-cabin increments of exposure to traffic-related air pollution.

Concepts: Pollution, New Jersey, Air pollution, Automobile, Parts-per notation, Rush hour, Toll road, New Jersey Turnpike

0

Mobile monitoring has provided a means for broad spatial measurements of air pollutants that are otherwise impractical to measure with multiple fixed site sampling strategies. However, the larger the mobile monitoring route the less temporally dense measurements become, which may limit the usefulness of short-term mobile monitoring for applications that require long-term averages. To investigate the stationarity of short-term mobile monitoring measurements, we calculated long term medians derived from a mobile monitoring campaign that also employed 2-week integrated passive sampler detectors (PSD) for NOx, Ozone, and nine volatile organic compounds at 43 intersections distributed across the entire city of Baltimore, MD. This is one of the largest mobile monitoring campaigns in terms of spatial extent undertaken at this time. The mobile platform made repeat measurements every third day at each intersection for 6-10 minutes at a resolution of 10 s. In two-week periods in both summer and winter seasons, each site was visited 3-4 times, and a temporal adjustment was applied to each dataset. We present the correlations between eight species measured using mobile monitoring and the 2-week PSD data and observe correlations between mobile NOx measurements and PSD NOx measurements in both summer and winter (Pearson’s r = 0.84 and 0.48, respectively). The summer season exhibited the strongest correlations between multiple pollutants, whereas the winter had comparatively few statistically significant correlations. In the summer CO was correlated with PSD pentanes (r = 0.81), and PSD NOx was correlated with mobile measurements of black carbon (r = 0.83), two ultrafine particle count measures (r =0.8), and intermodal (1-3 μm) particle counts (r = 0.73). Principal Component Analysis of the combined PSD and mobile monitoring data revealed multipollutant features consistent with light duty vehicle traffic, diesel exhaust and crankcase blow by. These features were more consistent with published source profiles traffic-related air pollutants than features based on the PSD data alone. Short-term mobile monitoring shows promise for capturing long-term spatial patterns of traffic-related air pollution, and is complementary to PSD sampling strategies.

Concepts: Time, Statistics, Spearman's rank correlation coefficient, Pollution, Pearson product-moment correlation coefficient, Term, Smog, Air pollution

0

Indiana Harbor and Ship Canal (IHSC) in East Chicago is an industrial waterway on Lake Michigan and a source of PCBs to Lake Michigan and the overlying air. We hypothesized that IHSC is an important source of airborne PCBs to surrounding communities. We used AERMOD to model hourly PCB concentrations, utilizing emission fluxes from a prior study and hourly meteorology provided by the State of Indiana. We also assessed dispersion using hourly observed meteorology from a local airport and high resolution profiles simulated by the Weather Research and Forecasting model. We found that emissions from IHSC waters contributed about 15% of the observed ΣPCB concentrations close to IHSC when compared on an hourly basis and about 10% of observed annual concentrations at a nearby school. Concentrations at the school due to emissions from IHSC ranged from 0 to 18,000 pg m(-3), up to 20 times higher than observed background levels, with an annual geometric mean (GSD) of 19 (31) pg m(-3). Our findings indicate that IHSC is an important source of PCBs to East Chicago, but not the only source. Four observed enriched PCB3 samples suggest a nearby non-Aroclor source.

Concepts: Canal, Michigan, Illinois, Chicago, Lake Michigan, Indiana, Northwest Indiana, South Shore Line

0

It has been well documented that air pollution adversely affects health, and epidemiological pollution-health studies utilise pollution data from automatic monitors. However, these automatic monitors are small in number and hence spatially sparse, which does not allow an accurate representation of the spatial variation in pollution concentrations required for these epidemiological health studies. Nitrogen dioxide (NO2) diffusion tubes are also used to measure concentrations, and due to their lower cost compared to automatic monitors are much more prevalent. However, even combining both data sets still does not provide sufficient spatial coverage of NO2 for epidemiological studies, and modelled concentrations on a regular grid from atmospheric dispersion models are also available. This paper proposes the first modelling approach to using all three sources of NO2 data to make fine scale spatial predictions for use in epidemiological health studies. We propose a geostatistical fusion model that regresses combined NO2 concentrations from both automatic monitors and diffusion tubes against modelled NO2 concentrations from an atmospheric dispersion model in order to predict fine scale NO2 concentrations across our West Central Scotland study region. Our model exhibits a 47% improvement in fine scale spatial prediction of NO2 compared to using the automatic monitors alone, and we use it to predict NO2 concentrations across West Central Scotland in 2006.

Concepts: Scientific method, Epidemiology, Prediction, Futurology, Air pollution, Nitrogen dioxide, Atmospheric dispersion modeling, Central Belt

0

Few studies examine urban air pollution in sub-Saharan Africa (SSA), yet urbanization rates there are among the highest in the world. In this study, we measured 8-hr average occupational exposure levels of fine particulate matter (PM2.5), black carbon (BC), ultra violet active-particulate matter (UV-PM), and trace elements for individuals who worked along roadways in Nairobi, specifically bus drivers, garage workers, street vendors, and women who worked inside informal settlements. We found BC and re-suspended dust were important contributors to PM2.5 levels for all study populations, particularly among bus drivers, while PM2.5 exposure levels for garage workers, street vendors, and informal settlement residents were not statistically different from each other. We also found a strong signal for biomass emissions and trash burning, which is common in Nairobi’s low-income areas and open-air garages. These results suggest that the large portion of urban residents in SSA who walk along roadways would benefit from air quality regulations targeting roadway emissions from diesel vehicles, dust, and trash burning. This is the first study to measure occupational exposure to urban air pollution in SSA and results imply that roadway emissions are a serious public health concern.

Concepts: Africa, Poverty, United States Environmental Protection Agency, Particulate, Smog, Air pollution, Dust, Soot

0

This study was carried out to characterize three aldehydes of health concern (formaldehyde, acetaldehyde, and acrolein) at a central Beijing site in the summer and early fall of 2008 (from June to October). Aldehydes in polluted atmospheres come from both primary and secondary sources, which limits the control strategies for these reactive compounds. Measurements were made before, during, and after the Beijing Olympics to examine whether the dramatic air pollution control measures implemented during the Olympics had an impact on concentrations of the three aldehydes and their underlying primary and secondary sources. Average concentrations of formaldehyde, acetaldehyde and acrolein were 29.3±15.1 μg/m(3), 27.1±15.7 μg/m(3) and 2.3±1.0 μg/m(3), respectively, for the entire period of measurements, all being at the high end of concentration ranges measured in cities around the world in photochemical smog seasons. Formaldehyde and acrolein increased during the pollution control period compared to the pre-Olympic Games, followed the changing pattern of temperature, and were significantly correlated with ozone and with a secondary formation factor identified by principal component analysis (PCA). In contrast, acetaldehyde had a reduction in mean concentration during the Olympic air pollution control period compared to the pre-Olympic period and was significantly correlated with several pollutants emitted from local emission sources (e.g., NO2, CO, and PM2.5). Acetaldehyde was also more strongly associated with primary emission sources including vegetative burning and oil combustion factors identified through the PCA. All three aldehydes were lower during the post-Olympic sampling period compared to the before and during Olympic periods, likely due to seasonal and regional effects. Our findings point to the complexity of source control strategies for secondary pollutants.

Concepts: Olympic Games, People's Republic of China, Pollution, Smog, Air pollution, Summer Olympic Games, 2008 Summer Olympics, Athens

0

Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates.

Concepts: Pollution, Smog, Environmentalism, National Ambient Air Quality Standards, Air pollution, Air Quality Index, Air dispersion modeling, Atmospheric dispersion modeling

0

In summer 2012, a landfill liner comprising an estimated 1.3 million shredded tires burned in Iowa City, Iowa. During the fire, continuous monitoring and laboratory measurements were used to characterize the gaseous and particulate emissions and to provide new insights into the qualitative nature of the smoke and the quantity of pollutants emitted. Significant enrichments in ambient concentrations of CO, CO2, SO2, particle number (PN), fine particulate (PM2.5) mass, elemental carbon (EC), and polycyclic aromatic hydrocarbons (PAH) were observed. For the first time, PM2.5 from tire combustion was shown to contain PAH with nitrogen heteroatoms (a.k.a. azaarenes) and picene, a compound previously suggested to be unique to coal-burning. Despite prior laboratory studies' findings, metals used in manufacturing tires (i.e. Zn, Pb, Fe) were not detected in coarse particulate matter (PM10) at a distance of 4.2 km downwind. Ambient measurements were used to derive the first in situ fuel-based emission factors (EF) for the uncontrolled open burning of tires, revealing substantial emissions of SO2 (7.1 g kg(-1)), particle number (3.5×10(16) kg(-1)), PM2.5 (5.3 g kg(-1)), EC (2.37 g kg(-1)), and 19 individual PAH (totaling 56 mg kg(-1)). A large degree of variability was observed in day-to-day EF, reflecting a range of flaming and smoldering conditions of the large-scale fire, for which the modified combustion efficiency ranged from 0.85-0.98. Recommendations for future research on this under-characterized source are also provided.

Concepts: Carbon dioxide, Polycyclic aromatic hydrocarbon, United States Environmental Protection Agency, Particulate, Smog, Sulfuric acid, Air pollution, Volcano

0

Allergenic pollen is one of the main triggers of Allergic Airway Disease (AAD) affecting 5% to 30% of the population in industrialized countries. A modeling framework has been developed using correlation and collinearity analyses, simulated annealing, and stepwise regression based on nationwide observations of airborne pollen counts and climatic factors to predict the onsets and durations of allergenic pollen seasons of representative trees, weeds and grass in the contiguous United States. Main factors considered are monthly, seasonal and annual mean temperatures and accumulative precipitations, latitude, elevation, Growing Degree Day (GDD), Frost Free Day (FFD), Start Date (SD) and Season Length (SL) in the previous year. The estimated mean SD and SL for birch (Betula), oak (Quercus), ragweed (Ambrosia), mugwort (Artemisia) and grass (Poaceae) pollen season in 1994-2010 are mostly within 0 to 6 days of the corresponding observations for the majority of the National Allergy Bureau (NAB) monitoring stations across the contiguous US. The simulated spatially resolved maps for onset and duration of allergenic pollen season in the contiguous US are consistent with the long term observations.

Concepts: Asthma, United States, Allergy, Developed country, United Kingdom, Birch, Pollen, Ragweed

0

Annual average daily particle number concentrations around a highway were estimated with an atmospheric dispersion model and a land use regression model. The dispersion model was used to estimate particle concentrations along Interstate 10 at 98 locations within El Paso, Texas. This model employed annual averaged wind speed and annual average daily traffic counts as inputs. A land use regression model with vehicle kilometers traveled as the predictor variable was used to estimate local background concentrations away from the highway to adjust the near-highway concentration estimates. Estimated particle number concentrations ranged between 9.8 × 10(3) particles/cc and 1.3 × 10(5) particles/cc, and averaged 2.5 × 10(4) particles/cc (SE 421.0). Estimates were compared against values measured at seven sites located along I10 throughout the region. The average fractional error was 6% and ranged between -1% and -13% across sites. The largest bias of -13% was observed at a semi-rural site where traffic was lowest. The average bias amongst urban sites was 5%. The accuracy of the estimates depended primarily on the emission factor and the adjustment to local background conditions. An emission factor of 1.63 × 10(14) particles/veh-km was based on a value proposed in the literature and adjusted with local measurements. The integration of the two modeling techniques ensured that the particle number concentrations estimates captured the impact of traffic along both the highway and arterial roadways. The performance and economical aspects of the two modeling techniques used in this study shows that producing particle concentration surfaces along major roadways would be feasible in urban regions where traffic and meteorological data are readily available.

Concepts: Statistics, Mathematics, Air pollution, Freeway, Air dispersion modeling, Atmospheric dispersion modeling, Arterial road, Interstate Highway System