Methodology for Siting Ambient Air Monitors at the Neighborhood Scale

Abstract

In siting a monitor to measure compliance with U.S. National Ambient Air Quality Standards (NAAQS) for par-ticulate matter (PM), there is a need to characterize variations in PM concentration within a neighborhood-scale region to achieve monitor siting objectives. A simple methodology is provided here for the selection of a neighborhood-scale site for meeting either of the two objectives identified for PM monitoring. This methodology is based on analyzing middle-scale (from 100 to 500 m) data from within the area of interest. The required data can be obtained from widely available dispersion models and emissions databases.

The performance of the siting methodology was evaluated in a neighborhood-scale field study conducted in Hudson County, NJ, to characterize the area’s inhalable particulate (PM₁₀) concentrations. Air monitors were located within a 2- by 2-km area in the vicinity of the Lincoln Tunnel entrance in Hudson County. Results indicate the siting methodology performed well, providing a positive relationship between the predicted concentration rank at each site and the actual rank experienced during the field study. Also discussed are factors that adversely affected the predictive capabilities of the model.     

Modeling and Spatially Distributing Forest Net Primary Production at the Regional Scale

Abstract

Forest, agricultural, rangeland, wetland, and urban landscapes have different rates of carbon sequestration and total carbon sequestration potential under alternative management options. Changes in the proportion and spatial distribution of land use could enhance or degrade that area’s ability to sequester carbon in terrestrial ecosystems. As the ecosystems within a landscape change due to natural or anthropogenic processes, they may go from being a carbon sink to a carbon source or vice versa. Satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of terrestrial carbon. The coupling of Landsat Thematic Mapper (TM) data with a physiologically based forest productivity model (PnET-II) and historic climatic data provides an opportunity to enhance field plot-based forest inventory and monitoring methodologies. We use periodic forest inventory data from the U.S. Department of Agriculture (USDA) Forest Service’s Forest Inventory and Analysis (FIA) Program to obtain estimates of forest area and type and to generate estimates of carbon storage for evergreen, deciduous, and mixed-forest classes. The area information is used in an accuracy assessment of remotely sensed forest cover at the regional scale. The map display of modeled net primary production (NPP) shows a range of forest carbon storage potentials and their spatial relationship to other landscape features across the southern United States. This methodology addresses the potential for measuring and projecting forest carbon sequestration in the terrestrial biosphere of the southern United States.     

Biofiltration of Trichloroethylene-Contaminated Air: A Pilot Study

Abstract

This project demonstrated the biofiltration of a trichloroethylene (TCE)-contaminated airstream generated by air stripping groundwater obtained from several wells located at the Anniston Army Depot, Anniston, AL. The effects of several critical process variables were investigated to evaluate technical and economic feasibility, define operating limits and preferred operating conditions, and develop design information for a full-scale biofilter system. Long-term operation of the demonstration biofilter system was conducted to evaluate the performance and reliability of the system under variable weather conditions. Propane was used as the primary substrate necessary to induce the production of a nonspecific oxygenase. Results indicated that the process scheme used to introduce propane into the biofiltration system had a significant impact on the observed TCE removal efficiency. TCE degradation rates were dependent on the inlet contaminant concentration as well as on the loading rate. No microbial inhibition was observed at inlet TCE concentrations as high as 87 parts per million on a volume basis.     

Source Apportionment of Phoenix PM2.5 Aerosol with the Unmix Receptor Model

Abstract

The multivariate receptor model Unmix has been used to analyze a 3-yr PM_2.5 ambient aerosol data set collected in Phoenix, AZ, beginning in 1995. The analysis generated source profiles and overall average percentage source contribution estimates (SCEs) for five source categories: gasoline engines (33 ± 4%), diesel engines (16 ± 2%), secondary SO₄ ^2? (19 ± 2%), crustal/soil (22 ± 2%), and vegetative burning (10 ± 2%). The Unmix analysis was supplemented with scanning electron microscopy (SEM) of a limited number of filter samples for information on possible additional low-strength sources. Except for the diesel engine source category, the Unmix SCEs were generally consistent with an earlier multivariate receptor analysis of essentially the same data using the Positive Matrix Factorization (PMF) model. This article provides the first demonstration for an urban area of the capability of the Unmix receptor model.     

Potential Interference Bias in Ozone Standard Compliance Monitoring

Abstract

The U.S. Environmental Protection Agency has established a federal reference method (FRM) for ozone (O₃) and allowed for designation of federal equivalent methods (FEMs). However, the ethylene‐chemiluminescence FRM for O₃ has been replaced by the UV photometric FEM by most state and local monitoring agencies because of its relative ease of operation. Accumulating evidence indicates that the FEM is prone to bias under the hot, humid, and stagnant conditions conducive to high O₃ formation. This bias may lead to overreporting hourly O₃ concentrations by as much as 20–40 ppb. Measurement bias is caused by contamination of the O₃ scrubber, a problem that is not detected by dry air calibration. An adequate wet test has not been codified, although a procedure has been proposed for agency consideration. This paper includes documentation of laboratory tests quantifying specific interferant responses, collocated ambient FRM/FEM monitoring results, and smog chamber comparisons of the FRM and FEMs with alternative scrubber designs. As the numbers of reports on monitor interferences have grown, interested parties have called for agency recognition and correction of these biases.     

Air Quality in Selected Megacities

Abstract

About half of the world's population now lives in urban areas because of the opportunity for a better quality of life. Many of these urban centers are expanding rapidly, leading to the growth of megacities, which are often defined as metropolitan areas with populations exceeding 10 million inhabitants. These concentrations of people and activity are exerting increasing stress on the natural environment, with impacts at urban, regional and global levels. In recent decades, air pollution has become one of the most important problems of megacities. Initially, the main air pollutants of concern were sulfur compounds, which were generated mostly by burning coal. Today, photochemical smog—induced primarily from traffic, but also from industrial activities, power generation, and solvents—has become the main source of concern for air quality, while sulfur is still a major problem in many cities of the developing world. Air pollution has serious impacts on public health, causes urban and regional haze, and has the potential to contribute significantly to global climate change. Yet, with appropriate planning megacities can efficiently address their air quality problems through measures such as application of new emission control technologies and development of mass transit systems.

This review is focused on nine urban centers, chosen as case studies to assess air quality from distinct perspectives: from cities in the industrialized nations to cities in the developing world. This review considers not only megacities, but also urban centers with somewhat smaller populations, for while each city—its problems, resources, and outlook—is unique, the need for a holistic approach to complex environmental problems is the same. There is no single strategy to reduce air pollution in megacities; a mix of policy measures will be needed to improve air quality. Experience shows that strong political will coupled with public dialogue is essential to effectively implement the regulations required to address air quality.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): Overview and Statistical Considerations

Abstract

Average concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5) in Steubenville, OH, have decreased by more than 10 μg/m³ since the landmark Harvard Six Cities Study¹ associated the city’s elevated PM_2.5 concentrations with adverse health effects in the 1980s. Given the promulgation of a new National Ambient Air Quality Standard (NAAQS) for PM_2.5 in 1997, a current assessment of PM_2.5 in the Steubenville region is warranted. The Steubenville Comprehensive Air Monitoring Program (SCAMP) was conducted from 2000 through 2002 to provide such an assessment. The program included both an outdoor ambient air monitoring component and an indoor and personal air sampling component. This paper, which is the first in a series of four that will present results from the outdoor portion of SCAMP, provides an overview of the outdoor ambient air monitoring program and addresses statistical issues, most notably autocorrelation, that have been overlooked by many PM_2.5 data analyses. The average PM_2.5 concentration measured in Steubenville during SCAMP (18.4 μg/m³) was 3.4g/m³ above the annual PM_2.5 NAAQS. On average, sulfate and organic material accounted for ～31% and 25%, respectively, of the total PM_2.5 mass. Local sources contributed an estimated 4.6 μg/m³ to Steubenville’s mean PM_2.5 concentration. PM_2.5 and each of its major ionic components were significantly correlated in space across all pairs of monitoring sites in the region, suggesting the influence of meteorology and long-range transport on regional PM_2.5 concentrations. Statistically significant autocorrelation was observed among time series of PM_2.5 and component data collected at daily and 1-in-4-day frequencies during SCAMP. Results of spatial analyses that accounted for autocorrelation were generally consistent with findings from previous studies that did not consider autocorrelation; however, these analyses also indicated that failure to account for autocorrelation can lead to incorrect conclusions about statistical significance.     

Integrated Assessment Modeling of Atmospheric Pollutants in the Southern Appalachian Mountains. Part I: Hourly and Seasonal Ozone

Abstract

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI’s assessment.     

Estrogenic and androgenic activities in total plasma measured with reporter-gene bioassays: relevant exposure measures for endocrine disruptors in epidemiologic studies?

Measurements of estrogenic and androgenic activities in total plasma with Chemically Activated LUciferase gene eXpression (CALUX?) bioassays could provide biologically relevant measures for exposure to endocrine disruptors in epidemiologic studies. The objective of this study was to explore the effects of a variety of sources of potential endocrine disruptors on estrogenic and androgenic activities in total plasma measured by CALUX?. Plasma samples and interview data on sources of potential endocrine disruptors were collected from 108 men with different exposures profiles. CALUX? measurements (BioDetection Services) involved human U2-OS cell lines controlled by the estrogen receptor alpha and the androgen receptor. Mean differences (beta) in 17β-estradiol equivalents (EEQs) and dihydrotestosterone equivalents (AEQs) between exposure groups were estimated using general linear models. Mean plasma AEQs and EEQs were 9.1×10(-1)ng/ml and 12.0pg/ml, respectively. Elevated AEQs were found in smokers (beta 1.9 (95%CI 0.1-3.6)×10(-1)ng/ml) and heavy drinkers (1.4 (0.2-3.1)×10(-1)ng/ml), and in men occupationally exposed to disinfectants (1.6 (0.3-3.5)×10(-1)ng/ml) or welding/soldering fumes (1.4 (-0.2-2.9)×10(-1)ng/ml). Occupational exposure to pesticides, disinfectants, and exhaust fumes seemed to be associated with increased plasma EEQs: 1.5 (-0.2-3.2)pg/ml, 2.1 (0.2-3.9)pg/ml, and 2.9 (0.6-5.2)pg/ml, respectively. Moderate to high plasma dioxin levels, measured in a subgroup by the dioxin-responsive CALUX?, were accompanied by a 20% increase in AEQs. This is the first study in which CALUX? was used to assess hormone activities in total plasma. Although the results are not yet readily interpretable, they indicate that these measurements can be valuable for epidemiologic studies on endocrine disruptors and give direction for further research.