Design of Monitor Networks to Meet Multiple Criteria

For most monitoring networks, demonstration of compliance with ambient air quality standards is only one of many interrelated purposes served. The network also may be needed (1) to assess current air quality, (2) to assess regional background air quality, (3) to determine individual source “culpability,” (4) to validate or calibrate a particular dispersion model, (5) to assess effectiveness of a control strategy, or (6) to determine the risk of damage to certain critical or sensitive receptors. Monitoring to support compliance with Prevention of Significant Deterioration regulations is now also an important issue for many new sources. The same network may have to perform many of these functions for several pollutants that have different source locations and different characteristic averaging times. This paper presents a method for systematically addressing each of these concerns. The method includes use of a statistical computer model, MONITOR. This model provides quantitative estimates of relative probabilities in order to assess whether a particular network design will meet each of these criteria. A sample application of the method is provided.     

Temporal Variations of PM2.5, PM10, and Gaseous Precursors during the 1995 Integrated Monitoring Study in Central California

ABSTRACT

The spatial and temporal distributions of particle mass and its chemical constituents are essential for understanding the source-receptor relationships as well as the chemical, physical, and meteorological processes that result in elevated particulate concentrations in California’s San Joaquin Valley (SJV). Fine particulate matter ₍PM_2.5), coarse particulate matter (PM₁₀), and aerosol precursor gases were sampled on a 3-hr time base at two urban (Bakersfield and Fresno) and two non-urban (Kern Wildlife Refuge and Chowchilla) core sites in the SJV during the winter of 1995–1996.

Day-to-day variations of PM_2.5 and PM₁₀ and their chemical constituents were influenced by the synoptic-scale meteorology and were coherent among the four core sites. Under non-rainy conditions, similar diurnal variations of PM_2.5 and coarse aerosol were found at the two urban sites, with concentrations peaking during the nighttime hours. Conversely, PM_2.5 and coarse aerosol peaked during the morning and afternoon hours at the two non-urban sites. Under rainy and foggy conditions, these diurnal patterns were absent or greatly suppressed.

In the urban areas, elevated concentrations of primary pollutants (e.g., organic and elemental carbons) during the late afternoon and nighttime hours reflected the impact from residential wood combustion and motor vehicle exhaust. During the daytime, these concentrations decreased as the mixed layer deepened. Increases of secondary nitrate and sulfate concentrations were found during the daylight hours as a result of photochemical reactions. At the non-urban sites, the same increases in secondary aerosol concentrations occurred during the daylight hours but with a discernable lag time. Concentrations of the primary pollutants also increased at the non-urban sites during the daytime. These observations are attributed to mixing aloft of primary aerosols and secondary precursor gases in urban areas followed by rapid transport aloft to non-urban areas coupled with photochemical conversion.     

Methane emissions from 20 landfills across the United States using vertical radial plume mapping

Landfill fugitive methane emissions were quantified as a function of climate type and cover type at 20 landfills using U.S. Environmental Protection Agency (EPA) Other Test Method (OTM)-10 vertical radial plume mapping (VRPM) with tunable diode lasers (TDLs). The VRPM data were initially collected as g CH₄/sec emission rates and subsequently converted to g CH₄/m²/day rates using two recently published approaches. The first was based upon field tracer releases of methane or acetylene and multiple linear regression analysis (MLRM). The second was a virtual computer model that was based upon the Industrial Source Complex (ISC3) and Pasquill plume stability class models (PSCMs). Calculated emission results in g CH₄/m²/day for each measured VRPM with the two approaches agreed well (r ² = 0.93). The VRPM data were obtained from the working face, temporary soil, intermediate soil, and final soil or synthetic covers. The data show that methane emissions to the atmosphere are a function of climate and cover type. Humid subtropical climates exhibited the highest emissions for all cover types at 207, 127, 102, and 32 g CH₄/m²/day, for working face (no cover), temporary, intermediate, and final cover, respectively. Humid continental warm summers showed 67, 51, and 27 g CH₄/m²/day for temporary, intermediate, and final covers. Humid continental cool summers were 135, 40, and 26 g CH₄/m²/day for the working face, intermediate, and final covers. Mediterranean climates were examined for intermediate and final covers only and found to be 11 and 6 g CH₄/m²/day, respectively, whereas semiarid climates showed 85, 11, 3.7, and 2.7 g CH₄/m²/day for working face, temporary, intermediate, and final covers. A closed, synthetically capped landfill covered with soil and vegetation with a gas collection system in a humid continental warm summer climate gave mostly background methane readings and average emission rates of only 0.09 g CH₄/m²/day flux when measurable.

Implications The OTM-10 method is being proposed by EPA to quantify surface methane emissions from landfill covers. This study of 20 landfills across the United States was done to determine the efficacy of using OTM-10 for this purpose. Two recently published models were used to evaluate the methane flux results found with VRPM optical remote sensing. The results should provide a sense of the practicality of the method, its limitations at landfills, and the impact of climate upon the cover's methane flux. Measured field data may assist landfill owners in refining previously modeled methane emission factor default values.     

A Review of the Role of Temperate Forests in the Global CO2 Balance

The role of temperate forests in the global carbon balance is difficult to determine because many uncertainties exist in the data, and many assumptions must be made in these determinations. Still, there is little doubt that increases in atmospheric CO₂ and global warming would have major effects on temperate forest ecosystems. Increases in atmospheric CO₂ may result in increases in photosynthesis, changes in water and nitrogen use efficiency, and changes in carbon allocation. Indirect effects of changes in global carbon balance on regional climate and on microenvironmental conditions, particularly temperature and moisture, may be more important than direct effects of increased CO₂ on vegetation. Increased incidence of forest perturbations might also be expected. The evidence suggests that conditions favorable to forest growth and development may exist in the northern latitudes, while southern latitude forests may undergo drought stress. Current harvest of temperate and world forests contributes substantial amounts of carbon to the atmosphere, possibly as much as 3 gigatons (Gt) per year. Return of this carbon to forest storage may require decades. Forest managers should be aware of the global as well as local impact their management decisions will have on the atmospheric carbon balance of the ecosystems they oversee.     

Active density-dependent habitat selection in a controlled population of small mammals

Density-dependent habitat selection has numerous and far-reaching implications to population dynamics and evolutionary processes. Although several studies suggest that organisms choose and occupy high-quality habitats over poorer ones, definitive experiments demonstrating active selection, by the same individuals at the appropriate population scale, are lacking. We conducted a reciprocal food supplementation experiment to assess whether voles would first occupy a habitat receiving extra food, then change their preference to track food supplements moved to another habitat. Meadow voles, as predicted, were more abundant in food-supplemented habitat than in others. Density declined when food supplements ceased because the voles moved to the new habitat receiving extra food. Although males and females appeared to follow different strategies, meadow-vole densities reflected habitat quality because voles actively selected the best habitat available. It is thus clear that behavioral decisions on habitat use can motivate patterns of abundance, frequency, and gene flow that have widespread effects on subsequent evolution.     

Estimating population impacts via dynamic occupancy analysis of Before-After Control-Impact studies

Estimating environmental impacts on populations is one of the main goals of wildlife monitoring programs, which are often conducted in conjunction with management actions or following natural disturbances. In this study we investigate the statistical power of dynamic occupancy models to detect changes in local survival and colonization from detection-nondetection data, while accounting for imperfect detection probability, in a Before-After Control-Impact (BACI) framework. We simulated impacts on local survival and/or detection probabilities, and asked questions related to: (1) costs and benefits of different analysis models, (2) confounding changes in detection with changes in local survival, (3) sampling design trade-offs, and (4) species with low vs. high rates of turnover. Estimating seasonal effects on local survival and colonization, as opposed to estimating Before-After effects, had little effect on the power to detect changes in local survival. Estimating a parameter that accounted for pretreatment differences in local survival between Control and Impact sites decreased power by 50%, but it was critical to include when such differences existed. When the experimental treatment had a negative impact on species detectability but analysis assumed constant detection, the Type I error rates were dramatically inflated (0.20 0.33). In general, there was low power (< 0.5) to detect a 50% decrease in local survival for all combinations of sites (N = 50 vs. 100), seasons sampled (8 vs. 12), and visits per site per season (4 vs. 6). Unbalanced designs performed worse than balanced designs, with the exception of the case of treatments being implemented in different seasons at different sites. Adding more control sites improved the ability to detect changes in local survival. Surveying more seasons after impact resulted in modest power gains, but at least three seasons before impact were required to successfully implement BACI occupancy studies. Turnover rates had a low impact on power. Occupancy studies conducted in a BACI design offer the opportunity to detect environmental impacts on wildlife populations without the costs of intensive studies. However, given the low power to detect small changes (20%) in local survival, these studies should be used when researchers are confident that major treatment impacts will occur or very large sample sizes are obtainable.