Atmospheric Factors Influencing Daily Sulfate Concentrations in Chicago Air

Abstract

Confidence interval construction for central tendency is a problem of practical consequence for those who must analyze air contaminant data. Determination of compliance with relevant ambient air quality criteria and assessment of associated health risks depend upon quantifying the uncertainty of estimated mean pollutant concentrations. The bootstrap is a resampling technique that has been steadily gaining popularity and acceptance during the past several years. A potentially powerful application of the bootstrap is the construction of confidence intervals for any parameter of any underlying distribution. Properties of bootstrap confidence intervals were determined for samples generated from lognormal, gamma, and Weibull distributions. Bootstrap t intervals, while having smaller coverage errors than Student's t or other bootstrap methods, under-cover for small samples from skewed distributions. Therefore, we caution against using the bootstrap to construct confidence intervals for the mean without first considering the effects of sample size and skew. When sample sizes are small, one might consider using the median as an estimate of central tendency. Confidence intervals for the median are easy to construct and do not under-cover. Data collected by the Northeast States for Coordinated Air Use Management (NESCAUM) are used to illustrate application of the methods discussed.     

A Comparison of Mass,Lead, Sulfate,and Nitrate Concentrations in a Field Study Using Dichotomous,Size-Selective,and Standard Hi-Vol Samplers

Air monitoring In the San Francisco Bay Area was carried out to measure outdoor community air concentrations of poly cyclic aromatic hydrocarbons (PAH) and mutagenlc activity (mutagenlclty) In participate organic matter (POM). Monitoring began In 1979 and Is currently conducted at six stations. PAH and mutagenlclty tests were performed on organic extracts prepared from high volume (hl-vol) filters composited every four months, by meteorological season. PAH were determined by high pressure liquid chromatography (HPLC) with fluorescence and ultraviolet detection. Mutagenlclty was measured In the Ames Salmonella bloas-say using strain TA98 with and without metabolic activation. The nine-year mean concentration of benzo(a)pyrene (BaP) was 0.4 ng/m³. The mutagenlcfty of this amount of BaP accounted for only about 0.2% of the observed mutagenicity In POM and other measured PAH accounted for even less. Concentrations of PAH and mutagenlclty were three to nine times higher during the winter than during other seasons. Year-to-year wintertime trends In several PAH were also seen. Early In the 1980s, winter concentrations of BaP and benzo (g,h,i)perylene Increased. However since the mld-1980’s, their concentrations have fallen. The decrease In PAH concentrations may be the result of an Increasing proportion of vehicles with relatively low organic emissions. In contrast to PAH, mutagenlcfty did not show significant year-to-year time trends.     

Some Heavy-Metal Pollutants in the Air of Naples

ABSTRACT

In this paper, assumptions regarding future land use as a key uncertainty is considered and its impact on risk analysis for contaminated sites is assessed. Risks are assessed for two land use scenarios (current-use industrial and future-use residential) using probabilistic models that incorporate uncertainty and variability in the exposure parameters. Residual risks are calculated for both industrial and residential cleanup standards. A Superfund site in northern California is considered.

In general, for the unremediated case, the future-use residential scenarios produce larger risks (1 to 3 orders of magnitude) than current- (continued) use industrial scenarios. For the Superfund site studied, the residual risks calculated for the remedy selected was not sufficiently protective of future-use residents in that it did not meet .S. Environmental Protection Agency (EPA) risk goals, but was protective of current-use workers, even though the cleanup criteria were based on residential use. Alternative risk management practices, such as deed restrictions, can be used in such cases.     

Blast Furnace Casthouse Control Technology and Recent Emissions Test Data

By the fall of 1980, three new and seven retrofit casthouse emission control systems had been installed in North America. A number of prototype systems are being evaluated by steel companies and regulatory agencies. By 1981, the U.S. steel industry had made commitments to install controls on at least 58 additional casthouses in the U.S.

This paper describes the current status of casthouse control technology in the U.S. and Canada as of the spring of 1981, addresses future trends, and presents emissions test data collected in 1980 and 1981. Mass emissions and inhalable particulate test results from sampling at DOFASCO’s No. 3 blast furnace casthouse are presented. Roof monitor visible emissions data are also provided to describe performance of installed and demonstration systems including three J&L plants, Wheeling-Pittsburgh and Bethlehem Steel, and Inland’s new furnace.     

Use of Energy Scenarios in Addressing the CO2 Question

A reference scenario for CO₂ emissions was developed using a model of world energy supply and demand. In the reference scenario, world GNP and world energy demand increase at average rates of 2.1 percent per year and 1.5 percent per year, respectively during the period 1975-2100. The corresponding annual CO₂ emissions rise to a maximum of 16 gigatons of carbon around 2050 and then decline as a result of a transition to nonfossil fuel energy systems. A modified scenario for high CO₂ emissions was obtained by assuming an abundant supply of low cost coal, thus eliminating the transition. A low case was developed in which the low cost of alternative energy (i.e., solar, nuclear) induces an earlier shift away from fossil fuels.

Annual emissions of the three scenarios were used as input to a global carbon cycle model and the CO₂ buildup in the atmosphere during the period 1980-2100 was determined by the model. All three scenarios showed continuous rises in atmospheric CO₂ concentration. The reference scenario reached 775 ppm by 2100. The high CO₂ case resulted in concentrations of over 1040 ppm, and for the low case the 2100 concentration was just under 700 ppm. If the climate theory is correct, even 700 ppm is sufficient to give significant climate warming, but by experiencing the change gradually over a century, adaptation may not be painful. An early transition to nonfossil fuel supplies makes the problem less severe but does not eliminate it.     

A Pilot Indoor-Outdoor Study of Organic Particulate Matter and Particulate Mutagenicity

Abstract

Many large metropolitan areas experience elevated concentrations of ground-level ozone pollution during the summertime “smog season”. Local environmental or health agencies often need to make daily air pollution forecasts for public advisories and for input into decisions regarding abatement measures and air quality management. Such forecasts are usually based on statistical relationships between weather conditions and ambient air pollution concentrations. Multivariate linear regression models have been widely used for this purpose, and well-specified regressions can provide reasonable results. However, pollution-weather relationships are typically complex and nonlinear—especially for ozone—properties that might be better captured by neural networks. This study investigates the potential for using neural networks to forecast ozone pollution, as compared to traditional regression models. Multiple regression models and neural networks are examined for a range of cities under different climate and ozone regimes, enabling a comparative study of the two approaches. Model comparison statistics indicate that neural network techniques are somewhat (but not dramatically) better than regression models for daily ozone prediction, and that all types of models are sensitive to different weather-ozone regimes and the role of persistence in aiding predictions.     

KAPPA-G,A Non-Gaussian Plume Dispersion Model: Description and Evaluation Against Tracer Measurements

This paper presents a mixed methodology for the simulation of atmospheric disperson phenomena in which vertical diffusion is computed using an analytical solution of the K-theory equation, while horizontal diffusion is simulated by the Gaussian formula. This new formulation, while maintaining a simple analytical form for the concentration field, incorporates the effects of power-law vertical profiles of both wind speed and eddy diffusivity. The performance of this approach, which has been implemented into a full computer package (KAPPA-G), is evaluated by comparison with data from SF₆ tracer experiments.