Formaldehyde Release from Simulated Wall Panels Insulated with Urea-Formaldehyde Foam Insulation

An important potential source of formaldehyde in the home is ureaformaldehyde foam insulation (UFFI). This study measures the long-term release of formaldehyde through the interior wall of test panels foamed with commercial urea-formaldehyde insulation. The measurements, made approximately 16 mo after initial foaming, were conducted under both static and dynamic air conditions with air flow selected to simulate a typical air exchange found in houses. Estimated room concentrations based on a simple model of uniform mixing within a room and measured emission rates are presented. Measurements of formaldehyde in the air from within the UFFI cavities are also reported.     

R&D Activities,Operating Experience Discussed at Fabric Alternatives Forum

ABSTRACT

Previously reported volatile organic compounds (VOC) radiocarbon (¹⁴C) measurements for 1992 summertime Atlanta, GA, have been compared with chromatographic data and emissions inventory predictions. The chromatographic approach that was used provided a more comprehensive VOC characterization than typically achieved, and the emissions inventory was research-grade level (date-, site-, and time-specific). The comparisons are in general agreement that biogenic emissions contribute only modestly (<10%) to the VOC content of the particular ambient samples that were collected and measured. The choices of sampling site (near city-center) and times (early morning and late evening) are major influences on the results, which consequently should not be regarded as representing the average VOC biogenic impact for the Atlanta area.     

An Evaluation of the Semi-VOST Method for Determining Emissions from Hazardous Waste Incinerators

The Semi-Volatile Organic Sampling Train method was investigated to determine its reliability and to determine the bias and precision of the method when used to determine emissions from hazardous waste incinerators. Experiments showed that the matrix and sampling variables usually involved in sampling emissions from a hazardous waste incinerator had no significant effect on the recovery of 11 different organic compounds. Significant losses of the sampled compounds can occur during sample preparation. The degree of loss appears to be directly related to the compounds, vapor pressure. These losses can be corrected for by adding deuterated surrogates to the sample and analyzing the surrogates along with the native compounds.

The bias determination was based on dynamic spiking of the sampling train with five deuterated organic compounds selected from Appendix VIII of the Resource Conservation and Recovery Act regulations. The results show biases of from -1 ± 8 percent to -18 ± 27 percent for chlorinated and nonchlorinated compounds. Pyridine, a water-soluble compound, showed a larger bias of-29 ± 13 percent. Particular attention to the recovery of water soluble compounds is necessary to minimize bias in their determinations. Further work is needed to determine the reliability of laboratory-determined retention volumes that are used to determine sampling conditions.     

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 New Audit Technique for EPA Method 25

A simple, inexpensive, and accurate technique for evaluating or auditing the sampling, recovery, and analytical phases of EPA Source Reference Method 25 has been developed. The technique involves spiking a U-shaped stainless steel cartridge containing Tenax® with known quantities of selected organic compounds and thermally desorbing them at temperatures from 160°C to 180°C to generate organic vapors quantitatively. The major advantages of this technique are that no other measurement methods can be used to determine the generated organic concentrations in lieu of Method 25; and that the cartridge can easily be taken to the field for evaluation. The organic compounds generated in test runs are collected and analyzed using the Method 25 procedure. The generation of organics is quantitative and recoveries were found to be 100 ± 10%. The time required for desorption of the majority of organics is generally less than forty-five minutes at a flow rate of 100 mL/min; however, based on laboratory experience the recommended sampling time is sixty minutes. These spiked cartridges are stable at room temperature over a two-month period. Results of interlaboratory studies showed close agreement with the expected concentrations based on calculations from the mass loadings and sample volumes.     

Development of Federal Air Standards to Reduce Sulfur Dioxide Emissions from New Industrial Boilers

Federal new source performance standards to control air emissions of sulfur dioxide from new industrial boilers were proposed by EPA on June 19, 1986. These standards would require boiler owners to reduce SO₂ emissions by 90 percent and meet an emission limit of 1.2 lb/MM Btu of heat input for coal-fired boilers and 0.8 lb/MM Btu for oil-fired boilers. In developing these standards, several regulatory options were considered, from standards that could be met by firing low sulfur fuels to standards that would necessitate flue gas treatment. The environmental, economic, and cost impacts of each option were analyzed. National impacts were estimated by a computer model that projects the population of new boilers over the 5-year period following proposal, predicts the compliance strategy that will be used to comply with the particular option (always assuming that the lowest cost method of compliance will be selected), and estimates the resulting emission reductions and costs. Impacts on specific industries and on model boilers were also analyzed. This paper focuses on these analyses and their results. The Agency's conclusions from these analyses, which led to the decision to establish percent reduction standards, are provided, and the proposed SO₂ standards are summarized. The proposed standards also include an emission limit for particulate matter from oil-fired boilers (0.1 lb/MM Btu). However, this article focuses only on the SO₂ standards.     

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.     

An Assessment of the Economic Effects of Ozone on U.S. Agriculture

Past attempts to measure the economic consequences of ozone on agriculture have been based on limited plant science information. This paper reports on an economic assessment of ozone on U.S. agriculture using recent crop response data from the National Crop Loss Assessment Network (NCLAN). The results are derived from a U.S. agricultural sector model that includes major crop and livestock production as well as domestic consumption, livestock feeding and export uses. The economic effects of four hypothetical ambient ozone levels are investigated. The analysis Indicates that the benefits to society of moderate (25%) ozone reductions are approximately $1.7 billion. A 25% Increase in ozone pollution results in costs (negative benefits) of $2.1 billion. These estimates do not reflect compliance costs of achieving the ozone changes and hence are not net benefits.     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.