Particulate,Carbon Monoxide,and Acid Emission Factors for Residential Wood Burning Stoves

Emissions from residential wood burning stoves are of Increasing concern in many areas. This concern is due to the magnitude of the emissions and the toxic and chemical characteristics of the pollutants. Recent testing of standard and new technology woodstoves has provided data for developing a family of particulate and carbon monoxide emission factor curves. This testing has also provided data illustrating the acidity of woodstove emissions. The particulate and carbon monoxide curves relate the actual stove emissions to the stove size and operating parameters of burn rate, fuel loading, and fuel moisture. Curves relating stove types to the acidity of emissions have also been constructed.

Test data show actual emissions vary from 3 to 50 grams per kilogram for particles and from 50 to 300 grams per kilogram for carbon monoxide. Since woodstove emissions are the largest single category of particulate emissions in many areas, it Is essential that these emissions be quantified specifically for geographic regions, allowing meaningful impact analysis modeling to be accomplished. Emission factors for particles and carbon monoxide are presented from several stove sizes and burn rates.

The acidic nature of woodstove emissions has been clearly demonstrated. Tests indicate woodstove flue gas condensate solutions to be predominantly in the 2.8 to 4.2 pH range. Condensate solutions from conventional woodstoves exhibited the characteristic buffering capacity of carboxylic acids when titrations were performed with a strong base. The environmental impact of buffered acidic woodstove emissions is not currently well understood; however, it is possible with the data presented here to make semi-quantitative estimates of acid emissions from particulate and carbon monoxide emission factors and wood use inventories.     

Improving Baghouse Performance at the Monticello Generating Station

At the Monticello station, operated by the Texas Utilities Generating Company, lignite coal obtained locally in Titus and Hopkins Counties fuels each of the three units. Units 1 and 2 are identical 575-MW Combustion Engineering (CE) boilers, each of which discharges its effluent to a 36- compartment shake/deflate cleaned baghouse paralleled with four electrostatic precipitators (ESP). Unit 3 is a larger boiler and is followed by an ESP and a scrubber. The Unit 1 and 2 baghouses were designed to clean 80 percent of the flue gas. Since startup, these baghouses have regularly experienced flange-to-flange pressure drops in excess of 10 in. H₂O, with large opacity spikes caused by ash bleeding through the bags after compartment cleanings. Because of higher-than-expected pressure drop, the baghouses receive only about 45-50 percent of the flue gas. Analysis has shown the Monticello lignite ash significantly differs from most other coal ashes. Testing has shown that the Monticello ash is not filtered effectively by many "standard" bag materials. However, this testing indicates that there are fabrics that show promise of eliminating the ash bleedthrough with little pressure drop penalty. Testing has also shown that injection of low concentrations (10-15 ppm) of ammonia (NH₃) into the flue gas significantly decreases ash bleedthrough, so that with NH₃ injection "standard" bag materials may perform adequately. Currently, fullcompartment testing of four fabrics, with and without NH₃ injection, is under way at the Unit 1 baghouse. The research conducted at the Monticello station is reviewed in this paper and the encouraging results from the full-compartment tests are presented.     

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.     

Ten-Year Ozone Trends in California and Texas

Ozone trends have been developed for 50 California sites located in six basins and for 15 Texas sites in two regions. All data were obtained directly from state or local monitoring agencies and have been standardized to the current ultraviolet calibration basis. Rigorous standards of data representativeness and statistical validity have been adhered to throughout. The effect of monitoring variance upon apparent trends is reviewed as well as implications of this work for the ozone control strategy. Trends for 1973-82 for three key robust ozone statistics were developed in detail and analyzed. These are: annual average, annual hours >120 ppb and average daily maximum hour (May through October). Summaries for three other statistics including annual maximum hour are also included as well as composite trends for California basins and Texas regions. The statistical significance of all trends is discussed.     

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.     

Eliminating Reheat from Existing FGD Systems

The Clean Air Act Amendments of the early 1970_s required coal burning utilities to reduce their emissions of sulfur dioxide. Lime or limestone based wet systems were employed for flue gas desulfurization (FGD). These systems reduced flue gas temperatures to below acid dew point conditions. Concerned about the prospect of ductwork exposed to a saturated, acid-rich environment, most utilities turned to stack gas reheat (SGR) to increase flue gas temperatures. By 1980, 82 percent of all FGD facilities employed SGR. Today there are about 130 FGD systems of which 101 employ some form of stack gas reheat.     

Experimental Characterization of Atmospheric Diffusion in Complex Terrain with Land-Sea Interactions

The body of information presented in this paper is directed to scientists working in atmospheric dispersion research and model development. Two years of field measurements in the coastal area of Bilbao in northern Spain show that the diffusion behavior in this complex terrain can be classified into several well defined patterns, which correspond to certain meteorological conditions. The approach taken has been the systematic use of SO₂ remote sensors (COSPEC) and ground level monitors in moving platforms which are used to follow and document the flow of the air mass. Results to date show that complex reentry cycles can occur and that synoptically different flows may be indistinguishable by wind sensors at ground level (affected by channeling), and yet result in totally different observed pollution levels by a fixed monitoring network (affected by topographical effects). These results are being used to parameterize the cause-effect relationships and guide the modeling efforts in this area of complex terrain.