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.     

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.     

Dangerous climate change and water resources in Australia

Water resources in Australia are sensitive to changes in rainfall. Ongoing droughts in south-west and south-east Australia are stressing water resources in the major cities and in agricultural regions. Climate change scenarios for Australia include reasonable prospects of long-term drying, which would exacerbate these issues. The dryer scenarios would entail major readjustments and costs on natural and human systems.