Marginal abatement cost curve for nitrogen oxides incorporating controls,renewable electricity,energy efficiency,and fuel switching

A marginal abatement cost curve (MACC) traces out the relationship between the quantity of pollution abated and the marginal cost of abating each additional unit. In the context of air quality management, MACCs are typically developed by sorting control technologies by their relative cost-effectiveness. Other potentially important abatement measures such as renewable electricity, energy efficiency, and fuel switching (RE/EE/FS) are often not incorporated into MACCs, as it is difficult to quantify their costs and abatement potential. In this paper, a U.S. energy system model is used to develop a MACC for nitrogen oxides (NO_x) that incorporates both traditional controls and these additional measures. The MACC is decomposed by sector, and the relative cost-effectiveness of RE/EE/FS and traditional controls are compared. RE/EE/FS are shown to have the potential to increase emission reductions beyond what is possible when applying traditional controls alone. Furthermore, a portion of RE/EE/FS appear to be cost-competitive with traditional controls.

Implications: Renewable electricity, energy efficiency, and fuel switching can be cost-competitive with traditional air pollutant controls for abating air pollutant emissions. The application of renewable electricity, energy efficiency, and fuel switching is also shown to have the potential to increase emission reductions beyond what is possible when applying traditional controls alone.     

Accumulation of silver in the liver of three species of pinnipeds

Silver in the three species of pinnipeds [northern fur seal (Callorhinus ursinus), Steller sea lion (Eumetopias jubatus), and harbor seal (Phoca vitulina)] caught in the North Pacific Ocean were analyzed using inductively coupled plasma-mass spectrometry, in order to understand accumulation and distribution of silver in pinnipeds. In northern fur seals, relatively high concentrations of silver were observed in the liver and body hair. Some 70% of the silver burden was concentrated in the liver. Hepatic silver concentrations were significantly correlated to age in northern fur seals (r = 0.766, P < 0.001, n = 49) and Steller sea lions (r = 0.496, P < 0.01, n = 28). Levels of silver concentrations per wet weight (microgram g-1) in the three pinnipeds ranged from 0.04 to 0.55 for northern fur seals, from 0.1 to 1.04 for Steller sea lions and from 0.03 to 0.83 for harbor seals. Silver concentrations in liver for all pinnipeds were significantly correlated with mercury, and selenium (P < 0.001). Molar ratios between silver to selenium approximated 1:180 in northern fur seals, 1:120 in Steller sea lions, and 1:60 in harbor seals. The silver-mercury molar ratios were approximately 1:170 in northern fur seals, and 1:80 both in the other species. Increase in silver accumulation in the liver was caused by the retention in nuclei and mitochondria fraction together with mercury and selenium in the cells of northern fur seals.     

Application of genetic algorithms for the design of ozone control strategies

Designing air quality management strategies is complicated by the difficulty in simultaneously considering large amounts of relevant data, sophisticated air quality models, competing design objectives, and unquantifiable issues. For many problems, mathematical optimization can be used to simplify the design process by identifying cost-effective solutions. Optimization applications for controlling nonlinearly reactive pollutants such as tropospheric ozone, however, have been lacking because of the difficulty in representing nonlinear chemistry in mathematical programming models. We discuss the use of genetic algorithms (GAs) as an alternative optimization approach for developing ozone control strategies. A GA formulation is described and demonstrated for an urban-scale ozone control problem in which controls are considered for thousands of pollutant sources simultaneously. A simple air quality model is integrated into the GA to represent ozone transport and chemistry. Variations of the GA formulation for multiobjective and chance-constrained optimization are also presented. The paper concludes with a discussion of the practically of using more sophisticated, regulatory-scale air quality models with the GA. We anticipate that such an approach will be practical in the near term for supporting regulatory decision-making.     

Global climate change: The quantifiable sustainability challenge

Population growth and the pressures spawned by increasing demands for energy and resource-intensive goods, foods, and services are driving unsustainable growth in greenhouse gas (GHG) emissions. Recent GHG emission trends are consistent with worst-case scenarios of the previous decade. Dramatic and near-term emission reductions likely will be needed to ameliorate the potential deleterious impacts of climate change. To achieve such reductions, fundamental changes are required in the way that energy is generated and used. New technologies must be developed and deployed at a rapid rate. Advances in carbon capture and storage, renewable, nuclear, and transportation technologies are particularly important; however, global research and development efforts related to these technologies currently appear to fall short relative to needs. Even with a proactive and international mitigation effort, humanity will need to adapt to climate change, but the adaptation needs and damages will be far greater if mitigation activities are not pursued in earnest. In this review, research is highlighted that indicates increasing global and regional temperatures and ties climate changes to increasing GHG emissions. GHG mitigation targets necessary for limiting future global temperature increases are discussed, including how factors such as population growth and the growing energy intensity of the developing world will make these reduction targets more challenging. Potential technological pathways for meeting emission reduction targets are examined, barriers are discussed, and global and U.S. modeling results are presented that suggest that the necessary pathways will require radically transformed electric and mobile sectors. While geoengineering options have been proposed to allow more time for serious emission reductions, these measures are at the conceptual stage with many unanswered cost, environmental, and political issues.

Implications:?This paper lays out the case that mitigating the potential for catastrophic climate change will be a monumental challenge, requiring the global community to transform its energy system in an aggressive, coordinated, and timely manner. If this challenge is to be met, new technologies will have to be developed and deployed at a rapid rate. Advances in carbon capture and storage, renewable, nuclear, and transportation technologies are particularly important. Even with an aggressive international mitigation effort, humanity will still need to adapt to significant climate change.     

Teenagers' part-time employment and their work-related attitudes and aspirations

We assessed the relationship between the quality (i.e., job characteristics, role stressors, and interpersonal relationships) and quantity of part-time employment, and work-related attitudes and aspirations among 349 students. Neither the linear nor the quadratic components of employment quantity predicted any of the outcome variables. Motivation to do good work was predicted both by role stressors and by family achievement orientation. Career maturity was predicted by role stressors at work, and cynicism by role stressors and satisfaction with interpersonal relationships. In contrast, job involvement was significantly related to family achievement orientation but not to any perceived job factors. These findings question the assumption that only intensive work during high school exerts negative effects for teenagers, and support the importance of employment quality for teenagers as well as adults. © 1998 John Wiley & Sons, Ltd.     

Application of Genetic Algorithms for the Design of Ozone Control Strategies

ABSTRACT

Designing air quality management strategies is complicated by the difficulty in simultaneously considering large amounts of relevant data, sophisticated air quality models, competing design objectives, and unquantifiable issues. For many problems, mathematical optimization can be used to simplify the design process by identifying cost-effective solutions. Optimization applications for controlling nonlinearly reactive pollutants such as tropospheric ozone, however, have been lacking because of the difficulty in representing nonlinear chemistry in mathematical programming models.

We discuss the use of genetic algorithms (GAs) as an alternative optimization approach for developing ozone control strategies. A GA formulation is described and demonstrated for an urban-scale ozone control problem in which controls are considered for thousands of pollutant sources simultaneously. A simple air quality model is integrated into the GA to represent ozone transport and chemistry. Variations of the GA formulation for multiobjective and chance-constrained optimization are also presented. The paper concludes with a discussion of the practicality of using more sophisticated, regulatory-scale air quality models with the GA. We anticipate that such an approach will be practical in the near term for supporting regulatory decision-making.     

Distribution of heavy metals in muscle, liver and kidney of northern fur seal (Callorhinus ursinus) caught off Sanriku, Japan and from the Pribilof Islands, Alaska

The concentrations of iron, manganese, zinc, copper, cadmium, and mercury were determined in muscle, liver and kidney of 67 northern fur seals (Callorhinus ursinus) collected off Sanriku, Japan, and from the Pribilof Islands, Alaska. Almost all the elements except cadmium were highest in liver. Cadmium levels in kidney were higher than those in liver and muscle for all animals analyzed. Concentrations of mercury increased significantly with age in muscle, liver and kidney, as did iron levels in muscle and liver and cadmium levels in muscle, while manganese concentrations decreased with age in muscle and kidney. The kidney also showed decreased copper concentration with age. Cadmium concentrations of the northern fur seals in this study were higher than the other otariids, reflecting a predominantly squid diet. Concentrations of manganese and mercury were found to be higher in the fur seals caught off Sanriku than in animals from the Pribilof Islands, while those of zinc and cadmium were found to be lower. Variable concentrations of cadmium might have been attributed to those in seawaters. Discriminant analysis of heavy metal concentrations was used to identify habitat. Sixty-three of 67 animals (94%) were correctly classified using this technique. Heavy-metal concentrations in tissues may provide a useful method to elucidate the primary feeding grounds of fur seals.