Partitioning coefficients of polycyclic aromatic hydrocarbons in stack gas from a municipal incinerator

In this study, solid-gas partitioning coefficients of PAHs on fly ash in stack gas from a municipal incinerator were determined according to elution analysis with gas-solid chromatography. The fly ash from the electrostatic precipitator was sieved and packed into a 1/4 inch (6.3 mm) pyrex column. Elution analysis with gas-solid chromatography was conducted for three PAHs, Napthalene, Anthracene, and Pyrene. The temperature for elution analysis was in the range of 100°C to 300°C. V_g, specific retention volume obtained from elution analysis, and S, specific surface area of fly ash measured by a surface area measurement instrument, were used to estimate the solid-gas partitioning coefficient, K_R. In addition, the relationships between K_R and temperature and K_R and PAH concentrations were investigated.     

Evaluating Experience with Renewables Portfolio Standards in the United States

Increased use of renewable energy is one of several promising methods for reducing emissions of local, regional, and global air pollutants, including greenhouse gas emissions associated with fossil-fuel based electricity production. Among the available options for encouraging renewable electricity generation, the renewables portfolio standard (RPS) has become especially popular in recent years. The RPS is a newly established policy mechanism, however, and experience with its use has not been widely documented and evaluated. This paper describes and evaluates the design, impacts, and early experience of 13 U.S. state RPS policies. These 13 policies share a common goal of encouraging renewable energy supply, but each specific RPS is designed differently. Our evaluation shows both successes and failures with this policy mechanism; some state RPS policies are positively impacting renewable energy development, while others have been poorly designed and will do little to advance renewable energy markets.We emphasize the importance of policy design details, and specifically highlight critical design pitfalls that have been commonly experienced. Though experience with the RPS is still limited, we have now gained some knowledge of the conditions and design features necessary to make an RPS policy work. An important objective of this article is therefore to identify and describe broad policy design principles and specific best practice design elements that might be used to guide the design of future renewables portfolio standards.     

Forecasting peak daily ozone levels--I. A regression with time series errors model having a principal component trigger to fit 1991 ozone levels

This research was motivated by the need to warn the population of Milwaukee, WI, on high-ozone days. A statistical model for the peak daily 1-hr ozone level is proposed. A Regression with Time Series Errors (RTSE) model, which includes a principal component (PC) trigger, is the basis for forecasting the peak daily 1-hr ozone level. The RTSE model, with a PC trigger, is first employed to estimate daily peak ozone measured at the University of Wisconsin, Milwaukee-North (UWM-N), during the 1991 ozone season. The RTSE model uses peak daily temperature, morning vector average wind direction, and the PC trigger as predictor variables. The PC trigger was designed to summarize atmospheric circumstances when peak ozone was greater than 100 parts per billion (ppb). It is verified that the RTSE model, with a PC trigger, significantly improves the prediction of peak daily ozone, particularly peak ozone greater than 100 ppb. In comparison with the RTSE model without the PC trigger, the RTSE model with a PC trigger raised the R2 from 0.680 to 0.809. It is suggested that the RTSE model, with the PC trigger, is an adequate statistical model that has the potential for real-time ozone forecasting.     

Electrostatic enhancement of collection efficiency of the fibrous filter pretreated with ionic surfactants

A study of the electrostatic enhancement of collection efficiency of filters pretreated with ionic surfactants has been carried out in controlled conditions with monodisperse aerosols. Cationic surfactant (dimethyl dioctadecylammonium bromide [DDAB]) and anionic surfactant (sodium oleate [SO]) were used to pretreat polypropylene fibrous filters as the positively and negatively charged filters, respectively. The effects of aerosol size, aerosol charge state, face velocity, aerosol type, and relative humidity (RH) were considered to elucidate their influence on the aerosol penetration. Results indicate that penetration through surfactant-pretreated filters was lower than that through untreated filters, and pretreatment of the filter with surfactant was observed not to affect the structure of the filter. The electrofieldmeter direct-measured the very clear electric field of filter when treating ionic surfactants. The results proved that pretreatment with surfactant caused filters to become charged. Comparing penetration through surfactant-pretreated filters with that through untreated filters with neutral aerosol, the penetration reduction factor of the surfactant-pretreated filters was in the range 1.3-2.2. Comparing aerosol penetration through the surfactant-pretreated filters with singly charged aerosol with that through untreated filters with uncharged aerosol indicates that the former decreases by a factor of 1.8-48.8. The surface fiber charges of the DDAB- and SO-pretreated filters were calculated to be 2.02 x 1(-10) C/m and -1.53 x 10(-1) degrees C/m. Moreover, the aerosol penetrations through the surfactant-pretreated filters increased with the face velocity. Surfactant-pretreated filters performed better against solid aerosol than against liquid aerosol. RH has no effect on aerosol penetration through the surfactant-pretreated filters. Regression equations for Coulombic and dielectrophoretic single-fiber efficiencies in terms of the dimensionless parameters could be fitted by the experimental measurements of surfactant-pretreated filters in this work.     

Deposition of fixed atmospheric nitrogen and foliar nitrogen content of bryophytes and Calluna vulgaris (L.) Hull

Atmospheric deposition of fixed nitrogen as nitrate and ammonium in rain and by dry deposition of nitrogen dioxide, nitric acid and ammonia has increased throughout Europe during the last two decades, from 2-6 kg N ha(-1) year(-1) to 15-60 kg N ha(-1) year(-1). The nitrogen contents of bryophytes and the ericaceous shrub Calluna vulgaris have been measured at a range of sites, with the objective of showing the degree to which nitrogen deposition is reflected in foliar plant nitrogen. Tissue nitrogen concentrations of herbarium bryophyte samples and current samples of the same species collected from the same sites were compared. No significant change in tissue nitrogen was recorded at a remote site in north-west Scotland where nitrogen inputs are small (< 6 kg N ha(-1) year(-1)). Significant increases in tissue N occurred at four sites ranging from 38% in central Scotland to 63% in Cumbria where nitrogen inputs range from 15 to 30 kg N ha(-1) year(-1). The relationships found between the estimated input of atmospheric nitrogen and the tissue nitrogen content of the selected bryophytes and Calluna at the sites investigated were found to be generally linear and fitted the form N(tissue) = 0.62 + 0.022 N(dep) for bryophytes and N(tissue) = 0.83 + 0.045 N(dep) for Calluna. There was thus an increase in total tissue nitrogen of 0.02 mg g(-1) dry weight for bryophytes and 0.045 mg g(-1) dry weight for Calluna for an increase in atmospheric nitrogen deposition of 1 kg ha(-1) year(-1). The lowest concentrations were found in north-west Scotland and the highest in Cumbria and the Breckland heaths of East Anglia, both areas of high atmospheric nitrogen deposition (30-40 kg N ha(-1) year(-1)). The implications of increased tissue nitrogen content in terms of vegetation change are discussed. Changes in atmospheric nitrogen deposition with time were also examined using measured values and values inferred from tissue nitrogen content of mosses. The rate of increase in nitrogen deposition is not linear over the 90-year period, and the increases were negligible over the period 1880-1915. However, during the period 1950 to 1990 the data suggest an increase in nitrogen deposition of 2 kg N ha(-1) every 10 years.     

Representing general theoretical concepts in structural equation models: the role of composite variables

Structural equation modeling (SEM) holds the promise of providing natural scientists the capacity to evaluate complex multivariate hypotheses about ecological systems. Building on its predecessors, path analysis and factor analysis, SEM allows for the incorporation of both observed and unobserved (latent) variables into theoretically-based probabilistic models. In this paper we discuss the interface between theory and data in SEM and the use of an additional variable type, the composite. In simple terms, composite variables specify the influences of collections of other variables and can be helpful in modeling heterogeneous concepts of the sort commonly of interest to ecologists. While long recognized as a potentially important element of SEM, composite variables have received very limited use, in part because of a lack of theoretical consideration, but also because of difficulties that arise in parameter estimation when using conventional solution procedures. In this paper we present a framework for discussing composites and demonstrate how the use of partially-reduced-form models can help to overcome some of the parameter estimation and evaluation problems associated with models containing composites. Diagnostic procedures for evaluating the most appropriate and effective use of composites are illustrated with an example from the ecological literature. It is argued that an ability to incorporate composite variables into structural equation models may be particularly valuable in the study of natural systems, where concepts are frequently multifaceted and the influence of suites of variables are often of interest.     

Critical Risk Indicators (CRIs) for the electric power grid: a survey and discussion of interconnected effects

The electric power grid is a critical societal resource connecting multiple infrastructural domains such as agriculture, transportation, and manufacturing. The electrical grid as an infrastructure is shaped by human activity and public policy in terms of demand and supply requirements. Further, the grid is subject to changes and stresses due to diverse factors including solar weather, climate, hydrology, and ecology. The emerging interconnected and complex network dependencies make such interactions increasingly dynamic, posing novel risks, and presenting new challenges to manage the coupled human–natural system. This paper provides a survey of models and methods that seek to explore the significant interconnected impact of the electric power grid and interdependent domains. We also provide relevant critical risk indicators (CRIs) across diverse domains that may be used to assess risks to electric grid reliability, including climate, ecology, hydrology, finance, space weather, and agriculture. We discuss the convergence of indicators from individual domains to explore possible systemic risk, i.e., holistic risk arising from cross-domain interconnections. Further, we propose a compositional approach to risk assessment that incorporates diverse domain expertise and information, data science, and computer science to identify domain-specific CRIs and their union in systemic risk indicators. Our study provides an important first step towards data-driven analysis and predictive modeling of risks in interconnected human–natural systems.

     

Increasing the effectiveness of environmental decision support systems: lessons from climate change adaptation projects in Canada and Australia

Regional Environmental Change - There is a need to increase regional and community level action towards adaptation to climate change. Natural resource managers and planners have to make challenging...