MODELING OF NONPOINT SOURCE POLLUTION OF NITROGEN AT THE WATERSHED SCALE1

ABSTRACT: The Watershed Nutrient Transport and Transformation (NTT-Watershed) model is a physically based, energy-driven, multiple land use, distributed model that is capable of simulating water and nutrient transport in a watershed. The topographic features and subsurface properties of the watershed are refined into uniform, homogeneous square grids. The vertical discretization includes vegetation, overland flow, soil water redistribution and groundwater zones. The chemical submodel simulates the nitrogen dynamics in terrestrial and aquatic systems. Three chemical state variables are considered (NO₃^-_-, NH₄⁺, and Org-N). The NTT-Watershed model was used to simulate the fate and transport of nitrogen in the Muddy Brook watershed in Connecticut. The model was shown to be capable of capturing the hydrologic and portions of the nitrogen dynamics in the watershed. Watershed planners could use this model in developing strategies of best management practices that could result in maximizing the reductions of nitrogen export from a watershed.     

Optimizing safety-constrained solvent selection for process systems with economic uncertainties

Solvents are very commonly used in industrial facilities for a multitude of reasons. Traditionally, solvent selection has been based on minimizing the process operating cost while satisfying a set of operational requirements. Regrettably, safety considerations have typically been overlooked during the design phase. In this paper, a systematic approach is introduced to integrate safety issues into solvent selection and provides a computationally effective method for establishing tradeoffs between the economic and safety objectives. In order to quantify the risk associated with the solvent, we focus on the potential spillage of the solvent and introduce a risk index that is a function of the amount of solvent used and stored, as well as the Permissible Exposure Limit (PEL) dictated by regulatory directives. An optimization formulation is developed and the associated mathematical program solved to select optimal solvents and blends while incorporating economic, technical, and safety considerations. Tradeoff (Pareto) curves are developed to represent the multi-objective optimization results and tradeoffs. Furthermore, economic-data uncertainty and variability over expected ranges are included in the optimization formulation to conduct an insightful sensitivity analysis. Finally, an illustrative case study is considered via increasing levels of complexity in order to evaluate the proposed optimization method which considers both operating cost and safety risk implications in the presence of economic uncertainties.     

From place to emplacement: the scalar politics of sustainability

ABSTRACT

Sustainability has emerged as a central concept for discussing the current state of the human-environment system and planning for its future. To delve into the depths of sustainability means to talk about ecology, economy, and equity as fundamentally interconnected. However, each continues to be colonised by normative epistemologies of ecological sciences, neoclassical economics, and development, suggesting that with enough science and development, a more equitable sustainability is achievable. In our analysis, place emerges as an alternative epistemology through which to analyze sustainability. Place exists at multiple spatial and temporal scales, understood through direct observation of boundaries, processes and patterns, phenomenologically through individual experience, and as a complex hybrid: always emerging through interactions among individuals and institutions. Despite the ubiquity of place in the socio-ecological literature, the complexity of place in relation to sustainability is under-theorised, and in as much as sustainability happens or does not happen in real places rather than in policies and models, a place-based sustainability framework is necessary to move forward. To address this gap, we developed the emplacement framework, consisting of four domains: displacement, misplacement, replacement, and emplacement. Each domain is dynamic, constructing place as praxis, and reframing sustainability as a site of collective inquiry and choices. Our goal is to facilitate the active and on-going practices of place-based research and engagement among scholars, activists, and other community members by providing a structure for transdisciplinary dialogue and the application of transdisciplinary research to enable better decision-making.     

Phosphorus transformations in plant-based and bio-waste materials induced by pyrolysis

Strategies are needed to increase the sustainability of phosphorus (P) fertiliser management in agriculture. This paper reports on the potential of pyrolysis treatment to recycle P from renewable materials previously regarded as wastes. The study used K-edge X-ray absorption near-edge structure (XANES) spectroscopy to examine chemical forms of P in the waste feedstock materials and corresponding biochars (pyrolysis at 480–500 °C) of four ligno-cellulosic, plant-based residues and five relatively P-rich livestock and water-treatment by-products, to acquire information on changes in potential P fertiliser value. Pyrolysis enriched P in the biochars by factors of 1.3–4.3, thus offering wide-ranging P fertiliser potential. XANES spectroscopy revealed hydroxyapatite (HAP) as one of the dominant chemical P compounds in the feedstocks, ranging from 14% (rice husks) to 98% (animal bone) of total P. For most materials, pyrolysis increased the proportion of HAP, and pyrophosphates were generated in several cases. These alterations possibly lead to diversity in the P solubility characteristics of the biochars if used as soil amendments; this is an important property of environmentally sound P fertilisers.     

A new RFLP marker,SP282, at the btk locus for genetic analysis in X-linked agammaglobulinaemia families

X-linked agammaglobulinaemia is an inherited recessive disease in which the primary defect lies in the failure of pre-B cells to develop into mature circulating B cells, due to a defective B-cell cytoplasmic tyrosine kinase (btk). For this study we introduced a new RFLP marker, SP282, which is tightly linked to the XLA locus. In conjunction with the marker DXS178, SP282 was used to identify a carrier female and predict her male offspring to be normal. Subsequently the fetus was shown to have a normal number of circulating B cells, and at 2·5 years of age, the non-affected phenotype of the child was confirmed.     

Comparing measured and modelled forest carbon stocks in high-boreal forests of harvest and natural-disturbance origin in Labrador, Canada

Understanding the effects of disturbance regimes on carbon (C) stocks and stock changes is a prerequisite to estimating forest C stocks and fluxes. Live-tree, dead-tree, woody debris (WD), stump, buried wood, organic layer, and mineral soil C stock data were collected from high-boreal black spruce (Picea mariana (Mill.) B.S.P.) stands of harvest and fire origin and compared to values predicted by the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3); the core model of Canada's National Forest Carbon Monitoring, Accounting and Reporting System. Data comparing the effect of natural and anthropogenic disturbance history on forest C stocks are limited, but needed to evaluate models such as the CBM-CFS3. Results showed that adjustments to the CBM-CFS3 volume-to-biomass conversion and partitioning parameters were required for the non-merchantable and branch C pools to accurately capture live-tree C stocks in the studied black spruce ecosystems. Accuracy of the CBM-CFS3 modelled estimates of dead organic matter and soil C pools was improved relative to regional default parameters by increased snag fall and >10 cm WD base decay rates. The model evaluation process also highlighted the importance of developing a bryophyte module to account for bryophyte C dynamics and the physical burial of woody debris by bryophytes. Modelled mineral soil C estimates were improved by applying a preliminary belowground slow C pool base decay rate optimized for the soil type of the studied sites, Humo-Ferric Podzols.     

Neural network and multiple regression models for PM10 prediction in Athens: a comparative assessment

Particulate atmospheric pollution in urban areas is considered to have significant impact on human health. Therefore, the ability to make accurate predictions of particulate ambient concentrations is important to improve public awareness and air quality management. This study examines the possibility of using neural network methods as tools for daily average particulate matter with aerodynamic diameter <10 microm (PM10) concentration forecasting, providing an alternative to statistical models widely used up to this day. Based on a data inventory, in a fixed central site in Athens, Greece, ranging over a two-year period, and using mainly meteorological variables as inputs, neural network models and multiple linear regression models were developed and evaluated. Comparison statistics used indicate that the neural network approach has an edge over regression models, expressed both in terms of prediction error (root mean square error values lower by 8.2-9.4%) and of episodic prediction ability (false alarm rate values lower by 7-13%). The results demonstrate that artificial neural networks (ANNs), if properly trained and formed, can provide adequate solutions to particulate pollution prognostic demands.     

Development of a database for accidents and incidents in the Greek petrochemical industry

The present paper describes the development of a database that comprises all incidents from the Greek petrochemical industry for the period 1997–2003. This database includes industrial incidents, accidents, operational accidents and near misses from all petrochemical sites in Greece and Cyprus. The design of the database has been conceived in a user-friendly way with additional possibilities for its further use, such as: statistical analysis of the data, calculation of safety indicators, accident reports and human factors analysis. The database allows the various participating industries to compare the analysis of indicators in their own installations with the national average, as the database comprises data from the entire Greek petrochemical industry. Special care has been given to include data from near misses too.