A Mathematical Model for the Effects of Fertilization on Nitrogen Concentrations in Unsaturated Soil on Blueberry Farms in Southern New Jersey

Nitrogen is commonly known as a food source for crops. However, the nitrogen compounds used in crop fertilizers, most commonly nitrate (NO₃) and ammonium (NH₄), are not widely understood. Blueberry plants do not take up these compounds as efficiently as organic nitrogen so varying amounts of leaching into the soil and groundwater will occur. A biogeochemical model consisting of ordinary and partial differential equations is implemented to computationally predict the concentrations of nitrate and ammonium in unsaturated soil of blueberry plants, specifically in the southern region of New Jersey. The model takes into account the type of soil of the region, the nitrate uptake of the plant, the water content in the roots region, the pressure heads in the soil pores, and the application rates of fertilizers containing nitrate, ammonium, and organic nitrogen. Computational simulations demonstrate that the model accounts for natural processes and, in addition, show that commonly used fertilizer application rates cause unnecessarily high concentrations of both nitrate and ammonium in the unsaturated soil level. Further, simulations show that decreasing nitrate fertilizer applications by 85.7% in annual and 91.8% in bi-annual schedules provides an optimal system for safe reapplication.     

Fly ash from biomass combustion as replacement raw material and its influence on the mortars durability

Journal of Material Cycles and Waste Management - Several types of industrial solid waste have been used as byproducts in the construction and materials industries. Some of the applications seem to...     

Developing Effective Decision Support for the Application of “Gentle” Remediation Options: The GREENLAND Project

Gentle remediation options (GRO) are risk management strategies/technologies that result in a net gain (or at least no gross reduction) in soil function as well as risk management. They encompass a number of technologies, including the use of plant (phyto‐), fungi (myco‐), and/or bacteria‐based methods, with or without chemical soil additives or amendments, for reducing contaminant transfer to local receptors by in situ stabilization, or extraction, transformation, or degradation of contaminants. Despite offering strong benefits in terms of risk management, deployment costs, and sustainability for a range of site problems, the application of GRO as practical on‐site remedial solutions is still in its relative infancy, particularly for metal(loid)‐contaminated sites. A key barrier to wider adoption of GRO relates to general uncertainties and lack of stakeholder confidence in (and indeed knowledge of) the feasibility or reliability of GRO as practical risk management solutions. The GREENLAND project has therefore developed a simple and transparent decision support framework for promoting the appropriate use of gentle remediation options and encouraging participation of stakeholders, supplemented by a set of specific design aids for use when GRO appear to be a viable option. The framework is presented as a three phased model or Decision Support Tool (DST), in the form of a Microsoft Excel‐based workbook, designed to inform decision‐making and options appraisal during the selection of remedial approaches for contaminated sites. The DST acts as a simple decision support and stakeholder engagement tool for the application of GRO, providing a context for GRO application (particularly where soft end‐use of remediated land is envisaged), quick reference tables (including an economic cost calculator), and supporting information and technical guidance drawing on practical examples of effective GRO application at trace metal(loid) contaminated sites across Europe. This article introduces the decision support framework. ©2015 Wiley Periodicals, Inc.     

Quantifying progress toward a conservation assessment for all plants

The Global Strategy for Plant Conservation (GSPC) set an ambitious target to achieve a conservation assessment for all known plant species by 2020. We consolidated digitally available plant conservation assessments and reconciled their scientific names and assessment status to predefined standards to provide a quantitative measure of progress toward this target. The 241,919 plant conservation assessments generated represent 111,824 accepted land plant species (vascular plants and bryophytes, not algae). At least 73,081 and up to 90,321 species have been assessed at the global scale, representing 21–26% of known plant species. Of these plant species, at least 27,148 and up to 32,542 are threatened. Eighty plant families, including some of the largest, such as Asteraceae, Orchidaceae, and Rubiaceae, are underassessed and should be the focus of assessment effort if the GSPC target is to be met by 2020. Our data set is accessible online (ThreatSearch) and is a baseline that can be used to directly support other GSPC targets and plant conservation action. Although around one‐quarter of a million plant assessments have been compiled, the majority of plants are still unassessed. The challenge now is to build on this progress and redouble efforts to document conservation status of unassessed plants to better inform conservation decisions and conserve the most threatened species.     

Monitoring saltwater intrusion in Rupert Bay,Québec,Canada, after the partial diversion of a major tributary

As part of a large hydroelectric project in northern Québec (Canada), a portion of the flow of the Rupert River was diverted toward the existing La Grande hydroelectric complex. As a result of the partial diversion, the discharge of the Rupert River at its mouth is reduced by an average of 50% annually. This corresponds to an 18% decrease in the total freshwater inflow into the bay and, thus, to a shift of the upstream limit of the saltwater intrusion in Rupert Bay. Changes in saltwater intrusion had been predicted numerically as part of the project’s environmental impact assessment (EIA). In the project’s conditions of authorization, monitoring the hydraulic conditions and the extent of saltwater intrusion in the Rupert Bay was required by government authorities. The objective of this paper is to present the results of this environmental monitoring and, more specifically, to validate the modifications predicted in the EIA in terms of both saltwater intrusion limit and hydraulic conditions in the Rupert Bay. Results obtained during 2 years of monitoring are within the predicted trends and order of magnitude of changes anticipated in the EIA. The results, thus, confirm that the shift of the upstream limit of the saltwater front along the channels of the bay was conservatively predicted by numerical modeling.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.