IMPLICATIONS OF ON‐GROUND NITROGEN LOADING AND SOIL TRANSFORMATIONS ON GROUND WATER QUALITY MANAGEMENT1

ABSTRACT: This paper presents a modeling approach based on a geographic information system (GIS) to estimate the variability of on‐ground nitrogen loading and the corresponding nitrate leaching to ground water. The methodology integrates all point and nonpoint sources of nitrogen, the national land cover database, soil nitrogen transformations, and the uncertainty of key soil and land use‐related parameters to predict the nitrate mass leaching to ground water. The analysis considered 21 different land use classes with information derived from nitrogen sources such as fertilizer and dairy manure applications, dairy lagoons, septic systems, and dry and wet depositions. Simulations were performed at a temporal resolution of one month to capture seasonal trends. The model was applied to a large aquifer of 376 square miles in Washington State that serves more than 100,000 residents with drinking water. The results showed that dairy manure is the main source of nitrogen in the area followed by fertilizers. It was also seen that nitrate leaching is controlled by the recharge rate, and there can be a substantial buildup of soil nitrogen over long periods of time. Uncertainty analysis showed that denitrification rate is the most influential parameter on nitrate leaching. The results showed that combining management alternatives is a successful strategy, especially with the use of nitrification inhibitors. Also, change in the land use pattern has a noticeable impact on nitrate leaching.     

Influence of canola and sunflower diet amendments on cattle feedlot manure

Cattle (Bos taurus) producers can replace a part of the traditional diet of barley (Hordeum vulgare L.) grain/silage with sunflower (Helianthus annus L.) seeds or canola meal (Brassica napus L.)/oil to enhance conjugated linoleic acids (CLA) content in milk and meat for its positive health benefits. The objective of this study is to investigate the effects of feeding sunflower or canola to finishing steers on cattle manure chemical properties and volatile fatty acid (VFA) content. The control diet contained 84% rolled barley and 15% barley silage, which provided only 2.6% lipid. The other six treatments had 6.6 to 8.6% lipid delivered from sources such as hay, sunflower seed (SS), canola meal/oil, and SS forage pellets. Manure samples (a mixture of cattle urine, feces, and woodchip bedding materials) were collected and analyzed after cattle had been on these diets for 113 d. The dietary source and level of lipid had no effect on organic N and nitrate N content in manure, but significantly affected ammonia N and VFA. Inclusion of SS forage pellets, hay, or canola meal/oil in cattle diets had no significant impact on manure characteristics, but SS significantly reduced the pH and increased propionic, isobutyric, and isovaleric content. In addition, N loss after excretion (mainly from urine N) increases with the pH and N levels in both feed and manure. The combination of SS with barley silage resulted in a lower VFA and NH3 content in manure and should be a more attractive option. To better manage N nutrient cycles and reduce NH3 related odor problems, feed and manure pH should be one of the factors to consider when determining feed mix rations.     

Wastewater treatment with multilayer media of waste and natural indigenous materials

Wastewater treatment using waste materials (refuse concrete, waste paper and charcoal) and natural indigenous rocks (andesite, limestone, granite and nitrolite) in the form of multilayer media was investigated. The removal of suspended solids (SS), phosphate ion, nitrate ion, ammonium ion, toxic metals and chemical oxygen demand (COD) were evaluated for the multilayer wastewater treatment system. Effective removal of heavy metals such as cadmium, chromium, mercury and lead was demonstrated. SS and phosphate ion were removed with relatively high efficiency and the COD after treatment was lessened using certain combinations of media. The present wastewater treatment system is simple, convenient and low cost. Therefore, this method can be applied in small scale plants for wastewater treatment in local and nonexclusive areas.     

Lead(II) and cadmium(II) removal from aqueous solution using processed walnut shell: kinetic and equilibrium study

The biosorption potential of processed walnut shell for Pb(II) and Cd(II) ions from aqueous solutions was explored. The effects of pH, contact time, initial ion concentration, and amount of dried adsorbent were studied in batch experiments. The maximum adsorption was achieved within the pH range 4.0–6.0. The equilibrium data were well fitted by the Langmuir isotherm model. The maximum monolayer adsorption capacities were found to be 32?g?kg^?1 and 11.6?g?kg^?1 for Pb(II) and Cd(II) ions, respectively. Kinetic data were best described by the pseudo-second-order model. The structural features of the adsorbent were characterized by Fourier transform infrared spectroscopy, which confirmed the involvement of hydroxyl (–OH), carboxyl (–COO^–), and carbonyl (C=O) groups in metal sorption. This readily available adsorbent is efficient in the uptake of Pb(II) and Cd(II) ions from an aqueous solution and could be used for the treatment of wastewater streams bearing these metal ions.     

Aminobenzenesulfonamide functionalized SBA-15 nanoporous molecular sieve: A new and promising adsorbent for preconcentration of lead and copper ions

A rapid method for the extraction and monitoring of nanogram level of Pb²⁺ and Cu²⁺ ions using uniform silanized mesopor (SBA-15) functionalized with aminobenzenesulfonamide groups and flame atomic absorption spectrometry (FAAS) is presented. Aminobenzenesulfonamide functionalized SBA-15 was synthesized according to procedure in the literature and the presence of organic groups in the silica framework was demonstrated by FT-IR spectra. The functionalized product showed the BET surface area 110 m²/g and pore diameter 5.1 nm, based on adsorption-desorption of N₂ at 77 K. The effect of several variables such as (amount of adsorbent, stirring time, pH and presence of other ions in the medium) has been studied. Lead and copper were completely extracted at pH greater than 3 after stirring for 10 min. The maximum capacity of the adsorbent was found to be 191.3 ± 1.4 and 155.0 ± 1.0 μg of lead and copper ions/mg functionalized SBA-15, respectively. The preconcentration factor of the method was found to be 200. The detection limit of the technique was 3.4 and 0.4 ng/mL for Pb²⁺ and Cu²⁺, respectively. The applications of this methodology for real samples were examined by various water type, black tea and pepper samples.     

Role of plant growth promoting rhizobacteria in the remediation of metal contaminated soils

Pollution of the biosphere by the toxic metals is a global threat that has accelerated dramatically since the beginning of industrial revolution. The primary source of this pollution includes the industrial operations such as mining, smelting, metal forging, combustion of fossil fuels and sewage sludge application in agronomic practices. The metals released from these sources accumulate in soil and in turn, adversely affect the microbial population density and physico-chemical properties of soils, leading to the loss of soil fertility and yield of crops. The heavy metals in general cannot be biologically degraded to more or less toxic products and hence, persist in the environment. Conventional methods used for metal detoxification produce large quantities of toxic products and are cost-effective. The advent of bioremediation technology has provided an alternative to conventional methods for remediating the metal-poisoned soils. In metal-contaminated soils, the natural role of metal-tolerant plant growth promoting rhizobacteria in maintaining soil fertility is more important than in conventional agriculture, where greater use of agrochemicals minimize their significance. Besides their role in metal detoxification/removal, rhizobacteria also promote the growth of plants by other mechanisms such as production of growth promoting substances and siderophores. Phytoremediation is another emerging low-cost in situ technology employed to remove pollutants from the contaminated soils. The efficiency of phytoremediation can be enhanced by the judicious and careful application of appropriate heavy-metal tolerant, plant growth promoting rhizobacteria including symbiotic nitrogen-fixing organisms. This review presents the results of studies on the recent developments in the utilization of plant growth promoting rhizobacteria for direct application in soils contaminated with heavy metals under a wide range of agro-ecological conditions with a view to restore contaminated soils and consequently, promote crop productivity in metal-polluted soils across the globe and their significance in phytoremediation.     

Environmental monitoring of complex hydrocarbon mixtures in water and soil samples after solid phase microextraction using PVC/MWCNTs nanocomposite fiber

A novel nanocomposite based on incorporation of multiwalled carbon nanotubes (MWCNTs) in polyvinyl chloride (PVC) was prepared. Proposed nanocomposite was coated on stainless steel wire by deep coating. Composition of nanocomposite was optimized based on results of morphological studies using scanning electron microscopy. The best composition (83% MWCNTs:17% PVC) was applied as a solid phase microextraction fiber. Complex mixture of aromatic (BTEX) and aliphatic hydrocarbons (C₅–C₃₄) were selected as model analytes, and performance of proposed fiber in extraction of the studied compounds from water and soil samples was evaluated. Analytical merits of the method for water samples (LODs = 0.10–1.10 ng L⁻¹, r² = 0.9940–0.9994) and for soil samples (LODs = 0.10–0.77 ng kg⁻¹, r² = 0.9946–0.9994) showed excellent characteristics of it in ultra trace determination of petroleum type environmental pollutants. Finally, the method was used for determination of target analytes in river water, industrial effluent and soil samples.     

Off-grid: community energy and the pursuit of self-sufficiency in British Columbia's remote and First Nations communities

Remote or off-grid communities in Canada primarily rely on diesel generators for the provision of their electricity. Often surrounded by potential renewable resources, they are characterised as the low-hanging fruit of greenhouse gas mitigation strategies. While much is said about the promises of community energy projects, as well as technologies and policy mechanisms for addressing the needs of these communities, little attention has been paid to what communities, themselves, might want for their energy projects and what the implications of those desires might be for both technology development and community energy policies. This paper aims to fill this gap by exploring the on-going energy pursuits of a number of remote First Nations communities in British Columbia. It identifies a desire for community self-sufficiency as a primary motivation for engaging with energy projects on the part of the communities and discusses the various meanings and implications of self-sufficiency in the context of community energy projects. These meanings and implications primarily include the two dimensions of material self-sufficiency and political self-determination, the latter of which suggests a view of community energy projects as processes of decolonisation among First Nation communities in British Columbia. It then suggests that the pursuit of this goal is somewhat incongruent with the approach that government and industry have taken in addressing community energy, especially the way in which remote communities are viewed as the low-hanging fruit of various sustainability projects.     

Evaluation of PCA and Gamma test techniques on ANN operation for weekly solid waste prediction

Artificial neural networks (ANNs) are suitable for modeling solid waste generation. In the present study, four training functions, including resilient backpropagation (RP), scale conjugate gradient (SCG), one step secant (OSS), and Levenberg–Marquardt (LM) algorithms have been used. The main goal of this research is to develop an ANN model with a simple structure and ample accuracy. In the first step, an appropriate ANN model with 13 input variables is developed using the afore-mentioned algorithms to optimize the network parameters for weekly solid waste prediction in Mashhad, Iran. Subsequently, principal component analysis (PCA) and Gamma test (GT) techniques are used to reduce the number of input variables. Finally, comparison amongst the operation of ANN, PCA-ANN, and GT-ANN models is made. Findings indicated that the PCA-ANN and GT-ANN models have more effective results than the ANN model. These two models decrease the number of input variables from 13 to 7 and 5, respectively.