Modelling and Optimization of Uranium (VI) Ions Adsorption Onto Nano-ZnO/Chitosan Bio-composite Beads with Response Surface Methodology (RSM)

Nano-ZnO-chitosan bio-composite beads were prepared for the sorption of \({\text{UO}}_{2}^{{2+}}\) from aqueous media. The resulting nano-ZnO/CTS bio-composite beads were characterized by TEM, XRD etc. The sorption of \({\text{UO}}_{2}^{{2+}}\) by bio-composite beads was optimized using RSM. The correlation between four variables was modelled and studied. According to RSM data, correlation coefficients (R²?=?0.99) and probability F-values (F?=?2.24?×?10^??10) show that the model fits the experimental data well. Adsorption capacity for nano-ZnO/CTS bio-composite beads was obtained at 148.7 mg/g under optimum conditions. The results indicate that nano-ZnO/CTS bio-composite beads are appropriate for the adsorption of \({\text{UO}}_{2}^{{2+}}\) ions from aqueous media. Also, the suitability of adsorption values to adsorption isotherms was researched and thermodynamic data were calculated.     

Estimating Potential Climate Change Effects on the Upper Neuse Watershed Water Balance Using the SWAT Model

Climate change poses water resource challenges for many already water stressed watersheds throughout the world. One such watershed is the Upper Neuse Watershed in North Carolina, which serves as a water source for the large and growing Research Triangle Park region. The aim of this study was to quantify possible changes in the watershed’s water balance due to climate change. To do this, we used the Soil and Water Assessment Tool (SWAT) model forced with different climate scenarios for baseline, mid‐century, and end‐century time periods using five different downscaled General Circulation Models. Before running these scenarios, the SWAT model was calibrated and validated using daily streamflow records within the watershed. The study results suggest that, even under a mitigation scenario, precipitation will increase by 7.7% from the baseline to mid‐century time period and by 9.8% between the baseline and end‐century time period. Over the same periods, evapotranspiration (ET) would decrease by 5.5 and 7.6%, water yield would increase by 25.1% and 33.2%, and soil water would increase by 1.4% and 1.9%. Perhaps most importantly, the model results show, under a high emission scenario, large seasonal differences with ET estimated to decrease by up to 42% and water yield to increase by up to 157% in late summer and fall. Planning for the wetter predicted future and corresponding seasonal changes will be critical for mitigating the impacts of climate change on water resources.     

A study on the determination of the natural park’s sustainable tourism potential

The surface site of Yesilyuva Nature Park encompasses natural, social, economic, and cultural characteristics and has become a marker of the region’s natural and cultural heritage. To support the preservation of this site, promotional activities should be planned. In this study, because of tourism and related opinions of residents and visitors alike in terms of their natural determination, an important cultural and historical feature is aimed at evaluating the tourism potential of Yesilyuva Nature Park. This framework is designed to establish prospective tourism sustainability. As a result, Yesilyuva Nature Park’s natural and cultural properties have been determined to be suitable for sustainable tourism activities using geographic information systems (GIS). This protection in the field, which balances sustainability and landscape design, will provide for the development of tourism activities. In the Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis and survey, residents and visitors reported that the most important feature of the Yesilyuva Nature Park was its natural beauty. Visitors often come to observe traditional and natural life and to engage in tourism activities. All the data, which includes maps derived from GIS, represents landscape planning for sustainable tourism areas in Yesilyuva Nature Park.     

Effects of calcium hydroxide and calcium chloride addition to bentonite in iron ore pelletization.

Pyrite ash is created as waste from the roasting of pyrite ores during the production of sulphuric acid. These processes generate great amounts of pyrite ash waste that is generally land filled. This creates serious environmental pollution due to the release of acids and toxic substances. Pyrite ash waste can be utilized in the iron production industry as a blast furnace feed to process this waste and prevent environmental pollution. The essential parameters affecting the pelletization process of pyrite ash were studied using bentonite as a binder. Experiments were then carried out using bentonite and a mixture of bentonite with calcium hydroxide and calcium chloride in order to make the bentonite more effective. The metallurgical properties of pyrite ash, bentonite, calcium hydroxide, calcium chloride, a mixture of these and sintered pellets were studied using X-ray analysis. The crushing strength tests were carried out to investigate the strength of pyrite ash waste pellets. The results of these analyses showed that pyrite ash can be agglomerated to pellets and used in the iron production industry as a blast furnace feed. The crushing strength of the pellets containing calcium hydroxide and calcium chloride in addition to bentonite was better than the strength of pellets prepared using only bentonite binder.     

Single-source impact analysis using three-dimensional air quality models

Isolating the effects of an individual emissions source on secondary air pollutants such as ozone and some components of particulate matter must incorporate complex nonlinear processes, be sensitive to small emissions perturbations, and account for impacts that may occur hundreds of kilometers away. The ability to evaluate these impacts is becoming increasingly important for efficient air quality management. Here, as part of a recent compliance enforcement action for a violation of the Clean Air Act and as an evaluation of ozone response to single-source emissions plumes, two three-dimensional regional photochemical air quality models are used to assess the impact on ozone from approximately 2000 to 3000 excess t/month of nitrogen oxides emitted from a single power plant in Ohio. Periods in May, July, and August are evaluated. Two sensitivity methods are applied: the "brute-force" (B-F) method and the decoupled direct method (DDM). Using DDM, maximum 1-hr averaged ozone concentrations are found to increase by up to 1.8, 1.3, and 2.2 ppbv during May, July, and August episodes, respectively, and concentration increases greater than 0.5 ppbv occur in Ohio, Pennsylvania, Maryland, New York, West Virginia, Virginia, and North and South Carolina. B-F results for the August episode show a maximum 1-hr averaged ozone concentration increase of 2.3 ppbv. Significant localized decreases are also simulated, with a maximum of 3.6 ppbv in Ohio during the August episode and decreases of 0.50 ppbv and greater in Ohio, Pennsylvania, Maryland, West Virginia, and Virginia. Maximum increases are compared with maximum decreases for the August period using second-order DDM and are found, in aggregate, to be greater in magnitude by 42%. When evaluated during hours when ozone concentrations exceed 0.060 ppm, the maximum increases in ozone are higher than decreases by 82%. The spatial extent of ozone increase in both cases is about triple that of reduction.     

Conjoint analysis for environmental evaluation

BACKGROUND, AIM AND SCOPE: Conjoint analysis and the related choice-modelling methods have been used for many years in marketing research to evaluate consumer behaviour and preferences for different kinds of product attributes. Recently, the number of applications in environmental science and management has started to grow. Conjoint analysis is found in many different forms, and the environmental studies evaluated in this review display the same range of methods as in other fields. The key characteristic of all these methods is that trade-offs are evaluated by jointly considering a number of important attributes. MAIN FEATURES: This paper is a review of the literature on environmental applications of conjoint analysis and assesses in which environmental area conjoint analysis has been most successful. The method and the design of the studies are reviewed as well. RESULTS: A total of 84 studies were found, dealing with environmental issues that were evaluated by conjoint analysis. The studies concern agriculture, ecosystem management, energy, environmental evaluation, forestry, land management, pollution, products, recreation, environmental risk analysis and waste management. DISCUSSION: Choice experiments seem to have a comparatively stronger position in environmental studies than elsewhere. Most of the environmental applications are related to natural resource management. This is somewhat surprising, but a number of reports have appeared also on product evaluation, which could be a key application area in the future. CONCLUSIONS: Compared to marketing and transportation, the number of environmental conjoint studies is rather small but increasing, and the method has proven to work effectively in eliciting preferences on environmental issues. In environmental issues, experimenters often use choice experiments, especially concerning ecosystem management and environmental evaluations. When it comes to evaluating preferences concerning agriculture, forestry, energy and products, a more traditional approach of conjoint analysis is favoured. RECOMMENDATIONS AND PERSPECTIVES: Two new areas of application are identified in this review--environmental communication and expert elicitation. Conjoint analysis can thus be developed into a useful instrument for environmental risk analysis and communication, both of which are necessary for an efficient approach to risk governance.     

A Variance Estimator for Constrained Estimates of Change in Relative Categorical Frequencies

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.     

Determining Ecoregions for Environmental and GMO Monitoring Networks

A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.