Multi-component adsorption of copper,nickel and zinc from aqueous solutions onto activated carbon prepared from date stones

The removal of Cu²⁺, Ni²⁺, and Zn²⁺ ions from their multi-component aqueous mixture by sorption on activated carbon prepared from date stones was investigated. In the batch tests, experimental parameters were studied, including solution pH, contact time, initial metal ions concentration, and temperature. Adsorption efficiency of the heavy metals was pH-dependent and the maximum adsorption was found to occur at around 5.5 for Cu, Zn, and Ni. The maximum sorption capacities calculated by applying the Langmuir isotherm were 18.68 mg/g for Cu, 16.12 mg/g for Ni, and 12.19 mg/g for Zn. The competitive adsorption studies showed that the adsorption affinity order of the three heavy metals was Cu²⁺?>?Ni²⁺?>?Zn²⁺. The test results using real wastewater indicated that the prepared activated carbon could be used as a cheap adsorbent for the removal of heavy metals in aqueous solutions.     

Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches

Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R² (LL R²) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.     

Contamination status and potential release of trace metals in a mangrove forest sediment in Ho Chi Minh City,Vietnam

Can Gio district is located in the coastal area of Ho Chi Minh City, southern Vietnam. Discharge of wastewater from Ho Chi Minh City and neighboring provinces to the rivers of Can Gio has led to concerns about the accumulation of trace metals (As, Cu, Cr, Ni, Pb, and Zn) in the coastal sediments. The main objective of this study was to assess the distribution of As, Cu, Cr, Ni, Pb, and Zn in surface and core sediments and to evaluate the contamination status in relation to local background values, as well as the potential release of these selected trace metals from sediments to the water environment. Sediment characteristization, including determination of fine fraction, pH, organic matter, and major elements (Al, Fe, Ca, K, Mg, and S), was carried out to investigate which parameters affect the trace metal enrichment. Fine fraction and Al contents were found to be the controlling proxies affecting the distribution of trace metals while other sediment characteristics did not show any clear influence on trace metals’ distribution. Although As concentrations in the sediments were much higher compared to its reference value in other areas, the enrichment factor based on local background values suggests minor contamination of this element as well as for Cr, Cu, and Pb. Risk assessment suggested a medium to very high risk of Mn, Zn, and Ni under acidification. Of importance is also that trace metals in sediments were not easily mobilized by organic complexation based on their low extractabilities by ammonium-EDTA extraction.

     

Gender-specific responses to climate variability in a semi-arid ecosystem in northern Benin

Highly erratic rainfall patterns in northern Benin complicate the ability of rural farmers to engage in subsistence agriculture. This research explores gender-specific responses to climate variability in the context of agrarian Benin through a household survey (n = 260) and an experimental gaming exercise among a subset of the survey respondents. Although men and women from the sample population are equally aware of climate variability and share similar coping strategies, their specific land-use strategies, preferences, and motivations are distinct. Over the long term, these differences would likely lead to dissimilar coping strategies and vulnerability to the effects of climate change. Examination of gender-specific land-use responses to climate change and anticipatory learning can enhance efforts to improve adaptability and resilience among rural subsistence farmers.     

Computing sustainable manufacturing index with fuzzy analytic hierarchy process

The growing industrial interest in adopting sustainability programmes has ushered in studies regarding sustainability indicators which have continually flourished in current literature. However, limited attention is given to the development of priority ranking, which is an important input for any adopting firm. This paper presents a hybrid multi-criteria approach in determining priority areas in sustainable manufacturing (SM). Using fuzzy analytic hierarchy process to address uncertainty in hierarchical decision-making, this paper determines SM priority strategies and eventually identifies even lower level strategies. The computed sustainable manufacturing index is presented at both the organizational and operational levels for a real case study of an industrial plastic manufacturing firm. This work provides a detailed and transparent hierarchical decision-making approach based on SM framework, the use of which could be valuable to practicing managers across industries in their pursuit of greater sustainability.