Optimized forest degradation model (OFDM): an environmental decision support system for environmental impact assessment using an artificial neural network

The purpose of this article is Artificial Neural Network (ANN) modeling using ecological and associated factors with forest degradation to predict the degradation of ecosystem, thereby enabling us to assess the environmental impacts of forest projects as an Environmental Decision Support System (EDSS). Results of the Multi-Layer Feed-Forward Network (MLFN), trained for Optimized Forest Degradation Model (OFDM), indicate that the performance of OFDM is more than other degradation models. Changes in forest management activities with higher value in sensitivity analysis help forest managers to decrease OFDM entity and environment impacts. The system is an intelligent EDSS, which allows the decision-maker to model criteria in forest degradation in order to reach and employ the optimal allocation plan. Considering results, multi criteria decision analysis (MCDA) approaches based on ANN, is an encouraging and robust method for solving MCDA problems.     

Modelling the adsorption of mercury onto natural and aluminium pillared clays

Introduction

The removal of heavy metals by natural adsorbent has become one of the most attractive solutions for environmental remediation. Natural clay collected from the Late Cretaceous Aleg formation, Tunisia was used as a natural adsorbent for the removal of Hg(II) in aqueous system.

Methods

Physicochemical characterization of the adsorbent was carried out with the aid of various techniques, including chemical analysis, X-ray diffraction, Fourier transform infrared and scanning electron micrograph. Batch sorption technique was selected as an appropriate technique in the current study. Method parameters, including pH, temperature, initial metal concentration and contact time, were varied in order to quantitatively evaluate their effects on Hg(II) adsorption onto the original and pillared clay samples. Adsorption kinetic was studied by fitting the experimental results to the pseudo-first-order and pseudo-second-order kinetic models. The adsorption data were also simulated with Langmuir, Freundlich and Temkin isotherms.

Results

Results showed that the natural clay samples are mainly composed of silica, alumina, iron, calcium and magnesium oxides. The sorbents are mainly mesoporous materials with specific surface area of <250 m² g^?1. From the adsorption of Hg(II) studies, experimental data demonstrated a high degree of fitness to the pseudo-second-order kinetics with an equilibration time of 240 min. The equilibrium data showed the best model fit to Langmuir model with the maximum adsorption capacities of 9.70 and 49.75 mg g^?1 for the original and aluminium pillared clays, respectively. The maximum adsorption of Hg(II) on the aluminium pillared clay was observed to occur at pH 3.2. The calculated thermodynamic parameters (?G°, ?H° and ?S°) showed an exothermic adsorption process. The entropy values varied between 60.77 and 117.59 J?mol^?1 K^?1, and those of enthalpy ranged from 16.31 to 30.77 kJ mol^?1. The equilibrium parameter (R _L) indicated that the adsorption of Hg(II) on Tunisian smectitic clays was favourable under the experimental conditions of this study.

Conclusion

The clay of the Aleg formation, Tunisia was found to be an efficient adsorbent for Hg(II) removal in aqueous systems.     

Nutrient concentrations within and below root zones from applied chicken manure in selected Hawaiian soils

The objective of this study was to evaluate the effects of chicken manure (CM) application rates on nutrient concentrations within and below the root zone of sweet corn (Zea mays L. subsp. mays) under Hawaiian conditions. The research was conducted in leeward (Poamoho) and windward (Waimanalo) areas of Oahu, Hawaii, where contrasts exist in both climatic and soil conditions. Suction cup were used to collect soil solutions from 30 and 60 cm depths. Soil solutions were collected six times during the growing season at each location and analyzed for different nutrients (N, P, K, Ca, Mg, Na, Fe, Mn, Zn, and Cu), nitrate-nitrogen (NO₃–N), ammonium-nitrogen (NH₄–N), electrical conductivity (EC), and pH. Analysis showed that CM rates significantly affected the concentration of macro-nutrients below the root zone at Poamoho and within the root zone at Waimanalo. In general, nutrient concentration increased with the increasing rates of CM application. There was a significant effect of CM on micro-nutrients except below the root zone at Poamoho. CM significantly affected NO₃–N concentration within the root zone for 15, 60 days after planting (DAP) at Poamoho, and 16, 28 DAP at Waimanalo. The effect was also significant on total nitrogen (N) concentration in the root zone across the two growing seasons at Waimanalo. There was a highly significant correlation between total N and NO₃–N, and EC within and below the root zone.     

A bibliometric study on blockchain-based supply chain: a theme analysis,adopted methodologies,and future research agenda

Environmental Science and Pollution Research - The emergence of the underlying blockchain technology of bitcoin has gained extensive attention from researchers and practitioners. As distributed...     

Polylactic acid synthesis,biodegradability, conversion to microplastics and toxicity: a review

Global pollution by plastics derived from petroleum has fostered the development of carbon–neutral, biodegradable bioplastics synthesized from renewable resources such as modern biomass, yet knowledge on the impact of bioplastics on ecosystems is limited. Here we review the polylactic acid plastic with focus on synthesis, biodegradability tuning, environmental conversion to microplastics, and impact on microbes, algae, phytoplankton, zooplankton, annelids, mollusk and fish. Polylactic acid is a low weight semi-crystalline bioplastic used in agriculture, medicine, packaging and textile. Polylactic acid is one of the most widely used biopolymers, accounting for 33% of all bioplastics produced in 2021. Although biodegradable in vivo, polylactic acid is not completely degradable under natural environmental conditions, notably under aquatic conditions. Polylactic acid disintegrates into microplastics faster than petroleum-based plastics and may pose severe threats to the exposed biota.

     

The need for constructing endangered fish habitats that conform to climate-driven flow changes in a western U.S. river

Warmwater fish habitat in the San Juan River of the southwestern United States has been reduced by over 30% as a result of water depletion, reservoir inundation, and cold-water dam releases combined with drought-related changes in hydrology. This reduction and a suite of other factors have contributed to declines in native fish populations including the federally endangered Colorado Pikeminnow (Ptychocheilus lucius) and Razorback Sucker (Xyrauchen texanus). Conservation efforts for these species include determining flow needs; protecting, managing, and augmenting habitats; and stocking hatchery fish. But the young of stocked fish have low survival due largely to a paucity of nursery habitat not being reformed and maintained under current conditions. Flow recommendations for Navajo Dam releases designed to mimic the river's natural hydrograph have not been met due to water shortages, and the desired outcomes of increased channel complexity and enhanced fish habitat have not been observed. Forecasted hydrology that includes ongoing drought shows that achieving the flow targets through further dam reoperations is unlikely. Mechanical construction of early life-stage habitats is a highly recommended complement to flow management for offsetting the effects of flow reduction and habitat loss. Habitats with features that are effective and resilient under a range of flows are important in counterbalancing the effects of climate change.     

Synthesis of CS/PVA Biodegradable Composite Nanofibers as a Microporous Material with Well Controllable Procedure Through Electrospinning

In this study, we have showed a facile route for fabrication of a novel microporous material based on chitosan (CS) and poly(vinyl alcohol) (PVA) biodegradable nanofibers that have high specific surface area, considerable porosity, and small diameter. Scanning electron microscopy, thermogravimetric analysis, differential scanning calorimetry, fourier transform infrared spectroscopy, Brunauer–Emmett–Teller surface area analysis, and CHNS/O elemental analyser were applied to characterize the fabricated CS/PVA composite nanofibers. Moreover, the influences of spinning conditions including concentration, voltage, electrospinning distance, and flow rate, on size distribution and pore diameter of the final product were systematically studied using 2^k?1 factorial design experiments, and the response surface optimization was used for determining the best synthesis parameter. The results obtained from 2^K?1 factorial design experiments showed that electrospinning parameters influenced the size distribution and pore diameter of the CS/PVA microporous material. Based on the response surface methodology, the CS/PVA product could be obtained with a high microporous diameter of 1.8 nm and a small diameter distribution of 15.0 nm under optimized conditions. The obtained results showed that the fabricated samples could be utilized in different applications.     

Effect of different biochars amendment on soil biological indicators in a calcareous soil

Environmental Science and Pollution Research - Previous studies suggest that biochar has potential to benefit soil when used as an amendment, but only few studies have investigated how the...     

Monitoring and assessment of seasonal land cover changes using remote sensing: a 30-year (1987–2016) case study of Hamoun Wetland,Iran

The availability of Landsat data allows improving the monitoring and assessment of large-scale areas with land cover changes in rapid developing regions. Thus, we pretend to show a combined methodology to assess land cover changes (LCCs) in the Hamoun Wetland region (Iran) over a period of 30-year (1987–2016) and to quantify seasonal and decadal landscape and land use variabilities. Using the pixel-based change detection (PBCD) and the post-classification comparison (PCC), four land cover classes were compared among spring, summer, and fall seasons. Our findings showed for the water class a higher correlation between spring and summer (R²?=?0.94) than fall and spring (R²?=?0.58) seasons. Before 2000, ~?50% of the total area was covered by bare soil and 40% by water. However, after 2000, more than 70% of wetland was transformed into bare soils. The results of the long-term monitoring period showed that fall season was the most representative time to show the inter-annual variability of LCCs monitoring and the least affected by seasonal-scale climatic variations. In the Hamoun Wetland region, land cover was highly controlled by changes in surface water, which in turn responded to both climatic and anthropogenic impacts. We were able to divide the water budget monitoring into three different ecological regimes: (1) a period of high water level, which sustained healthy extensive plant life, and approximately 40% of the total surface water was retained until the end of the hydrological year; (2) a period of drought during high evaporation rates was observed, and a mean wetland surface of about 85% was characterized by bare land; and (3) a recovery period in which water levels were overall rising, but they are not maintained from year to year. After a spring flood, in 2006 and 2013, grassland reached the highest extensions, covering till more than 20% of the region, and the dynamics of the ecosystem were affected by the differences in moisture. The Hamoun wetland region served as an important example and demonstration of the feedbacks between land cover and land uses, particularly as pertaining to water resources available to a rapidly expanding population.