A comprehensive review of hydrophobic silica and composite aerogels: synthesis,properties and recent progress towards environmental remediation and biomedical applications

Environmental Science and Pollution Research - The hydrophobicity of silica and composite aerogels has enabled them to acquire applications in a variety of fields. With remarkable structural,...     

Using decision science to evaluate global biodiversity indices

Global biodiversity indices are used to measure environmental change and progress toward conservation goals, yet few indices have been evaluated comprehensively for their capacity to detect trends of interest, such as declines in threatened species or ecosystem function. Using a structured approach based on decision science, we qualitatively evaluated 9 indices commonly used to track biodiversity at global and regional scales against 5 criteria relating to objectives, design, behavior, incorporation of uncertainty, and constraints (e.g., costs and data availability). Evaluation was based on reference literature for indices available at the time of assessment. We identified 4 key gaps in indices assessed: pathways to achieving goals (means objectives) were not always clear or relevant to desired outcomes (fundamental objectives); index testing and understanding of expected behavior was often lacking; uncertainty was seldom acknowledged or accounted for; and costs of implementation were seldom considered. These gaps may render indices inadequate in certain decision-making contexts and are problematic for indices linked with biodiversity targets and sustainability goals. Ensuring that index objectives are clear and their design is underpinned by a model of relevant processes are crucial in addressing the gaps identified by our assessment. Uptake and productive use of indices will be improved if index performance is tested rigorously and assumptions and uncertainties are clearly communicated to end users. This will increase index accuracy and value in tracking biodiversity change and supporting national and global policy decisions, such as the post-2020 global biodiversity framework of the Convention on Biological Diversity.     

Environmental impacts of new Coronavirus outbreak in Iran with an emphasis on waste management sector

Journal of Material Cycles and Waste Management - The COVID-19 pandemic have brought several environmental problems worldwide, among which management of municipal solid wastes (MSW) is of great...     

Reviewing the strategies for climate change and sustainability after the US defiance of the Paris Agreement: an AHP–GMCR-based conflict resolution approach

Environment, Development and Sustainability - In the landmark Paris Agreement, the global economies agreed to put forward their best efforts in mitigation and adaptation of climate change. The...     

Single and joint oxidative stress–related toxicity of sediment-associated cadmium and lead on Bellamya aeruginosa

Environmental Science and Pollution Research - The biotoxicity of heavy metals in sediments toward benthic organisms has evoked great concern for the health of freshwater ecosystems. This study...     

Health risk assessment of occupational exposure to styrene in Neyshabur electronic industries

Environmental Science and Pollution Research - Styrene is one of the essential components in making thousands of everyday products. Occupational exposure to styrene causes pulmonary, neurological,...     

Rapid estimation of compost enzymatic activity by spectral analysis method combined with machine learning

The aim of this study was to investigate the feasibility of using visible near-infrared (VisNIR) diffuse reflectance spectroscopy (DRS) as an easy, inexpensive, and rapid method to predict compost enzymatic activity, which traditionally measured by fluorescein diacetate hydrolysis (FDA-HR) assay. Compost samples representative of five different compost facilities were scanned by DRS, and the raw reflectance spectra were preprocessed using seven spectral transformations for predicting compost FDA-HR with six multivariate algorithms. Although principal component analysis for all spectral pretreatments satisfactorily identified the clusters by compost types, it could not separate different FDA contents. Furthermore, the artificial neural network multilayer perceptron (residual prediction deviation = 3.2, validation r² = 0.91 and RMSE = 13.38 μg g^?1 h^?1) outperformed other multivariate models to capture the highly non-linear relationships between compost enzymatic activity and VisNIR reflectance spectra after Savitzky–Golay first derivative pretreatment. This work demonstrates the efficiency of VisNIR DRS for predicting compost enzymatic as well as microbial activity.     

Evaluation of poly-aromatic hydrocarbons (PAHs) in the aquatic species of Suez Gulf water along El-Sokhna area to the Suez refineries

The Egyptian Red Sea environment especially along El-Sokhna area to the Suez refineries (Suez) is severely contaminated with organic compounds, as well as overfishing. This may be well contributory to recent serious declines in fish stocks. Fish embryos are also particularly vulnerable to oil exposure, even at extremely low concentrations of less than one part per billion. Consequently, even traces of oil pollution at levels often considered safe for wildlife can cause severe damage to fish. Sixteen polycyclic aromatic hydrocarbons (PAHs) were investigated in ten fish species of aquatic species by high performance liquid chromatography (HPLC). The compositions of PAHs determined in all samples were measured in order to use them as chemical markers for identifying different sources of PAH pollutants in the studied region. The total content of these16 PAHs ranged from 399.616 up to 67,631.779 ng/g wet weight. The data show that these values are considered to be alarmingly high enough to cause lethal toxicity effect by accumulation. All studied aquatic species samples are characterized by relatively high concentrations of the six-membered ring PAHs. The origin of PAHs in the collected samples is either petrogenic, biogenic, or mixed petrogenic and biogenic.     

Time‐based differences in the effects of positive and negative affectivity on perceived supervisor support and organizational commitment among newcomers

Building on the broaden‐and‐build theory and research on the negativity bias, this study examines how trait affectivity, as a stable predisposition predicting the pattern of emotional responding, shapes newcomers' perceptions of supervisor support and experience of organizational commitment. Using latent growth modeling and data collected at four points in time from newcomers (N = 158), we found the initial level of perceived supervisor support to mediate a negative relationship between negative affectivity and the level of commitment. Moreover, although newcomers experienced a general decrease in perceived supervisor support and a related decrease in commitment, those with high positive affectivity experienced a weaker decrease in perceived supervisor support, which led to a weaker decrease in commitment. Incidentally, positive affectivity was also positively related to the initial level of commitment. Two post hoc studies indicated that positive and negative affectivity exerted their effects controlling for state affect and replicated the relationship between change in perceived support and commitment. We discuss how these findings inform our understanding of trait affectivity's influence on newcomers' work attitudes.     

Study of the accumulation of contaminants by Cyperus alternifolius,Lemna minor,Eichhornia crassipes,and Canna × generalis in some contaminated aquatic environments

Environmental Science and Pollution Research - Today, environmental pollution, especially heavy metal pollution, is known as a new and possibly more dangerous pollutant than other environmental...