Global trends and characteristics of vermicompost research over the past 24 years

This study aims to investigate a practical bibliometric analysis and discuss its trends to evaluate the global scientific production of vermicompost research from 1993 to 2017 and explain its several advantages to our environment and waste management. The data were from the database of the Science Citation Index (SCI) published by the ISI Web of Science and illustrated by Excel and VOS viewer. According to the 2174 publications, this article was conducted based on four significant aspects, including publications growth trends, countries/territories, categories and journals, and keywords co-occurrence network analysis. This study revealed remarkable positive growth trends of the research and the number of articles related to vermicompost over the last 24 years with more countries participating in this field. Although the USA has the most collaboration with other countries, developing countries such as India, which was the most productive one, made significant progress in sharing articles within the study period. Based on analyses of dominant categories, the most common subject category was Environmental Science, and the most productive journal was Bioresource Technology. Finally, we analyzed author keywords to the extracted research article emphasis. The results showed that mainstream research claim vermicomposting with the help of Eisenia fetida earthworms which converts several wastes such as sewage sludge to a soil improvement fertilizer. It is an essential approach to eliminate heavy metals from the wastes and provide essential nutrients to improve the growth and yield of plants.

     

Critical reflections on the theory and practice of social sustainability in the built environment – a meta-analysis

This article presents a critical reflection on the theory and practice of social sustainability in the built environment, identifies areas of agreement and disagreement, explores theoretical and conceptual gaps and challenges, and suggests practical implications for future research and urban policy. It argues that despite revisionist approaches which challenge the tripartite structure of sustainable development, social dimension of sustainability remains an essential valid pillar. Utilising a qualitative meta-analysis methodology for undertaking critical analysis of previous research and publications on the topic, key themes of theory and practice of social sustainability are identified and critically examined. Accordingly, 10 key formative characteristics of social sustainability and their research and policy implications are introduced. The article concludes with institutional observations for policy-makers to achieve greater success in addressing largely underestimated dimensions of social sustainability in urban settings.     

Assessing the effects of dam building on land degradation in central Iran with Landsat LST and LULC time series

This study aimed to analyze the impact of Zayandehrood Dam on desertification using the spatio-temporal dynamics of land use/land cover (LULC) and land surface temperature (LST) in an arid environment in central Iran from 1987 to 2014. The LULC and LST images were calculated from Landsat TM, ETM+, and OLI data, and their accuracies were assessed against reference data using error matrix and linear regression analysis. Results showed that salty and bare lands increased up to 57,302 ha, while agricultural lands declined substantially (28,275.58 ha) in the region. The changes in LULC classes resulted in dramatic variations in LST values. The average temperature showed a 5.03 °C increase, and the minimum temperature increased by 5.66 °C. LST had an increasing trend in bare lands (8.74 °C), poor rangelands (6.8 °C), agricultural lands (9.46 °C), salty lands (9.6 °C), and residential areas (3.18 °C) in this 27-year period. Rainfall and temperature trend analysis revealed that the main cause of these extreme changes in LULC and LST was largely attributed to the drying up of Zayandehrood River due to dam construction and allocating water mainly for industrial sectors. Results indicate that in addition to LULC changes, the spatio-temporal variations of LST can be used as an effective index in desertification assessment and monitoring in arid environments.     

Laboratory waste minimization by recovery of silver as nano-silver colloidal dispersion from waste silver chloride

The use of cyclic experiments, where the product of one reaction becomes the starting material for the next experiment, was proposed as an effective protocol for waste minimization in an educational lab. A simple, cheap and pollution-free method was developed for recovering silver as nano-silver colloidal dispersion from waste silver chloride in the laboratories of the Faculty of Health, Safety and Environment. Silver nanoparticles of the size 5–18 nm were recovered in the presence of sodium borohydride as a reducing agent and polyvinylpyrrolidone as a stabilizer agent. The nano-silver particles were studied for their formation, structure, stability and size using UV–Vis spectroscopy, transmission electron microscopy and dynamic light scattering techniques. The antibacterial assays of nanoparticles showed satisfactory results for Escherichia coli ATCC25922, Staphylococcus aureus ATCC 29213, and Acinetobacter baumanii (Clinical isolate). A laboratory experiment was designed in which students synthesize yellow colloidal silver solution from chemical waste silver chloride and estimate particle size using visible spectroscopy.     

PREDICTING EROSION AND DEPOSITION ON A STRIPMINED AND RECLAIMED AREA1

ABSTRACT A rill-interrill erosion model was applied to a mined and reclaimed area. Soil loss from the interrill areas was estimated by the Universal Soil Loss Equation (USLE). The model considers the fate and ultimate disposition of the sediment from interrill areas along with the fate and destination of soil materials detached by the rill flow. The net sediment loss was predicted by comparing, for a given flow, the amounts of eroded soil to rill transport capacity. When applied to a selected stripmined and reclaimed site the model displayed the location of contributing areas and the amount of erosion and deposition. The predicted areal distribution of erosion and deposition was compared to measured data. Agreement between the predicted and measured values was within 25 percent.     

Estimating and mapping forest biomass using regression models and Spot-6 images (case study: Hyrcanian forests of north of Iran)

Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.     

Groundwater depth and elevation interpolation by kriging methods in Mohr Basin of Fars province in Iran

Prediction of groundwater depth and elevation is important in quantitative water management especially in arid areas. There are several basins in southwest of Iran, in Zagross Mountain, in which the water wells are distributed along a narrow elliptic ring band around the region. To find the most applicable interpolation method, both of the groundwater depth and elevation are predicted by different kriging methods. It is found that the groundwater elevation and depth can be predicted by different methods. Furthermore, it is found that the methods in which the trend is eliminated predicted the groundwater elevation and depth in central part of the region is with less standard error. Furthermore, the methods with no trend elimination, predicted the groundwater depths with less error near the water wells. Dividing the area to hydro-geologically homogeneous sub-areas improved the interpolation precision.