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.     

The implementation of data reconciliation for evaluating a full-scale petrochemical wastewater treatment plant

Data reconciliation and mass balance analysis were conducted for the first time to improve the data obtained from a petrochemical wastewater treatment plant (WWTP), and the results were applied to evaluate the performance of the plant. Daily average values for 209 days from the inlet and outlet of the plant obtained from WWTP documentation center along with the results of four sampling runs in this work were used for data reconciliation and performance evaluation of the plant. Results showed that standard deviation and relative errors in the balanced data of each measurement decreased, especially for the process wastewater from 24.5 to 8.6 % for flow and 24.5 to 1.5 % for chemical oxygen demand (COD). The errors of measured data were −137 m³/day (−4.41 %) and 281 kg/day (7.92 %) for flow and COD, respectively. According to the balanced data, the removal rates of COD and 5-day biological oxygen demand (BOD₅) through the aeration unit were equal to 37 and 46 %, respectively. In addition, the COD and BOD₅ concentrations were reduced by about 61.9 % (2137 kg/day) and 78.1 % (1976 kg/day), respectively, prior to the biological process. At the same time, the removal rates of benzene, toluene, and styrene were 56, 38, and 69 %, respectively. The results revealed that about 40 % of influent benzene (75.5 kg/day) is emitted to the ambient air at the overhead of the equalization basin. It can be concluded that the volatilization of organic compounds is the basic mechanism for the removal of volatile organic compounds (VOCs) and it corresponds to the main part of total COD removal from the WWTP.

     

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.     

Drivers of local people’s participation in sustainable natural resource management: a case study in central Iran

The driving forces behind natural resource management (NRM) vary among countries. Most NRM programmes focus on biophysical drivers such as soil, water and vegetation, with little attention directed towards the nuanced sociocultural and religious drivers of sustainable natural resource management (SNRM) practices. This paper explores those understudied drivers that influence local people’s participation (LPP) in SNRM in Isfahan, Iran. Using a multi-stage stratified sampling method, we selected 200 natural resource experts and natural resource users to complete a questionnaire about their perceptions of SNRM. Results reveal that sociocultural and religious beliefs are the major drivers of SNRM. The results also indicate that subsidiary drivers include: a sense of responsibility towards SNRM; the conviction that natural resources belong to God and should therefore be preserved; participation to preserve natural resources because of training courses and media influence; a long-established custom of preserving natural resources; and the specific impact of environmental television programmes. Demographic analysis finds a significant relationship between educational level and LPP in SNRM. This study’s results therefore suggest that natural resource managers would benefit from a deeper understanding of the local sociocultural and religious contexts that motivate people to participate in SNRM.     

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.     

Water and waste load allocation in rivers with emphasis on agricultural return flows: application of fractional factorial analysis

In this paper, a new methodology is developed to handle parameter and input uncertainties in water and waste load allocation (WWLA) in rivers by using factorial interval optimization and the Soil, Water, Atmosphere, and Plant (SWAP) simulation model. A fractional factorial analysis is utilized to provide detailed effects of uncertain parameters and their interaction on the optimization model outputs. The number of required optimizations in a fractional factorial analysis can be much less than a complete sensitivity analysis. The most important uncertain inputs and parameters can be also selected using a fractional factorial analysis. The uncertainty of the selected inputs and parameters should be incorporated real time water and waste load allocation. The proposed methodology utilizes the SWAP simulation model to estimate the quantity and quality of each agricultural return flow based on the allocated water quantity and quality. In order to control the pollution loads of agricultural dischargers, it is assumed that a part of their return flows can be diverted to evaporation ponds. Results of applying the methodology to the Dez River system in the southwestern part of Iran show its effectiveness and applicability for simultaneous water and waste load allocation in rivers. It is shown that in our case study, the number of required optimizations in the fractional factorial analysis can be reduced from 64 to 16. Analysis of the interactive effects of uncertainties indicates that in a low flow condition, the upstream water quality would have a significant effect on the total benefit of the system.     

Monitoring of trace amounts of heavy metals in different food and water samples by flame atomic absorption spectrophotometer after preconcentration by amine-functionalized graphene nanosheet

We are introducing graphene oxide modified with amine groups as a new solid phase for extraction of heavy metal ions including cadmium(II), copper(II), nickel(II), zinc(II), and lead(II). Effects of pH value, flow rates, type, concentration, and volume of the eluent, breakthrough volume, and the effect of potentially interfering ions were studied. Under optimized conditions, the extraction efficiency is >97 %, the limit of detections are 0.03, 0.05, 0.2, 0.1, and 1 μg L^?1 for the ions of cadmium, copper, nickel, zinc, and lead, respectively, and the adsorption capacities for these ions are 178, 142, 110, 125, and 210 mg g^?1. The amino-functionalized graphene oxide was characterized by thermogravimetric analysis, transmission electron microscopy, scanning electron microscopy, and Fourier transform infrared spectrometry. The proposed method was successfully applied in the analysis of environmental water and food samples. Good spiked recoveries over the range of 95.8–100.0 % were obtained. This work not only proposes a useful method for sample preconcentration but also reveals the great potential of modified graphene as an excellent sorbent material in analytical processes.     

Rapid spectrophotometric determination of trace amounts of palladium in water samples after dispersive liquid–liquid microextraction

A simple, rapid, and efficient dispersive liquid–liquid microextraction method, followed by UV–Vis spectrophotometry was developed for the preconcentration and determination of Pd ions in water samples. Pd ions react with α-furildioxime (chelating agent) to form a hydrophobic complex. Various parameters were altered to study and optimize their effects on the extraction efficiency, such as pH, ligand concentration, the type and volume of extraction and dispersive solvents, extraction time, and salt concentration. Under optimized conditions, the method exhibited an enrichment factor (C _org/C _aq) of 25 and recovery more than 98 % within a very short extraction time. The linearity of the method ranged from 10 to 200 μg?L^?1. The limit of detection was 1.1 μg?L^?1. The relative standard deviation for the concentration of 100 μg?L^?1 of Pd was 2.3 % (n?=?10). Finally, the developed method was successfully applied to the extraction and determination of Pd in tap, river, mineral, and sea water samples.