Assessing sustainable development in urban areas using cognitive mapping and MCDA

As interest in sustainability-related issues has increased over recent years, so too has urban sustainability risen to the fore, in academic, practitioner, and policymaking circles alike. Urban sustainability requires a balance between environmental concerns, the economy, and social development in urban areas. However, over the years, there has been an exponential increase in urban density, accompanied by increased economic activity and high levels of consumption, which have hindered urban planning and made the sustainable management of urban areas more difficult. It has therefore become increasingly necessary to combine the interests of the various stakeholders involved in – or affected by – urban planning measures, in order to achieve a balance between their needs, those of the environment and future generations, and the need for economic development. Sustainability evaluation models can in this sense be considered a baseline condition for sustainable development. However, most existing evaluation systems present limitations in terms of criteria identification and the calculation of the respective trade-offs. To address these issues, the current study aims to combine cognitive mapping and the Analytic Hierarchy Process (AHP) to prioritize the determinants of sustainable development in urban areas. The advantages and limitations of our proposal are also analyzed.     

Degradation of a Terephthalate-containing Polyester by a Thermophilic Microbial Consortium

Biomax^® is an aliphatic-aromatic polyester. The biodegradability of Biomax^® was studied at 58 °C using a laboratory scale bioreactor. The bioreactor was inoculated with bacteria derived from compost and supplemented with powdered Biomax^® and an additional energy source. After a period of acclimation, the microorganisms in the bioreactor were capable of metabolizing the major components of the polymer, i.e., TPA and ethylene glycol. TPA and ethylene glycol were detected in the bioreactor only when they were added. Degradation and disintegration of the powdered Biomax^® was monitored by laser diffraction. The particle size distribution of the powdered polymer progressively shifted toward smaller sizes until the diameters of the polymer particles were indistinguishable from bacteria. The types of microbes in the bioreactor were determined by analyzing 16S rRNA gene sequences. The bacteria belonged to 35 different groups, and the majority of the bacteria appeared to represent new species.     

Removal of toxic heavy metal ions from waste water by functionalized magnetic core–zeolitic shell nanocomposites as adsorbents

Functionalized magnetic core–zeolitic shell nanocomposites were prepared via hydrothermal and precipitation methods. The products were characterized by vibrating sample magnetometer, X-ray powder diffraction, Fourier transform infrared spectroscopy, nitrogen adsorption–desorption isotherms, and transmission electron microscopy analysis. The growth of mordenite nanocrystals on the outer surface of silica-coated magnetic nanoparticles at the presence of organic templates was well approved. The removal performance and the selectivity of mixed metal ions (Pb²⁺ and Cd²⁺) in aqueous solution were investigated via the sorption process. The batch method was employed to study the sorption kinetic, sorption isotherms, and pH effect. The removal mechanism of metal ions was done by chem–phys sorption and ion exchange processes through the zeolitic channels and pores. The experimental data were well fitted by the appropriate kinetic models. The sorption rate and sorption capacity of metal ions could be significantly improved by optimizing the parameter values.     

Hydrochemical Identification of Groundwater Resources and Their Changes under the Impacts of Human Activity in the Chah Basin in Western Iran

Chemical properties and pollution of water resources were studied in the Chah basin that is located in the Hamadan province, western Iran. Water quality was characterized according to its major constituents and the geological features of the area. Chemical analysis results indicate that groundwaters show wide concentration ranges in major inorganic ions, reflecting complex hydrochemical processes. Groundwater in the studied area is, for the most part, weakly to moderately mineralized and dominated by the calcium (Ca(2+)) and bicarbonate (HCO3-) ions. Within the basin, three different hydrogeochemical facies have been identified: Ca-HCO(3), Ca-SO(4) and Mg-HCO(3). The predominant water type of groundwater samples is the Ca-HCO(3) facies in the recharge area and has a tendency toward Mg-HCO(3) and Ca-SO(4) facies along the direction of water flow. The samples were classified into four groups based on chloride (Cl(-)) and nitrate (NO3-) concentrations and the processes that control water chemistry has been discussed. The results explained the importance of cation exchange, mineral weathering, and anthropogenic activities on groundwater chemistry. It was indicated that cation exchange and Cl-salt inputs are the major process controlling the water chemistry of the low Cl(-) and high [NO3-] (group 2) and high Cl(-) and [NO3-] (group 4). Groundwaters low in NO3- and high in Cl(-) (group 3) and low in NO3- and Cl(-) (group 1) are mainly affected by cation exchange and mineral dissolution. Pollution of groundwaters appeared to be affected by the application of fertilizers, irrigation practice, and solubility of mineral phases and discharge of domestic sewage. Measuring and predicting the mass loading of pollutant to groundwater from specific agricultural systems seems to be useful aids in controlling pollutions in groundwater.     

Assessment of anticipated performance index of some deciduous plant species under dust air pollution

Environmental Science and Pollution Research - Green vegetation improvement is an economical strategy to mitigate dust air pollution. The anticipated performance index (API) is considered a main...     

Soil phosphorus forms and their variations in selected paddy soils of Iran

Fractionation of soil phosphorus (P) can provide useful information for assessing the risk of soil P as the potential sources of eutrophication in aquatic systems. Little information exists on P forms in paddy soils of Isfahan Province in central Iran, where P fertilizers have been continuously applied for at least 45 years. The objectives of this study were to investigate concentrations and proportions of P forms in paddy soils and correlate the content of P forms with basic soil properties. Soil samples from three paddy sites were obtained, and soil P forms were determined by a modified Hedley fraction method. Results show that the total P concentrations ranged from 288 to 850 mg kg^?1 and were enriched in site 1. In all sites, the rank order of P fractions was HCl-P (CARB-P)?>?residual-P (RES-P)?>?NaOH-P (Fe-Al-P)?>?KCl-P (EXCH-P), indicating that Ca compounds are the main soil components contributing to P retention in these calcareous paddy soils. The EXCH-P represented on average?<?1 % of the total P, while the Fe-Al-P ranged 3.3–18 %. The CARB-P showed considerable contribution (63.6–85.6 %) to the total P. The Pearson correlation matrix indicated that Fe-Al-P only was positively correlated with total P, but did not show any significant correlations with other soil geochemical properties. Calcium-bound P fraction was significantly correlated with the clay, silt, cation exchange capacity, and total P.     

Geostatistical Evaluation of Spatial Variation Related to Groundwater Quality Database: Case Study for Arak Plain Aquifer,Iran

Geostatistical methods are one of the advanced techniques to interpolate groundwater quality data. Geostatistical interpolation techniques employ both the mathematical and the statistical properties of the measured points. Compiling the data distribution on spatial and temporal domain is of crucial importance in order to evaluate its quality and safety. The main purpose of this paper is to assess groundwater quality of Arak plain, Iran, by an unbiased interpolated method so called Kriging. Therefore, seven quality variables of Arak plain aquifer including TDS, SAR, EC, Na⁺, TH, Cl^?, and SO₄ ^2? have been analyzed, studied, and interpreted statistically and geostatistically. Utilized data in this study were collected from 97 water well samples in Arak plain, in 2012. After normalizing data, variogram as a geostatistical tool for defining spatial regression was calculated and experimental variograms have been plotted by GS⁺ software, then the best theoretical model was fitted to each variogram based on minimum RSS error. Cross validation was used to determine the accuracy of the estimated data. The uncertainty of the method could be well assessed via this method since the method not only gave the average error (around 0 in this study) but also gave the standard deviation of the estimations. Therefore, more than 3800 points were estimated by ordinary Kriging algorithm in places which have not been sampled. Finally, estimation maps of groundwater quality were prepared and map of estimation variance, EV, has been presented to assess the quality of estimation in each estimated point. Results showed that the Kriging method is more accurate than the traditional interpolation algorithms not honoring the spatial properties of the database.     

Sample Preparation Followed by High Performance Liquid Chromatographic (HPLC) Analysis for Monitoring Muconic Acid as a Biomarker of Occupational Exposure to Benzene

Factors affecting solid phase extraction (SPE) of trans,trans-muconic acid (ttMA), as a benzene biomarker, including sample pH, sample concentration, sample volume, sample flow rate, washing solvent, elution solvent, and type of sorbent were evaluated. Extracted samples were determined by HPLC-UV(highperformance liquid chromatography-ultraviolet). The analytical column was C18, UV wave length was 259 nm, and the mobile phase was H2O/methanol/acetic acid run at flow rate of 1 ml/min. A strong anion exchange silica cartridge was found successful in simplifying SPE. There was a significant difference between recoveries of ttMA when different factors were used (p < .001). An optimum recovery was obtained when sample pH was adjusted at 7. There was no significant difference when different sample concentrations were used (p > .05). The optimized method was then validated with 3 different pools of samples showing good reproducibility over 6 consecutive days and 6 within-day experiments.