Re-examining the water affordability: A comparison of alternative measures

Water affordability is determined by the percentage of income households that must allocate to municipal water services, while factoring in essential or basic needs water use. With the rise in water prices reported in most areas of the country along with somewhat stagnant income growth—a combination that suggests ceteris paribus—more of a household's disposable income is being spent on water services. This paper adds to the discussion in three ways. First, given the lack of a consistent definition for “affordability” and the subjective connotation associated with such a term, we develop and compare five different water expenditure ratios, including two different measures of water for essential needs, as well as measures for indoor, efficient, and actual water use. Second, because of the granularity of our data, we illustrate how such “affordability” measures can vary significantly within a water district and thus highlight how using district- or county-level income measures can mask the degree to which affordability is an issue for households living in low-income block groups. Our results indicate that the choice of income measure and type of water service use can influence affordability measures substantially.     

How renewable energy and service growth influence environmental quality: Evidence from a sustainable development perspective

The present study inspects the relationships between the carbon dioxide (CO₂) emissions, real GDP, renewable and non-renewable energy consumption, as well as the service growth for top ten countries (TTC) in service activities. The empirical modeling used in the study involves the procedures of cointegration and tests of Granger causality to inspect the dynamic interaction between the variables during the period from 1980 to 2018. The results of the present study suggest that the variables are cross-sectionally dependent. In addition, the variables appear to be cointegrated based on several tests. The long-run outcomes revealed an inversed U-shaped form between emissions-GDP proving the validity of the environmental Kuznets curve assumption. The fully modified ordinary least squares and dynamic OLS estimates show that the non-renewable energy and economic growth contribute to the increase of CO₂ emissions, while service value-added leads to decrease emissions. Furthermore, the renewable energy coefficient comes through as negative but insignificant for the selected panel. The TTC in service should stimulate the usage of renewable energy in various service events for following the path of sustainable development. Devising the investment plans associated with the use of renewable energies is quite essential for the advancement of the service sector leading to mitigating emissions portion.     

Analytical solution to evaluate salt precipitation during CO2 injection in saline aquifers

Carbon dioxide sequestration in deep saline aquifers is a means of reducing anthropogenic atmospheric emissions of CO₂. Among various mechanisms, CO₂ can be trapped in saline aquifers by dissolution in the formation water. Vaporization of water occurs along with the dissolution of CO₂. Vaporization can cause salt precipitation, which reduces porosity and impairs permeability of the reservoir in the vicinity of the wellbore, and can lead to reduction in injectivity. The amount of salt precipitation and the region in which it occurs may be important in CO₂ storage operations if salt precipitation significantly reduces injectivity. Here we develop an analytical model, as a simple and efficient tool to predict the amount of salt precipitation over time and space. This model is particularly useful at high injection velocities, when viscous forces dominate.First, we develop a model which treats the vaporization of water and dissolution of CO₂ in radial geometry. Next, the model is used to predict salt precipitation. The combined model is then extended to evaluate the effect of salt precipitation on permeability in terms of a time-dependent skin factor. Finally, the analytical model is corroborated by application to a specific problem with an available numerical solution, where a close agreement between the solutions is observed. We use the results to examine the effect of assumptions and approximations made in the development of the analytical solution. For cases studied, salt saturation was a few percent. The loss in injectivity depends on the degree of reduction of formation permeability with increased salt saturation. For permeability-reduction models considered in this work, the loss in injectivity was not severe. However, one limitation of the model is that it neglects capillary and gravity forces, and these forces might increase salt precipitation at the bottom of formation particularly when injection rate is low.     

The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R² were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R² confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.     

The determinants of environmental quality in the SAARC region: a spatial heterogeneous panel data approach

Environmental Science and Pollution Research - In recent years, financial development, trade policies, and energy performance have attracted attention due to their behavior on environmental...     

Comparison the effects of bioaugmentation versus biostimulation on marine microbial community by PCR–DGGE: A mesocosm scale

In order to better understand the effects of biostimulation and bioaugmentation processes on a marine microbial community, three different mesocosm experiments were planned. Natural seawater(10.000 L) was artificially polluted with crude oil(1 L) and(1) inorganic nutrients(Biostimulating Mesocosm, BM),(2) inorganic nutrients and an inoculum of Alcanivorax borkumensis SK2(Single Bioaugmentation Mesocosm, SBM),(3) inorganic nutrients and inoculums of A. borkumensis SK2 and Thalassolituus oleivorans MIL-1(Consortium Bioaugmentation Mesocosm, CBM). During the experimental period(20 days), samples were taken from each mesocosm and the community structure was analyzed by PCR–DGGE. The 16 S r RNA gene DGGE banding patterns and sequence analysis demonstrated that biostimulation had the lowest effect on microbial biodiversity in the mesocosms; however, the biodiversity of the marine microbial community dramatically decreased in the CBM(Shannon index was 0.6 in T3). The community structures among the three mesocosms were also markedly different,and major bacteria derived from DGGE bands were related to uncultured Gamma Proteobacteria. The biodegradation results show that the Single Bioaugmentation Mesocosm(SBM) system had the highest percentage of degradation(95%) in comparison to the BM mesocosm(80%) and CBM(70%).     

Process development for recovery of copper and precious metals from waste printed circuit boards with emphasize on palladium and gold leaching and precipitation

A novel hydrometallurgical process was proposed for selective recovery of Cu, Ag, Au and Pd from waste printed circuit boards (PCBs). More than 99% of copper content was dissolved by using two consecutive sulfuric acid leaching steps in the presence of H₂O₂ as oxidizing agents. The solid residue of 2nd leaching step was treated by acidic thiourea in the presence of ferric iron as oxidizing agent and 85.76% Au and 71.36% Ag dissolution was achieved. The precipitation of Au and Ag from acidic thiourea leachate was investigated by using different amounts of sodium borohydride (SBH) as a reducing agent. The leaching of Pd and remained gold from the solid reside of 3rd leaching step was performed in NaClO-HCl-H₂O₂ leaching system and the effect of different parameters was investigated. The leaching of Pd and specially Au increased by increasing the NaClO concentration up to 10 V% and any further increasing the NaClO concentration has a negligible effect. The leaching of Pd and Au increased by increasing the HCl concentration from 2.5 to 5 M. The leaching of Pd and Au were endothermic and raising the temperature had a positive effect on leaching efficiency. The kinetics of Pd leaching was quite fast and after 30 min complete leaching of Pd was achieved, while the leaching of Au need a longer contact time. The best conditions for leaching of Pd and Au in NaClO-HCl-H₂O₂ leaching system were determined to be 5 M HCl, 1 V% H₂O₂, 10 V% NaClO at 336 K for 3 h with a solid/liquid ratio of 1/10. 100% of Pd and Au of what was in the chloride leachate were precipitated by using 2 g/L SBH. Finally, a process flow sheet for the recovery of Cu, Ag, Au and Pd from PCB was proposed.