Application of soft computing to predict water quality in wetland

Prediction of water quality is a critical issue because of its significant impact on human and ecosystem health. This research aims to predict water quality index (WQI) for the free surface wetland using three soft computing techniques namely, adaptive neuro-fuzzy system (ANFIS), artificial neural networks (ANNs), and group method of data handling (GMDH). Seventeen wetland points for a period of 14 months were considered for monitoring water quality parameters including conductivity, suspended solid (SS), biochemical oxygen demand (BOD), ammoniacal nitrogen (AN), chemical oxygen demand (COD), dissolved oxygen (DO), temperature, pH, phosphate nitrite, and nitrate. The sensitivity analysis performed by ANFIS indicates that the significant parameters to predict WQI are pH, COD, AN, and SS. The results indicated that ANFIS with Nash-Sutcliffe Efficiency (NSE = 0.9634) and mean absolute error (MAE = 0.0219) has better performance to predict the WQI comparing with ANNs (NSE = 0.9617 and MAE = 0.0222) and GMDH (NSE = 0.9594 and MAE = 0.0245) models. However, ANNs provided a comparable prediction and the GMDH can be considered as a technique with an acceptable prediction for practical purposes. The findings of this study could be used as an effective reference for policy makers in the field of water resource management. Decreasing variables, reduction of running time, and high speed of these approaches are the most important reasons to employ them in any aquatic environment worldwide.

     

Assessing and selecting interventions for river water quality improvement within the context of population growth and urbanization: a case study of the Cau River basin in Vietnam

In this study, a multi-criteria methodology is proposed to identify and prioritize interventions for water quality improvement with the aid of computer simulation models. The methodology can be used to elaborate and compare future socio-economic development scenarios to select the best interventions based on three criteria: (1) ideas of experts and stakeholders about the importance of scenarios, (2) impacts of each scenario on surface water quality in watershed, and (3) benefit–cost analysis for each scenario. A score is computed for each scenario based on a weighted sum technique which enables to take into consideration different level of importance for the three criteria. The methodology is applied to Cau River basin in Vietnam, with the aid of a computer tool, to assess interventions for river water quality improvement within the context of population growth and urbanization. The results show that fast future population growth in upstream has significant impacts. In 2020, an increase of 116 % of the population in Bac Kan town can lead to an increase of 120 and 135 % in BOD₅ and NH₄ ⁺ median concentrations, respectively, with the implementation of a treatment plant for 10,000 people in Bac Kan town. Therefore, the increase of the domestic wastewater treatment plant’s capacity in Bac Kan town, at least twice as the projection of local government, is necessary. These results will help decision makers to select the best interventions for Cau River basin management.     

Determining contamination level of heavy metals in road dust from busy traffic areas with different characteristics

This study identified the levels and sources of heavy metal contamination in road dust from busy traffic areas in a typical industrial city in Korea. This study compared the total concentrations, as determined by aqua regia digestions and atomic absorption spectroscopy, of cadmium (Cd), copper (Cu), lead (Pb), zinc (Zn) and nickel (Ni) in the road dust from areas with different characteristics such as traffic rotaries, downtown areas, circulation roads, and asphalt and concrete highways. The contamination levels of the heavy metals in the road dust were evaluated using the contamination factor and the degree of contamination. The contamination levels of the heavy metals in the road dust were highly dependent on traffic volume and atmospheric dispersion from traffic rotaries. Industrial emissions and the frequency of brake use and vehicles coming to a complete stop were additional factors that affected the contamination levels in downtown areas. The concrete highway had higher contamination levels of the heavy metals than the asphalt highway. Vehicle speed was also a strong contributing factor to the degree of contamination of heavy metals in the road dust from the circulation roads and highways.     

Advanced Aerogels from Wool Waste Fibers for Oil Spill Cleaning Applications

Journal of Polymers and the Environment - Oil spills causes severe degradation to marine ecosystems and poses long term health effects on many animals on the food chain, including humans. A...     

Green environmental technologies and waste utilization

Environmental Science and Pollution Research -     

Electron microscopy study of biosorbents from marine macro alga Durvillaea potatorum

Biosorbents derived from the biomass of marine algae have shown to have high uptake capacities for heavy metals and the internal structure has been generally assumed to be pseudo-homogenous. In this paper, the microstructures of biosorbents derived from Australian marine alga Durvillaea poratorum were analysed using scanning electron microscopy. The structural components of the biosorbent resembled fiber-like cylinders. The internal structure was a highly connected network of cylinders with varying sizes. Methods of drying and pre-treatment of the biomass also affected the details of the internal structure. Calcium chloride followed by thermal treatment provided the most uniform cylinder networks for the biosorbents. Heavy metal Cu2+ and Cd2+ binding in the biomass was confirmed by using an electron probe microanalyser.     

Optimal Control Models and Elicitation of Attitudes towards Climate Damages

This paper examines the consequences of various attitudes towards climate damages through a family of stochastic optimal control models (RESPONSE): cost-efficiency for a given temperature ceiling; cost-benefit analysis with a pure preference for current climate regime and full cost-benefit analysis. The choice of a given proxy of climate change risks is actually more than a technical option. It is essentially motivated by the degree of distrust regarding the legitimacy of an assessment of climate damages and the possibility of providing in due time reliable and non controversial estimates. Our results demonstrate that (a) for early decades abatement, the difference between various decision-making frameworks appears to matter less than the difference between stochastic and non stochastic approach given the cascade of uncertainty from emissions to damages; (b) in a stochastic approach, the possibility of non-catastrophic singularities in the damage function is sufficient to significantly increase earlier optimal abatements; (c) a window of opportunity for action exists up to 2040: abatements further delayed may induce significant regret in case of bad news about climate response or singularities in damages.     

Comparative study on water-soluble inorganic ions in PM2.5 from two distinct climate regions and air quality

Recently, air quality has significantly improved in developed country, but that issue is of concern in emerging megacity in developing country.In this study, aerosols and their precursor gas were collected by NILU filter pack at two distinct urban sites during the winter and summer in Osaka, Japan and dry and rainy seasons in Ho Chi Minh City(HCMC),Vietnam.The aims are to investigate the contribution of water-soluble inorganic ions(WSIIs) to PM_(2.5), thermodynamic characterization and possible formation pathway of secondary inorganic aerosol(SIA).The PM_(2.5) concentration in Osaka(15.8 μg/m~3) is lower than that in HCMC(23.0 μg/m~3), but the concentration of WSIIs in Osaka(9.0 μg/m~3) is two times higher than that in HCMC(4.1 μg/m~3).Moreover, SIA including NH_4~+, NO_3~-and SO_4~(2-)are major components in WSIIs accounting for 90% and 76%(in molar) in Osaka and HCMC,respectively.Thermodynamic models were used to understand the thermodynamic characterization of urban aerosols.Overall, statistical analysis results indicate that very good agreement(R~2 0.8) was found for all species, except for nitrate aerosol in HCMC.We found that when the crustal species present at high amount, those compositions should be included in model calculation(i.e.in the HCMC situation).Finally, we analyzed the characteristics of NH_4~+– NO_3~-– SO_4~(2-)system.A possible pathway to produce fine nitrate aerosol in Osaka is via the homogeneous reaction between NH_3 and HNO_3, while nonvolatile nitrate aerosols can be formed by the heterogeneous reactions in HCMC.     

A comprehensive simulation approach for pollutant bio-transformation in the gravity sewer

A comprehensive pollutant transformation model for sewer systems is established. The model comprises fermentation, sulfate reduction and ammonification processes. Biochemical reactions related to distinct carbon sources are depicted in the model. Pollutant transformation is attributed to different biochemical reaction processes. Presently, several activated sludge models (ASMs) have been developed to describe a few biochemical processes. However, the commonly used ASM neither clearly describe the migratory transformation characteristics of fermentation nor depict the relationship between the carbon source and biochemical reactions. In addition, these models also do not describe both ammonification and the integrated metabolic processes in sewage transportation. In view of these limitations, we developed a new and comprehensive model that introduces anaerobic fermentation into the ASM and simulates the process of sulfate reduction, ammonification, hydrolysis, acidogenesis and methanogenesis in a gravity sewer. The model correctly predicts the transformation of organics including proteins, lipids, polysaccharides, etc. The simulation results show that the degradation of organics easily generates acetic acid in the sewer system and the high yield of acetic acid is closely linked to methanogenic metabolism. Moreover, propionic acid is the crucial substrate for sulfate reduction and ammonification tends to be affected by the concentration of amino acids. Our model provides a promising tool for simulating and predicting outcomes in response to variations in wastewater quality in sewers.