Assessment of Ecological Quality of the Tajan River in Iran Using a Multimetric Macroinvertebrate Index and Species Traits

The objectives of this study were to assess the biological water of the Iranian Tajan River using different metrics, i.e., a Multimetric Macroinvertebrate Index (MMI) and a traits-based method. Twenty-eight physico-chemical parameters, 10 habitat factors, and abundance of macroinvertebrates were obtained for 17 sites. The Shahid-Rajaie dam divides the Tajan River into an up- and downstream part, with different land uses. Eighteen metrics were used to represent four components of ecosystem quality, including tolerance (Hilsenhoff, SIGNAL), diversity (Margalef, Shannon–Wiener, Simpson, and Evenness), abundance (total number of taxa, individuals, Ephemeroptera, Plecoptera, Trichoptera, EPT, and Insects), and composition of assemblages (% Ephemeroptera, % Plecoptera, % Trichoptera, and % EPT Taxa). The integrated MMI was calculated by averaging the obtained scores of all indices. In the next step, we gathered information on 22 biological traits of macroinvertebrates to evaluate whether (group of) traits could be identified that are indicative for specific or general stress. Result showed a decrease in MMI from upstream (very good water quality) to downstream (bad) due to human activities. Industrial activities like pulping and papermaking operations or sand mining in the downstream part had more effects than agriculture and fish ponds in the upstream part. A redundancy analysis biplot showed the variation between the modalities of trait of macroinvertebrates and their correlation with physico-chemical parameters in Tajan River. The findings show that traits can be indicative for different kind of stress but that more effort has to be put in gathering data sets to disentangle the effect of habitat quality, pollution, and the physico-chemical properties of high- versus lowland rivers.     

The evolution of socio-ecological systems: changing palm species management in the Colombian Amazon as an indicator of ecological and institutional change

We investigate natural resource governance in three indigenous communities in the Colombian Amazon. We base our analysis on an evolutionary governance model in which governance dimensions emerge as relevant through time. The less accessible of the communities represents earlier steps in governance evolution, while the more physically accessible is more integrated into the western scene. We observe how increased physical accessibility in a community brings in western governance models which hybridize with more traditional ones, influencing the couplings between the social and ecological systems. We zoom in on changing management of three commonly used palm species and illustrate how detailed studies of natural resource management contribute to understanding governance evolution. By comparing governance evolutions we were able to gain insights and improve our understanding on how natural resource management changes in communities transiting into western ways of living. In doing so we recognized points of rigidity and flexibility which might influence the social ecological systems capacity to adapt to changing conditions.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Potential application of high pressure carbon dioxide in treated wastewater and water disinfection: Recent overview and further trends

Recently emerging disadvantages in conventional disinfection have heightened the need for finding a new solution. Developments in the use of high pressure carbon dioxide for food preservation and sterilization have led to a renewed interest in its applicability in wastewater treatment and water disinfection. Pressurized CO₂ is one of the most investigated methods of antibacterial treatment and has been used extensively for decades to inhibit pathogens in dried food and liquid products. This study reviews the literature concerning the utility of CO₂ as a disinfecting agent, and the pathogen inactivation mechanism of CO₂ treatment is evaluated based on all available research. In this paper, it will be argued that the successful application and high effectiveness of CO₂ treatment in liquid foods open a potential opportunity for its use in wastewater treatment and water disinfection. The findings from models with different operating conditions (pressure, temperature, microorganism, water content, media …) suggest that most microorganisms are successfully inhibited under CO₂ treatment. It will also be shown that the bacterial deaths under CO₂ treatment can be explained by many different mechanisms. Moreover, the findings in this study can help to address the recently emerging problems in water disinfection, such as disinfection by-products (resulting from chlorination or ozone treatment).     

Inclusion of people with disabilities,their needs and participation,into disaster management: a comparative perspective

In the field of disaster management, not many have considered the role and needs of people with disabilities despite their number and condition. The purpose of this paper is to push for specific inclusion of people with disabilities, their needs and participation, into disaster management by studying relevant cases from Indonesia, Korea, and the USA. Qualitative content analysis was used as a major methodology by comparing three factors identified in these nations: government policies, schools and advocacy groups’ efforts, and families and local communities’ awareness. Three models, one from each country, were considered major takeaways from this study: the Indonesian moral inclusion, the Korean medical treatment without exclusion, and the US’ extending social inclusion. In addressing the needs and participation of people with disabilities in disaster management, the following recommendations are put forward: for Indonesia, a move away from olden beliefs and misconceptions on disability (e.g. as a punishment) is imperative. In Korea, relevant fundamental laws (e.g. the Basic Act on Emergency and Safety Management) need to be revised while also studying advanced laws on the subject. For the USA, though the country is already advanced, overall improvement is still needed in terms of association with international non-governmental organizations, increase in the number of (emergency or disaster) response officials, and provision of better medical treatment.     

Biological methane production coupled with sulfur oxidation in a microbial electrosynthesis system without organic substrates

Methane is produced in a microbial electrosynthesis system (MES) without organic substrates. However, a relatively high applied voltage is required for the bioelectrical reactions. In this study, we demonstrated that electrotrophic methane production at the biocathode was achieved even at a very low voltage of 0.1 V in an MES, in which abiotic HS⁻ oxidized to SO₄²⁻ at the anodic carbon-cloth surface coated with platinum powder. In addition, microbial community analysis revealed the most probable pathway for methane production from electrons. First, electrotrophic H₂ was produced by syntrophic bacteria, such as Syntrophorhabdus, Syntrophobacter, Syntrophus, Leptolinea, and Aminicenantales, with the direct acceptance of electrons at the biocathode. Subsequently, most of the produced H₂ was converted to acetate by homoacetogens, such as Clostridium and Spirochaeta 2. In conclusion, the majority of the methane was indirectly produced by a large population of acetoclastic methanogens, namely Methanosaeta, via acetate. Further, hydrogenotrophic methanogens, including Methanobacterium and Methanolinea, produced methane via H₂.     

Applying value of information methods to prioritize elements for water quality management with an example of linear alkylbenzene sulfonate in the Yodo River,Japan

Narrowing the decision space is crucial in water quality management at the meso-scale for developing countries, where a lack of data and financial budgets prevent the development of appropriate management plans and result in serious water quality degradation in many rivers. In this study, a framework for handling this task is proposed, comprising a lumped water quality model, with sensitivity and uncertainty analyses, and a management domain, including loss estimation and value of information analysis. Through a case study with linear alkylbenzene sulfonate (LAS) in the Yodo River, it is found that non-point sources and flow rate are factors that influence LAS concentration at the hot spot location. By considering the entire process of water quality management planning, we identify that the definition of the cost function of LAS treatment determines the appropriate estimation for the expected loss in reducing LAS under uncertain water quality conditions. The value of information analysis with “expected value of including uncertainty” and “expected value of perfect information” further helps estimate the benefit of including uncertainty in decision-making and the financial cost for obtaining more information regarding inputs that have been previously prioritized.