Background: Many rural electrification projects around the world employ micro hydropower plants (MHPs). These installations provide immediate and direct benefits to the local people. However, the sustainability of their operation in the long run remains a vital issue. Without proper sustainability assessment, the projects may face operational problems. However, to date, only a few empirical studies exist which offer tools to assess sustainability of MHP projects post-implementation. Given that every site has peculiar characteristics that could largely vary from site to site, there is a need to develop a model which could assess and compare the feasibility of the projects from the sustainability point of view before the project is implemented. For this purpose, a thorough sustainability assessment model was developed for an MHP project in a mountainous region of Nepal. Methods: This paper presents a sustainability assessment model for micro hydropower plants. In order to collect the data necessary to run the model, different sets of questionnaires were prepared for all relevant stakeholders. The developed model was used to assess an overall sustainability of a 26-kW plant at Mahadevsthan in Dhading District of Nepal. At this site, 15 community households, a project management committee member, an operator, and three policy makers/micro hydro experts were interviewed. The indicator system developed here was finalized with the stakeholder's participation. Results: A sustainability assessment model for the operation of micro hydropower plants in a remote rural area of Nepal was developed. Our model includes 54 assessment indicators taking into account economic, social, environmental, and technical sustainability dimensions and a scoring system (ranging from 1 to 5, with 5 being the best). It was found that the social dimension shows the best performance with a score of 4.17 for the studied MHP, followed by environmental (3.94), economic (3.74), and technical dimensions (3.04). Conclusions: The results show that the developed model creates a qualitative and quantitative basis for sustainability assessment of MHPs, allowing easiness for comparison of micro hydro projects, providing an effective decision-making support tool in rural electrification and development sector. The input of all stakeholders in identifying site-specific indicators that are relevant to the sustainability of the projects is crucial for minimizing biases in the assessment framework.
The use of miniaturized Gas Chromatography -Differential Mobility Spectrometry (GC-DMS) is shown for the detection and identification of coliform bacteria (including Escherichia coli) grown in five different media: Colilert ® -18, glucose broth, M9-medium, tryptophan broth, and tryptic soy broth. After incubation in the different media, headspace containing the volatile compounds were analyzed by the GC-DMS and the results were validated by Gas Chromatography -Mass Spectrometry (GC-MS). Results showed that the GC-DMS and GC-MS were able to detect onitrophenol released by coliform bacteria incubated in Colilert ® -18. In addition to that, GC-MS was able to detect indole compound released by coliform bacteria grown in all media. Neither GC-DMS nor GC-MS could detect 4methylumbelliferone from the headspace of E. coli grown in media containing 4-methylumbelliferyl-β-D-glucoronide (MUG) substrate, which was available in Colilert ® -18. With the miniaturized GC-DMS being portable and can be operated using ambient pressure, this method offers a potential on-site detection of coliform bacteria.
In this study, we demonstrate that the combination of an enzymatic method (based on Colilert-18 medium) and gas chromatography-differential mobility spectrometry (GC-DMS) can reduce the time required for detection of coliform bacteria (including Escherichia coli) from 18 to 2.5 h. The presented method includes the incubation (~2.5 h) of the sample containing coliform bacteria in Colilert-18 medium. The incubation time of 2.5 h is required for the activation of the β-galactosidase enzyme. Produced during the incubation biomarker o-nitrophenol (ONP) can be detected by means of GC-DMS within just 200 s. The detection limit for ONP was 45 ng (on-column). The method developed in this work provides significantly shorter analysis time compared with standard methods, and can be potentially adapted to the field conditions. Therefore, this method is a promising tool for an early detection of coliform bacteria (including E. coli). Graphical Abstract Fast detection of coliform bacteria by means of GC-DMS.
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