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Water scarcity is increasing in most Indian cities, exemplified by the recent 2019 Chennai water crisis. Though there were measures initiated at both institutional and local levels, water scarcity has continued. One possible solution is to install energy-efficient renewable energy-powered desalination plants (REpDP) for Indian cities, especially those in favorable climatic zones. The modeling of REpDP combined with multi-criteria decision analysis (MCDA) is proposed to prioritize the optimal site and REpDP selection for providing low-cost freshwater. A standalone seawater reverse osmosis (SWRO) based REpDP that delivers water at a rate of 1.5 m3/h is modeled. Based on the SWRO operation; analytical modeling is carried out to optimize the hybrid energy configuration that combines solar, wind, hydrokinetic with backup energy facilities. The Fuzzy-TOPSIS MCDA with five attributes is performed to rank the modeled alternatives for selected coastal cities. The analysis identified Dwarka in the state of Gujarat, India, as the most suitable urban zone. The results also indicated that the electricity and freshwater production cost for the optimal configuration with an energy recovery scheme provide savings up to 10% and 36.4%, respectively. A comparison is made with EDAS and BWM methods. It provides consistency in results with the Fuzzy-TOPSIS.
J. Vishnupriyan; Dhanasekaran Arumugam; Nallapaneni Manoj Kumar; Shauhrat S. Chopra; Pachaivannan Partheeban. Multi-criteria decision analysis for optimal planning of desalination plant feasibility in different urban cities in India. Journal of Cleaner Production 2021, 315, 128146 .
AMA StyleJ. Vishnupriyan, Dhanasekaran Arumugam, Nallapaneni Manoj Kumar, Shauhrat S. Chopra, Pachaivannan Partheeban. Multi-criteria decision analysis for optimal planning of desalination plant feasibility in different urban cities in India. Journal of Cleaner Production. 2021; 315 ():128146.
Chicago/Turabian StyleJ. Vishnupriyan; Dhanasekaran Arumugam; Nallapaneni Manoj Kumar; Shauhrat S. Chopra; Pachaivannan Partheeban. 2021. "Multi-criteria decision analysis for optimal planning of desalination plant feasibility in different urban cities in India." Journal of Cleaner Production 315, no. : 128146.
Bioconversion of food waste into sophorolipid-based biosurfactants is a promising emerging technology. It is important to evaluate the environmental impacts associated with the latest advancements in sophorolipid production as it matures to maximize sustainability on scale-up. This study takes a dynamic Life Cycle Assessment (dLCA) approach to address the inherent uncertainties and evaluate the environmental performances. It demonstrates the dLCA framework by conducting the new traversal of food waste-derived industrial-scale sophorolipid production, with the combination of Techno-Economic Analysis (TEA). A systematic investigation of the environmental-economic implications of the two pathways to produce SL crystals and syrup. The global warming potential (GWP) for 1 kg of SL crystals and syrup was 7.9 kg CO2 eq. and 5.7 kg CO2 eq., respectively. The Ashby-like charts based on the LCA and TEA results at the pilot plant highlighted the trade-offs between systemic environmental costs and economic benefits for design decisions.
Xiaomeng Hu; Karpagam Subramanian; Huaimin Wang; Sophie L.K.W. Roelants; Wim Soetaert; Guneet Kaur; Carol Sze Ki Lin; Shauhrat S. Chopra. Bioconversion of food waste to produce industrial-scale sophorolipid syrup and crystals: dynamic life cycle assessment (dLCA) of emerging biotechnologies. Bioresource Technology 2021, 337, 125474 .
AMA StyleXiaomeng Hu, Karpagam Subramanian, Huaimin Wang, Sophie L.K.W. Roelants, Wim Soetaert, Guneet Kaur, Carol Sze Ki Lin, Shauhrat S. Chopra. Bioconversion of food waste to produce industrial-scale sophorolipid syrup and crystals: dynamic life cycle assessment (dLCA) of emerging biotechnologies. Bioresource Technology. 2021; 337 ():125474.
Chicago/Turabian StyleXiaomeng Hu; Karpagam Subramanian; Huaimin Wang; Sophie L.K.W. Roelants; Wim Soetaert; Guneet Kaur; Carol Sze Ki Lin; Shauhrat S. Chopra. 2021. "Bioconversion of food waste to produce industrial-scale sophorolipid syrup and crystals: dynamic life cycle assessment (dLCA) of emerging biotechnologies." Bioresource Technology 337, no. : 125474.
Waste generation is a continuous process that needs to be managed effectively to ensure environmental safety and public health. The recent circular economy (CE) practices have brought a new shape for the waste management industry, creating value from the generated waste. The shift to a CE represents one of the most significant challenges, particularly in sorting and classifying generated waste. Addressing these challenges would facilitate the recycling industry and helps in promoting remanufacturing. But in the COVID times, most of the generated waste is getting mixed with conventional waste types, especially in the global south. The pandemic has resulted in colossal infectious waste generation. Its handling became the most significant challenge raising fears and concerns over sorting and classifying. Hence, this study proposes an Artificial Intelligence (AI) based automated solution for sorting COVID related medical waste streams from other waste types and, at the same time, ensures data-driven decisions for recycling in the context of CE. Metal, paper, glass waste categories, including the polyethylene terephthalate (PET) waste from the pandemic, are considered. The waste type classification is done based on the image-texture-dependent features, which provided an accurate sorting and classification before the recycling process starts. The features are fused using the proposed decision-level feature fusion scheme. The classification model based on the support vector machine (SVM) classifier performs best (with 96.5 % accuracy, 95.3 % sensitivity, and 95.9 % specificity) in classifying waste types in the context of circular manufacturing and exhibiting the abilities to manage the COVID related medical waste mixed.
Nallapaneni Manoj Kumar; Mazin Abed Mohammed; Karrar Hameed Abdulkareem; Robertas Damasevicius; Salama A. Mostafa; Mashael S. Maashi; Shauhrat S. Chopra. Artificial Intelligence-based Solution for Sorting COVID Related Medical Waste Streams and Supporting Data-driven Decisions for Smart Circular Economy Practice. Process Safety and Environmental Protection 2021, 152, 482 -494.
AMA StyleNallapaneni Manoj Kumar, Mazin Abed Mohammed, Karrar Hameed Abdulkareem, Robertas Damasevicius, Salama A. Mostafa, Mashael S. Maashi, Shauhrat S. Chopra. Artificial Intelligence-based Solution for Sorting COVID Related Medical Waste Streams and Supporting Data-driven Decisions for Smart Circular Economy Practice. Process Safety and Environmental Protection. 2021; 152 ():482-494.
Chicago/Turabian StyleNallapaneni Manoj Kumar; Mazin Abed Mohammed; Karrar Hameed Abdulkareem; Robertas Damasevicius; Salama A. Mostafa; Mashael S. Maashi; Shauhrat S. Chopra. 2021. "Artificial Intelligence-based Solution for Sorting COVID Related Medical Waste Streams and Supporting Data-driven Decisions for Smart Circular Economy Practice." Process Safety and Environmental Protection 152, no. : 482-494.
Industrial symbiosis (IS) promotes collaboration among traditionally unrelated industries, finding ways to use waste from one as a raw material for another. To enhance IS sustainability, it is essential that involved firms are aware of potential costs and benefits of new exchanges to make informed decisions. Previous assessments have primarily focused on environmental and financial implications of potenial IS synergies, but social implications are rarely addressed. Even when considered, only a limited set of social indicators, such as job creation, development of social ties, and trust among partners, are used. Such an unbalanced focus on sustainability aspects may contribute to problem shifting and suboptimal selection of new synergies. A comprehensive life cycle sustainability assessment (LCSA) of IS, covering all three dimensions is clearly lacking. Conventionally, a triple bottom line (TBL) approach is used to evaluate sustainability; however, we explore the concept of capitals and develop a capital‐based LCSA framework as a means to evaluate sustainability of IS by examining the stocks and flows of eight different types of capital, or resources creating value, in a system. Measuring stocks and flows is conceptually much closer to the actual definition of sustainability (meeting the needs of the present by maintaining the available stocks without compromising the future needs), when compared to the TBL approach of simply aggregating environmental, social, and economic impact assessment results. This novel LCSA approach is tested at a facility with active IS, The Plant in Chicago, considering three alternative fuel usage scenarios for baking bread at an on‐site bakery.
Karpagam Subramanian; Shauhrat S. Chopra; Weslynne S. Ashton. Capital‐based life cycle sustainability assessment: Evaluation of potential industrial symbiosis synergies. Journal of Industrial Ecology 2021, 1 .
AMA StyleKarpagam Subramanian, Shauhrat S. Chopra, Weslynne S. Ashton. Capital‐based life cycle sustainability assessment: Evaluation of potential industrial symbiosis synergies. Journal of Industrial Ecology. 2021; ():1.
Chicago/Turabian StyleKarpagam Subramanian; Shauhrat S. Chopra; Weslynne S. Ashton. 2021. "Capital‐based life cycle sustainability assessment: Evaluation of potential industrial symbiosis synergies." Journal of Industrial Ecology , no. : 1.
The United Nations (UN) have formulated seventeen Sustainable Development Goals (SDGs) and thus, humans were trying to traverse the sustainable path. Meanwhile, the COVID-19 pandemic has emerged and forced out the ephemeral conventional approaches. Thus, the post-COVID world indicates the need for sustainable development and strategies in par with the ecosystem. The authors propose this study as a guide to direct the post-pandemic scenario into the sustainable pathway by prioritizing energy sustainability to engage the actions for achieving the SDGs. The analysis in this study commences with the investigation of pronounced impacts in the energy sector with its influence on the progress towards sustainability. To pursue the path of energy sustainability, a qualitative analysis is performed in a parallel approach from the key viewpoint of the renewable and sustainable energy transition, digital transformation of the energy sector and energy affordability in the post-COVID world. A SWOT-AHP hybrid methodology is employed to identify the significance of each strategy or issues to be focused on immediately in the post-COVID world. The study also discusses energy sustainability from political bodies and policy makers’ perspective, and the actual scenario where we are headed is revealed with the aid of process-tracing method. Furthermore, a novel quantitative analysis is established to represent the SDG’s interaction and the result shows that the SDG 7 is the underpinning goal in relative to other SDGs. In context with it, the mapping of energy sustainability to the sustainable world is accomplished. The ultimate inference from envisioning the SDGs through energy sustainability shows that a sustainable world would result after the pandemic. However, the changes in the energy market, investment preferences and more importantly, the decisions influenced by the political bodies in the post-COVID-world is decisive in achieving the same in a stipulated time frame.
Rajvikram Madurai Elavarasan; Rishi Pugazhendhi; Taskin Jamal; Joanna Dyduch; M.T. Arif; Nallapaneni Manoj Kumar; Gm Shafiullah; Shauhrat S. Chopra; Mithulananthan Nadarajah. Envisioning the UN Sustainable Development Goals (SDGs) through the lens of energy sustainability (SDG 7) in the post-COVID-19 world. Applied Energy 2021, 292, 116665 .
AMA StyleRajvikram Madurai Elavarasan, Rishi Pugazhendhi, Taskin Jamal, Joanna Dyduch, M.T. Arif, Nallapaneni Manoj Kumar, Gm Shafiullah, Shauhrat S. Chopra, Mithulananthan Nadarajah. Envisioning the UN Sustainable Development Goals (SDGs) through the lens of energy sustainability (SDG 7) in the post-COVID-19 world. Applied Energy. 2021; 292 ():116665.
Chicago/Turabian StyleRajvikram Madurai Elavarasan; Rishi Pugazhendhi; Taskin Jamal; Joanna Dyduch; M.T. Arif; Nallapaneni Manoj Kumar; Gm Shafiullah; Shauhrat S. Chopra; Mithulananthan Nadarajah. 2021. "Envisioning the UN Sustainable Development Goals (SDGs) through the lens of energy sustainability (SDG 7) in the post-COVID-19 world." Applied Energy 292, no. : 116665.
A ‘nexus’ approach, comprising interrelated systems components of energy, water, and food, has been suggested to accelerate progress towards achieving sustainable development goals on food waste and related issues, like climate change. The current body of literature usually focuses on food security, especially in relation to production and waste management in the supply chain. The food service sector (FSS), a major consumer-facing component of the food system, has often been overlooked or neglected. There exists, then, an opportunity to better understand the interlinkages between food waste, energy, water, and emissions – the FEWE Nexus – to assist this sector in developing more sustainable operations, such as kitchen equipment management and menu development. To fill this gap, we introduce a novel FEWE Nexus Framework, to understand the flow of nexus components associated with receiving, storing, preparing, cooking, cleaning, and serving menu items. A key aspect of the methodological approach for FEWE evaluation is life cycle assessment (LCA). This is embodied in a comprehensive nexus audit tool comprising several indicators to monitor and quantify energy and water consumption, emissions from cooking, food waste generated, and type and efficiency of equipment used. Further, a stakeholder engagement survey is integrated, allowing for stakeholder feedback on applications of the audit tool, and to assess the impacts and acceptance of potential interventions. Finally, we describe how an iterative nexus approach can enable decision makers in the FSS to robustly estimate nexus components and establish a baseline to track their progress towards minimizing wastages and maximize efficiency.
Karpagam Subramanian; Shauhrat S. Chopra; Christopher M. Wharton; William Yonge; Julie Allen; Rozanne Stevens; Sam Fahy; Paschal Simon Milindi. Mapping the food waste-energy-water-emissions nexus at commercial kitchens: A systems approach for a more sustainable food service sector. Journal of Cleaner Production 2021, 301, 126856 .
AMA StyleKarpagam Subramanian, Shauhrat S. Chopra, Christopher M. Wharton, William Yonge, Julie Allen, Rozanne Stevens, Sam Fahy, Paschal Simon Milindi. Mapping the food waste-energy-water-emissions nexus at commercial kitchens: A systems approach for a more sustainable food service sector. Journal of Cleaner Production. 2021; 301 ():126856.
Chicago/Turabian StyleKarpagam Subramanian; Shauhrat S. Chopra; Christopher M. Wharton; William Yonge; Julie Allen; Rozanne Stevens; Sam Fahy; Paschal Simon Milindi. 2021. "Mapping the food waste-energy-water-emissions nexus at commercial kitchens: A systems approach for a more sustainable food service sector." Journal of Cleaner Production 301, no. : 126856.
Fostering high-resolution disaster resilience assessment is essential for high-density cities (HDCs) given their congested built environment. This study introduces and demonstrates a spatial disaster resilience profiling (S-DReP) framework for HDCs. First, an indicator set is presented for resilience assessment in HDCs within a built environment. Second, this indicator set is adopted to identify the spatially-varying patterns of neighbourhood disaster resilience in HDCs. In contrast to typical resilience frameworks, the developed framework also takes into account the spatio-environmental factors within the built environment. As an illustrative example, we demonstrate the application of S-DReP framework to one of the most populated districts in Hong Kong, namely Sha Tin. Building-level data for 24 indicators and infrastructure data are used to compute a spatially-relative disaster resilience index. To inform the planners with disparities among different resilience components, the Analysis of Variance approach is employed to explore the distribution of resilience. To identify the priority intervention areas, the spatial assessments are made using several geo-information models. The proposed S-DReP framework provides a roadmap to establish an urban resilience knowledge system in HDCs enabling practitioners, decision-makers, and local bodies to design action plans for future vigilance reducing the worsening impacts of hazards on cities.
Muhammad Sajjad; Johnny C.L. Chan; Shauhrat S. Chopra. Rethinking disaster resilience in high-density cities: Towards an urban resilience knowledge system. Sustainable Cities and Society 2021, 69, 102850 .
AMA StyleMuhammad Sajjad, Johnny C.L. Chan, Shauhrat S. Chopra. Rethinking disaster resilience in high-density cities: Towards an urban resilience knowledge system. Sustainable Cities and Society. 2021; 69 ():102850.
Chicago/Turabian StyleMuhammad Sajjad; Johnny C.L. Chan; Shauhrat S. Chopra. 2021. "Rethinking disaster resilience in high-density cities: Towards an urban resilience knowledge system." Sustainable Cities and Society 69, no. : 102850.
This cross‐disciplinary study examines gender inclusion and intersectionality in the knowledge production of sustainability research. Building on studies of gender inclusion as essential for quality research, we develop a three‐step framework that analyzes the socio‐demographic profile of researchers (sustainability by whom?), key research trajectories (sustainability of what?), and beneficiaries of sustainability research (sustainability for whom?). Our methods include a survey and a bibliometric analysis. The survey was administered at the joint conference of the International Society for Industrial Ecology and the International Symposium on Sustainable Systems and Technology in 2017. The survey results show gendered differences in collaboration patterns. The survey results also indicated a good level of gender inclusion among the experts in this field, but the bibliometric analysis showed that gender issues remain marginal in the studies of industrial ecology. In contrast to industrial ecology, we found increasing attention to gender in other areas of sustainability research (climate change, corporate social responsibility, food production, resource management, energy policy, and environmental behavior and education), but even there, “gender” tends to be equated with “women” in traditional gender roles, ignoring the role of intersectionality—the intersection of gender with income, age, and other demographic characteristics. Therefore, this study makes recommendations to approach gender critically, by using theoretical lenses from gender studies scholarship (i.e., gender as a constructed, intersectional, dynamic category). We show how these lenses enable better assessments of the environmental impacts of industrial processes on people of diverse backgrounds in the context of changing patterns of work and consumption.
Venera R. Khalikova; Mushan Jin; Shauhrat S. Chopra. Gender in sustainability research: Inclusion, intersectionality, and patterns of knowledge production. Journal of Industrial Ecology 2021, 1 .
AMA StyleVenera R. Khalikova, Mushan Jin, Shauhrat S. Chopra. Gender in sustainability research: Inclusion, intersectionality, and patterns of knowledge production. Journal of Industrial Ecology. 2021; ():1.
Chicago/Turabian StyleVenera R. Khalikova; Mushan Jin; Shauhrat S. Chopra. 2021. "Gender in sustainability research: Inclusion, intersectionality, and patterns of knowledge production." Journal of Industrial Ecology , no. : 1.
Traditional triple bottom line approach used in existing neighbourhood sustainability assessment (NSA) tools provide an unbalanced focus on sustainability dimensions and are non-spatial. As a consequence, these tools may not aid decision-making process of different stakeholders. For this purpose, we propose an urban sustainability spatial hotspot analysis that integrates the Five Capitals Model (FCM) with Geographic Information Systems (GIS). The FCM based NSA framework redefines sustainability in existing NSA tools as it considers the maintenance of five major stocks – natural, social, human, financial, and manufactured – in a neighbourhood. The evaluation of the flow of these stocks is conducted at the level of each residential estate based on indicators that are mapped to the Sustainable Development Goals (SDGs). GIS is integrated to facilitate bottom-up model of indicator development with high-resolution data and discover spatial inequalities through heat maps. The developed method is applied to Sha Tin neighbourhood in Hong Kong. Heat maps generated identify priority intervention areas in Sha Tin that need much attention. The developed tool aims to democratize the use of NSAs by addressing different decision-making challenges for a diverse set of stakeholders across various levels.
Karpagam Subramanian; Shauhrat S. Chopra; Ezgi Cakin; Jiarun Liu; Zizhen Xu. Advancing neighbourhood sustainability assessment by accounting for sustainable development goals: A case study of Sha Tin neighbourhood in Hong Kong. Sustainable Cities and Society 2020, 66, 102649 .
AMA StyleKarpagam Subramanian, Shauhrat S. Chopra, Ezgi Cakin, Jiarun Liu, Zizhen Xu. Advancing neighbourhood sustainability assessment by accounting for sustainable development goals: A case study of Sha Tin neighbourhood in Hong Kong. Sustainable Cities and Society. 2020; 66 ():102649.
Chicago/Turabian StyleKarpagam Subramanian; Shauhrat S. Chopra; Ezgi Cakin; Jiarun Liu; Zizhen Xu. 2020. "Advancing neighbourhood sustainability assessment by accounting for sustainable development goals: A case study of Sha Tin neighbourhood in Hong Kong." Sustainable Cities and Society 66, no. : 102649.
Harnessing energy from the sunlight using solar photovoltaic trees (SPVTs) has become popular at present as they reduce land footprint and offer numerous complimentary services that offset infrastructure. The SPVT’s complimentary services are noticeable in many ways, e.g., electric vehicle charging stations, landscaping, passenger shelters, onsite energy generated security poles, etc. Although the SPVT offers numerous benefits and services, its deployment is relatively slower due to the challenges it suffers. The most difficult challenges include the structure design, the photovoltaic (PV) cell technology selection for a leaf, and uncertainty in performance due to weather parameter variations. This paper aims to provide the most practical solution supported by the performance prioritization approach (PPA) framework for a typical multilayered SPVT. The proposed PPA framework considers the energy and sustainability indicators and helps in reporting the performance of a multilayered SPVT, with the aim of selecting an efficient PV leaf design. A three-layered SPVT (3-L SPVT) is simulated; moreover, the degradation-influenced lifetime energy performance and carbon dioxide (CO2) emissions were evaluated for three different PV-cell technologies, namely crystalline silicon (c-Si), copper indium gallium selenide (CIGS), and cadmium telluride (CdTe). While evaluating the performance of the 3-L SPVT, the power conversion efficiency, thermal regulation, degradation rate, and lifecycle carbon emissions were considered. The results of the 3-L SPVT were analyzed thoroughly, and it was found that in the early years, the c-Si PV leaves give better energy yields. However, when degradation and other influencing weather parameters were considered over its lifetime, the SPVT with c-Si leaves showed a lowered energy yield. Overall, the lifetime energy and CO2 emission results indicate that the CdTe PV leaf outperforms due to its lower degradation rate compared to c-Si and CIGS. On the other side, the benefits associated with CdTe cells, such as flexible and ultrathin glass structure as well as low-cost manufacturing, make them the best acceptable PV leaf for SPVT design. Through this investigation, we present the selection of suitable solar cell technology for a PV leaf.
Nallapaneni Manoj Kumar; Shauhrat S. Chopra; Maria Malvoni; Rajvikram Madurai Elavarasan; Narottam Das. Solar Cell Technology Selection for a PV Leaf Based on Energy and Sustainability Indicators—A Case of a Multilayered Solar Photovoltaic Tree. Energies 2020, 13, 6439 .
AMA StyleNallapaneni Manoj Kumar, Shauhrat S. Chopra, Maria Malvoni, Rajvikram Madurai Elavarasan, Narottam Das. Solar Cell Technology Selection for a PV Leaf Based on Energy and Sustainability Indicators—A Case of a Multilayered Solar Photovoltaic Tree. Energies. 2020; 13 (23):6439.
Chicago/Turabian StyleNallapaneni Manoj Kumar; Shauhrat S. Chopra; Maria Malvoni; Rajvikram Madurai Elavarasan; Narottam Das. 2020. "Solar Cell Technology Selection for a PV Leaf Based on Energy and Sustainability Indicators—A Case of a Multilayered Solar Photovoltaic Tree." Energies 13, no. 23: 6439.
Microbial biosurfactants are surface-active molecules which are naturally produced by a range of microorganisms. They have advantages over chemical surfactants such as lower toxicity, higher biodegradability, anti-tumor, and anti-microbial properties. Sophorolipids (SLs) are one of the most promising biosurfactants, that represent the largest share of the biosurfactant market. Researchers are developing novel approaches for SL production by utilizing renewable feedstocks and advanced separation technologies. However, challenges still exist regarding consumption of materials, enzymes, and electricity, that are primary fossil based. Researchers lack a clear understanding of the associated environmental impacts. It is imperative to quantify and optimize the environmental impacts associated with this emerging technology very early in its design phase to guide a sustainable scale-up. It is necessary to take a collaborative perspective, wherein life cycle assessment (LCA) experts work with experimentalists, to quantify environmental impacts and provide recommendations for improvements in the SL production pathway. Studies that have analyzed the environmental sustainability of microbial biosurfactant production are very scarce in literature. Hence, in this work, we explore the possibility of applying LCA to evaluate the environmental sustainability of SL production. A dynamic LCA (dLCA) framework that quantifies the environmental impacts of a process in an iterative manner, is proposed and applied to evaluate SL production. The first traversal of the dLCA is associated with the selection of an optimal feedstock, results identified food waste as the optimal feedstock. The second traversal compared fermentation coupled with alternative separation techniques, and highlighted that the fed-batch fermentation of food waste integrated with the in-situ separation technique resulted in less environmental impacts. These results can guide experimentalists to further optimize those processes, and improve the environmental sustainability of SL production. Resultant datasets can be iteratively used in subsequent traversals to account for technological changes and mitigate the corresponding impacts before scaling up.
Xiaomeng Hu; Karpagam Subramanian; Huaimin Wang; Sophie L.K.W. Roelants; Ming Ho To; Wim Soetaert; Guneet Kaur; Carol Sze Ki Lin; Shauhrat S. Chopra. Guiding environmental sustainability of emerging bioconversion technology for waste-derived sophorolipid production by adopting a dynamic life cycle assessment (dLCA) approach. Environmental Pollution 2020, 269, 116101 .
AMA StyleXiaomeng Hu, Karpagam Subramanian, Huaimin Wang, Sophie L.K.W. Roelants, Ming Ho To, Wim Soetaert, Guneet Kaur, Carol Sze Ki Lin, Shauhrat S. Chopra. Guiding environmental sustainability of emerging bioconversion technology for waste-derived sophorolipid production by adopting a dynamic life cycle assessment (dLCA) approach. Environmental Pollution. 2020; 269 ():116101.
Chicago/Turabian StyleXiaomeng Hu; Karpagam Subramanian; Huaimin Wang; Sophie L.K.W. Roelants; Ming Ho To; Wim Soetaert; Guneet Kaur; Carol Sze Ki Lin; Shauhrat S. Chopra. 2020. "Guiding environmental sustainability of emerging bioconversion technology for waste-derived sophorolipid production by adopting a dynamic life cycle assessment (dLCA) approach." Environmental Pollution 269, no. : 116101.
Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-way flow of electricity and data between the peers within the electricity system networks (ESN) and its clusters. The self-healing capabilities of SG allow the peers to become active partakers in ESN. In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations. With this, the SG will able to “detect, react, and pro-act” to changes in usage and address multiple issues, thereby ensuring timely grid operations. However, the “detect, react, and pro-act” features in DER-based SG can only be accomplished at the fullest level with the use of technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and the Blockchain (BC). The techniques associated with AI include fuzzy logic, knowledge-based systems, and neural networks. They have brought advances in controlling DER-based SG. The IoT and BC have also enabled various services like data sensing, data storage, secured, transparent, and traceable digital transactions among ESN peers and its clusters. These promising technologies have gone through fast technological evolution in the past decade, and their applications have increased rapidly in ESN. Hence, this study discusses the SG and applications of AI, IoT, and BC. First, a comprehensive survey of the DER, power electronics components and their control, electric vehicles (EVs) as load components, and communication and cybersecurity issues are carried out. Second, the role played by AI-based analytics, IoT components along with energy internet architecture, and the BC assistance in improving SG services are thoroughly discussed. This study revealed that AI, IoT, and BC provide automated services to peers by monitoring real-time information about the ESN, thereby enhancing reliability, availability, resilience, stability, security, and sustainability.
Nallapaneni Manoj Kumar; Aneesh A. Chand; Maria Malvoni; Kushal A. Prasad; Kabir A. Mamun; F.R. Islam; Shauhrat S. Chopra. Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids. Energies 2020, 13, 5739 .
AMA StyleNallapaneni Manoj Kumar, Aneesh A. Chand, Maria Malvoni, Kushal A. Prasad, Kabir A. Mamun, F.R. Islam, Shauhrat S. Chopra. Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids. Energies. 2020; 13 (21):5739.
Chicago/Turabian StyleNallapaneni Manoj Kumar; Aneesh A. Chand; Maria Malvoni; Kushal A. Prasad; Kabir A. Mamun; F.R. Islam; Shauhrat S. Chopra. 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids." Energies 13, no. 21: 5739.
In dense urban areas, the use of building integrated photovoltaics (BIPV) façades are becoming popular and they are bringing many advantageous along with the energy-saving features. However, at the same time, they raise tensions in capital investments and overall returns. “Solsmaragden” is one of such a commercial building, that is integrated with BIPV façade with the peak power of 127.5 kW and owned by Union eiendomsutvikling AS in Norway. In this paper, a lifecycle cost analysis (LCCA) of BIPV façade integrated to “Solsmaragden” is investigated based on on-field recorded data after four years of operation (2016–2019). While formulating LCCA, numerous benefits from system power generation, societal and environmental benefits, and financial gains due to three different end-of-life material recovery approaches were also considered. The result based on the field monitored performance showed that the net present value (NPV), discounted payback period, internal rate of return and levelised cost of energy of the system is equal to 478,934 NOK, 22 years, 6% and 1.28 NOK/kWh, respectively. It is observed that the BIPV system as a building envelope material for different orientations of the building skin could reimburse not only all the investment costs but also become a source of income for the buildings. The results also illustrated that the granted subsidy is substantially covering the societal and environmental benefits of this project.
Hassan Gholami; Harald Nils Røstvik; Nallapaneni Manoj Kumar; Shauhrat S. Chopra. Lifecycle cost analysis (LCCA) of tailor-made building integrated photovoltaics (BIPV) façade: Solsmaragden case study in Norway. Solar Energy 2020, 211, 488 -502.
AMA StyleHassan Gholami, Harald Nils Røstvik, Nallapaneni Manoj Kumar, Shauhrat S. Chopra. Lifecycle cost analysis (LCCA) of tailor-made building integrated photovoltaics (BIPV) façade: Solsmaragden case study in Norway. Solar Energy. 2020; 211 ():488-502.
Chicago/Turabian StyleHassan Gholami; Harald Nils Røstvik; Nallapaneni Manoj Kumar; Shauhrat S. Chopra. 2020. "Lifecycle cost analysis (LCCA) of tailor-made building integrated photovoltaics (BIPV) façade: Solsmaragden case study in Norway." Solar Energy 211, no. : 488-502.
Karpagam Subramanian; Shauhrat S Chopra; Ezgi Cakin; Xiaotong Li; Carol Sze Ki Lin. Environmental life cycle assessment of textile bio-recycling – valorizing cotton-polyester textile waste to pet fiber and glucose syrup. Resources, Conservation and Recycling 2020, 161, 1 .
AMA StyleKarpagam Subramanian, Shauhrat S Chopra, Ezgi Cakin, Xiaotong Li, Carol Sze Ki Lin. Environmental life cycle assessment of textile bio-recycling – valorizing cotton-polyester textile waste to pet fiber and glucose syrup. Resources, Conservation and Recycling. 2020; 161 ():1.
Chicago/Turabian StyleKarpagam Subramanian; Shauhrat S Chopra; Ezgi Cakin; Xiaotong Li; Carol Sze Ki Lin. 2020. "Environmental life cycle assessment of textile bio-recycling – valorizing cotton-polyester textile waste to pet fiber and glucose syrup." Resources, Conservation and Recycling 161, no. : 1.
Neuromodulation techniques such as deep brain stimulation (DBS) are a promising treatment for memory-related disorders including anxiety, addiction, and dementia. However, the outcomes of such treatments appear to be somewhat paradoxical, in that these techniques can both disrupt and enhance memory even when applied to the same brain target. In this article, we hypothesize that disruption and enhancement of memory through neuromodulation can be explained by the dropout of engram nodes. We used a convolutional neural network (CNN) to classify handwritten digits and letters and applied dropout at different stages to simulate DBS effects on engrams. We showed that dropout applied during training improved the accuracy of prediction, whereas dropout applied during testing dramatically decreased the accuracy of prediction, which mimics enhancement and disruption of memory, respectively. We further showed that transfer learning of neural networks with dropout had increased the accuracy and rate of learning. Dropout during training provided a more robust “skeleton” network and, together with transfer learning, mimicked the effects of chronic DBS on memory. Overall, we showed that the dropout of engram nodes is a possible mechanism by which neuromodulation techniques such as DBS can both disrupt and enhance memory, providing a unique perspective on this paradox.
Shawn Tan; Richard Du; Jose Angelo Udal Perucho; Shauhrat S. Chopra; Varut Vardhanabhuti; Lee Wei Lim. Dropout in Neural Networks Simulates the Paradoxical Effects of Deep Brain Stimulation on Memory. Frontiers in Aging Neuroscience 2020, 12, 1 .
AMA StyleShawn Tan, Richard Du, Jose Angelo Udal Perucho, Shauhrat S. Chopra, Varut Vardhanabhuti, Lee Wei Lim. Dropout in Neural Networks Simulates the Paradoxical Effects of Deep Brain Stimulation on Memory. Frontiers in Aging Neuroscience. 2020; 12 ():1.
Chicago/Turabian StyleShawn Tan; Richard Du; Jose Angelo Udal Perucho; Shauhrat S. Chopra; Varut Vardhanabhuti; Lee Wei Lim. 2020. "Dropout in Neural Networks Simulates the Paradoxical Effects of Deep Brain Stimulation on Memory." Frontiers in Aging Neuroscience 12, no. : 1.
Finding an appropriate technique to detect an islanding issue is one of the major challenges associated with the design of a resilient grid-linked photovoltaic-based distributed power generation (PV-DPG) system. In general, the technique used for islanding detection must be able to sense the disruptions from the electric grid and quickly disconnect PV-DPG from the grid. The quick disconnection of PV-DPG mostly avoids power quality problems, damage to power assets, voltage stability issues, and frequency instability. In this paper, a new islanding detection technique that is based on tunable Q-factor wavelet transform (TQWT) and an artificial neural network (ANN) is proposed for PV-DPG. The proposed approach consists of two steps: in the first step, the vital detection parameters are computed by performing simulations considering all possible switching transients, islanding events, and faults from the grid side. Then, the decomposition of obtained signals is done using TQWT on different levels. Using the obtained coefficients, at each level, features such as range, minimum, mean, standard deviation, maximum, energy, and log energy entropy are computed. The optimal feature set was selected as the input for the second step. The classification of the non-islanding and islanding states for PV-DPG is made using the ANN classifier in the second step, which achieved an accuracy of 98%. The results representing the efficiency of the proposed approach in noisy and non-noisy environments are also explained. Overall, it is understood that the proposed islanding detection technique would provide suitable insights to detect an islanding issue.
S. Ananda Kumar; M. S. P. Subathra; Nallapaneni Manoj Kumar; Maria Malvoni; N. J. Sairamya; S. Thomas George; Easter S. Suviseshamuthu; Shauhrat S. Chopra. A Novel Islanding Detection Technique for a Resilient Photovoltaic-Based Distributed Power Generation System Using a Tunable-Q Wavelet Transform and an Artificial Neural Network. Energies 2020, 13, 4238 .
AMA StyleS. Ananda Kumar, M. S. P. Subathra, Nallapaneni Manoj Kumar, Maria Malvoni, N. J. Sairamya, S. Thomas George, Easter S. Suviseshamuthu, Shauhrat S. Chopra. A Novel Islanding Detection Technique for a Resilient Photovoltaic-Based Distributed Power Generation System Using a Tunable-Q Wavelet Transform and an Artificial Neural Network. Energies. 2020; 13 (16):4238.
Chicago/Turabian StyleS. Ananda Kumar; M. S. P. Subathra; Nallapaneni Manoj Kumar; Maria Malvoni; N. J. Sairamya; S. Thomas George; Easter S. Suviseshamuthu; Shauhrat S. Chopra. 2020. "A Novel Islanding Detection Technique for a Resilient Photovoltaic-Based Distributed Power Generation System Using a Tunable-Q Wavelet Transform and an Artificial Neural Network." Energies 13, no. 16: 4238.
Even in today’s modern electric grid infrastructure, the uncertainty in the power supply is more often seen and is mainly due to power outages. The reasons for power outages might be any of the following: extreme weather events, asset failure, natural disasters, power surges, acute accidents, and even operational errors by the workforce. Such uncertain situations are permitting us to think of it as a resilience problem. In most cases, the power outages may last from a few minutes to a few weeks, depending on the nature of the resilience issue and the power supply system (PSS) configuration. Therefore, it is imperative to understand and improve the resilience of a PSS. In this paper, a four-component resilience framework is proposed to study and compare the resilience of three different PSS configurations of residential electricity users (REUs) considering the realistic power outage conditions in the humid subtropical ecosystem. The proposed PSS configurations contain electric grid (EG), natural gas power generator (NGPG), battery energy storage (BES), and photovoltaics (PV) as the assets. The three PSS configurations of a REUs are EG + BES, EG + NGPG + BES, and EG + PV + BES, respectively, and in these, one REU is only the consumer and the other two REUs are prosumers. By using the proposed framework, simulations are performed on the three PSS configuration to understand the increasing load resiliency in the event of a power outage. Also, a comparative techno-economic and life cycle based environmental assessment is performed to select the most resilient PSS configuration among the EG + BES, EG + NGPG + BES, and EG + PV + BES for an REU. From the results, it was established that EG + PV + BES configuration would enhance the power resilience of an REU better than the other two PSS configurations. Besides, it is also observed that the identified resilient PSS configuration is cost-effective and environmentally efficient. Overall, the proposed framework will enable the REUs to opt for the PSS configuration that is resilient and affordable.
Nallapaneni Manoj Kumar; Aritra Ghosh; Shauhrat S. Chopra. Power Resilience Enhancement of a Residential Electricity User Using Photovoltaics and a Battery Energy Storage System Under Uncertainty Conditions. Energies 2020, 13, 4193 .
AMA StyleNallapaneni Manoj Kumar, Aritra Ghosh, Shauhrat S. Chopra. Power Resilience Enhancement of a Residential Electricity User Using Photovoltaics and a Battery Energy Storage System Under Uncertainty Conditions. Energies. 2020; 13 (16):4193.
Chicago/Turabian StyleNallapaneni Manoj Kumar; Aritra Ghosh; Shauhrat S. Chopra. 2020. "Power Resilience Enhancement of a Residential Electricity User Using Photovoltaics and a Battery Energy Storage System Under Uncertainty Conditions." Energies 13, no. 16: 4193.
In this chapter, brief insights into the life cycle assessment (LCA) and environmental impacts of solar PV systems will be given. To begin with, the role of solar PV systems in the new energy sector will be highlighted, considering the global scenario. Then, the focus will be drawn onto the environmental impacts associated with solar PV systems. Before going into the details of environmental impacts, brief insights on the methods used for estimating environmental impacts, both in the conventional way as well as using LCA simulation tools, are given. In addition to the commercially available LCA tools, prospective suggestions based on the latest digital technologies are made. Digital tools such as the Internet of Things (IoT), the industrial IoT, and blockchain technology that support the LCA of PV systems are highlighted. Various indicators/impact categories that are generally considered in LCA are also discussed. In later sections, the environmental impacts of PV systems are discussed, considering the life cycle stages in three broad categories: manufacturing, operational, and end of life. Also, the environmental impacts of PV systems due to the current linear business model that is in practice are discussed. Lastly, the circular business model implementation for PV systems and its role in mitigating environmental impacts is highlighted.
Nallapaneni Manoj Kumar; Shauhrat S. Chopra; Pramod Rajput. Life cycle assessment and environmental impacts of solar PV systems. Photovoltaic Solar Energy Conversion 2020, 391 -411.
AMA StyleNallapaneni Manoj Kumar, Shauhrat S. Chopra, Pramod Rajput. Life cycle assessment and environmental impacts of solar PV systems. Photovoltaic Solar Energy Conversion. 2020; ():391-411.
Chicago/Turabian StyleNallapaneni Manoj Kumar; Shauhrat S. Chopra; Pramod Rajput. 2020. "Life cycle assessment and environmental impacts of solar PV systems." Photovoltaic Solar Energy Conversion , no. : 391-411.
A solar photovoltaic (PV) system includes the main components of PV modules, a solar inverter, and a bias of system (BoS), which can generate AC and DC power. However, the desired efficiency of PV systems relies on many factors as well as understanding the component functionality and configuration. Moreover, comprehension of the monitoring techniques and reliable engineering methods are crucial to assure the service life of the PV systems. In this chapter, various components of PV systems are discussed, including modules, convertors, inverters, storage, charge controller, and cables as well as designing different types of PV systems, namely grid-connected, standalone, and hybrid PV systems. Furthermore, this chapter provides detailed information about the monitoring methods, failure identifications, and characterizations of PV systems and ultimately, the effects of environmental and climate conditions on the reliability and durability of PV systems.
Mohammadreza Aghaei; Nallapaneni Manoj Kumar; Aref Eskandari; Hamsa Ahmed; Aline Kirsten Vidal de Oliveira; Shauhrat S. Chopra. Solar PV systems design and monitoring. Photovoltaic Solar Energy Conversion 2020, 117 -145.
AMA StyleMohammadreza Aghaei, Nallapaneni Manoj Kumar, Aref Eskandari, Hamsa Ahmed, Aline Kirsten Vidal de Oliveira, Shauhrat S. Chopra. Solar PV systems design and monitoring. Photovoltaic Solar Energy Conversion. 2020; ():117-145.
Chicago/Turabian StyleMohammadreza Aghaei; Nallapaneni Manoj Kumar; Aref Eskandari; Hamsa Ahmed; Aline Kirsten Vidal de Oliveira; Shauhrat S. Chopra. 2020. "Solar PV systems design and monitoring." Photovoltaic Solar Energy Conversion , no. : 117-145.
PV power plants, so-called grid-connected PV systems, generate AC power for various applications, besides the electricity supply for grid networks. PV power plants are classified into small-scale PV systems (e.g., 1–100 kW) that are used for commercial and residential rooftops and utility-scale PV systems (e.g., > 100 kW), namely ground-mounted systems that supply electric power for urban and industrial applications. This chapter addresses detailed aspects of the implementation phases, that is, the development, engineering, procurement, construction, operation, and maintenance of solar PV power plants. Furthermore, the autonomous monitoring concept is introduced and discussed. Moreover, the quality assurance services, safety issues, and economic issues, namely financial models, feed-in-tariff (FiT), internal rate of return (IRR), net present value (NPV), and payback periods (PBP), are discussed in this chapter.
Mohammadreza Aghaei; Aref Eskandari; Shima Vaezi; Shauhrat S. Chopra. Solar PV power plants. Photovoltaic Solar Energy Conversion 2020, 313 -348.
AMA StyleMohammadreza Aghaei, Aref Eskandari, Shima Vaezi, Shauhrat S. Chopra. Solar PV power plants. Photovoltaic Solar Energy Conversion. 2020; ():313-348.
Chicago/Turabian StyleMohammadreza Aghaei; Aref Eskandari; Shima Vaezi; Shauhrat S. Chopra. 2020. "Solar PV power plants." Photovoltaic Solar Energy Conversion , no. : 313-348.