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Urban densification is seen as a possible solution in response to the intense urbanization and sustainable development. Urban densification counteracts the negative effects of urban sprawl, which include increased mobility challenges, demand of natural resources, greenhouse gas emissions, and encroachment on green spaces. In spite of its benefits, urban densification creates pressure on the existing buried water infrastructure (BWI) (i.e., drinking water, wastewater, and stormwater) and the environment. The impacts of urban densification on the level of service of BWI are overlooked in the published literature. This study aims to identify and discuss the key drivers, induced pressures, their effects on the level of service, corresponding impacts, and finally the possible responses using the Driver-Pressure-State-Impact-Response (DPSIR) linkage-based sustainability assessment framework. The DPSIR framework was selected due to its simplicity and most powerful communication tool between environment and society. The outcome of this study provide a conceptual model, which interlinks the steps (i) identification of system indicators, (ii) data processing, (iii) decision making, and (iv) impact analysis with factors influencing the integrated level of service of BWI at three different levels. Together these steps create a basis for evaluating the level of service of multifaceted BWI. The uncertainties associated with scenarios, datasets, and model development could be a challenge during the application of proposed conceptual framework. The proposed conceptual model may serve as reference for multi-stakeholders in understanding the dynamic balance between urban densification, BWI, and sustainable use of water services. • DPSIR framework has been adopted to highlight the impacts of urban densification. • Integrated level of service of buried water infrastructure is defined at three levels. • A conceptual model has been developed to assess the integrated level of service. [ABSTRACT FROM AUTHOR]

Recharging infrastructure (RI) deployment plays a vital role in improving the public recharging availability for transport electrification. Decarbonizing transportation using low-emission electricity requires massive RI network. Even though the consumers are reluctant to purchase electric vehicles (EVs) until RIs are sufficiently placed, the investors are not willing to invest in RIs due to recharging demand uncertainties. Therefore, a scientific planning framework is needed to ensure the sustainable deployment of EV-RIs in complex networks. In this study, a lifecycle thinking-based multi-period infrastructure-planning framework is proposed to develop sustainable public EV-RIs in an urban context. This framework consists of a temporal model to find the dynamic EV-RI demands, a stochastic model to obtain travel distances, and a multi-objective optimization model to select the best desirable capacities and locations for potential EV-RIs. A case study of a typical medium-scale municipality in Canada was assessed using the proposed framework and validated using conventional infrastructure planning scenarios. The geo-processing data, regional travel behaviors, and recharging characteristics were used as model inputs. The results of the case study showed that the proposed framework can be used to estimate multi-period public recharging demands, minimize lifecycle costs, maximize service coverage and infrastructure utilization, and ensure reasonable paybacks compared to conventional planning approaches. Moreover, this framework can be used to compare different investment assistances, which are required in the early stages of the RI deployment process to encourage investors. Furthermore, government and private institutions can use this framework to identify recharging demands, permitting, and developing RIs in the long-run. • Lifecycle thinking-based planning framework is proposed to develop EV recharging infrastructure. • Temporal and spatial models were used to obtain EV recharging demands and travel distances. • Location-based data, regional travel behaviors, and temporal variations were used as inputs. • Multi-objective optimization was used to obtain capacities and locations for potential facilities. • The method was applied to medium-scale community and validated using expert opinion. [ABSTRACT FROM AUTHOR]

The absence or lack of effective stakeholder engagement during project life cycle, especially at the earlier stages of planning and implementation often negatively impacts the expected performance of projects. These coupled consequences of the lack of contextual knowledge from the stakeholders as well as lack of their support in the field necessitates effective stakeholder engagement. However, this integration faces challenges such as limitations of project resources and conflicting interests of the stakeholders. In this sense, project resources can be allocated based on the priorities of the fields of conflicts to facilitate stakeholder engagement of the projects. The goal of this paper is to provide a framework to enhance effectiveness of the stakeholder engagement in projects by systematically ranking the potential conflicts while combining the viewpoints of stakeholders and project management team. For this purpose, we draw on stakeholder theory, value-based management, matrix-based dependency modeling, and Total Quality Management to develop a stakeholder engagement framework while considering fuzzy inputs for reflecting the ambiguities at the project life cycle. The proposed approach is then applied to plan stakeholder engagement in case of a green building project in Iran. Practically, application of the proposed framework facilitates stakeholder engagement for project managers in line with sustainable goals through early assessment of the fields of potential conflicts of interests. • Developing the sustainability paradigm by integrating various theories and concepts. • Extending the literature of stakeholder engagement in projects. • Integrating stakeholders' and project decision-makers' viewpoints into decisions. • Prioritizing stakeholder engagement actions by assessing their conflicting interests. • Proposing and implementing a quantitative approach to organize steering committees in projects. [ABSTRACT FROM AUTHOR]

• A cradle-to-gate LCA is performed to investigate the environmental impacts due to construction of modular and conventional buildings. • An AHP-based framework is proposed to develop the environmental indices for the material production, construction, and cradle-to-gate phases. • The environmental impacts of construction of three conventional and modular homes in the Okanagan, British Columbia, Canada, are benchmarked. • A basis to create a benchmarking database for environmental performance of modular and conventional construction methods is provided. Traditional on-site and modular off-site methods are the main construction methods in the residential building sector. Regardless of different advantages and disadvantages offered by each of these two construction methods, the overall environmental trade-offs between them are still unclear. This paper applies a cradle-to-gate life cycle assessment (LCA) to benchmark the environmental performance of conventional and modular construction methods. To this end, three single-family buildings (one conventional and two modular) designed and constructed in the Okanagan, British Columbia, Canada, were used as representatives of typical houses built by on-site and off-site methods in the region. The required data such as raw materials, material and workforce transportation, and energy resources was collected from the corresponding homebuilders through a questionnaire survey. Then, the environmental impact measures such as global warming potential were calculated through LCA analyses. Subsequently, the calculated impact measures along with their importance weights were incorporated into an analytic hierarchy process (AHP) based framework to develop a set of environmental impact indices for the material production phase, the construction phase, and summation of these phases (i.e., cradle-to-gate). Furthermore, a sensitivity analysis was performed to eliminate the human subjectivity involved in AHP. Eventually, individual impact measures and also the developed impact indices were compared and contrasted between the benchmarking buildings. The analyses revealed that construction of the first modular building resulted less environmental impacts than the other two buildings. Nevertheless, the lowest environmental performance was due to the second modular building. This disclosed that none of the modular and conventional construction methods is the absolute option for environmentally friendly construction. However, implementation of strategies such as optimal designs and decrease in material and worker transportation of both modular and conventional building projects and increase in annual production of modular manufacturing centers can reduce the material and energy consumption and the subsequent environmental impacts. This paper also provides a basis to create a benchmarking database by adding future LCA studies for new modular and conventional building projects. [ABSTRACT FROM AUTHOR]

Supplying the energy needs of a community through renewable energy sources is a vital aspect in developing sustainable communities. Many variations and uncertainties affect the development of a renewable-powered net-zero energy system. Community developers face challenges in making the investment decisions when planning community-level renewable energy (RE) projects. This study aims to address the need for reliable methods to assess RE project deployment strategies. To achieve this, the key decision variables were identified and dynamic project performance was assessed for a Canadian RE case study. A framework was developed using system dynamics for rating renewable energy project deployment scenarios. A fuzzy logic-based optimization process was used to identify the optimal system capacities and energy mix. The optimal energy supply mix was identified as follows for the case study: grid electricity- 56%, solar PV – 28%, biomass – 11%, and waste-to-energy– 5%. The results of the system dynamics based rating indicated that stage-by-stage construction that also accounts for community growth in facility capacity sizing provides the best outcomes for the community, with 42.8% of the community's energy demand supplied with renewables. The developed model can help community developers to identify the best energy choices and investment strategies when planning community energy systems. • Energy planning involved technical, economic, and environmental dimensions. • Planning hybrid RE systems at community level supports net-zero development. • Multi-objective optimization is used to identify the optimal energy supply mix. • System dynamics modelling is used to evaluate long-term RE project performance. • Phased development with capacity growth is a better choice for community RE. [ABSTRACT FROM AUTHOR]

• Building-level hybrid RE systems support net-zero development goals and climate change mitigation. • Energy planning is multi-dimensional, and is affected by uncertainties. • A life cycle thinking based fuzzy decision support model is presented for identifying optimal hybrid building energy mix. • A combinatorial multi-objective optimisation was adopted considering the most viable RE technologies in the local market. • Solar PV and geothermal heating are the optimal residential energy choices for BC, under the selected case study scenario. The increasing concerns about the environmental and economic impacts of conventional centralised energy generation and fossil fuel usage have prompted an interest in renewable-based decentralised energy systems. Implementing such systems at building level can facilitate the development of net-zero energy buildings. Energy system planning is a multi-faceted problem that involves technical, economic, environmental, and social dimensions, and affects multiple stakeholders at different levels. A multi-objective optimisation approach is needed to identify the optimal energy choices at building level, while paying attention to stakeholder priorities and other constraints. The objective of this study is to develop a model to identify the optimal mix of renewable energy (RE) while also accounting for uncertainties, which can be integrated at building level with life cycle thinking. A framework was proposed for planning an optimised hybrid RE system at building level to support the net-zero development goals. The optimisation model was developed considering the objectives of minimising energy system cost, maximising operational cost savings, minimising the life cycle environmental impacts, and maximising the RE fraction. A combinatorial optimisation approach was adopted to reflect the practical engineering aspects of energy planning problems based on technologies available in the market. The developed framework was demonstrated through a case study conducted for an average multi-unit residential buildings (MURB) located in British Columbia, Canada. The results indicated that under the defined stakeholder priorities and constraints, ground source heat pumps and solar photovoltaics (PV) are the optimal energy choices for MURB, and the optimal energy system combination supplied 44% of the building's energy demand through RE. The findings will inform and guide community developers and other stakeholders with an interest in residential buildings, on the most suitable clean energy options for their building project during the pre-project planning stage. [ABSTRACT FROM AUTHOR]

Various chemicals used in hydraulic fracturing have raised environmental and human health (EHH) concerns regarding water resources contamination, leading to the transition towards the use of chemicals with minimum EHH hazards. Chemical hazard screening and indexing approaches have been used to measure the chemical hazard of hydraulic fracturing, and each approach is associated with inherent advantages and limitations. In this study, the two chemical hazard assessment approaches were discussed, and an integrated chemical hazard screening and indexing system was developed to combine the strengths of the two approaches. The integrated system was applied to assess the EHH hazards of representative hydraulic fracturing chemicals used in British Columbia, Canada. The hazard screening results showed that more than half of the ingredients and additives were classified into high hazard groups. Moreover, the integrated system generated more critical hazard assessment results than two hazard indexing systems, revealing that using the individual hazard indexing approach could result in underestimated EHH hazards for chemicals. The integrated system can significantly improve the data confidence levels of hazard assessment results compared to a previously developed indexing system. The integrated system can also help formulate fracturing fluids with low EHH hazards by identifying ingredients of high hazard concerns. [ABSTRACT FROM AUTHOR]

• An integrated chemical hazard screening and indexing system was developed. • The existing chemical hazard screening and indexing approaches were discussed. • More than half of the assessed chemicals were screened into high hazard groups. • Individual hazard indexing systems could generate underestimated hazard results. Various chemicals used in hydraulic fracturing have raised environmental and human health (EHH) concerns regarding water resources contamination, leading to the transition towards the use of chemicals with minimum EHH hazards. Chemical hazard screening and indexing approaches have been used to measure the chemical hazard of hydraulic fracturing, and each approach is associated with inherent advantages and limitations. In this study, the two chemical hazard assessment approaches were discussed, and an integrated chemical hazard screening and indexing system was developed to combine the strengths of the two approaches. The integrated system was applied to assess the EHH hazards of representative hydraulic fracturing chemicals used in British Columbia, Canada. The hazard screening results showed that more than half of the ingredients and additives were classified into high hazard groups. Moreover, the integrated system generated more critical hazard assessment results than two hazard indexing systems, revealing that using the individual hazard indexing approach could result in underestimated EHH hazards for chemicals. The integrated system can significantly improve the data confidence levels of hazard assessment results compared to a previously developed indexing system. The integrated system can also help formulate fracturing fluids with low EHH hazards by identifying ingredients of high hazard concerns. [ABSTRACT FROM AUTHOR]

To discover an applicable technology for urea abatement from swimming pool water (SPW), this study compared the performances of seven ultraviolet (UV)-based technologies on urea removal, including UV alone, UV coupled with hydrogen peroxide (UV/H 2 O 2), sulfite (UV/Na 2 SO 3), potassium persulfate (UV/K 2 S 2 O 8), a combination of UV and vacuum UV (UV/VUV), and UV/VUV in tandem with either H 2 O 2 (VUV/H 2 O 2) or potassium persulfate (VUV/K 2 S 2 O 8). Among them, UV and UV/Na 2 SO 3 showed little removal ability, and UV/H 2 O 2 removed only 12.8% of urea within 3-h experiments, while UV/VUV degraded 71.7% of urea without introducing substantial total dissolved solids (TDS). Therefore, UV/VUV was considered as a promising technology for further exploration. In comparison, although UV/K 2 S 2 O 8 exhibited higher urea removal than UV/VUV, it caused dramatic increases of TDS, which made the regulatory threshold for the TDS increment difficult to maintain. Within UV/VUV studies, some common components in SPW (e.g., cyanuric acid, humic acid, nitrate, and bicarbonate) inhibited the removal process, whereas chloride and sulfate facilitated it, while free chlorine at doses ≤ 3 mg-Cl 2 /L and pH levels from 6.8 to 8.0 imposed little impact on urea degradation. Overall, UV/VUV degraded 40.0% and 22.2% of urea from tap water and SPW, respectively; both were lower than the efficiency observed in ultrapure water. As for reaction byproducts, urea phototransformation via UV/VUV yielded nitrate and ammonia as the key products with the mass balance of nitrogen element being met. However, the contents of organic carbon decreased at a rate slightly lower than urea degradation, suggesting that urea was mostly mineralized and slightly converted to unknown organic compounds. The results hence demonstrate that UV/VUV is an effective alternative for urea removal from SPW. Image 1 • Seven (V)UV-based processes were compared to control urea. • VUV exhibited higher urea removal yet lower TDS increment than others. • Direct VUV irradiation and indirect oxidation via HO · and SO 4 · - degraded urea. • SO 4 2− and Cl− enhanced yet organic matter inhibited removal of urea. • The key pathway for urea photolysis was mineralization, leading to NH 4 + & NO 3 −. [ABSTRACT FROM AUTHOR]

Rapidly increasing catastrophic environmental incidents and changes in global climate have compelled researchers to take proactive measures for climate change mitigation. Consequently, reducing greenhouse gas emissions has become one of the most significant global targets. The transportation sector has a massive carbon footprint accounting for 22% of the total carbon dioxide emissions. In this regard, road transport contributes the largest fraction of the total emissions within the transportation sector. Conversely, the railway which is the cleanest form of transportation contributes slightly more than 1% of the total emissions. Moreover, since most of the rail systems are operated by government or private companies, it is relatively convenient to implement policies and replace conventional technology with environmentally friendly ones. This could be achieved by taking certain measures from technical and operational viewpoints for conserving energy to lower the carbon intensity of all transport modalities. Hence, this review paper focuses on investigating the railway sector to encourage a modal shift to the least carbon-intensive option. This study provides a critical review of the past and present rail technologies in terms of the environmental, economic, social, and technical perspectives. Moreover, a comparative assessment of the various locomotive types has been performed. The results reveal that battery-hydrogen hybrid locomotives are the best choice to be considered as a future locomotive technology. Hydrogen locomotives have the potential to be a promising alternative to diesel railway locomotives. However, certain technical barriers need to be overcome to enhance the overall system's performance and reliability to further improve the viability of its deployment in the railway sector. [Display omitted] • A critical review of the various rail technologies is provided through different viewpoints. • The assessment constitutes environmental, economic, social, and technical perspectives. • A decision-support tool for comparison of four rail technologies is also developed. • Battery-hydrogen hybrid locomotive results in the highest score of 1.47. • Standalone hydrogen locomotive results in the second highest score of 1.38. [ABSTRACT FROM AUTHOR]

Low impact developments (LIDs) are becoming increasingly popular in North America as viable solution for sustainable runoff management. Although hydrological performance of LIDs in relation to climates is readily available, there is still a gap on the evaluation of environmental and economic impacts of these infrastructures. We have evaluated the cradle-to- site lifecycle environmental and economic impacts of four LIDs using a case study of the stormwater management system at UBC Okanagan campus in BC, Canada. The environmental impacts and costs are determined via ReCiPe, TRACI, and net present value (NPV) method, respectively, and incorporated to obtain eco-efficiency of these LIDs. We found that the box planter and naturally occurring wetland on campus are the best LIDs with lower impacts (approximately 2.5% of the total impacts) than other LIDs. The cost savings from wetland are enormous due to zero construction and periodic maintenance after every five years. The box planter and wetland occupy the most favorable quadrant III of the eco-efficiency matrix whilst, bioswales and rain gardens are found in quadrant IV and I, respectively. When compared to the constructed wetland, an increase in the economic impacts is found without any influence on the eco-efficiency of the overall placement on eco-efficiency matrix. The maintenance phase contributes more to environmental impacts than the construction, whereas the life cycle cost analysis shows the opposite. [Display omitted] • Life cycle impacts, life cycle cost, and eco-efficiency is assessed for four Low Impact Developments (LIDs). • Box planter and naturally occurring wetland have significantly lower impacts than rain gardens. • The maintenance phase contributes more to environmental impacts than the construction phase. • The cost for construction is higher than maintenance phase. [ABSTRACT FROM AUTHOR]

Production of hydrogen fuel from municipal solid waste can serve as a potential solution to two looming environmental crises: global warming caused by undesirable emissions of greenhouse gases and the ever-increasing generation and accumulation of waste in the environment. However, the actual implementation and continuous operation of waste-to-hydrogen conversion facilities require consideration of numerous factors. This study explored the variability of several factors related to waste-to-hydrogen, such as location selection, geographic availability of municipal solid waste, pricing of by-products and waste acceptance, constantly fluctuating energy costs, and carbon credit market values from potential carbon trading systems. Four waste conversion processes previously studied for their triple-bottom-line sustainability have been used as baseline scenarios. The variability of multiple factors and their impacts were assessed via parametric analyses. The effects of these fluctuating factors on the economic and environmental performances of waste-to-hydrogen conversion and the establishment of processing facilities were captured. The results of this study will be beneficial for the industry, private investors, policymakers, and governments while making critical decisions such as location selection, deriving price formulas, and selecting plant capacity. • Implementation of four waste-to-hydrogen processes is studied. • Variabilities impacting levelized cost of hydrogen and global warming are assessed. • Economies of scale attained in all processes except waste pyrolysis. • Waste gate fee, carbon credits, and by-product sales reduce levelized costs. • Areas with high population density are suited for waste-to-hydrogen implementation. [ABSTRACT FROM AUTHOR]

Water is a finite resource. Increasing population, rapid urbanization, and climate change incidents are continuously adding pressure on freshwater supplies. Overcoming these issues require change in current urban water management (UWM) strategy. In this study, a conceptual model of One Water Community has been developed that aims to reduce potable water use (R PWU) using One Water Approach (OWA). Based on OWA's six guiding principles, five interventions (i.e., control factors) and sixteen parameters have been identified. Each parameter is simulated twice by running 10,000 iterations to calculate a percentage reduction of potable water use at 90th, 50th, and 10th percentiles. A Taguchi-based optimization method has been used to determine the optimum combination of parameters from each of the five control factors [water saving appliances (WSA), reclaimed water use (RWU), resource recovery (RR), low impact development (LID), and good governance (GG)]. L 16 orthogonal array experimental design plan was considered in conducting the trials. ANOVA analysis showed that RWU, RR, and WSA were the most influential factors on R PWU performance at 90th, 50th, and 10th percentiles. Validation tests validated the model by predicting the S/N ratio at the optimum condition. The findings indicated that water sense labeled urinals, reclaimed water for agriculture purposes, emissions reductions from treatment plants, bioswales, and increased public awareness were the most optimum parameters in achieving the highest potable water reduction potential at the 90th percentile. The developed model will open new avenues in UWM, which will assist decision-makers in building sustainable, reliable, and resilient urban water systems. [Display omitted] • One Water Approach concept is capable to bring a change in urban water management. • A conceptual model of One Water Community was developed based on six principles. • Five factors and sixteen parameters were identified to reduce potable water use. • A Taguchi based technique was employed to determine optimum parameters combination. • Experimental values were greater than predicted values to justify the optimum condition established in the study. [ABSTRACT FROM AUTHOR]

Abstract Disinfection by-products (DBPs) in indoor swimming pool water and air have long been a critical human health risk concern. This study investigated the effects of several indoor swimming pool design and management factors (e.g. ventilation, water treatment, pool operations, pool type) on the concentrations of DBPs, such as trihalomethanes (THMs) and chloramines, in pool water and air. Two sampling campaigns, A and B, were carried out to measure the concentrations of DBPs under different conditions. In both campaigns, 46 pool water samples, seven tap water samples, and 28 ambient air samples were collected and analyzed. Regression models were also developed and validated for investigating the combined effects of design and management factors on total trihalomethanes (TTHM) and trichloramine. The model results show that pool water characteristics (e.g., total organic content, temperature, conductivity, pH and alkalinity) and management factors (e.g., the number of bathers and sprayers) have direct effects on DBP concentrations. Pool water characteristics such as UV absorbance, hardness, and oxidation-reduction potential and a management factor UV intensity have inverse effects on DBPs levels. Based on the correlation analysis, other factors such as fan speed, fresh air, pool age, and basin area were found to be correlated with the concentrations of individual THMs and trichloramine in both water and air. It was also observed that the concentration of THMs varies with pool type. It is note worthy that the effects of the number of sprayers was quantified for the first time. This study comprehensively assessed pool design and management factors and identified their effects on DBPs, providing indoor swimming pool facilities with useful information to control DBPs in the indoor swimming environment. Graphical abstract Unlabelled Image Highlights • Disinfection by-products in air and water were analyzed at five aquatic centers. • Effects of water treatment processes on trihalomethanes and trichloramine were compared. • Correlation of design and management factors with disinfection by-products was evaluated. • Regression models were developed for trihalomethanes and trichloramine. • First time to quantify the effect of number of spray features on air and water quality [ABSTRACT FROM AUTHOR]

Abstract Introduction : The safety of oil and gas pipelines is an increasing concern for the public, government regulators, and the industry. A safety management system cannot be efficient without having an effective integrity management program (IMP) and a strong safety culture. IMP is a formal document (policies, planning, scheduling, and technical processes) while safety culture is a measure of views, beliefs, and traditions about safety. For regulatory authorities and O&G companies, assessing the effectiveness of both the IMP and safety culture through regulatory audits is a daunting task with indistinct findings. Method : An integrated framework based on regulatory audits is developed to assess the maturity of safety culture based on IMP efficacy through risk-based approach by using failure mode and effect analysis (FMEA). The framework focuses on three distinct aspects, the probability of failure occurrence in case of the non-compliance of regulatory and program requirements, severity of non-compliance, and effectiveness of the corrective actions. Results : Program requirements and performance indicators are translated into assessment questions which are grouped into 18 IMP components. Subsequently, these components are linked with four safety culture attributes. Sensitivity analysis revealed that four IMP components, i.e., organizational roles and responsibilities, policy and commitment, risk assessment, and training and competency, significantly affect the safety culture maturity level. Conclusions : Individual assessment of IMP and safety culture in O&G sector consumes extensive time and efforts in the auditing process. The framework facilitates the process by pursuing common criteria between IMP and safety culture. The O&G companies and regulator can prioritize the improvement plans and guidelines using the framework's findings. Practical applications : The integrated framework developed in this research will improve the existing assessment mechanism in O&G companies. The framework has been effectively implemented on a case of 17 upstream O&G pipeline-operating companies in the province of British Columbia, Canada. [ABSTRACT FROM AUTHOR]

Abstract Developing net-zero energy communities powered by renewable energy (RE) resources has become a popular concept. To make the best choices for community-level net-zero energy systems, it is necessary to identify the best energy technologies at local level. Evaluation of RE technologies has to be extended from technical and economic aspects to include environmental and social wellbeing. It is possible to identify the true costs and benefits of energy use by taking a cradle-to-grave life cycle perspective. In this study, a RE screening and multi-stage energy selection framework was developed. A fuzzy multi-criteria decision making approach was used in ranking the technologies to incorporate the conflicting requirements, stakeholder priorities, and uncertainties. Different scenarios were investigated to reflect different decision maker priorities. Under a pro-environment scenario, small hydro, onshore wind, and biomass combustion technologies perform best. Under a pro-economic decision scenario, biomass combustion, small hydro, and landfill gas have the best rankings. Triple bottom line sustainability was combined with technical feasibility through a ruled-based approach to avoid the theoretical pitfalls inherent in energy-related decision making. This assessment is geared towards providing decision makers with flexible tools, and is expected to aid in the pre-project planning stage of RE projects. Highlights • Energy planning needs to be done at community level for optimal outcomes. • Considering life cycle impacts and uncertainty is important in energy planning. • Different decision scenarios were considered in selecting technologies. • Small hydro and biomass perform particularly well for British Columbia. • The developed method provides decision makers with flexible planning tools. [ABSTRACT FROM AUTHOR]

Abstract Water disinfection involves the use of different types of disinfectants, which are oxidizing agents that react with natural organic matter (NOM) to form disinfection by-products (DBPs). The United States Environmental Protection Agency (USEPA) has established threshold limits on some DBPs, which are known as regulated DBPs (R-DBPs). The human health risks associated with R-DBPs in drinking water distribution systems (DWDSs) and application of stricter regulations have led water utilities to switch from conventional disinfectant (i.e., chlorination) to alternative disinfectants. However, the use of alternative disinfectants causes formation of a new suit of DBPs known as unregulated DBPs (UR-DBPs), which in many cases can be more toxic. There is a growing concern of UR-DBPs formation in drinking water. This review prioritizes some commonly occurring UR-DBP groups and species in DWDSs based on their concentration level, reported frequency, and toxicity using an indexing method. There are nine UR-DBPs group and 36 species that have been identified based on recent published peer-reviewed articles. Haloacetonitriles (HANs) and haloacetaldehydes (HALs) are identified as important UR-DBP groups. Dichloroacetonitrile (DCAN) and trichloroacetaldehye (TCAL) are identified as critical UR-DBPs species. The outcomes of this review can help water regulators to identify the most critical UR-DBPs species in the context of drinking water safety and provide them with useful information to develop guidelines or threshold limits for UR-DBPs. The outcomes can also help water utilities in selecting water treatment processes for the mitigation of human health risk posed by UR-DBPs through drinking water. Graphical abstract Image 1 Highlights • Unregulated disinfection by-products in drinking water were comprehensively reviewed. • Commonly occurred unregulated disinfection by-products were prioritized. • Haloacetonitriles were identified as the most important group. • Dichloroacetonitrile and trichloroacetaldehyde were the most critical species. [ABSTRACT FROM AUTHOR]

Abstract Household energy consumption and carbon footprints change with household characteristics such as type of residence, energy system performance, vehicle performance, and users' behavioral patterns. Accordingly, alternative energy technologies, such as clean electricity, hydrogen fuel cells, and energy efficient interventions, are being adopted in many parts of the world to reduce the residential, industrial, and transportation emissions. This paper presents a comprehensive research framework to identify the most desirable building retrofits and incentive schemes for Canadian households. Globally available incentive policies for low-emission vehicles and locally available retrofit options for single-family detached houses were identified during this study. A decision support tool based on life cycle thinking was developed to assess economic parameters, such as capital investment and annualized consumer cost, and environmental parameters such as greenhouse gas emissions. In order to rank and select the most desirable building retrofit, the TOPSIS ranking method was used. The linear programing graphical method was used to select the best incentive policy for low-emission vehicles. Finally, scenario analysis was used to compare different households based on regional economic and environmental characteristics. Provinces which have low-emission electricity grids such as Manitoba, British Columbia, and Quebec can primarily focus on incentives for electrified transportation. Additionally, the incentives for retrofits such as greener appliances and heating, ventilation, and air conditioning systems would also significantly reduce building carbon footprint. Conventional residential buildings with fossil fuel vehicles are more desirable for provinces like Saskatchewan, Alberta, and Nova Scotia which have high-emission electricity grids. Based on the outcomes of this research, a scientific incentive planning and management approach considering regional economic and environmental characteristics was introduced. Highlights • Life cycle thinking-based economic factors and operating emissions of single-detached household were analyzed. • Possible retrofit incentives and retrofit combinations were ranked based on regional economic and environmental factors. • Regions with low emission electric grids can primarily focus on incentives for electrified transportation system. • Conventional households and fossil-vehicles are desired for the areas with higher emission factor electric grid. [ABSTRACT FROM AUTHOR]

The role of energy transition amidst the energy crisis and how policymakers can drive down emissions while focusing on energy security are critical. Given the geo-political situation, energy crisis volatility, energy shortage and climate change all affect the green transition and the short-term priorities for energy companies and policymakers. Energy security is not an isolated issue but has widespread implications as various sectors depend on energy supply to function properly. Governments around the world are faced with this trilemma, how to balance energy security with energy sustainability while also considering energy affordability. Sustainability has been in focus for about a decade. However, energy security is suddenly becoming one of the most important priorities that policymakers need to consider. Unfortunately, the renewable energy infrastructure is not yet ready to replace the growing volume of energy demand from hydrocarbon, which the world has been dependent on. This means, for now, a surge in energy generation through hydrocarbon to meet the existing energy demand deficit. However, it is important not to lose focus on the challenge of energy sustainability and climate change adaption and mitigation. Where trends like carbon capture and storage; solar, wind, hydro, green hydrogen, etc.; renewable energy infrastructure and integrations, with supply chain and engineering services consideration [in aspect for the growing market in this space] need better attention with regards to investment and full-scale implementation. This paper aims to analyze this 1st energy crisis of green transition with a priori on energy poverty with consideration of major influences and associated impacts. Furthermore, it proposes a specific framework for inclusive investigations, which considers the entire energy ecosystem with consideration of major influences, to enable the policymakers to better drive the green transition. This involves formulating energy policies that are not entirely conservative towards renewable energy sources but instead promote investments in both green and relatively more environmentally benign energy sources compared to high emission hydrocarbons. In this regard, this paper renders exhaustive prospects and recommendations. • The nexus between energy transition, energy poverty and their impacts are investigated. • Influence of climate change, COVID-19, geo-politics, and energy infrastructure on energy transition. • Exhaustive prospects and recommendations are rendered. • Requirement for inclusive investigations and recognition of energy poverty. [ABSTRACT FROM AUTHOR]

A fuzzy-based indexing approach was developed for the management of hydraulic fracturing chemical additives. The environmental and human health hazards of an additive are converted to hazard indices using an indexing system. To account for uncertainties, a fuzzy-based approach is adopted based on fuzzy inference and fuzzy clustering analysis to assess the risk potential of different additives for informed chemical management decision making. The assessment of the randomly selected additives showed that this fuzzy-based indexing approach gave different chemical hazard assessment results for about 30% of the assessed additives. This shows that accounting for uncertainties using this methodology can lead to better informed chemical management decision making. The hazard assessment results also indicate that based on current indexing methodology more than half of the additives permitted for use in hydraulic fracturing operations are considered moderate environmental and human health hazards. However, based on the new fuzzy-based approach the majority (80%) of the additives were identified as low and very low risk potential due to their low use frequencies. [ABSTRACT FROM AUTHOR]

Evolutionary games with the fuzzy set are attracting growing interest. While among previous studies, the role of the reliability of knowledge in such an infrastructure is still virgin and may become a fascinating issue. Z-number is combined with “restriction” and “reliability”, which is an efficient framework to simulate the thinking of human. In this paper, the stable strategies analysis based on the utility of Z-number in the evolutionary games is proposed, which can simulate the procedure of human’s competition and cooperation more authentically and more flexibly. Some numerical examples and an application are used to illustrate the effectiveness of the proposed methodology. Results show that total utility of Z-number can be used as an index to extend the classical evolutionary games into ones linguistic-based, which is applicable in the real applications since the payoff matrix is always determined by the knowledge of human using uncertain information, e.g., (outcome of the next year, about fifty thousand dollars, likely). [ABSTRACT FROM AUTHOR]

The rapid expansion of unconventional natural gas production has triggered considerable public concerns, particularly regarding environmental and human health (EHH) risks posed by various chemical additives used in hydraulic fracturing (HF) operations. There is a need to assess the potential EHH hazards of additives used in real-world HF operations. In this study, HF additive and fracturing fluid data was acquired, and EHH hazards were assessed using an indexing approach. The indexing system analyzed chemical toxicological data of different ingredients contained within additives and produced an aggregated EHH safety index for each additive, along with an indicator describing the completeness of the chemical toxicological data. The results show that commonly used additives are generally associated with medium-level EHH hazards. In each additive category, ingredients of high EHH concern were identified, and the high hazard designation was primarily attributed to ingredients' high aquatic toxicity and carcinogenic effects. Among all assessed additive categories, iron control agents were identified as the greatest EHH hazards. Lack of information, such as undisclosed ingredients and chemical toxicological data gaps, has resulted in different levels of assessment uncertainties. In particular, friction reducers show the highest data incompleteness with regards to EHH hazards. This study reveals the potential EHH hazards associated with chemicals used in current HF field operations and can provide decision makers with valuable information to facilitate sustainable and responsible unconventional gas production. [ABSTRACT FROM AUTHOR]

During the recent past, the individual responsibility of climate change mitigation has been acknowledged by the society at large. Energy planning is pivotal in mitigating GHG emissions and adopting climate resilient strategies. However, community level energy planning has been overlooked in the urban development planning and the approval process. Many energy and emission reduction approaches are still voluntary for the developers and been pursued on ad-hoc basis. The objective of this study is to propose a systematic framework for renewable energy integration in community development. A scenario-based study was conducted for an upcoming neighbourhood in Okanagan, British Columbia (BC), Canada. Scenarios were assessed based on the life cycle cost (LCC) and GHG emission reduction. The scenarios were then compared based on costs and benefits to key stakeholders. Results of this study revealed that a higher share of renewable sources in the energy mix does not necessarily reduce LCC or GHG emissions. The benefits which can be achieved via incorporating renewables to the regional energy mix varies, depending on the existing energy sources in the mix. Therefore, regional power grid mix influences the feasibility and acceptability of RE integration at a given location. Developers should be aware of the optimal investment level which could be fully or partially recovered by premium home prices. The government should promote this practice via various incentives such as tax credits, grants etc. Findings of this research would mainly inform urban developers in renewable energy planning and local government in formulating climate action policies. [ABSTRACT FROM AUTHOR]

Climate-conscious development is a topic which has received widespread attention. One consequence of this is the prominence of greenhouse gas (GHG) emissions reduction targets set at various administrative levels (i.e. global, national, provincial and local governments). Despite the global interest, current models are incapable of integrating GHG emission reduction into the urban planning. This study presents lessons learned from a climate conscious growth study conducted for a fast-growing municipality in Okanagan, British Columbia, Canada, offering a model for local government target-setting generalizable across networks of communities, leading to significant cumulative GHG reductions at global scale. The study uses the results of engineering-based research to evaluate multiple planning scenarios developed to explore options for the subject municipality’s future urban form and the associated GHG emissions for the target year 2040. Overall municipal GHG emissions for each scenario were simulated in the study considering the residential and transportation emissions projections. The findings indicated that the lowest emissions scenario was the ultra-compact growth model without area structure plan (ASP) allocations. Accordingly, it was concluded that a densified growth strategy with a higher share of multi-unit residential development is technically the best path forward in municipal growth planning to meet climate action targets. Negative public perception of increased densification in urban areas remains an obstacle to the technically best solution. Moreover, per capita basis could be a more feasible approach for GHG emissions target setting. This study’s outcomes are expected to inform public sector institutions and decision makers in setting GHG targets and climate action planning. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has unprecedentedly entangled the physical world with cyber technologies and its integration with building infrastructure (BI) is no different. Integration of IoT can impart BI with upscale features like remote operations, automated management and user-centric facilities by developing an interconnected cognitive building (CB) ecosystem. However, this integration has entered an ambiguous phase of realizing mature adoption and practical utilization of IoT in BI for both academic and industrial domains. This ambiguity restricts the IoT and BI stakeholders to comprehend and acknowledge the full operational competency of IoT in BI. Thus, a significant research gap exists that deeply investigates the practical implementation and mature adoption of IoT in BI. The prime objective of this study is to establish a comprehensive review by exploring the state-of-art academic, technological and industrial research to identify major technological and behavioural interventions that successfully enhance the integration of IoT in BI. Besides, this study also highlights significant technical and non-technical challenges that require substantial research efforts for maturing the adoption of IoT in BI. The findings of the study argue that the full operational competency of IoT in BI is not yet realized and a dedicated effort from both IoT and BI stakeholders is required to provide modern BI with a generic IoT framework having cognitive intelligence and context-aware computing capabilities. The proposed study will assist the researchers in realizing the full operational competency of IoT in BI for more exciting innovations. • Adoption and implementation of IoT in building infrastructure are investigated. • Technological and behavioural interventions for cognitive intelligence in buildings. • Requirement of a seamlessly unified IoT framework for future buildings. • Trends, challenges and future research to effectively implement IoT in buildings. [ABSTRACT FROM AUTHOR]

[Display omitted] • Renewable natural gas (RNG) can be produced from landfill gas, wastewater sludge, and animal waste. • Triple bottom line performance of waste-derived gaseous fuel was assessed using LCA and LCC. • Animal manure-derived RNG production provides the best environmental performance. • LFG-derived RNG yield the highest suitability from neutral and environmental perspectives. • RNG production suitability varies with regional conditions and decision contexts. Renewable natural gas (RNG) is one of the most prominent fuels that help reduce upstream emissions from conventional natural gas networks without significant infrastructure changes. While the current resources for RNG are insufficient, there is a substantial interest in establishing the viability of integrating RNG into the gaseous-fuel industry portfolio. However, holistic studies that support the assessment and selection of the fuel production paths are limited. Therefore, the current study attempts to close that gap by introducing a systematic approach to assess the project viability of RNG investments. Twelve waste-to-RNG configurations were evaluated based on three types of waste feedstock and four biogas upgrade technologies in three selected population centres. Life cycle environmental and life cycle cost assessment tools were employed to determine the ecological footprint and economic performance of RNG production routes. Multi-criteria decision-making was applied using the TOPSIS method under varying stakeholder perspectives to derive suitability indices for RNG investments. Finally, recommendations were provided based on the results obtained for successfully implementing waste-to-RNG supply chain paths. According to study findings, not all RNG production methods guarantee positive returns. The least environmental impacts were assured by the anaerobic digestion of animal manure. However, the lowest returns were obtained via the same route. From a pro-economic and neutral decision perspective, landfill gas-based RNG production achieved higher suitability scores. The proposed framework is flexible and can be customized to suit varying decision priorities. The findings are geared towards supporting utility providers, community developers, and potential investors to foresee the success of planned RNG projects to ensure sustainable gaseous fuel networks. [ABSTRACT FROM AUTHOR]

Sustainability evaluation of pavement alternatives for given traffic loading and environmental conditions has always been a challenging task for pavement designers and managers. Pavement engineers and managers mainly use life cycle cost analysis (LCCA) to make a decision while the recent focus of academic research and regulatory agencies was more on the life cycle assessment (LCA) to evaluate the environmental impacts of different pavement alternatives. LCCA and LCA for more recent technologies, such as geosynthetics, have been relatively less addressed so far. Moreover, uncertainties due to inadequate data can also reduce effectiveness of the decision making process during the planning phase. In this research, an integrated LCCA and LCA framework is developed for sustainability evaluation of different pavement alternatives based on an integrated economic and environmental trade-off analysis. The framework can effectively evaluate different pavement technologies, including flexible, concrete, geosynthetics, and their combinations under different subgrade characteristics and traffic conditions. The fuzzy composite programming (FCP) is used: (i) to deal with the uncertainties associated with limited data and vagueness in experienced judgment, (ii) to integrate the results obtained from LCCA and LCA, and (iii) for final ranking of pavement alternatives. For final selection, decision makers can trade-off between cost and environmental impacts over the life cycle of the pavement alternative. The study results indicate that geosynthetics can be used to enhance the pavement service life for low volume roads with optimized cost and minimum environmental impacts. [ABSTRACT FROM AUTHOR]

Continuous performance improvement (CPI) can be a useful approach to overcome water quality problems impacting small communities. Small drinking water systems (SDWSs) struggle to meet regulatory requirements and often lack the economic and human resource flexibility for immediate improvement. A CPI framework is developed to provide SDWS managers and operators an approach to gauge their current performance against similar systems and to track performance improvement from the implementation of the new technologies or innovations into the future. The proposed CPI framework incorporates the use of a water quality index (WQI) and functional performance benchmarking to evaluate and compare drinking water quality performance of an individual water utility against that of a representative benchmark. The results are then used to identify and prioritize the most vulnerable water quality indicators and subsequently identify and prioritize performance improvement strategies. The proposed CPI framework has been demonstrated using data collected from SDWSs in the province of Newfoundland and Labrador (NL), Canada and using the Canadian Council of Ministers of the Environment (CCME) WQI. [ABSTRACT FROM AUTHOR]

Water utilities often rely on water main failure prediction models to develop an effective maintenance, rehabilitation and replacement (M/R/R) action plan. However, the understanding of water main failure becomes difficult due to various uncertainties. In this study, a Bayesian updating based water main failure prediction framework is developed to update the performance of the Bayesian Weibull proportional hazard (BWPHM) model. Applicability of the proposed framework is illustrated with modeling failure prediction of cast iron and ductile iron pipes of the water distribution network of the City of Calgary, Alberta, Canada. The Bayesian updating models have effectively improved the water main failure prediction whenever new data or information becomes available. The proposed framework can assess the model performance in the light of uncertain and evolving information and will help the water utility authorities to attain an acceptable level of service considering financial constraints. [ABSTRACT FROM AUTHOR]

The global climate is being heavily affected by greenhouse gas (GHG) emissions, the most significant of which is carbon dioxide (CO 2). According to the Pan-Canadian framework on clean growth and climate change, Canada has set ambitious targets to realize a low carbon future. Amongst the available emission reduction strategies, on-site carbon capture, utilization, and storage (CCUS) is a proven technology capable of abating CO 2 emissions from fossil fuel-based energy systems. However, the viability of CCUS technologies is still uncertain and is subjected to numerous dynamic parameters. This study aims to assess the long-term economic viability of integrating carbon capture technologies into community emission planning. Key decision variables were identified, and the dynamic economic performance of CCUS investments was assessed for academic complexes located in two locations in Canada. A system dynamics model was developed to assess the future costs of carbon capturing projects. The study outcomes showed that CCUS is more feasible in provinces with high reliance on fossil fuel energy sources. Moreover, a significant portion of carbon capture costs is taken by infrastructure. Government policies have a critical role in accelerating the commercialization of CCUS technologies. The findings from this study are geared toward providing useful decision-support tools for policy experts, investors, and utility providers who are responsible for policy and investment decisions. Policymakers and investors will be benefited from the proposed model to develop customized regional policies and make investment decisions by considering dynamic regional aspects. Moreover, the results provide insight into what areas require attention in making CCUS economically viable. • System dynamics modelling can be used to predict carbon capture costs subjected to dynamic parameters. • Emission reduction with carbon capturing may change depending on regional parameters. • Carbon capture costs are sensitive to energy demand, grid composition, and carbon dioxide transport distances for utilization. • Community energy Infrastructure development and climate policies are essential in improving economies of carbon capturing technology. [ABSTRACT FROM AUTHOR]

Passive houses optimize energy gains and losses to attain higher energy efficiencies, comfort levels, and affordability. This article allows attaining a broader understanding of the risks and opportunities of passive technologies and their impacts through a social cost-benefit analysis framework. Time value of money was incorporated to evaluate the net present values (NPV), cost-benefit ratios, and internal rates of return. Five alternative houses consisting of passive and net-zero technologies were compared against a conventional design (traditional model). The base model with renewable energy integrations indicated higher impacts on the cumulative cost-benefits in economic, social, and environmental perspectives. Furthermore, a sensitivity analysis evaluated the effects of independent variables such as the interest rate and energy consumption on the performance metrics. This paper allows users to attain a holistic idea of implementing passive dwellings in a selected region through a social cost-benefit point of view. • A framework to evaluate passive house application for a region was developed. • Economic, social, environmental costs and benefits were considered in the framework. • Socio-environmental factors have a significant impact on the study's performance. • Incorporation of renewable energy provides higher benefits for the alternatives. • Passive houses increase overall benefits and decrease environmental impacts. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sustainability of four waste-to-hydrogen conversion methods is evaluated. • Pyro-gasification and bioreactor landfills are assessed in hydrogen production. • Lifecycle thinking and VIKOR method-based multicriteria decision-making are used. • Reactor heating method, electricity mix, and waste transportation fuel are varied. • Gasification provides highest yields; pyrolysis causes lowest lifecycle impacts. Waste-derived hydrogen (H 2) has been identified as a clean energy source which could simultaneously abate greenhouse gas (GHG) emissions and avert municipal solid waste (MSW) from being deposited in perpetual landfills. In this study, four waste-to-hydrogen processes – gasification, pyrolysis, integrated pyrolysis-gasification, and landfill bioreactor technology – are studied with MSW as feedstock. Following technological evaluations, life cycle assessment and life cycle costing are performed for different scenarios and configurations to evaluate their environmental footprint, levelized cost of H 2 , and energy return on investment. Finally, multicriteria decision-making was applied using the VIKOR method under four weighting schemes to evaluate the four processes under varying decision-making contexts. Gasification results in the highest H 2 outputs and energy returns, whereas pyrolysis produces the lowest levelized cost due to its biochar by-product formation. Nevertheless, all four technologies proved to be performing optimally under different weightings of environmental, economic, and social elements, suggesting the versatility of the waste-to-hydrogen concept and its suitability to be applied in various decision-making contexts. The results and novelties of this study would contribute toward planning and investment decision-making in sustainable H 2 production and clean energy. [ABSTRACT FROM AUTHOR]

The ever-increasing anthropogenic greenhouse gas (GHG) emissions worldwide make it quite challenging to meet country-specific Nationally Determined Contributions (NDC) targets. Therefore, it is evident that the existing emissions abatement measures need to be taken a step further. Internationally Transferred Mitigation Outcomes (ITMOs) are allowed in Article 6.2 of the Paris Agreement as a cooperative approach to achieving NDC goals. There is a potential to create ITMOs between Canada and China by replacing coal use in China with British Columbia (BC)'s liquefied natural gas (LNG) supply. Replacing coal with LNG in energy generation applications is a promising approach to mitigate emissions. With global and national pressures to reduce emissions, China has created a market for LNG imports to cater to its rising natural gas (NG) consumption due to the coal-to-gas source switching strategy. However, the terms under Article 6.2 requires generated ITMOs to ensure environmental integrity, support sustainable development goals, and have a robust accounting system. Therefore, the current study aims to quantify the life cycle environmental outcomes of generating ITMOs by exporting LNG from BC to Chinese end-users while integrating uncertainties and to provide policy recommendations in adherence with the requirements of Article 6.2. Different LNG export scenarios were generated in the study and environmental impacts of each scenario were assessed and compared using a life cycle assessment (LCA) framework developed by the authors. Sensitivity and uncertainty analyses were conducted to understand the impacts created by the data uncertainties in the final result. By replacing conventional coal with NG, approximately 40–45% and 26%–32% emissions reductions can be obtainable for Chinese textile and chemical industries, respectively. The highest emissions reduction of approximately 60% was observed when coal is replaced with NG for district heating. The life cycle emissions (LCE) quantification framework provided in the study provides stakeholders with a systematic approach to determine the total GHG emissions and emissions reduction potential of different LNG export scenarios. [ABSTRACT FROM AUTHOR]

Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, and finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies. [ABSTRACT FROM AUTHOR]

Multi-criteria decision making process is a widely concerned issue. In traditional studies, it is assumed that a decision maker’s behaviors are not affected by others. However, competitive environment is more general in real world where everybody maximizes his benefits and each people is inevitably influenced by others’ behaviors. In this paper, an evidential game theory framework is proposed in order to address the multi-criteria decision making process in the competitive environment. The proposed framework includes five stages, namely game analysis, decision-making analysis, strategies evaluations, fusion of evaluations, decision based on equilibrium, respectively. Within the proposed framework, a representation form of uncertain information called belief structure derived from Dempster–Shafer theory is employed to model the uncertainty involving experts’ subjective evaluations. The game theory is used to find the optimal combination of strategies in the interactive decision situations. The application of the proposed evidential game theory framework is given by an illustrative example. [ABSTRACT FROM AUTHOR]

Abstract: The exposure and toxicological data used in human health risk assessment are obtained from diverse and heterogeneous sources. Complex mixtures found on contaminated sites can pose a significant challenge to effectively assess the toxicity potential of the combined chemical exposure and to manage the associated risks. A data fusion framework has been proposed to integrate data from disparate sources to estimate potential risk for various public health issues. To demonstrate the effectiveness of the proposed data fusion framework, an illustrative example for a hydrocarbon mixture is presented. The Joint Directors of Laboratories Data Fusion architecture was selected as the data fusion architecture and Dempster–Shafer Theory (DST) was chosen as the technique for data fusion. For neurotoxicity response analysis, neurotoxic metabolites toxicological data were fused with predictive toxicological data and then probability-boxes (p-boxes) were developed to represent the toxicity of each compound. The neurotoxic response was given a rating of “low”, “medium” or “high”. These responses were then weighted by the percent composition in the illustrative F1 hydrocarbon mixture. The resulting p-boxes were fused according to DST's mixture rule of combination. The fused p-boxes were fused again with toxicity data for n-hexane. The case study for F1 hydrocarbons illustrates how data fusion can help in the assessment of the health effects for complex mixtures with limited available data. [Copyright &y& Elsevier]

The day-ahead energy management scheme (EMS) of a microgrid faces different uncertainties due to the inaccuracy of predictions. Moreover, offline EMS assumes that renewable generation and load demand predictions are perfect, which is practically difficult to achieve. Although real-time EMS (RT-EMS) can overcome these uncertainties by employing online measurements, utilization of storage units in RT-EMS needs further investigation because the solution does not achieve the global optimal. In this study, a multi-objective RT-EMS is proposed by considering the costs and life cycle environmental impacts of energy sources. The suggested RT-EMS is designed using Lyapunov optimization method and then enhanced through the proposed adaptive utilization of the storage units. The charging and discharging of the storage units are scheduled adaptive to the time-of-use market price, resulting in lower environmental impacts because the life cycle environmental impact of energy storage is significant. Therefore, the proposed RT-EMS is a multi-objective problem, and a Pareto front is derived from compromising between the operational cost and the environmental impacts. The proposed market price-based RT-EMS is evaluated using numerical studies on the modified IEEE 33-bus test system and real-world data. • A multi-objective economic-environmental real-time energy management system is proposed. • Environmental impacts of energy sources are considered in the proposed energy scheduling problem • Online optimization is modeled using the Lyapunov technique with the Variable V method. • Adaptive use of distributed energy storage units is proposed based on the time-of-use electricity price. • Environmental impacts and operational costs are enhanced by the adaptive use of energy storage units. [ABSTRACT FROM AUTHOR]

• Maintenance scheduling of generation units in a CHP-integrated system with demand response. • Impact analysis of risk management in the maintenance mechanism. • Decision making under market uncertainty for maintenance scheduling. • Coordination of long-term maintenance scheduling and short-term maintenance energy management. • Scenario-based stochastic modeling of the mixed-integer non-linear maintenance programming problem. The periodic outage planning of generation units for maintenance services is critical for their economic operation. Ignoring it can lead to premature degradation, high repair costs, and system reliability deterioration due to unexpected outages. Accordingly, generation maintenance scheduling (GMS) can optimally handle this challenge. In a power system with combined heat and power (CHP), although CHP units can efficiently supply power and heat demand, continuous operation of such units can cause an increase in unexpected failure rate and repair costs. Accordingly, this research accomplishes GMS coordination in CHP-integrated energy systems to optimally determine the maintenance plan of units. Firstly, the yearly GMS is planned and then the short-term generation scheduling is optimized. The proposed GMS problem is modeled as a mixed-integer nonlinear programming problem while considering the technical constraints, CHP feasible operation region, and power and heat balance. Moreover, the uncertainty in the market price is considered and the CVaR measure is employed to deal with the risks in the GMS. Furthermore, demand response is also assumed in the short-term generation scheduling while evaluating the impact of the yearly GMS. Numerical simulations with scenario-based optimization are used to evaluate the proposed CHP GMS problem with uncertainty in market price. [ABSTRACT FROM AUTHOR]

The electricity grid with a high penetration of renewable energy can enable travelers to travel free of emissions using state-of-the-art electric vehicles (EVs). Extensive electric vehicle demands at the peak-times, and an increase in electricity consumption due to population growth, have led to higher utility infrastructure investments. Mobile energy hubs i.e. clustered EVs parked in a dedicated location, can be used as an innovative demand-side management solution to reduce long-term utility infrastructure investments. They can store and release electricity to the grid based on consumer demand. However, a scientific planning approach for grid integration has been overlooked. Accordingly, this study proposes a comprehensive framework required to plan and develop mobile energy hubs based on optimization of life cycle cost, access distance and parking duration considering the temporal variation of EV recharging demands. The results of the study show that the framework developed can minimize lifecycle costs, and improve infrastructure utilization by accounting for the interests of all stakeholders. The total cost with the proposed robust optimization model under uncertainties of 50% is lesser than the robust cost calculated from a scenario-based approach. Furthermore, the developed framework is useful for recharging infrastructure planners to devise the deployment schedules and attract investors based on the economic viability of the planned strategies. • Transport electrification is a solution to reduce dependence on fossil fuels. • Increase in EV usage requires upgradation of grid infrastructure to meet demands. • EVs could be used as a pooled resource for services with vehicle-grid integration. • A planning framework for MEHs can deliver economic and environmental benefits. • Results indicate the robust planning model attains 50% robustness to uncertainties. [ABSTRACT FROM AUTHOR]

Heterotrophic plate count (HPC) constitutes a common indicator for monitoring of microbiological water quality in distribution systems (DS). This paper aims to identify factors explaining the spatiotemporal distribution of heterotrophic bacteria and model their occurrence in the distribution system. The case under study is the DS of Quebec City, Canada. The study is based on a robust database resulting from a sampling campaign carried out in about 50 DS locations, monitored bi-weekly over a three-year period. Models for explaining and predicting HPC levels were based on both one-level and multi-level Poisson regression techniques. The latter take into account the nested structure of data, the possible spatiotemporal correlation among HPC observations and the fact that sampling points, months and/or distribution sub-systems may represent clusters. Models show that the best predictors for spatiotemporal occurrence of HPC in the DS are: free residual chlorine that has an inverse relation with the HPC levels, water temperature and water ultraviolet absorbance, both having a positive impact on HPC levels. A sensitivity analysis based on the best performing model (two-level model) allowed for the identification of seasonal-based strategies to reduce HPC levels. [Copyright &y& Elsevier]

On-site carbon capturing, storage, and utilization (CCSU) has proven its' potential to reduce CO 2 emissions from large-scale fossil fuel combustion systems. However, the integration of CCSU in community-scale on-site energy generation applications such as district energy systems has not been comprehensively explored in literature. This study aims to propose a life cycle thinking-based framework to compare and prioritize emission reduction strategies that include CCSU and renewable energy technologies to develop zero-emission community energy systems. The framework incorporates multi-criteria decision-making approaches to rank and prioritize community energy emission mitigation strategies. A scenario-based method was employed in assessing the performance of CCSU technologies along with other compatible alternative energy choices. The framework was demonstrated for all the provinces in Canada. Results show that CCSU is more favorable for regions with high dependence on fossil fuel-based energy sources. CCSU could reach the commercial scale if the cost of emission avoided drops below the cost of CO 2 emissions.. The findings of this study are geared towards providing practical decision-support tools for stakeholders who hold responsible for policy and investment decisions in community energy. The developed framework is a generalized technique that provides the flexibility to be employed in any location across the globe. • Emission planning based on techno-economic and environmental performance. • Prospect of CCSU rises if cost of emission reduction drops below cost of emissions. • Cost of infrastructure takes up more than 70% of overall CCSU project costs. • Energy mix, carbon tax, and infrastructure impact emission planning decisions. [ABSTRACT FROM AUTHOR]

• LHS-CD method is adopted to assess supply adequacy under demand uncertainty. • Typical scenarios are selected based on the Markov stochastic process. • The assessment results of gas supply reliability are demonstrated in four aspects. • The reasons for gas supply shortages are analyzed in detail. An integrated methodology to assess the gas supply reliability of a gas pipeline network considering stochastic demands is proposed in this study. Typical scenarios are selected based on the structural reliability calculated by probability theory and stochastic process, including the normal scenario and some failure scenarios with a high probability. For each specific scenario, the gas supply condition is assessed based on the Latin hypercube sampling with the Cholesky decomposition method under stochastic demands. The maximum flow method based on the Dijkstra algorithm is adopted to determine whether the gas demand of customers can be fully covered and optimize the supply scheme under shortages. Finally, the assessment results are demonstrated from the following four aspects: the probability distribution of gas shortages under the normal scenario, identification of units with a high failure probability and vulnerable units, the reasons of gas supply shortages and corresponding probabilities, and the probability distribution of supply reliability for a gas pipeline network and each customer. The methodology is applied to a large-scale gas pipeline network in China. The results of the supply reliability assessment are analyzed in detail, and the sensitivity analysis of the gas demand uncertainty level on gas supply reliability is conducted. [ABSTRACT FROM AUTHOR]

Global climate change is a key concern in today's world, especially with the growth of population and industrial activities. One of the biggest sources of climate change is anthropogenic greenhouse gas emissions. In Canada, buildings are the third largest emitter of greenhouse gases, contributing to 12% of the country's equivalent Carbon dioxide emissions. These emissions have various negative impacts on the planet, which impede the transition towards a cleaner environment and more sustainable communities. Attention has now shifted towards Carbon dioxide reduction in addition to the currently practiced energy efficiency improvements and source switching, which is also important in achieving Canada's 2030 climate action goals. The current study attempts to address the above gap by investigating the feasibility of installing carbon capturing unit at building level, based on the perceptions of building managers in both multi-unit residential buildings and non-residential buildings. A Modified Digital Logic approach was used to identify the key factors that determine the acceptability of the unit, based on experts' input. Six primary criteria were identified to design a questionnaire and structured interviews to evaluate the acceptability of building level carbon capturing unit to stakeholders. The findings indicated that around 50% of non-residential building managers were interested in installing the carbon capturing unit, whereas none of the multi-unit building managers were in favor of the unit installation. The lack of interest is attributed to different factors such as unit scalability, inability to accurately estimate the short and long-term economic benefits, and other alternate plans to reduce carbon dioxide emissions. Specifically, when establishing relationship between cost and unit scalability, 82% of residential unit managers and 50% of non-residential managers opined that the unit should be capable of being upgraded to accommodate a larger area and capture more emissions in order to justify the proposed cost of the unit. The findings provide important insights for policy makers in understanding the acceptability of carbon capturing unit at building level and to further develop and promote this emerging technology in the market. [Display omitted] [ABSTRACT FROM AUTHOR]

• Operational schemes of compressors and peak shaving measures of gas storages are considered in the model. • Operating envelopes of compressors and thermodynamic equations of natural gas are considered in constraints. • The line pack at the end of the time horizon and the operating cost are considered as two objectives subject to multiple legal and physical constraints. • The transient peak shaving optimization model is established under demand uncertainty. It is the primary responsibility of a gas pipeline company to satisfy the gas demand of customers and ensure the economical operation of its pipelines. This paper presents a stochastic multi-objective transient peak shaving optimization model that considers uncertainty in gas demand while optimizing operational schemes of compressors and peak shaving measures of underground gas storages. The model is a rigorous multi-objective non-linear program (NLP) constrained by governing gas flow equations, operating envelopes of centrifugal compressors, and thermodynamic equations that model natural gas properties. The proposed multi-objective model aims to minimize the operational costs (the sum of the electricity cost of compressor stations and the gas withdrawal cost of underground gas storage) and maximize the line pack at the end of the time horizon subject to multiple legal and physical constraints. The model was tested on a real gas pipeline system, and a set of Pareto optimal solutions are obtained. The optimal operational schemes and peak shaving measures under three typical Pareto optimal solutions are analyzed in detail, and numerical results are presented following stochastic and robust optimization approaches. [ABSTRACT FROM AUTHOR]

Production of high volumes of wastewater by hydraulic fracturing operations is a challenging issue in the unconventional gas industry in North America. A scheduling-based solution is required to optimally manage the produced wastewater. This study develops a novel, hybrid, multi-objective linear programming model to optimize hydraulic fracturing wastewater management alternatives. Minimizing overall wastewater treatment cost, environmental impacts, and undesirable deviations from different goals were simultaneously considered the main objectives of the system. The model used data from a case example operating for 31 weeks, and it determined the volume of wastewater and treated water over all periods. The results indicated that onsite treatment is the best possible alternative for reuse in subsequent fracking, in those weeks in which all constraints were satisfied. Offsite treatment was the second ranking alternative when the volume of wastewater was higher than the capacity of onsite treatment, and deep well injection was the result when no water was needed for subsequent fracking. A sensitivity analysis was conducted by weighting the objectives to express their importance levels. Compared to other objectives, environmental impact had greater effect on the selection of the optimal alternatives over each period. Image 1 • A multi-objective framework was developed based on goal and linear programming. • Objectives were weighted based on different weighting scenarios. • The model can optimally solve hydraulic fracturing wastewater management problems. • The model can be simply updated and applied in water and wastewater management. [ABSTRACT FROM AUTHOR]

The environmental impacts of the mining industry as well as reduction strategies are important issues that have been highlighted as a result of the environmentally-friendly policy of green mining. As part of that policy, this study developed an approach based on a multi-layer artificial neural network and fuzzy cognitive map to predict the vertical and horizontal distribution of blast-induced dust emissions, simultaneously. Hence, a fuzzy cognitive map based on the cause-and-effect analysis concept was first designed to extract inputs' weights. An optimal network with two hidden layers was then implemented to predict the vertical and horizontal dust distributions in a mine close to residential and agricultural areas. The performance evaluation of the approach indicated good results by the R2 of 0.9933 and 0.9267 between the measured and predicted values for the horizontal and vertical distributions, respectively. Furthermore, the predicted and measured outputs over every blasting round were in accordance due to the slight mean absolute and root mean square errors of 0.009 and 0.018, respectively. A sensitivity analysis revealed that all inputs, excluding air humidity on the vertical distribution, had acceptable effects on the dust distribution outputs by the strength of higher than 0.7. Based on a reduction solution that we suggested, one round was blasted by taking water capsules together with stemming material in 40% of the whole blast holes. The results indicated that the maximum horizontal distribution of blast-induced dust was decreased about six times. The approach can be straightforwardly updated and used for other mining cases. • Fuzzy cognitive map and neural network were integrated for dust prediction. • Vertical and horizontal dust distributions were simultaneously predicted. • A real critical case was applied to investigate the capability of approach. • Horizontal dust distribution was highly decreased through the suggested solution. [ABSTRACT FROM AUTHOR]

• Energy planning needs multi-objective decision making and uncertainty integration. • The most suitable planning methods needs to be identified for optimal outcomes. • The optimization models lead to similar results but different computational times. • When cost and impact uncertainty increases, suitability of renewables decreases. • Robust optimization technique has high potential when planning under uncertainty. Distributed energy systems renewable energy are one solution to the environmental and economic concerns of energy use. While energy planning and optimization have been conducted mainly as a mathematical exercise, practical approaches that incorporate the engineering realities and uncertainties are limited. Decision makers find challenges in community energy planning due to the lack of expertise, planning tools, and information. While a multitude of models and tools are currently available, there are no means of identifying the most appropriate or accurate methods, especially considering uncertainty. The main objective of this study is to compare and identify the strengths and limitations of various mathematical modelling techniques used in energy planning for grid connected renewable energy systems. As a case study demonstration, different multi-objective optimization techniques with and without uncertainty consideration (i.e. robust optimization, linear optimization, Taguchi Orthogonal Array method, and Monte Carlo simulation) were applied on a selected neighborhood in British Columbia. The optimization outcomes and the time and effort for evaluation were compared for the different methods. The findings indicate that robust optimization can be used to develop an uncertainty-based decision model. It significantly reduces evaluation time compared to the other methods. Although the presence of uncertainties can change the optimal configuration of a planned energy system, the assessment method itself does not significantly impact the outcomes. The findings of this study will enable the energy planners and researchers to compare different multi-objective optimization techniques, and to select the best for planning renewable energy projects, especially during the pre-project planning stage. [ABSTRACT FROM AUTHOR]

Aquatic centres (ACs) are becoming exceedingly popular in the urban agglomerations of cold climate countries like Canada but functioning without assessing the state of their sustainability performance. Previous studies examined health and safety, water and indoor air quality, and energy consumption aspects without aiming at the holistic sustainability performance assessment. The present research is the first systematic effort for benchmarking of ACs. A hierarchical-based framework arranged 81 performance indicators to appraise the key components, including water management, indoor environment, personnel, service quality, energy, social, and operations. Fuzzy AHP and fuzzy mean clustering methods evaluated the identified PIs based on the opinion of experts (from Canadian aquatic centres) on their importance, measurability, and understandability. Finally, the selection process ranked a set of 63 most suitable PIs under 14 sub-criteria. Fuzzy-based methods efficiently handled the subjective scoring process and the difference of opinion among the experts. The criteria performance indices inform the top-level management while the sub-indices stipulate the operations management for honing in the lacking indicators. Using the selected PIs, the AC's management can allocate the available resources for both the short-term (e.g., efficient response to complaints) and long-term (e.g., replacing failed manually operated fixtures with the sensor-operated ones) improvement actions. The selected PIs will enhance the sustainability of ACs in Canada and other cold regions around the globe through a structured benchmarking process. Unlabelled Image • Aquatic centres are facing issues in attaining sustainability objectives. • Seven performance criteria and 81 indicators were identified for assessment. • Expert opinion were gathered from five aquatic centres. • Weights were generated using fuzzy analytic hierarchy process. • Sixty-three performance indicators were selected using fuzzy c-means clustering. [ABSTRACT FROM AUTHOR]