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Inconsistencies of the single multi-criteria decision making (SMCD) methods in criteria weight assessment make them unreliable and have led to the wrong siting of industrial parks, which are often abandoned as brownfields that emit GHG. Eco-industrial parks (EIPs) are replacing brownfields but require robust decision-making tools to weigh and rank suitable locations for industry clusters' synergies. Integrated multi-criteria decision making (IMCDM) to address the weaknesses and strengthen the advantages of SMCDM methods, and a model to overlay criteria weights and spatial data easily and accurately were developed. The spatial criteria data for 2009 and 2019 from Tanjung Langsat Industrial Area were collected and prepared by GIS to test the SMCDM and IMCMD consistency weighting and the model resilience. The SMCDM (AHP, ANP and F-AHP) and the IMCDM weights with the 2009 criteria data identified the entire water bodies around the brownfield as suitable sites, making them inconsistent. The 2019 data with the SMCDM weights identified tiny sites as best, also making them inconsistent. The integrated hierarchy network fuzzy analytic process (HN-FAP) and the hierarchy network analytic process (HNAP) with the 2019 criteria data identified part of the water bodies as suitable making it inconsistent. The hierarchy fuzzy analytic process (H-FAP) and the network fuzzy hierarchy analytic process (NFh-AP) identified larger suitable sites without overlaps making them consistent algorithms. The H-FAP and NFh-AP procedures eliminate the weaknesses and consolidate the strengths, giving optimally consistent criteria weights. The two algorithms' consistency and the model efficiency can use different criteria weights and spatial data inputs from elsewhere for 4IR-driven EIP modelling to help brownfield-EIP stakeholders. Future research would address the reverse ranking of MCDM methods when alternatives are added or removed. • Single choice-making criteria assessment inconsistency led to wrong industrial site. • Unfavourable industrial sites have been abandoned to brownfields that emit GHG. • EIP is replacing brownfields for industry clusters, synergy and cleaner production. • Combined decision-making consistent tools and an overlay analysis model are created. • The integrated tools show clear suitable EIP sites using concentrated spatial data. [ABSTRACT FROM AUTHOR]

Process Integration (PI) for resource conservation has become an increasingly popular topic of research in line with growing emphasis toward circular economy and rising concern on environmental protection. PI for resource conservation in continuous processes has been relatively well-established as compared to PI developments for batch processes that have lagged behind and are gradually getting attention. This paper presents a comprehensive and up-to-date review on the development and future research direction of batch process integration (BPI) methodologies for resource conservation covering energy, water and other types of industrial resources. The BPI methodologies are categorized according to batch process scheduling flexibility. The first category is the fixed, or pre-specified schedule BPI methodologies whereby time is treated as a parameter. The second category is the flexible or variable-schedule BPI methodologies that considers time as a variable. The fixed and flexible-schedule batch processes are further sub-divided and analyzed as graphical and mathematical programming-based BPI tools. Covering literature from 2000 to 2021 that comprises more than 160 publications in over twenty years period on BPIRC progress, trends and direction, the review highlights the significant role of BPI in driving small to medium scale industries toward cleaner production and circular economy. Review on twenty year progress, direction and impact of batch process integration related to conservation of energy, water and other resources that contributes toward cleaner production and circular economy. [Display omitted] • Lack of review on batch process integration (BPI) for resource conservation. • BPI contributes toward cleaner production and circular economy. • Review classified based on resource type, schedule flexibility and type of BPI tools. • Six key areas of development covering energy, water and other materials. • Twenty year progress, direction and impact of BPI on small to medium scale industries. [ABSTRACT FROM AUTHOR]

Globally, most industrial parks that have not gone through a proper site selection process have been neglected or underutilised and such active sites tend to burn a lot of fuels and generate greenhouse gases. Technology must be used to conduct on-site investigations of the spatial and non-spatial factors of industrial parks, especially the emerging Eco-Industrial Park (EIP). The paper seeks to appraise the global application, capability and acceptability of Geographic Information System (GIS) and Multi-Criteria Decision-Making (MCDM) tools in the EIP sites selection and planning. Also, to identify the benefits of mixing MCDM tools when integrating with GIS. There have been some reviews on the use of GIS and MCDM methods, but so far, there is none on the role of GIS and MCDM methods in EIP site selection. Geospatial and MCDM tools can be used to carefully select EIP sites, where materials and energy can be shared to achieve cleaner production, reduce environmental pollution and promote sustainable development. To understand the usage of these tools and their role in the EIP site selection process, a critical review of twenty-two papers published from 2007 to 2020 indexed by Google Scholar, Springer, IEEE Xplore and Web of Science have been developed for the first time. The articles are classified based on country/region, journal of publication, year and citations of publication, the authors and technologies applied. The results show that most studies on EIP site selection come from Iran and China. The Journal of Environmental Monitoring and Assessment has the highest number of articles published at 28%. The highest number of articles was published in 2014 with 312 citations. GIS and Analytic Hierarchy Process (AHP) topped the technologies used, accounting for 42% and 24% respectively, and hybrid tools 34%. As categorised by criteria content, there was an overlap of criteria in most journals. Though, water bodies, utilities, infrastructure, and natural characteristics were prominent. Renewable energy resources were not given attention by most researchers, and risk assessment was absent from the site selection literature. A blend of traditional MCDM tools constitutes the state-of-the-art tools, and when these are combined with GIS in EIP site surveys, they execute to obtain actual results. Future EIP site selection that is integrated with risk assessment is envisioned to be industry 4.0 (4IR)-driven through a combination of GIS and artificial intelligence, and the recently developed MCDM hybrid modules. [Display omitted] • Poor site selection has led to industrial park being neglected or underutilised. • Abandoned/underutilised active industrial parks can burn fuels to cause GHG. • First time of critical review of role of GIS and MCDM tools in EIP site selection. • GIS and AHP currently mainly used for large-scale EIP site criteria selection. • EIP site choice risk study using GIS, AI and MCDM hybrid can sustain industry 4.0 [ABSTRACT FROM AUTHOR]

This paper proposed a novel methodology to retrofit Heat Exchanger Storage Networks (HESN) of batch processes using a modified graphical retrofit tool, namely batch Stream Temperature Enthalpy Plot (batch STEP). Unlike other graphical retrofit tools, batch STEP maintains individual characteristic of process streams as well as serves as the one-stop retrofit tool to retrofit direct and indirect HESN simultaneously. The conventional batch heat integration typically aimed to synthesise new Heat Recovery Loops (HRLs) for heat recovery enhancement without exploiting the benefits of reusing existing HRLs in saving the additional volume of heat storage units (HSUs) and space allocated for retrofit. Thus, this paper extends the STEP continuous retrofit methodology to batch processes by introducing a batch STEP diagram for identification of the potential process streams to be integrated into existing HRLs and potential modifications of existing HRLs operating temperature. The methodology also introduces HRL– problem table algorithm (HRL-PTA) and heuristics to target the maximum indirect heat recovery and integrate process streams into the existing HRLs systematically. The methodology proposed achieves plant savings of 23.9%–60.0% for hot utility, 25.9%–42.2% for cold utility and a reduction of 6.3%–8.1% for additional volume of HSUs required in two illustrative case studies. [Display omitted] • An extended STEP graphical tool for retrofitting HESN of batch processes. • Diagnosis of process streams to be integrated into existing heat recovery loops (HRLs). • Diagnosis of potential modification of existing HRLs operating temperature. • The maximum indirect heat recovery by existing HRLs is targeted. • Integration of heat supply and load into existing HRLs is guided. [ABSTRACT FROM AUTHOR]

Renewable energy is crucial to reducing climate change as it replaces fossil fuel-based energy sources partially. However, renewable energy facilities are highly dependent on climate conditions. There have been few studies in Malaysia focusing on the impacts of extreme temperature and precipitation on energy systems. None of the studies used the risk assessment method to examine the effects. This research aims to study the possible risks associated with common renewable energy systems in Malaysia (solar photovoltaic, anaerobic biogas system, biomass, and hydropower) using a risk matrix approach. The mitigation action plan to reduce extreme weathepact on each energy system will also be presented in this study. Three extreme temperature and precipitation scenarios were used to explore the potential impacts on infrastructures, energy resources, power capacity, and efficiency of solar photovoltaic systems, hydropower, biomass, and biogas power plant. The trend of daily temperature and precipitation in Malaysia from 1970 to 2070 is also presented. By 2070, Malaysia will be experiencing greater change in rainfall, as well as warmer temperatures and more droughts. Results of the study show that biomass is the most vulnerable to extreme temperature and precipitation. • Risk assessment on solar PV, hydropower, biomass and biogas using a risk matrix approach were presented. • Malaysia will experience a higher change in rainfall, warmer and more droughts by 2070. • Biomass is the most vulnerable to extreme temperature and precipitation. [ABSTRACT FROM AUTHOR]

The development of biomass-based cogeneration energy systems in Malaysia is progressing to meet the circular economy concept and sustainability goal. This comprehensive review aims to report recent advancements in biomass-based cogeneration/biomass co-firing technology in Malaysia correlated with the optimization modeling role. First, this work presents the outlook and current scenario of cogeneration systems in Malaysia by observing performance and the challenges confronted by the technologies. Next, investigation of technical issues concerning the key players of the technologies and the biomass supply chain. This work had prepared using quantitative content-based analysis-meta-analysis. The practical implication of this review enables a complex optimization model that integrates biomass-based cogeneration and biomass supply chain considering economic and environmental viability. It will further enhance progress toward the Malaysian "Industry 4.0-driven" energy initiative. A novel optimization model grounded on Industry 4.0 parameters will foster new opportunities for researchers. [Display omitted] • The biomass cogeneration outlook, current scenario, successes and regional challenges in Malaysia. • Technical and operational issues of the biomass based-cogeneration and biomass co-firing. • Role of optimization modeling in the biomass based-cogeneration, biomass co-firing and biomass supply chain advancements. • New directions and the potential of those technologies in the era of Industry 4.0 [ABSTRACT FROM AUTHOR]