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Countries across the world have undertaken measures to raise efficiencies of industrial operations to reduce greenhouse gas (GHG) emissions. An Eco-Industrial Park (EIP) that promotes industrial symbiosis effectively cuts down on GHG emissions from industrial processes. An EIP is a complex multi-criteria spatial initiative that requires a location with the facilities and features to host clusters of industries that collaborate to synergise resources, ultimately reducing carbon emissions. To make EIP site selection optimal and precise, this study presents a hybrid fuzzy-analytic hierarchy process (F-AHP) and geographic information system (GIS) model that was tested using six criteria for EIP site selection defined by Boolean logic. The GIS was used to generate the 2019 Land Use Land Cover (LULC), Euclidean distance, and reclassified raster layers of Tanjung Langsat Industrial Area (TLIA) spatial data. The criteria weights were assessed using F-AHP (triangular fuzzy numbers), and sensitivity analysis (SA) was used to check for any weight variation. The 2 % and 3 % changes in SA are insignificant when compared to the original weight. Waterbodies, roads, residential, industries, surface temperature, and slope have weight importance of 28, 22, 15, 14, 12, and 7 %. In the northern part of TLIA, the GIS-FAHP hybrid model produced the best (dark green 5 %) suitable EIP site, the second-best (light green 45 %) and moderately-suitable (yellow 25 %) sites surround the best site, while the low (light brown 15 %) and unsuitable (red 10 %) locations are near to the coast. The designed hybrid model approach demonstrates that TLIA is suitable for EIP development. The hybrid tool was developed for the selection of greenfield sites and the conversion of brownfield industrial parks to EIP status. The economic, environmental, social, and technical status of any site evaluated and accepted for EIP development is important to reduce carbon emissions. [ABSTRACT FROM AUTHOR]

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]

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]