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To achieve carbon neutrality by 2050, Malaysian government has identified green hydrogen (H2) as one of the potential energy sources. However, the high production cost of green H2 and technical complications of H2 storage conditions for distribution undermines the strategic framework of the H2 roadmap in Malaysia. The lack of investments in pre-requisite support infrastructure for the H2 production, conversion, and storage technologies impedes the progress of the H2 economy in Malaysia. Recently, ammonia (NH3) has emerged as a promising carbon-free energy carrier due to its increased ease and safety during transportation and storage. There is limited literature regarding the inclusion of an NH3 synthesis and storage loop in green H2 supply chains. This research proposes a systematic approach for the techno-economic evaluation of green H2 supply chains with green NH3 as a clean energy carrier of H2 storage and distribution. A superstructure-based mathematical optimisation model was developed to synthesise the optimum supply chain network configuration for a given optimisation objective. A case study is solved to illustrate the proposed model. [ABSTRACT FROM AUTHOR]

Household products such as dishwasher products and multipurpose cleaners may contain specific chemical ingredients to meet the consumer needs. However, some of the ingredients may result in skin and respiratory irritation. Thus, a systematic methodology to estimate the extent of hazard and risk for consumers’ exposure to the products is needed. In this work, an index-based methodology is presented to estimate the severity of the hazards and risks of the ingredients at during the early stage of product design. Higher score was assigned to the higher potential of hazard and risk, and vice versa. The hazard potential was determined based on hazard classification by the Global Harmonised System (GHS). Risk assessment was performed by considering the Margin of Exposure (MOE) and Risk Characterization Ratio (RCR). To demonstrate the proposed methodology, the dermal and inhalation hazards as well as risks from ingredients used in formulation of liquid detergent were evaluated.

Computer Aided Molecular Design (CAMD) techniques have been extensively applied to design solvents for different applications. Most of the CAMD problems only aim at generating solvents that meet the predefined functionality. Nevertheless, it is important to consider the effect of solvent on the safety, health and environmental impacts during the recovery process. This paper presents a single stage CAMD framework that simultaneously quantifies the environmental impact of the solvent recovery process. The environmental impact of the process can be estimated through IChemE Sustainability Metrics. Besides, molecular properties that have an impact on the quantitative evaluation of the environmental impact of solvent recovery process are included in this framework. Weighted sum method coupled with Fuzzy Analytic Hierarchy Process (FAHP) weighting approach is employed to solve the multi-objective molecular design framework. A case study on solvent design for residual oil extraction from palm pressed fiber is presented to illustrate the proposed framework. In this work, only energy balance around multistage evaporator is incorporated into CAMD formulation as energy required to recover the solvent contributes to the largest portion of the whole process. The results show that the designed solvents simultaneously possess target functionalities and reduce the environmental impact of solvent recovery process.

Hydrogen (H2) energy has a high potential to become a source of future sustainable fuel to replace fossil fuel. At present, natural gas conversion is the conventional process to produce H2. However, this process produces carbon dioxide (CO2) emissions as a by-product. CO2 capture, utilisation, and storage (CCUS) technologies can be integrated in conventional H2 plants to address this issue. By doing so, conventional H2 plants can be retrofitted to produce cleaner H2 called blue H2. This work presents a mathematical model to optimise blue H2 processes integrated with CCUS technologies. The research objectives are to determine optimal and feasible decarbonisation systems for H2 production and optimal storage technologies for the produced H2 with minimum cost. The developed optimisation-based model considers different grey H2 processes, CO2 capture technologies, CO2 transportation, utilisation, storage, and H2 storage. The model factors technology efficiency, costing and overall energy consumption. The developed model is demonstrated with a blue H2 production case study. The optimised blue H2 process with CCUS was obtained with the optimisation objective of minimising total annualised cost (TAC). [ABSTRACT FROM AUTHOR]

Rural electrification is an ongoing issue in Sarawak, a state in East Malaysia. About 7 % of Sarawak’s rural population is still inaccessible to electricity. However, adding more fossil fuel resources to electrify Sarawak fully will result in increased carbon emissions. This will contradict Malaysia’s plans to reduce 45 % of carbon dioxide emission from 2010 levels by 2030. Therefore, low carbon energy resources must be deployed to meet rising energy demands in rural areas. Before deploying these energy resources, it is necessary to determine minimum targets to achieve carbon emission reductions. This can be planned via carbon emission pinch analysis (CEPA). Thus, this study presents a regional planning model built upon CEPA that would assist in optimising the energy generation planning and the technical selection of energy generation technologies. This study will also analyse the usage of low carbon energy resources considering the carbon emission reduction targets to meet electrical demands in rural communities. An energy planning case study for a region in Malaysia, known as Sarawak, is solved to illustrate the carbon emission pinch analysis method. The results from the case study show that the consumption of carbon-intensive resources reduces when the additional capacity for new low carbon resources is allowed in the model. As a result, the consumption of coal, natural gas and diesel in 2040 has reduced to 4,449,151 MWh, 24, 673,913 MWh and 480,074 MWh, respectively, compared to the consumption in 2020. [ABSTRACT FROM AUTHOR]

Oil palm is recognised as the most productive oil crop with highest oil yield per hectare of agriculture land. The palm oil products generated from oil palm are widely used in our daily life, contributing from food processing, personal care and hygiene sectors as well as the biofuel industry. However, the reputation of oil palm has been declining as it was accused for causing environmental and social problems, such as deforestation, workers exploitation. In order to achieve sustainable production and consumption of palm oil products, traceability of the products is very important. With the complete traceability, the origin location and quantity of palm oil products distributed along the supply chain can be identified and tracked in both the forward and backward directions. In this work, a systematic approach is developed to evaluate the traceability of palm oil products from oil palm plantations to palm oil mills. A scoring system with qualitative measure is developed to quantify the traceability of the feedstock (fresh fruit bunches). A mixed integer non-linear programming model is then developed to maximise the economic performance while tracking the traceability of the fresh fruit bunches in a supply chain. A case study in Perak, Malaysia is solved to illustrate the proposed approach. Two scenarios are solved to determine the maximum traceability and economic performance. In the first scenario, the maximum economic performance of the supply chain is determined as RM 16.8 x 106 per annum with traceability of 0.688. In scenario 2, when optimisation objective is set as maximise traceability, the maximum traceability of 0.753 with economic performance of RM 12 x 106 per annum is obtained. [ABSTRACT FROM AUTHOR]