Insight into the Sustainable Integration of Bio- and Petroleum Refineries for the Production of Fuels and Chemicals.

A petroleum refinery heavily depends on crude oil as its main feedstock to produce liquid fuels and chemicals. In the long term, this unyielding dependency is threatened by the depletion of the crude oil reserve. However, in the short term, its price highly fluctuates due to various factors, such as regional and global security instability causing additional complexity on refinery production planning. The petroleum refining industries are also drawing criticism and pressure due to their direct and indirect impacts on the environment. The exhaust gas emission of automobiles apart from the industrial and power plant emission has been viewed as the cause of global warming. In this sense, there is a need for a feasible, sustainable, and environmentally friendly generation process of fuels and chemicals. The attention turns to the utilization of biomass as a potential feedstock to produce substitutes for petroleum-derived fuels and building blocks for biochemicals. Biomass is abundant and currently is still low in utilization. The biorefinery, a facility to convert biomass into biofuels and biochemicals, is still lacking in competitiveness to a petroleum refinery. An attractive solution that addresses both is by the integration of bio- and petroleum refineries. In this context, the right decision making in the process selection and technologies can lower the investment and operational costs and assure optimum yield. Process optimization based on mathematical programming has been extensively used to conduct techno-economic and sustainability analysis for bio-, petroleum, and the integration of both refineries. This paper provides insights into the context of crude oil and biomass as potential refinery feedstocks. The current optimization status of either bio- or petroleum refineries and their integration is reviewed with the focus on the methods to solve the multi-objective optimization problems. Internal and external uncertain parameters are important aspects in process optimization. The nature of these uncertain parameters and their representation methods in process optimization are also discussed

Sustainability assessment of xylitol production from empty fruit bunch

Empty fruit bunch (EFB), one of the wastes from palm oil production, can be utilized into fuels and chemicals. The aim of this paper is to find the optimum capacity to produce xylitol from EFB. The optimum capacity was found by simultaneously considering its profitability, hazard potential and environmental performances. The process was developed and simulated using Aspen Plus to analyze its technical challenges and economic performances, covering net present values, internal rate of returns and payback period. On the other hand, hazard identification and ranking (HIRA) was used to evaluate its safety performances, while Simapro V.8.5.2 was used to assess the environmental impact via a life cycle assessment (LCA). The results show that the high consumption of steam in chemical hydrogenation causes the main contribution of Global warming potential (GWP) by 62%. This acid pre-treatment is also considered the most toxic part of the process while the hydrogenation of xylitol is the most hazardous part based on fire and explosion perspectives. Then, multi-objective optimization using Genetic Algorithm (GA) was performed in Matlab to find the optimum capacity. The methodology and result of this work lay the foundation of future works in utilizing

Sustainability assessment of xylitol production from empty fruit bunch

Empty fruit bunch (EFB), one of the wastes from palm oil production, can be utilized into fuels and chemicals. The aim of this paper is to find the optimum capacity to produce xylitol from EFB. The optimum capacity was found by simultaneously considering its profitability, hazard potential and environmental performances. The process was developed and simulated using Aspen Plus to analyze its technical challenges and economic performances, covering net present values, internal rate of returns and payback period. On the other hand, hazard identification and ranking (HIRA) was used to evaluate its safety performances, while Simapro V.8.5.2 was used to assess the environmental impact via a life cycle assessment (LCA). The results show that the high consumption of steam in chemical hydrogenation causes the main contribution of Global warming potential (GWP) by 62%. This acid pre-treatment is also considered the most toxic part of the process while the hydrogenation of xylitol is the most hazardous part based on fire and explosion perspectives. Then, multi-objective optimization using Genetic Algorithm (GA) was performed in Matlab to find the optimum capacity. The methodology and result of this work lay the foundation of future works in utilizing