The aim of this study was to determine the feasibility of using high pressure CO2 for sterilization of Ginseng powder, as an alternative method to conventional techniques such as gamma-irradiation and ethylene oxide. The Ginseng sample used in this study was originally contaminated with fungi and 5 x 10(7) bacteria/g that was not suitable for oral use. This is the first time that high pressure CO2 has been used for the sterilization of herbal medicine to decrease the total aerobic microbial count (TAMC) and fungi. The effect of the process duration, operating pressure, temperature, and amount of additives on the sterilization efficiency of high pressure CO2 were investigated. The process duration was varied over 15 h; the pressure between 100 and 200 bar and the temperature between 25 and 75 degrees C. A 2.67-log reduction of bacteria in the Ginseng sample was achieved after long treatment time of 15 h at 60 degrees C and 100 bar, when using neat carbon dioxide. However, the addition of a small quantity of water/ethanol/H2O2 mixture, as low as 0.02 mL of each additive/g Ginseng powder, was sufficient for complete inactivation of fungi within 6 h at 60 degrees C and 100 bar. At these conditions the bacterial count was decreased from 5 x 10(7) to 2.0 x 10(3) TAMC/g complying with the TGA standard for orally ingested products. A 4.3 log reduction in bacteria was achieved at 150 bar and 30 degrees C, decreasing the TAMC in Ginseng sample to 2,000, below the allowable limit. However, fungi still remained in the sample. The complete inactivation of both bacteria and fungi was achieved within 2 h at 30 degrees C and 170 bar using 0.1 mL of each additive/g Ginseng. Microbial inactivation at this low temperature opens an avenue for the sterilization of many thermally labile pharmaceutical and food products that may involve sensitive compounds to gamma-radiation and chemically reactive antiseptic agents.

This article describes a unique industrial symbiosis employing an algae cultivation unit (ACU) at the core of a novel eco-industrial park (EIP) integrating fossil-fuel fired power generation, carbon capture, biofuel production, aquaculture, and wastewater treatment. A new modelling framework capable of designing and evaluating materials and energy exchanges within an industrial eco-system is introduced. In this scalable model, an algorithm was developed to balance the material and energy exchanges and determine the optimal inputs and outputs based on the industrial symbiosis objectives and participating industries. Optimizing the functionality of the ACU not only achieved a substantial emission reduction, but also boosted aquaculture, biofuel, and other chemical productions. In a power-boosting scenario (PBS), by matching a 660 MW fossil fuel-fired power plant with an equivalent solar field in the presence of ACU, fish-producing aquaculture and biofuel industries, the net CO2 emissions were cut by 60% with the added benefit of producing 39 m3 biodiesel, 6.7 m3 bioethanol, 0.14 m3 methanol, and 19.55 tons of fish products annually. Significantly, this article shows the potential of this new flexible modelling framework for integrated materials and energy flow analysis. This integration is an important pathway for evaluating energy technology transitions towards future low-emission production systems, as required for a circular economy.

This paper reviews research trends in modeling for low-carbon energy production. The focus is on two currently significant low-carbon energy processes; namely, bioenergy and post-combustion carbon capture (PCC) processes. The fundamentals of these two processes are discussed and the role of modeling and simulation tools (MSTs) is highlighted. The most popular modeling software packages are identified and their use in the literature is analyzed. Among commercially available packages, it is found that no single software package can handle all process development needs such as, configuration studies, techno-economic analysis, exergy optimization, and process integration. This review also suggests that optimal modeling results reported in literature can be viewed as optimal at the individual plant level, but sub-optimal for plant superstructure level. This review has identified key gaps pertinent to developing hybrid models that describe integrated energy production processes. ASPEN Plus is found to be dominant for modeling both bioenergy and PCC processes for both steady-state and dynamic modes respectively.