Financial appraisal of wet mesophilic AD technology as a renewable energy and waste management technology

Cost-Energy Optimum Pathway for the UK Food Manufacturing Industry to Meet the UK National Emission Targets

This paper investigates and outlines a cost-energy optimised pathway for the UK food manufacturing industry to attain the national Greenhouse Gas (GHG) emission reduction target of 80%, relative to 1990 levels, by 2050. The paper employs the linear programming platform TIMES, and it models the current and future technology mix of the UK food manufacturing industry. The model considers parameters such as capital costs, operating costs, efficiency and the lifetime of technologies to determine the cheapest pathway to achieve the GHG emission constraints. The model also enables future parametric analyses and can predict the influence of different economic, trade and dietary preferences and the impact of technological investments and policies on emissions. The study showed that for the food manufacturing industry to meet the emission reduction targets by 2050 the use of natural gas as the dominant source of energy in the industry at present, will have to be replaced by decarbonised grid electricity and biogas. This will require investments in Anaerobic Digestion (AD), Combined Heat and Power (CHP) plants driven by biogas and heat pumps powered by decarbonised electricity.

Biogas recovery from two-phase anaerobic digestion of food waste and paper waste: Optimization of paper waste addition

In order to optimize the biogas recovery from the co-digestion of food waste (FW) and paper waste (PW), the effect of PW content on two-phase anaerobic digestion (TPAD) was investigated. The mixtures of FW and PW, with the ratios of 10:0, 8:2, 6:4 and 5:5 (total solids), were fed into TPAD to recover biomethane. After the long-term expriment, it is elucidated that the methanogenesis in TPAD was stable for PW ≤ 40%. When PW = 50%, NH₄HCO₃ was added to the methanogenic phase to provide nitrogen. As the indicators of the stability of the anaerobic process, the ammonia and alkalinity in the methanogenic phase were simulated for their decreasing trend. The simulation results quantified the nitrogen deficiency in the methanogenic phase for PW = 50%. Also, the comparison of alkalinity and ammonia revealed that ammonia was the major contributor to the alkalinity. Furthermore, via stoichiometric calculations, high C/N ratios were found to increase the microbial yield and exacerbated the nitrogen deficiency. In the energy estimation, adding PW showed significant increase only when PW ≥ 40%. It was concluded that 40% was the optimal PW content for bioenergy augmentation from co-digestion of FW and PW using TPAD.

Pollutant in palm oil production process

Palm oil mill effluent (POME) is a by-product of the palm industry and it releases large amounts of greenhouse gases (GHGs). Water systems are also contaminated by POME if it is released into nonstandard ponds or rivers where it endangers the lives of fish and water fowl. In this paper, the environmental bottlenecks faced by palm oil production were investigated by analyzing the data collected from wet extraction palm oil mills (POMs) located in Malaysia. Strategies for reducing pollution and technologies for GHG reduction from the wet extraction POMs were also proposed. Average GHG emissions produced from processing 1 ton of crude palm oil (CPO) was 1100 kg CO2eq. This amount can be reduced to 200 kg CO2eq by capturing biogases. The amount of GHG emissions from open ponds could be decreased from 225 to 25 kg CO2eq/MT CPO by covering the ponds. Installation of biogas capturing system can decrease the average of chemical oxygen demand (COD) to about 17,100 mg/L and stabilizing ponds in the final step could decrease COD to 5220 mg/L. Using a biogas capturing system allows for the reduction of COD by 80% and simultaneously using a biogas capturing system and by stabilizing ponds can mitigate COD by 96%. Other ways to reduce the pollution caused by POME, including the installation of wet scrubber vessels and increasing the performance of biogas recovery and biogas upgrading systems, are studied in this paper.

IMPLICATIONS

Around 0.87 m3 POME is produced per 1 ton palm fruit milled. POME consists of around 2% oil, 2-4% suspended solid, 94-96% water. In palm oil mills, more than 90% of GHGs were emitted from POME. From 1 ton crude palm oil, 1100 kg CO2eq GHGs are generated, which can be reduced to 200 kg CO2eq by installation of biogas capturing equipment.

The role of different methanogen groups evaluated by Real-Time qPCR as high-efficiency bioindicators of wet anaerobic co-digestion of organic waste

Methanogen populations and their domains are poorly understood; however, in recent years, research on this topic has emerged. The relevance of this field has also been enhanced by the growing economic interest in methanogen skills, particularly the production of methane from organic substrates. Management attention turned to anaerobic wastes digestion because the volume and environmental impact reductions. Methanogenesis is the biochemically limiting step of the process and the industrially interesting phase because it connects to the amount of biogas production. For this reason, several studies have evaluated the structure of methanogen communities during this process. Currently, it is clear that the methanogen load and diversity depend on the feeding characteristics and the process conditions, but not much data is available. In this study, we apply a Real-Time Polymerase Chain Reaction (RT-PCR) method based on mcrA target to evaluate, by specific probes, some subgroups of methanogens during the mesophilic anaerobic digestion process fed wastewater sludge and organic fraction of the municipal solid waste with two different pre-treatments. The obtained data showed the prevalence of Methanomicrobiales and significantly positive correlation between Methanosarcina and Methanosaetae and the biogas production rate (0.744 p < 0.01 and 0.641 p < 0.05). Methanosarcina detected levels are different during the process after the two pre-treatment of the input materials (T-test p < 0.05). Moreover, a role as diagnostic tool could be suggested in digestion optimisation.