Impact of feed injection and batch processing methods in hydrothermal liquefaction
Graphical abstract
Introduction
The global population is projected to reach 9.7 billion by 2050 [1], which puts increasing stress on the environment in terms of food, energy, and water demand. This stress is exacerbated by organic waste production. For example, in 2015, food waste accounted for approximately 30–40 percent of the total food supply in the U.S., with approximately 40 million tons wasted [2]. Other wastes, including sewage sludge, dairy waste, and anaerobic digestate from biogas production are also generated across the globe. Such wastes contain high amounts of biodegradable organics that can be recovered and used as a sustainable energy source. Valorizing organic wastes also reduces the need for waste treatment technologies such as landfilling and composting, reducing extraneous greenhouse gas (GHG) emissions and water pollution [3].
The high moisture content (typically > 80%) in these organic wastes limits the economic feasibility of combustion and pyrolysis due to the high enthalpy of vaporization of water [4]. Hydrothermal liquefaction (HTL) utilizes sub- and supercritical water to facilitate depolymerization reactions such as hydrolysis, decarboxylation, and decarbonylation of the organic compounds in the waste feedstocks and convert them into oil through repolymerization [4]. The produced oil usually has a higher heating value (HHV) of 20–40 MJ/kg and can be further upgraded through traditional hydrogenation processes [5], catalytic cracking with hydrogen and commercially available noble metal catalysts [6] or combine with supercritical fluids [7], catalytic esterification [8], etc.
Currently, Most of the published work on HTL uses a “batch-processing” method [[9], [10], [11], [12], [13], [14]] where feedstocks are prepared and sealed in an autoclave (or tubular) reactor having volumes ranging from 1 to 2000 ml [15]. The reactor is then heated to the target temperature and held for the desired residence time. However, due to the different sizes (in terms of length to diameter ratio and volume), heating rates, and target temperatures of the reactor, the heating time can range from less than one minute [16] to several hours [17,18] before the set temperature is reached. This slow heating process could result in unwanted side reactions and decrease oil yield and quality.
The semi-continuous or continuous method is less commonly utilized [19,20] due to the complexity in system configuration and higher operational costs compared to batch. However, continuous feed injection and product extraction are more energy-efficient and economical than batch processing when operating an HTL process on a larger scale. In this method, the reactor with water is preheated to the set temperature, and the feedstock is then injected into the reactor through a high-pressure pump. This method avoids the slow temperature ramping process, therefore, reducing unwanted side reactions [21] and maximizing oil production. Feed injection is often carried out for the HTL process of algae [[22], [23], [24]] due to the high slurry flowability of algal feedstocks. Feed injection is also used in tubular HTL reactor systems when studying water-soluble model compounds such as carbohydrates [25,26] and proteins [27,28] in the supercritical water gasification (SCWG) process for the production of H2 and CH4 [[29], [30], [31]].
However, no systematic study has been performed, to date, on differences between the two methods – batch processing and feed injection. In this study, a comprehensive comparison of batch processing and feed injection was performed using starch, a model compound for carbohydrates that are commonly seen in food wastes [32]. The oil yield, oil composition, and carbon distribution among the oil, aqueous, and solid phases were analyzed. Different feedstock injection rates were also employed to study its influence on the HTL reaction pathway.
Section snippets
Feedstock and pretreatment
Potato starch was purchased from Sigma-Aldrich (reagent grade, powder). The feedstock was analyzed for C, H, N, and O contents using CE-440 Elemental Analyzer (Exeter Analytical, Inc.) before running HTL experiments. Table 1 lists the results, including the calculated atomic ratio and higher heating value (HHV). HHV is calculated using the modified Dulong’s formula, asHHV = 0.338×[C]+1.428×([H] – [O]/8)where HHV is in MJ/kg; [C], [H], and [O] are carbon, hydrogen, and oxygen contents of the
Results and discussions
Starch and cellulose are two very similar carbohydrates with the same building block of glucose. Unlike cellulose, which is built with beta glucose, starch is a polymer of alpha glucose linked together through glycosidic bonds. The reaction of cellulose in subcritical water and formation of bio-oil has been well-studied [4,[34], [35], [36]]. Cellulose is first hydrolyzed into glucose, which is then epimerized into more chemically reactive fructose. From fructose, multiple dehydration reactions
Conclusions
This study evaluates the effect of feedstock injection and batch processing methods in hydrothermal liquefaction on product distribution and compositions. On the macro scale, no significant difference was observed for oil properties in terms of yield, higher heating value (HHV), and energy recovery (ER). The batch method produces much higher solids (∼ 10 wt%) than injection due to hydrothermal carbonization reactions during temperature ramping. Increase in injection rate results in an increase
Declaration of Competing Interest
The authors of this paper declare no conflict of interest.
Acknowledgments
The authors thank Dr. Roy Posmanik from Newe Ya'ar Research Station in Israel for his help in the experimental setup. This research was supported by National Institute of Food and Agriculture, contract #2016-69007-25149, US-Israel Binational Agricultural Research Development Fund, contract US-5051-17, and NYS Department of Economic Development, contract #C150124. The authors also thank the Academic Venture fund of Cornell’s Atkinson Center for Sustainable Future and the Cornell Energy Institute.
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