Dataset Information

Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach

ABSTRACT: The utilization of various feedstocks of unique characteristics in producing biogas could potentially enhance the application of clean fuel from biomass wastes. Two modelling tools were used to explore biogas production from plant and animal wastes. In this study, corn chaff was inoculated with cow dung digestate using different mixing ratios of substrate/inoculum (S/I) of 1:1, 1:1.55, and 1:3.5 for hydraulic retention time (HRT) of 25, 31, and 37 days as modelled using Central Composite Design (Face Centered Design) to optimize the process and predict the optimal response. The result shows that the mixture ratio of 1:1.55 for 37 days gave a cumulative highest biogas yield of 6.19 L under mesophilic conditions. The model p-value is <0.0001, an indication that the model term is significant. The python coding of the input factors gave the optimal value of 4.71 L, which is similar to the result obtained via CCD. Thus, both CCD (Face Centered Design) and python coding are reliable in the optimization of biogas production as they both predicted the same optimal values and approximately the same highest cumulative biogas yield. The GC-MS characterization of produced biogas revealed that it contains 68% methane and 22.76% CO2. Other constituents present are confirmed by FTIR analysis results. The methane in produced biogas has a flashpoint of -182 °C, which is extremely flammable. This data shows that both CCD and python coding can model biogas production with high accuracy and biogas produced can be used for heating purposes. Cow dung digestate, Anaerobic digestion, Corn chaff, Biogas production, Optimization, Python coding, RSM.

SUBMITTER: Iweka S

PROVIDER: S-EPMC8593443 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The aim of this study was to evaluate life cycle environmental impacts associated with the generation of electricity from biogas produced by the anaerobic digestion (AD) of agricultural products and waste. Five real plants in Italy were considered, using maize silage, slurry, and tomato waste as feedstocks and cogenerating electricity and heat; the latter is not utilized. The results suggest that maize silage and the operation of anaerobic digesters, including open storage of digestate, are the main contributors to the impacts of biogas electricity. The system that uses animal slurry is the best option, except for the marine and terrestrial ecotoxicity. The results also suggest that it is environmentally better to have smaller plants using slurry and waste rather than bigger installations, which require maize silage to operate efficiently. Electricity from biogas is environmentally more sustainable than grid electricity for seven out of 11 impacts considered. However, in comparison with natural gas, biogas electricity is worse for seven out of 11 impacts. It also has mostly higher impacts than other renewables, with a few exceptions, notably solar photovoltaics. Thus, for the AD systems and mesophilic operating conditions considered in this study, biogas electricity can help reduce greenhouse gas (GHG) emissions relative to a fossil-intensive electricity mix; however, some other impacts increase. If mitigation of climate change is the main aim, other renewables have a greater potential to reduce GHG emissions. If, in addition to this, other impacts are considered, then hydro, wind, and geothermal power are better alternatives to biogas electricity. However, utilization of heat would improve significantly its environmental sustainability, particularly global warming potential, summer smog, and the depletion of abiotic resources and the ozone layer. Further improvements can be achieved by banning open digestate storage to prevent methane emissions and regulating digestate spreading onto land to minimize emissions of ammonia and related environmental impacts.

Project description:The use of wildflower species as biogas feedstock carries the risk that their seeds survive anaerobic digestion (AD) and cause weed problems if spread with the digestate. Risk factors for seed survival in AD include low temperature, short exposure and hardseededness (HS). However, it is not possible to predict how AD will affect seed viability of previously unstudied species. In laboratory-scale reactors, we exposed seeds of eight species from a mixture of flowering wild plants intended as biogas feedstock and three reference species to AD at two mesophilic temperatures. Half of the species were HS, the other was non-HS (NHS). Viability was determined using a combination of tetrazolium and germination tests. Viability and germinability were modeled as functions of exposure time using a dose-response approach. Responses to AD varied considerably among species, and none of the considered influencing factors (time, temperature, HS) had a consistent effect. Seed lots of a species differed in inactivation times and seed-killing efficacy. The HS species Melilotus officinalis, Melilotus albus, and Malva sylvestris were particularly AD-resistant. They were the only ones that exhibited biphasic viability curves and tended to survive and germinate more at 42°C than at 35°C. Viability of the remaining species declined in a sigmoidal curve. Most NHS species were inactivated within a few days (Cichorium intybus, Daucus carota, Echium vulgare, and Verbascum thapsus), while HS species survived longer (Malva alcea). AD stimulated germination in the HS species A. theophrasti and its AD-resistance overlapped with that of the most resistant NHS species, C. album and tomato. In all seed lots, germinability was lost faster than viability, implying that mainly dormant seeds survived. After the maximum exposure time of 36 days, seeds of HS species and Chenopodium album were still viable. We concluded that viability responses to mesophilic AD were determined by the interplay of AD-conditions and species- and seed-lot-specific traits, of which HS was an important but only one factor. For the use of wildflowers as biogas feedstock, we recommended long retention times and special care with regard to HS species.

Dataset Information

Optimization of biogas yield from anaerobic co-digestion of corn-chaff and cow dung digestate: RSM and python approach

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets