NIR Monitoring of Ammonia in Anaerobic Digesters Using a Diffuse Reflectance Probe

The feasibility of using a diffuse reflectance probe attached to a near infrared spectrometer to monitor the total ammonia nitrogen (TAN) content in an anaerobic digester run on cattle manure was investigated; as a previous study has indicated that this probe can be easily attached to an anaerobic digester. Multivariate modelling techniques such as partial least squares regression and interval partial least squares methods were used to build models. Various data pre-treatments were applied to improve the models. The TAN concentrations measured were in the range of 1.5 to 5.5 g/L. An R2 of 0.91 with an RMSEP of 0.32 was obtained implying that the probe could be used for monitoring and screening purposes

Optimization of the anaerobic digestion process by substrate pretreatment and the application of NIRS

Biogas production is a complex process depending on many factors and is an area that is being researched intensively. This thesis is based on studies that were aimed at optimizing the biogas production process by:• Reducing the time taken to assess the biochemical methane potentials (BMP) of substrates (specifically meadow grasses) by rapid analytical methods such as near infra-red spectroscopy (NIRS), in-vitro organic matter digestibility assay and the neutral detergent fibre assay• Applying NIRS as a monitoring tool to assess the concentrations of ammonia (which is inhibitory to the process) in the contents of anaerobic digesters.• Improving the BMP of materials such as cattle manure and dewatered pig manure and chicken manure by thermal pre-treatment at various temperatures between 100°C and 225°CResults show that the NIRS method can be used to discriminate between meadow grasses with high or low BMP. In detecting the ammonia content, NIRS was shown to have the potential to be a process monitoring tool. Thermal pre-treatment proved to be most effective on dewatered pig manure which showed improvements at lower pretreatment temperatures. Cattle manure required pre-treatment temperatures higher than 175°C to show improvement. Chicken manure did not show any improvements but instead showed a decrease in BMP at 225°C

Optimisation and inhibition of anaerobic digestion of livestock manure

The objectives of this study were to:(1) optimise methane production of livestock manure during anaerobic digestion, focusing on the addition of mixed enzymes, thermal pre-treatment and codigestion, and (2) develop a better understanding of ammonia and sulphide inhibition during digestion of animal manure . Enzyme addition increased methane yield of manure following incubation prior to digestion. Thermal pre-treatment increased methane yield but was only energetically favourable when a surplus of thermal energy was available. Digestion of acidified manure showed sulphide inhibition but no inhibition was measured when processing solid fractions of acidified manure. Co-digestion of non-acidified manure with the solid fractions of acidified manure was found to be a promising method of increasing methane yield in terms of digester volume. Total volatile acids, isobutyric and isovaleric acid and total ammonia nitrogen were found to be useful indicators of ammonia inhibition

Use of GIS to Find Optimum Locations for Anaerobic Digestion or Composting Facilities in Maine

As per US EPA, in 2017, 41 million tons of food waste was generated, but only 6.3% was diverted from landfills (US EPA, 2020). When landfilled or incinerated, organic waste (food waste, sludge, manure, agricultural waste) causes environmental pollution through greenhouse gas emissions, land, water, and air pollution. In contrast, if we compost or digest organic waste, we can generate soil additives and a mixture of methane and carbon dioxide gas to produce electricity or energy. Both digestion and composting reduce greenhouse gas emissions, improve the land through additives, and boost the economy. Many countries are adopting anaerobic digestion and composting to handle organic waste. There are currently 250 anaerobic digesters in the US (Pennington, 2018). There are 1200 wastewater recovery facilities in the US with anaerobic digestion, and approximately 20% of them co-digest sludge with other organic materials (Pennington, 2019). Meanwhile, the process of anaerobic digestion is chemically and biologically complex. In 2018 alone, as per EPA, eleven anaerobic digesting facilities were shut down (Pennington, 2019). There were various underlying factors such as; lack of feedstock, economic infeasibility, system shock, hampering the sensitive areas like wetlands through leaching from the storage areas. Thus, while starting a facility, there are many factors to consider for its long-run success. One of the most crucial factors to consider is the site location. Social acceptance, economic viability, job opportunities, and environmental disturbance are all site-dependent. Hence it is critical to optimize the choice. This study used ArcGIS Pro 2.6 to find the optimum location for organic waste management facilities in Maine. There are three anaerobic digesters in Maine, of which one is currently closed, and approximately 92 composting facilities handle a large amount of yard trimmings and some food waste. Most of the composting facilities are small scale with 4.3% composting food waste and 4.3% composting sewage sludge. In this study, data on food waste, manure, and sludge were gathered from Maine DEP, EPA, US Farms Data, and published reports to estimate the approximate amount of organic waste. A capture rate of 20% was used for food waste to estimate the amount of food waste collected. For the analysis, four scenarios: (1) the largest anaerobic digester (Fiberight) does not resume, or (2) resumes its work, and (3) co-digesting waste with or (4) without sludge were taken into consideration. To be more area-specific, the analysis was done for the Maine Department of Transportation (DOT) regions: Eastern, Northern, Southern, Mid-Coast, and Western Regions. Eight criteria- food waste availability, sludge availability, transportation cost, distance from residential areas, slope, land cover, distance from airports, and environmentally sensitive areas like conserved lands and wetlands were used to find the optimum locations. Analytical Hierarchy Process determined the criteria weights before assigning them in the suitability modeler of ArcGIS Pro to find the optimum locations. By transforming these criteria, the five best locations in Maine and three possible optimum locations in each region for each scenario were identified. Opportunities for the upgrading of existing farms with excess manure, transfer stations, composting facilities, and WRRFs were identified. The facilities that coincide in all the scenarios are the optimum facilities that work in all scenarios. Hence feasibility study can be started on those facilities. In the Northern region, Caribou WWTF and Pinelands Farms Natural Meats Inc. coincide in all scenarios, making them the best existing facilities that could be upgraded in the future. Similarly, in the Eastern region, the transfer station of the Town of Lincoln, and the Dover Foxcroft WRRF coincide in all scenarios, making them the best existing facilities that could be upgraded in the Eastern region. Four farms and the transfer station of the town of Clinton coincide in all scenarios in Mid-Coast. Out of these four farms, Stedy Rise farms and Caverly Hills LLC are 330 acres and 840 acres and generate excess manure of 4096 tons /year and 4175 tons/year. These farms could be good locations for a new facility using food waste. In the Southern region, no single facility was identified in all the scenarios, but Sanford WRRF and a few farms could be chosen for feasibility analysis. In the Western region, six farms and the transfer station of the town of Turner coincide in all the scenarios. Feasibility analysis can be done in these facilities to determine which can be upgraded as a new waste management facility utilizing food waste

Modelling, Optimisation and Control of Anaerobic Co-digestion Processes

La digestión anaerobia es un proceso biológico que ocurre espontáneamente en la naturaleza. Sin embargo, el rendimiento de metanización varía mucho dependiendo del tipo de residuo y condiciones ambientales a las que los residuos están expuestos. La tesis “Modelling, Optimisation and Control of Anaerobic Co-digestion Processes” contribuye a la modelización, optimización y control de procesos de co-digestión con el objetivo de mejorar el rendimiento del proceso. Los fundamentos de la digestión anaerobia y co-digestión se presentan en el Capítulo 1, junto con una revisión bibliográfica sobre la modelización del proceso, centrándose principalmente en la descripción y aplicaciones del Anaerobic Digestion Model No. 1 (ADM1), y una revisión de las distintas estrategias de control que están disponibles en la actualidad. El Capítulo 2 describe detalladamente la planta piloto que se utilizó para realizar los ensayos experimentales del trabajo de investigación. En el Capítulo 3 se desarrolla y valida un método generalizado para incorporar diversos sustratos solubles fermentables en un modelo basado en ADM1. Las reacciones de fermentación de sustratos tales como el etanol, no incluidos originalmente en ADM1, se implementan como reacciones de fermentación equivalente de glucosa. Suponiendo que la acidogénesis es el paso más rápido en la digestión anaerobia, una descripción exacta de la estequiometría de la fermentación de sustratos solubles (etanol, glicerol...) y productos (acetato, butirato y propionato) no es necesaria siempre que se cumplan los balances de masa y de electrones, puesto que todos estos ácidos intermedios se convierten rápidamente en acetato, H2 y CO2 en sistemas metanogénicos. El tratamiento de residuos sólidos mediante digestión anaerobia es atractivo por su alto contenido en materia orgánica y al potencial de recuperación de energía. En el caso de sólidos, la etapa de desintegración-hidrólisis es el paso más lento del proceso. El Capítulo 4 presenta un nuevo enfoque para la modelización de las etapas de desintegración e hidrólisis de sustratos sólidos complejos. Éstos se suponen que están compuestos de una fracción fácilmente biodegradable y otra lentamente biodegradable. El modelo propuesto considera una desintegración desacoplada de estas dos fracciones para describir mejor la degradación de los residuos sólidos. La co-digestión puede mejorar el rendimiento de las plantas de biogás en términos de productividad de metano y estabilidad de la operación si se combinan adecuadamente los diferentes co-sustratos. El Capítulo 5 formula y valida un método de optimización basado en programación lineal que calcula la mejor mezcla de alimentación para sistemas de co-digestión, capaz de maximizar la producción de metano a cada velocidad de carga orgánica aplicada. La mezcla resultante está sujeta a un conjunto de restricciones fisicoquímicas, que se definen en base al conocimiento heurístico del proceso. Finalmente, el Capítulo 6 presenta una estrategia de control para co-digestión anaerobia. La mezcla óptima obtenida por programación lineal se alimenta a un digestor operando en continuo y un sistema de diagnosis evalúa el rendimiento del proceso. En función de los resultados de la diagnosis, la acción de control modifica las restricciones aplicadas en el cálculo de la alimentación. Esta acción de control permite calcular una nueva mezcla de sustratos y un nuevo TRH para el próximo período de operación. Como resultado, la estrategia funciona como un controlador en lazo cerrado que optimiza la mezcla de alimentación al digestor y posteriormente evalúa el rendimiento de operación con la mezcla alimentada

Renewable Energy

This book discusses renewable energy resources and systems as well as energy efficiency. It contains twenty-three chapters over six sections that address a multitude of renewable energy types, including solar and photovoltaic, biomass, hydroelectric, and geothermal. The information presented herein is a scientific contribution to energy and environmental regulations, quality and efficiency of energy services, energy supply security, energy market-based approaches, government interventions, and the spread of technological innovation