On-farm Energy Research Articles

Factors explaining the differences in the adoption of circular economy measures among farms in Southwest Finland

Transitioning to a circular economy is essential for addressing the inefficiencies and environmental impacts of traditional agricultural practices that rely on synthetic fertilizers and fossil resources. These conventional methods degrade soil, increase greenhouse gas emissions, and pollute waterways through nutrient runoff. A circular economy enhances sustainability by minimizing waste, optimizing resource use, and recycling nutrients. This study analyzes the adoption of circular economy practices among farms in Southwest Finland and identifies influencing factors. A survey distributed to farmers measured the extent of circular practices and the challenges faced. Cross-tabulations and logistic regression analyses evaluated how farm characteristics and farmer attitudes impact implementation. Results show a slow and variable transition among farms. About 50% of respondents have reduced mineral fertilizer use, although trading in byproducts and especially on-farm energy production from byproducts remains uncommon. Many farmers highlight insufficient policy support. The study concludes that policy interventions, training, and education are essential to accelerate adoption and stresses the importance of tailored, regional decision-making for effective policy development.

Predicting future climate scenarios: a machine learning perspective on greenhouse gas emissions in agrifood systems

Global climate change is an extensive phenomenon characterized by alterations in weather patterns, temperature trends, and precipitation levels. These variations substantially impact agrifood systems, encompassing the interconnected components of farming, food production, and distribution. This article analyzes 8,100 data points with 27 input features that quantify diverse aspects of the agrifood system’s contribution to predicted Greenhouse Gas Emissions (GHGE). The study uses two machine learning algorithms, Long-Short Term Memory (LSTM) and Random Forest (RF), as well as a hybrid approach (LSTM-RF). The LSTM-RF model integrates the strengths of LSTM and RF. LSTMs are adept at capturing long-term dependencies in sequential data through memory cells, addressing the vanishing gradient problem. Meanwhile, with its ensemble learning approach, RF improves overall model performance and generalization by combining multiple weak learners. Additionally, RF provides insights into the importance of features, helping to understand the significant contributors to the model’s predictions. The results demonstrate that the LSTM-RF algorithm outperforms other algorithms (for the test subset, RMSE = 2.977 and R2 = 0.9990). These findings highlight the superior accuracy of the LSTM-RF algorithm compared to the individual LSTM and RF algorithms, with the RF algorithm being less accurate in comparison. As determined by Pearson correlation analysis, key variables such as on-farm energy use, pesticide manufacturing, and land use factors significantly influence GHGE outputs. Furthermore, this study uses a heat map to visually represent the correlation coefficient between the input variables and GHGE, enhancing our understanding of the complex interactions within the agrifood system. Understanding the intricate connection between climate change and agrifood systems is crucial for developing practices addressing food security and environmental challenges.

Integration of Renewable Energy Solutions in Agricultural Operations

The integration of renewable energy solutions in agricultural operations presents a transformative approach to enhancing sustainability, reducing greenhouse gas emissions, and improving the economic viability of farming practices and explores the various renewable energy technologies applicable to agriculture, including solar, wind, biomass, and biogas energy solutions. Each technology is examined for its specific applications within the agricultural sector, highlighting its potential benefits and the challenges faced in implementation. Solar energy, through photovoltaic and thermal systems, offers significant potential for powering irrigation, greenhouse operations, and processing facilities, thereby reducing reliance on fossil fuels and grid electricity. Wind energy, with its ability to generate electricity through turbines, is particularly valuable in regions with consistent wind patterns, contributing to both onfarm energy needs and grid supply. Biomass energy, utilizing agricultural residues and dedicated bioenergy crops, provides a sustainable solution for heating and energy generation, while also addressing waste management challenges. Biogas production, through anaerobic digestion of organic waste, presents a dual benefit of generating renewable energy and improving nutrient recycling in farming systems. Government subsidies, feedin tariffs, research funding, and technical support play pivotal roles in encouraging farmers to transition to renewable energy sources. Case studies from various regions illustrate the practical implementation of these technologies, demonstrating their impact on enhancing agricultural productivity, reducing environmental footprints, and fostering energy independence, including policymakers, researchers, and farmers, about the opportunities and challenges in adopting sustainable energy practices. The findings underscore the importance of continued innovation, supportive policies, and collaborative efforts to achieve a resilient and sustainable agricultural sector.

69 The Holos model for estimating greenhouse gases and soil carbon: Characterizing regionalized beef farm model systems

Abstract The objective of this work is to characterize regionally representative beef farm systems that represent dominant or typical surveyed management practices for 11 beef-producing regions across Canada. This work fulfills two further purposes 1) to improve and expand the Holos model interface; and 2) to facilitate the estimation of greenhouse gas (GHG) emissions and soil carbon (C) changes on beef farms in different regions of Canada. Holos version 4 is the whole-farm model of Agriculture and Agri-Food Canada’s to estimate GHG emissions and changes in soil C on Canadian farms in response to shifts in management practices. Holos can be implemented in all 10 Canadian provinces and accounts for GHG emissions from crop and livestock production [enteric and manure methane (CH4), manure and soil N2O emissions], farm machines and infrastructure [on-farm energy carbon dioxide (CO2) emissions], as well as from the upstream production of some farm inputs (synthetic fertilizer and pesticides). The model is designed to utilize data readily available on the farm to answer, ‘What if?’ scenarios, whereby the user can test the effect of changing management practices on their whole-farm GHG budget. To reduce the data input burden on the user, Holos V4 has built-in model livestock systems for beef, dairy, swine and poultry production that characterize the dominant features of these operations in Canada at the national scale based on relevant literature/data and expert opinion. Regarding beef production, we have characterized regionally specific model beef farms for incorporation into Holos, one for each of 11 Canadian beef-producing regions. General characteristics and management practices for each farm were based on the 2011 Beef Farm Survey (Sheppard et al., 2015), which summarizes management information from 1,009 Canadian beef farms, combined with data from the Canadian Cow-Calf Cost of Production Network (Canfax 2023). Each regional farm includes cow-calf, backgrounding in confinement, backgrounding on pasture and finishing components, and considers all the specific feed (e.g., forage, grains, by-products) required for each stage of the beef cycle. These 11 model farms are simulated within the current Holos V4 model to explore the impacts of variation in beef management practices on farm GHG emissions across Canada and on soil C stocks on lands used to produce feed and graze cattle. An overview of the national-level dairy, swine and poultry components in Holos will be presented along with a more detailed perspective of whole-farm GHG budget and multi-decadal soil C dynamics in regionalized beef farms. The impact of management and environmental factors that lead to differences in GHG emissions and soil C stocks in beef farms will also be explored.

On-farm energy input-output and economic analysis of important essential oil-bearing Mint species in subtropical India

On-farm energy input-output and economic analysis of important essential oil-bearing Mint species in subtropical India

The Carbon Footprint of a 5000-Milking-Head Dairy Operation in Central Texas

Texas is the third-largest milk-producing state in the U.S., with Central Texas being the second-largest milk-producing region in Texas. The average size of a dairy herd in Texas is 1829 cows. In Central Texas alone, there are 88,000 dairy cows. However, there is a lack of environmental impact research for this region. The overall objective of this case study is to evaluate the net carbon and carbon equivalent balances for a large dairy operation in Central Texas. The dairy selected for this study has a herd size of 5000 milking cows. The data assumptions were made regarding the selected dairy’s performance and production for the 2021 production year. These data include herd size and management, milk production, crop production, feed purchases, and on-farm energy usage. The USDA-Integrated Farm System Model (IFSM) was used to estimate the daily and annual greenhouse gas emissions and environmental footprint of the dairy by quantifying the operation’s carbon footprint based on its 2021 performance and management practices. Research outcomes identify and quantify sources of greenhouse gas (GHG) emissions produced on the dairy farm. Additionally, the carbon footprint (CF) was determined by estimating the CO2 equivalents (CO2-eq) emitted or sunk from animal and manure emissions, direct and indirect land emissions, net biogenic and anthropogenic CO2 emissions, and the production of resource inputs. The results of this case study indicated that the carbon footprint (CF) of the 5000-milking-head dairy in Central Texas was 0.40 lb. of CO2 per lb. of fat- and protein-corrected milk (FPCM) when considering biogenic CO2 and 0.83 lb. of CO2 per lb. of FPCM without biogenic CO2.

Energy Use in Greenhouses in the EU: A Review Recommending Energy Efficiency Measures and Renewable Energy Sources Adoption

This study conducts a review of energy use in the EU greenhouse agriculture sector. The studies presented illustrate that energy use in greenhouses is varied and generally dependent on fossil sources. High energy systems, which are more dominant in northern Europe, are generally heavily climate controlled and energy use is dominated by heating and cooling processes, while low energy systems, which are dominant in southern Europe, show a mixture of energy uses including heating, cooling, irrigation, lighting, fertilisers, and pesticides. Our review also provides a discussion of energy efficiency measures and renewable energy sources adoption for greenhouse production. Finally, our review indicates that accurate and reliable studies on energy use in greenhouse production are scarce and fragmented and that a range of differing methodologies are currently used to estimate on-farm energy use. The development of a comprehensive methodology and categorisation for measuring energy use in greenhouse agricultural production would, in our view, catalyse further studies in this sector, considerably improve our understanding of energy use in greenhouses and support the green transition. Based on this, this paper proposes a basic framework for measuring energy use in greenhouse agriculture.

Pre- and post-production processes increasingly dominate greenhouse gas emissions from agri-food systems

Abstract. We present results from the FAOSTAT emissions shares database, covering emissions from agri-food systems and their shares to total anthropogenic emissions for 196 countries and 40 territories for the period 1990–2019. We find that in 2019, global agri-food system emissions were 16.5 (95 %; CI range: 11–22) billion metric tonnes (Gt CO2 eq. yr−1), corresponding to 31 % (range: 19 %–43 %) of total anthropogenic emissions. Of the agri-food system total, global emissions within the farm gate – from crop and livestock production processes including on-farm energy use – were 7.2 Gt CO2 eq. yr−1; emissions from land use change, due to deforestation and peatland degradation, were 3.5 Gt CO2 eq. yr−1; and emissions from pre- and post-production processes – manufacturing of fertilizers, food processing, packaging, transport, retail, household consumption and food waste disposal – were 5.8 Gt CO2 eq. yr−1. Over the study period 1990–2019, agri-food system emissions increased in total by 17 %, largely driven by a doubling of emissions from pre- and post-production processes. Conversely, the FAOSTAT data show that since 1990 land use emissions decreased by 25 %, while emissions within the farm gate increased 9 %. In 2019, in terms of individual greenhouse gases (GHGs), pre- and post-production processes emitted the most CO2 (3.9 Gt CO2 yr−1), preceding land use change (3.3 Gt CO2 yr−1) and farm gate (1.2 Gt CO2 yr−1) emissions. Conversely, farm gate activities were by far the major emitter of methane (140 Mt CH4 yr−1) and of nitrous oxide (7.8 Mt N2O yr−1). Pre- and post-production processes were also significant emitters of methane (49 Mt CH4 yr−1), mostly generated from the decay of solid food waste in landfills and open dumps. One key trend over the 30-year period since 1990 highlighted by our analysis is the increasingly important role of food-related emissions generated outside of agricultural land, in pre- and post-production processes along the agri-food system, at global, regional and national scales. In fact, our data show that by 2019, pre- and post-production processes had overtaken farm gate processes to become the largest GHG component of agri-food system emissions in Annex I parties (2.2 Gt CO2 eq. yr−1). They also more than doubled in non-Annex I parties (to 3.5 Gt CO2 eq. yr−1), becoming larger than emissions from land use change. By 2019 food supply chains had become the largest agri-food system component in China (1100 Mt CO2 eq. yr−1), the USA (700 Mt CO2 eq. yr−1) and the EU-27 (600 Mt CO2 eq. yr−1). This has important repercussions for food-relevant national mitigation strategies, considering that until recently these have focused mainly on reductions of non-CO2 gases within the farm gate and on CO2 mitigation from land use change. The information used in this work is available as open data with DOI https://doi.org/10.5281/zenodo.5615082 (Tubiello et al., 2021d). It is also available to users via the FAOSTAT database (https://www.fao.org/faostat/en/#data/EM; FAO, 2021a), with annual updates.

Global Challenges and Responses: Agriculture, Economic Globalization, and Environmental Sustainability in Central Asia

Economic globalization (EG) accelerates very fast in Central Asia. This could cause environmental degradation, according to the environmental Kuznets curve (EKC) hypothesis. The study aims to determine how the EG of agriculture impacts environmental sustainability, and to test the EKC hypothesis on the agricultural sector in six Central Asian countries. Particularly, some main hypotheses were proposed using secondary data from Kazakhstan, Kyrgyzstan, Mongolia, Tajikistan, Turkmenistan, and Uzbekistan from 1994 to 2019. This study uses five explanatory variables: agricultural exports value (EXP), agriculture forestry and fishing value-added (AVA), the exchange rate (EXR), total natural resource rents (RENT), and external debt stocks (DEBT), while the dependent variable in this study is the CO2 emissions from on-farm energy use (EMS), temperature changes (TEMP), and forest fires (FIRE). These data are analyzed using panel data regression. As a result, AVA and RENT raise EMS; EXC raises TEMP but lowers EMS; DEBT raises TEMP but can lower FIRE. Hence, we propose recommendations to improve this condition, including a clear roadmap, enhanced partnerships, and regional and international support.

Water, Energy and Carbon Tradeoffs of Groundwater Irrigation-Based Food Production: Case Studies from Fergana Valley, Central Asia

In arid environments, water shortages due to over-allocation of river flow are often compensated by lift irrigation or pumping groundwater. In such environments, farmers using pumped irrigation can deploy on-farm energy-efficient and water-saving technologies; however, pumping water requiring extra energy is associated with carbon emissions. This study explores how to increase crop production using pumped irrigation with minimal energy and carbon emissions. The purpose of this research is twofold: first, to examine on-farm energy consumption and carbon emissions in gravity and groundwater irrigation systems; and second, to explore system-level alternatives of power generation and water management for food production based on the results from the farm-level analysis. This study employs a novel system-level approach for addressing water, energy, and carbon tradeoffs under pumped irrigation using groundwater. These tradeoffs are assessed at farm and system levels. On-farm level estimates showed that farm-level interventions were insufficient to produce mutual gains. According to the results of the system-level evaluation, system-level interventions for water and energy conservation, the use of renewable energy to pump water for irrigation, and river basin scale cooperation are all required to maintain crop production while reducing energy consumption and carbon emissions.

The Effects of Using Pretreated Cotton Gin Trash on the Production of Biogas from Anaerobic Co-Digestion with Cow Manure and Sludge

Anaerobic co-digestion (AcoD) has been practiced for decades to convert waste into value-added energy products, especially biogas. This study aimed to assess the potential of biogenic methane (CH4) production from the co-digestion of pretreated cotton gin trash (CGT), cow manure, and sludge. CGT contains high cellulosic content, making it a reliable feedstock for biogenic methane production. To further improve the biogas quantity and quality, the CGT was subjected to physical pretreatments, i.e., hot water (HW), ultra-sonication (US), and a combination of both (HW+US). After 91 days of AcoD, 79–110 L of biogas was produced by the treatments. Among the treatments, HW+US-pretreated CGT presented maximum biogas production capacity, at 110 L. Besides, this treatment showed the high-quality biogenic CH4 content, 52.4% of the total biogas volume, with an improved conversion rate of 0.37 L/g of volatile suspended solids consumed. In addition, this study discussed the structural changes in feedstock due to pretreatments and correlated them with the corresponding biogenic methane production. The study reports the potential of pretreated CGT conversion to CH4. It will impact the circular economy by contributing to on-farm energy requirements and reducing the financial expenditures incurred in this regard.

Environmental life cycle assessment of yellow mealworm (Tenebrio molitor) production for human consumption in Austria \u2013 a comparison of mealworm and broiler as protein source

PurposeGlobal food production needs to increase to provide enough food for over 9 billion people living by 2050. Traditional animal production is among the leading causes for climate change and occupation of land. Edible insects might be a sustainable protein supply to humans, but environmental life cycle assessment (LCA) studies on them are scarce. This study performs an LCA of a small-scale production system of yellow mealworms (Tenebrio molitor) in Central Europe that are supplied with organic feedstuff.MethodsA combined ReCiPe midpoint (H) and CED method is used to estimate the potential environmental impacts from cradle-to-gate. Impact categories include global warming potential (GWP), non-renewable energy use (NREU), agricultural land occupation (ALOP), terrestrial acidification potential (TAP) and freshwater eutrophication potential (FEP). The robustness of the results is tested via sensitivity analyses and Monte Carlo simulations.Results and discussionImpacts related to the production of 1 kg of edible mealworm protein amount to 20.4 kg CO2-eq (GWP), 213.66 MJ-eq (NREU), 22.38 m2 (ALOP), 159.52 g SO2-eq (TAP) and 12.41 g P-eq (FEP). Upstream feed production and on-farm energy demand related to the heating of the facilities are identified as environmental hot-spots: Depending on the impact category, feed supply contributes up to 90% and on-farm heating accounts for up to 65% of overall impacts. The organic mealworm production system is contrasted with a selected Austrian organic broiler production system, to which it compares favourably (18–72% lower impacts per category), with the exception of freshwater eutrophication (6% higher impacts).ConclusionsThis case study shows that the Austrian mealworm production system compares favourably to traditional livestock systems. Compared to LCAs from large-scale T. molitor rearing facilities in France and in the Netherlands, however, the Austrian production system cannot compete for the reasons of production scale, feed conversion efficiency and type of production system. Nevertheless, the investigated mealworms represent a sustainable protein alternative that should be added to the Western diet.

Energy audits and eco-feedback: Exploring the barriers and facilitators of agricultural energy efficiency improvements on Australian farms

Energy audits and eco-feedback: Exploring the barriers and facilitators of agricultural energy efficiency improvements on Australian farms

Greenhouse gas emissions from food systems: building the evidence base

New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO2eq yr−1 in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO2eq yr−1, were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO2eq cap−1, with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.

Small-scale biodiesel production for on-farm energy security: a sustainable income diversification opportunity for oilseed producers

This article reports the results of a comparative analysis of biodiesel production from two major summer oilseed crops, accounting the economic risk of production. The objective is to provide the necessary knowledge for the feasible adaptation of oilseed crops for on-farm production of biodiesel. Investment in small-scale biodiesel processing units for on-farm production was investigated at three different stages, namely the production of oilseed, processing of oil and processing of biodiesel. The annualized net revenue from the biodiesel production was calculated considering a 15-year time period. The results show the potential for a positive return from biodiesel production; however, there is a potential for negative return under low-yield scenarios. According to Monte Carlo simulation, the profit range generated across random samples for biodiesel production from both oilseed crops yields a positive net return. The probability of a negative return on biodiesel production from sunflower was lower than that from soybean.

Life cycle assessment of a circular, urban mushroom farm

Life cycle assessment of a circular, urban mushroom farm

How does soil carbon sequestration affect greenhouse gas emissions from a sheep farming system? Results of a life cycle assessment case study

How does soil carbon sequestration affect greenhouse gas emissions from a sheep farming system? Results of a life cycle assessment case study

Small-scale biochar production on Swedish farms: A model for estimating potential, variability, and environmental performance

Several small-scale pyrolysis plants have been installed on Swedish farms and uptake is increasing in the Nordic countries. Pyrolysis plants convert biomass to biochar for agricultural applications and syngas for heating applications. These projects are driven by ambitions of achieving carbon dioxide removal, reducing environmental impacts, and improving farm finances and resilience. Before policy support for on-farm pyrolysis projects is implemented, a comprehensive environmental evaluation of these systems is needed. Here, a model was developed to jointly: (i) simulate operation of on-farm energy systems equipped with pyrolysis units; (ii) estimate biochar production potential and its variability under different energy demand situations and designs; and (iii) calculate life cycle environmental impacts. The model was applied to a case study farm in Sweden. The farm’s heating system achieved net carbon dioxide removal through biochar carbon sequestration, but increased its impact in several other environmental categories, mainly due to increased biomass throughput. Proper dimensioning of heat-constrained systems is key to ensure optimal biochar production, as biochar production potential of the case farm was reduced under expected climate change in Sweden. To improve the environmental footprint of future biochar systems, it is crucial that expected co-benefits from biochar use in agriculture are realised. The model developed here is available for application to other cases.

The influence of microbial community dynamics on anaerobic digestion efficiency and stability: A Review

An essential component in sustainable energy development is the production of bioenergy from waste. The most successful bioenergy technology worldwide is anaerobic digestion (AD), which is a microbially-mediated process of organic feedstock conversion into energy-rich compounds (volatile fatty acids (VFA) and biogas) for renewable energy generation. AD is deployed in a range of situations including systems for on-farm energy recovery from animal and plant waste to the processing of food and municipal solid waste (with the additional benefit of land-fill reduction).Anaerobic digesters rely on a diverse microbial community working syntrophycally through a series of interrelated biochemical processes.Each stage in anaerobic digestion is carried out by different microbial groups. Thus, to optimise energy recovery from the AD process, the microbial community must have stable performance over time, balancing the various metabolic functions and taxonomic community composition in digesters. Complicating this balance, it has been found that the presence of ammonia, sulphate, and hydrogen sulphide in substantial concentrations often cause failure in the AD process. Thus, these substances cause adverse shifts in microbial community composition and/or inhibit bacterial growth, that influencing AD performance. ©2020. CBIORE-IJRED. All rights reserved

Производство и использование энергии в фермерских хозяйствах США

Производство и использование энергии в фермерских хозяйствах США