Lower Greenhouse Gas Emissions Research Articles

Methods of wind energy harnessing: A state-of-the-art and bibliometric analysis

Wind energy is one of the most promising alternatives for obtaining a sustainable electricity generation model with low greenhouse gas emissions. The maturity of this technology, coupled with its low investment costs and good performance, makes it highly interesting for countries to develop projects within this field. However, its high operation intermittency caused by the natural behavior of wind requires preliminary research on the technical conditions (Installation, Capacity, Environmental, Legal, Administrative, Logistics) of the geographical area wherein the wind energy project is planned. This paper provides an overview of the state-of-the-art research studies on the potential of wind energy within a territory. This review describes current methodological alternatives for assessing wind energy generation projects and potential energy studies in different geographical areas globally. Therefore, a bibliometric analysis is included, examining the scientific research trends in the field of wind energy in addition to the different technologies and innovations that have contributed to the viability of a greater wind energy generation project. Finally, the study discusses the technical restriction criteria faced by any such project. This paper also seeks to become a point of reference for future reviews and decision-making in wind projects.

Identifying a sustainable rice-based cropping system via on-farm evaluation of grain yield, carbon sequestration capacity and carbon footprints in Central China

ContextRice-based cropping system is a major anthropogenic source of direct greenhouse gases (GHG) emissions, agricultural inputs also produces numerous indirect GHG emissions and environmental problems. Identification of rice cropping systems with lower GHG emissions and higher grain yields is of great significance to ensure food security while minimizing agricultural carbon footprint (CF). ObjectiveThis study aimed to identify the optimal rice-based cropping system with lower greenhouse effects and comparable annual yield in central China. MethodsUsed life cycle assessment, a two-year field experiment was performed to evaluate the direct and indirect GHG emissions, CF, and carbon sequestration capacity in the six rice-based cropping systems widely used in central China, which consisted of fallow-early rice-late rice, rapeseed-early rice-late rice, fallow-ratoon rice, rapeseed-ratoon rice (RRaR), fallow-middle rice, and rapeseed-middle rice. ResultsThe results showed that compared with the three systems with fallow season, the three systems with rapeseed had lower annual CH4 emissions. The two systems with ratoon rice had lower annual indirect and direct GHG emissions than the two systems with double rice. The three systems with rapeseed had higher annual biomass, grain yields, and fixed carbon in biomass and significantly lower CF than the three systems with fallow season, and RRaR had the highest value of fixed carbon in biomass. The systems with ratoon rice had lower average CF than those systems with double rice. CH4 emissions from paddy fields were the primary source of total annual GHG and the main component of CF. Compared with the three systems with fallow season, the three systems with rapeseed had significantly higher annual carbon sequestration capacity based on net ecosystem production (NEP). Ratoon rice systems had higher average NEP than double- and middle-rice systems. RRaR had the lowest CF per unit yield and highest NEP among all the six systems. ConclusionsThe results indicated that appropriate rice-based cropping systems may alleviate the greenhouse effect via reducing GHG emissions and enhancing paddy NEP, RRaR could achieve relatively higher annual grain yield and carbon sequestration capacity as well as lower CF. SignificanceThis study highlight conversion of double rice and middle rice systems to RRaR may help improve grain yield and mitigate greenhouse effect. The findings may provide a theoretical basis for selection of sustainable development of rice based cropping systems in central China.

Techno-economic Assessment of Solar-driven Polygeneration System for Agri-food Industries

This paper examines the technical, economic and environmental assessment of a solar-driven polygeneration system (SDPS) of a dairy industry located in Tauste, Zaragoza, Spain. The results showed that the proposed SDPS has a solar fraction of 64.3% with a lower cost and lower greenhouse gas (GHG) emissions than conventional system.

Circular battery production in the EU: Insights from integrating life cycle assessment into system dynamics modeling on recycled content and environmental impacts

AbstractThe European Union (EU) Battery Regulation aims to establish a circular battery production and sets minimum battery material recycled targets for new batteries from post‐production and post‐consumer waste batteries. However, it is uncertain whether these targets can be met due to dynamic market developments and if their compliance results in environmental benefits. Therefore, this study examines the circular battery production in the EU and its impact on material flows and the environment from a market perspective. We combined a system dynamic market model with process models for battery production and recycling, using prospective life cycle assessment. According to our analysis, the projected amount of post‐consumer waste alone may not meet the specified levels of recycled materials due to long battery lifetimes. Thereby, the targets for cobalt are particularly ambitious, with a gap of between 9.8 and 14.6 percentage points for most scenarios. In the case of reduced battery lifetimes, the achievable recycled content across all materials increases by more than 75% in 2032 and by more than 85% in 2037. The avoidance of post‐production waste leads to 9% lower greenhouse gas (GHG) emissions compared to recycling with 100% recycling efficiency. Thus, attributable amounts of post‐production waste and unfavorable prolonged use of batteries create misguided incentives to meet legal targets. Additionally, the delay between production and recycling limits the potential for circular production as this depends significantly on market conditions. Our study highlights, that besides recycling, the industry should especially advance production processes including upstream material extraction and refinement to reduce environmental impacts.

Understanding the Dairy Sector in Slovenia: A Modeling Approach for Policy Evaluation and Decision Support

This study investigates the dairy sector in Slovenia, focusing on farm heterogeneity, efficiency in resource utilization, and policy implementations. Through a modeling approach, we explore the differences among dairy farms, considering factors such as herd size, farm management, natural conditions, and production potential. Based on 32 typical dairy farms, representing the entire dairy sector, composed of 6400 dairy farms, the analysis was performed using the farm model (SiTFarm). We emphasize the importance of accurate assessments, given the variability of policy impacts across farm types. While medium-to-large, specialized farms dominate milk production, smaller farms, particularly in less favored areas, hold social and environmental importance despite facing competitive challenges. Addressing environmental sustainability could involve promoting practices that improve milk yield and include grazing, as this tends to lower greenhouse gas emissions per kilogram of milk (−5%). Dairy farms contribute about one-third of the generated revenue in Slovene agriculture, of which a good half goes to farms located in less favored areas. They manage a good quarter of permanent grassland in Slovenia, and it is certainly the sector that can achieve the highest return on these areas. In 75% of the farms, the gross margin is higher than 1756 EUR/ha and using best practices they exceed 3400 EUR/ha. The model results indicate that the average hourly rate on dairy farms during the observed period falls within the range of EUR 7.3 to 17.4 of gross margin for most farms, with the top-performing ones exceeding 24 EUR/h. However, due to the significant reliance on budgetary payments (on average, 58% of the gross margin), the implementation of the common agricultural policy strategic plan generally leads to a deterioration in the economic indicators of dairy farms. This impact is particularly pronounced on medium-sized and larger farms, increasing the effect on income due to the substantial fixed costs involved. Our findings underscore the interplay between policy interventions, farm characteristics, and sectoral outcomes, offering valuable insights for policy-makers and stakeholders.

Green hydrogen: Paving the way for India's decarbonization revolution.

The potential of green hydrogen to make India self-sufficient and energy-independent is reviewed in this study. We integrated technological advancements, economic analysis, and policy frameworks to provide a comprehensive overview of the green hydrogen landscape in India. This review examines cost reductions in electrolyzer technology, the potential for renewable energy integration, and the socio-economic benefits of green hydrogen adoption. Additionally, the study proposes innovative policy measures tailored to India's unique conditions, such as targeted subsidies and incentives for green hydrogen production and use. The research highlights significant cost reductions and increased renewable power generation as key factors contributing to the economic viability of green hydrogen in India. It underscores the importance of large-scale production and advancements in electrolyzer technology. Furthermore, the study emphasizes the necessity of clear regulatory frameworks, infrastructure development, and financing to support the deployment of a green hydrogen economy in India. By implementing a strategic roadmap for green hydrogen, India can reduce its reliance on fossil fuels, lower greenhouse gas emissions, and become a major player in the global green hydrogen market. The proposed policy measures and technological advancements are crucial for successfully adopting and deploying green hydrogen, ensuring energy self-sufficiency and long-term economic sustainability for India.

Forest dynamics in LCA: Integrating carbon fluxes from forest management systems into the life cycle assessment of a building

The urgent issue of climate change has sparked increasing interest in using wood to reduce buildings' greenhouse gas emissions (GHGe). While attributional life cycle assessment (LCA) methods are commonly employed to estimate GHGe from buildings, they lack a temporal distribution of carbon fluxes from biogenic materials, overlooking forest management impacts on emissions and sequestration. Consequently, we investigated the integration of forest and building systems, examining emissions associated with three different forest management scenarios at stand and landscape levels. Our findings suggest a 6 % to 81 % lower GHGe for the building using this study's approach compared to the static methodology recommended by the European Standard EN16485 in a 50 year perspective. However, the accumulated impact over the building's lifetime remains similar. Hence, both methods incentivize building designers’ to use wood to lower GHGe, although the dynamic integration postpones benefits from the forests' carbon sequestration to later stages of the building's lifetime.

Guidelines for efficient nitrogen preservation in sewage sludge-based fertilizers

This study explores sustainable methods to mitigate nitrogen (N) loss in agriculture amid rising food demands and limited arable land. It examines sewage sludge (SS) as an alternative to synthetic N fertilizers. SS is rich in nitrogen (4.21 ± 0.42 %) and phosphorus (3.60 ± 0.72 %), making it suitable for nutrient recovery and soil enhancement. Unfavorable sludge management methods result in the loss of 950,000 tons of nitrogen, meeting almost 10 % of the EU's nitrogen fertilization demand. This research evaluates SS treatment methods, including chemical conversion, thermal treatment, and biological composting, focusing on nitrogen conservation efficiency. Results show nitrogen loss during hydrolysis is minimized at pH 4 to 8 but increases significantly as ammonia (NH3) at pH 9 to 11, ranging from 4.2 % to 9 %. Neutralizing the hydrolysate is crucial; using solid KOH resulted in 13.5 % nitrogen loss, 11 times more than using slightly alkaline ash (1.22 %). Adding ash during drying reduced nitrogen emissions by 30 % compared to traditional drying at 105 °C. Improving the C/N ratio with food residues reduced nitrogen losses by 46.3 % during composting. These findings highlight the importance of pH control in chemical processes and temperature regulation in thermal treatments. Adding residues from other processes, such as biomass combustion waste, enhances SS processing conditions. Understanding nitrogen retention mechanisms is crucial for the environmental sustainability of SS usage. Efficient nitrogen retention strategies improve the fertilization value of SS and reduce its environmental footprint by lowering greenhouse gas emissions, particularly ammonia. Reducing nitrogen loss during SS treatment significantly lowers ammonia emissions, a major contributor to greenhouse gas emissions. These results help determine optimal methods for managing and processing SS to minimize emissions and increase agricultural usability.

Development of comprehensive models for precise prognostics of ship fuel consumption

This study incorporates two unique machine learning algorithms, Huber regression and Light Gradient Boosting Machines (LGBM), for estimating ship consumption of fuel. These methods are employed to create forecasting models for ship fuel consumption during journeys, which is especially useful when interacting with non-linear data. The study then analyzes and evaluates the prediction accuracy of these two approaches compared to a baseline model generated using linear regression. The results of the investigation show that both methods establish extremely accurate predictions while handling non-linear data quickly. However, the Huber-based model outperforms the LGBM in terms of prediction accuracy, with an R-squared value of 0.979 versus 0.917 for the LGBM. In addition, the Huber-based model has a diminished prediction error, with an RMSE of 2.278, compared to the LGBM model's RMSE of 4.55. The graphical methods of the violin plot and Taylor’s diagram further established the superiority of Huber ML. These findings imply that Huber regression could be a suitable option for estimating in-route ship fuel usage in real time. As a consequence, this study emphasises the potential benefits of machine learning for accurately predicting ship fuel consumption, providing encouraging possibilities to optimise fuel usage while lowering greenhouse gas emissions.

How green is my reusable bronchoscope?

IntroductionSingle-use bronchoscopes have replaced reusable ones in many institutions. This study aimed to evaluate the environmental and financial impacts of both strategies: reusable and single-use bronchoscopes. Material and methodsWe conducted a pragmatic study in a 21-bed polyvalent ICU, in Saint-Brieuc, Bretagne, France. The eco-audit consisted of estimating greenhouse gas (GHG) emissions, considering the life cycle of each strategy. Greenhouse gas (GHG) emissions related to construction, packaging, transport and waste elimination were compared between 2 devices: the reusable bronchoscope, a Pentax® FI-16RBS that was disinfected twice daily; and the single-use bronchoscope, the bronchoflex agile® from TSC. ResultsFor the reusable bronchoscope, GHG emissions were marginally impacted by the number of bronchoscopies performed (from 185 kg eq.CO2 per year to 192 kg eq.CO2 for 10 or 110 bronchoscopies per year). For the reusable device, GHG emissions directly depended on the number of bronchoscopies performed with 3.82 kg eq.CO2 emitted per bronchoscopy. The breakeven point for the reusable bronchoscope was estimated at 50 bronchoscopies in terms of GHG emissions and 96 bronchoscopies for financial considerations. ConclusionConsidering current practice in our ICU, reusable bronchoscopes have lower GHG emissions when used more than 50 times a year and a lower cost when used more than 96 times a year as compared with single-use bronchoscopes.

Evaluating the economic and environmental benefits of deploying a national-scale, thermo-chemical plastic waste upcycling infrastructure in the United States

Emerging chemical technologies can upcycle plastic waste by producing high-value polymers and other products. In this work, we study the economic and environmental benefits of deploying an upcycling infrastructure in the continental United States for producing low-density polyethylene (LDPE) and polypropylene (PP) from post-consumer plastic waste. Our analysis is based on a computational framework that integrates techno-economic analysis, life cycle assessment, and value chain optimization. Our results demonstrate that the infrastructure generates a market of nearly 20 billion USD and creates value which is robust to various externalities, opening compensation opportunities for residential waste producers. Our analysis also indicates that the infrastructure can achieve a plastic-to-plastic degree of circularity of 34% relative to residential plastic waste production, and leads to significant environmental benefits over alternative waste disposal methods, including 69%–75% lower greenhouse gas emissions than WtE or 86 avoided new landfills over the next 50 years.

Co-incorporating green manure and crop straw increases crop productivity and improves soil quality with low greenhouse-gas emissions in a crop rotation

In a nine-year field experiment in a wheat–maize–sunflower cropping system in Hetao Irrigation Area, Inner Mongolia, China, organic amendments applied as straw, manure, green manure, and the combination of green manure and straw increased wheat and maize yield, soil aggregate stability, and soil microbial activity in comparison with chemical fertilizer, without changing greenhouse gas emission intensity.

Rethinking environmental sustainability in rainfed cropping systems

Activity data from a 30-year on-farm experiment with six soil-management treatments were used to develop inventory data for environmental partial life-cycle assessment (LCA). The purpose was to compare the treatments based on environmental outcomes and evaluate conservation agriculture (CA) in Australia's dryland cropping zone. Multiple trade-offs were revealed that highlight the need for a nuanced approach to sustainable intensification and show that rules-based CA is not sufficient to guarantee low greenhouse gas (GHG) emissions, nor low overall environmental impact. Nutrient mining in dryland cropping even under CA can lead to losses in soil carbon that can double GHG intensity. In these systems, additional nutrient inputs can reduce the loss of soil carbon as well as net GHG emissions, demonstrating the critical need to include the effects of soil carbon change in LCA to prevent perverse outcomes.The treatment involving strategic tillage and nutrient balancing, along with stubble retention, had the lowest GHG intensity, but there was a trade-off with the higher embedded impacts across several other environmental categories. Higher fertiliser input could lead to toxicity impacts, due to heavy-metal content, that contribute significantly to the Human health endpoint. However, limitations in modelling such local, site-specific impacts were considerable and more research is needed to address this.In general, trade-offs were found to exist between impacts from on-farm activities versus upstream manufacture of inputs; between GHG emissions and land use (yield) versus other environmental categories; and between different on-farm GHG emission sources. Despite these trade-offs, the treatments all had similar overall scores in the Human health and Ecosystems damage categories. There was no single treatment with low, or high, impact scores across all environmental indicators, indicating that trade-offs need to be carefully considered when making farm-management decisions in the context of net-zero or carbon-neutral farming.

Steam & Power Dashboard

Abstract— The development of the Steam and Power Dashboard represents a significant advancement in energy management practices for industrial plants. By integrating data from steam and power systems, the dashboard offers real-time monitoring and analysis capabilities, allowing plant operators to identify inefficiencies and make informed decisions to optimise energy consumption. The research study delves into the design and implementation of the dashboard, highlighting its user-friendly interface and its ability to provide actionable insights for improving plant performance. Furthermore, the impact of the Steam and Power Dashboard on energy efficiency, cost savings, and greenhouse gas emissions is a key focus of the research. The findings demonstrate that the dashboard is effective in enabling plant operators to make data-driven decisions that lead to significant improvements in energy management practices. These improvements not only result in cost savings for the plant but also contribute to reducing the plant’s environmental impact by lowering greenhouse gas emissions. Overall, this research contributes to the advancement of sustainable energy strategies in industrial settings by showcasing the benefits of utilising innovative technologies, such as the Steam and Power Dashboard, to improve energy management practices and drive towards a more sustainable future. IndexTerms – – Python, SQL, EDA

Economic, Societal, and Environmental Impacts of Available Energy Sources: A Review

The impacts that the available energy sources have had on society, the environment, and the economy have become a focus of attention in recent years, generating polarization of opinions. Understanding these impacts is crucial for rational evaluation and the development of strategies for economic growth and energy security. This review examines such impacts of the main energy resources currently exploited or in development, including fossil fuels, geothermal, biomass, solar, hydropower, hydrogen, nuclear, ocean, and wind energies on society through analysis and comparison. It is essential to consider how high energy demand influences energy prices, the workforce, and the environment and to assess the advantages and disadvantages of each energy source. One significant finding from this review is that the levelized cost of energy (LCOE) may vary substantially depending on the energy source used and show substantial ranges for different applications of the same energy source. Nuclear energy has the lowest LCOE range whereas ocean energy has the highest LCOE range among the nine energy sources considered. Fossil fuels were found to have the most substantial societal impacts, which involved on the positive side providing by far the largest number of jobs and highest tax revenues. However, on the negative side, fossil fuels, biomass, and nuclear energy sources pose the most significant health threats and social well-being impacts on communities and societies compared to other energy sources. On the other hand, solar, ocean and wind energy pose the lowest risk in terms of health and safety, with solar and wind also currently providing a substantial number of jobs worldwide. Regarding environmental consequences, fossil fuels generate the highest greenhouse gas (GHG) emissions and have the highest adverse impacts on ecosystems. In contrast, nuclear, ocean, solar and wind energies have the lowest GHG emissions and low to moderate impacts on ecosystems. Biomass, geothermal and hydropower energy sources have moderate to high ecosystem impacts compared to the other energy sources. Hydropower facilities require the most materials (mainly concrete) to build per unit of energy generated, followed by wind and solar energy, which require substantial steel and concrete per unit of energy generated. The lack of substantial materials recycling causes associated with solar and wind energy sources. All the energies that use thermal power generation process consume substantial quantities of water for cooling. The analysis and comparisons provided in this review identified that there is an urgent need to transition away from large-carbon-footprint processes, particularly fossil fuels without carbon capture, and to reduce the consumption of construction materials without recycling, as occurs in many of the existing solar and wind energy plants. This transition can be facilitated by seeking alternative and more widely accessible materials with lower carbon footprints during manufacturing and construction. Implementing such strategies can help mitigate climate change and have a positive impact on community well-being and economic growth.

Comparison of Bio-Coke and Traditional Coke Production with Regard to the Technological Aspects and Carbon Footprint Considerations

In a world facing the challenges of climate change, it is imperative to prioritize the search for sustainable technical solutions. This study focuses on evaluating the environmental impact of using bio-coke compared to traditional metallurgical coke, employing Life Cycle Assessment (LCA) as the evaluation tool. Bio-coke, produced from a blend of coking coals enriched with biomass, offers greater environmental potential than traditional coke due to a reduced share of non-renewable raw materials. The steel and coking industries are significant contributors to carbon dioxide emissions. LCA provides a comprehensive assessment of the environmental impact of bio-based additives, considering raw material deliveries, the coking process, application in metallurgy, and product end-of-life disposal. The analysis results indicate that the use of biomass additives leads to lower greenhouse gas emissions compared to coke production without bio-additives. Given the urgency of addressing global warming and the increasing demand for sustainable energy sources, this study’s findings can advocate for bio-coke as a more environmentally friendly alternative to traditional coke in the steel industry.

Solar Operated Car Enabled with AI

The convergence of renewable energy and artificial intelligence (AI) has spurred a transportation revolution, exemplified by the rise of solar-powered cars equipped with advanced AI capabilities. This abstract digs into the integration of solar energy and AI technology in autos, examining their synergistic potential to transform the automotive industry and pave the way for a more sustainable future.The paper presents the concept of solar-powered cars and discusses their importance in reducing environmental concerns connected with regular fossil-fuelled vehicles. Solar energy, captured by solar panels built into the vehicle's construction, provides a clean and abundant power source, minimizing reliance on non-renewable resources and lowering greenhouse gas emissions. Furthermore, advances in solar panel efficiency and energy storage technology have increased the practicality of solar-powered vehicles for widespread use.. Furthermore, AI-powered autonomous driving capabilities improve safety by reducing human error and allowing for proactive collision avoidance methods. The paper highlights how AI-enabled solar-powered vehicles have the potential to completely change the automotive sector and hasten the shift to a sustainable transportation network

Changing the order and ratio of substrate filling reduced CH4 and N2O emissions from the aerated constructed wetlands

Constructed wetlands (CWs) have been used to enhance pollutant removal by filling several types of material as substrates. However, research on substrate filling order remains still limited, particularly regarding the effects of greenhouse gas (GHG) emissions. In this study, six CWs were constructed using zeolite and ferric‑carbon micro-electrolysis (Fe-C) fillers to evaluate the effect of changing the filling order and ratio on pollutant removal, GHGs emissions, and associated microbial structure. The results showed that the order of substrate filling significantly impacted pollutant removal performance on CWs. Specifically, CWs filled with zeolite in the top layer exhibited superior NH4+-N removal compared to those filled in the lower layer. Moreover, the highest NH4+-N removal (95.0 % ± 1.9 %) was observed in CWs with a zeolite to Fe-C volume ratio of 8:2 (CWZe-1). Moreover, zeolite-filled at the top had lower GHGs emissions, with the lowest CH4 (0.22 ± 0.10 mg m−2 h−1) and N2O (167.03 ± 61.40 μg m−2 h−1) fluxes in the CWZe-1. In addition, it is worth noting that N2O is the major contributor to integrated global warming potential (GWP) in the six CWs, accounting for 81.7 %–90.8 %. The upper layer of CWs filled with zeolite exhibited higher abundances of nirK, nirS and nosZ genes. The order in which the substrate was filled affected the microbial community structure and the upper layer of CWs filled with zeolite had higher relative abundance of nitrifying genera (Nitrobacter, Nitrosomonas) and denitrifying genera (Zoogloea, Denitratisoma). Additionally, N2O emission was reduced by approximately 41.2 %–64.4 % when the location of the aeration of the CWs was changed from the bottom to the middle. This study showed that both the order of filling the substrate and the aeration position significantly affected the GHGs emissions from CWs, and that CWs had lower GHGs emissions when zeolites were filled in the upper layer and the aeration position was in the middle.

The greenhouse gas performance of selected biodegradable and recalcitrant plastics in U.S. landfills

Biodegradable plastics are often considered to exhibit superior environmental performance compared to conventional recalcitrant plastics. Here, we assess the greenhouse gas (GHG) emissions of selected biodegradable and recalcitrant plastics made from both fossil and biogenic carbon (C) as disposed in a national average U.S. landfill. This average landfill incorporates consideration of size, precipitation, landfill gas management, and gas collection installation schedule. The GHG emissions of an 80% biodegradable polycaprolactone (PCLf) made from fossil C and a 2% biodegradable poly(butylene succinate) (PBSb) made from biogenic C were evaluated to represent the range of anaerobic biodegradabilities. The 2% biodegradable PBSb has lower GHG emissions than the 80% biodegradable PCLf in the national average landfill. In the best case, which includes aggressive gas collection, conversion of gas to energy, and disposal in a large landfill, the PCLf results in 2423 kg CO2e/mt, which is well above PBSb (−1956 kg CO2e/mt), a hypothetical biogenic and 80% biodegradable PCLb (4739 kg CO2e/mt), and recalcitrant fossil plastic (0 kg CO2e/mt). From a disposal perspective, a recalcitrant biogenic plastic is optimal given the long-term storage of carbon. This study informs the direction of materials research to develop materials that minimize their overall environmental footprint at end-of-life.

Energy Efficiency and Greenhouse Gas Emission Reduction Potential of Solar PV and Biomass-Based Systems for a Food Processing Plant

The industrial sector is one of the most energy-intensive sectors, with a share of 38% (156EJ) of all energy used globally in 2020. Historical energy demand and consumption data from the poultry processing plant have been analyzed to lower greenhouse gas emissions (GHG) and reliance on traditional energy sources. The study includes energy, economic, and emissions analyses for (a) solar photovoltaic (PV) systems, (b) biomass fuels, and (c) coal-fired with wood. Fixed, single, and two-axis tracking solar PV systems that are company-owned and funded by banks are considered. The historical energy consumption data shows that 52.36% of energy demand is met by electrical energy and 47.63% by thermal energy. The yearly electricity demand is 9,938 MWh, costs $1,192,560, and emits 5117.6 tCO2. Thermal energy demand is based on an annual use of 898 tonnes of coal and 71.6 tonnes of liquefied petroleum gas (LPG), which costs $ 143,681 and emits 2,977.7 tonnes of carbon dioxide (tCO2). Feasibility of 1.3 MW, fixed axis company-owned, solar PV plant shows an annual electricity production of 1,876 MWh, GHG emission reduction of 965.9 tCO2 with a payback period of 3.4 years. Biomass system delivers yearly fuel cost savings of $25,724, reducing 2,784 tCO2 with a 1.9-year payback period. Co-firing biomass offers a 3.58% fuel cost saving and 557 tCO2 with a 0.93-year payback period. It concluded that the wood fuel feedstock biomass option is the best renewable energy resource for large-scale poultry facilities and can reduce 34.08% of cumulative GHG emissions.