To achieve national and global air quality and climate change objectives, the agricultural sector increasingly requires dependable decision support tools for gaseous emissions at the farm level. We evaluated thirteen greenhouse gas (GHG)-based decision support systems (DSS), considering criteria such as not only the accessibility, user-friendliness, stakeholder involvement, sustainability methodology, and modeling aspects, but also the input parameters and outputs provided, all crucial for decision making. While most DSSs provide information for facilitating their use, only four are suitable for inexperienced users, and stakeholder participation in DSS development is infrequent. The dominant methodology for farm-level GHG estimation is IPCC 2006, with quantitative models primarily used for indicators’ assessment. Scenario and contribution analyses are the prevailing decision support approaches. Soil, crop, and fertilizer types are the most implemented non-livestock-related inputs, while climate- and feed-related costs are the least required. All DSSs assess farm-level mitigation measures, but less than half offer sustainability consultation. These tools promote environmental sustainability by evaluating mitigation strategies, disseminating farm sustainability information, and guiding sustainable farm management. Yet, challenges such as disparate estimation methods, result variations, comparison difficulties, usability concerns, steep learning curves, the lack of automation, the necessity for multiple tools, the limited integration of the results, and changing regulations hinder their wider adoption.

Food systems and, to an extent, the pig sector are major contributors of greenhouse gas (GHG) emissions globally. At the same time, significant amounts of waste are produced from the food sector. The aim of this study is to examine the implementation of circular bio-economy practices in the Greek pig sector to improve its environmental performance. More specifically, in collaboration with a pig farm in Northern Greece and a waste management company, the collection and processing of bakery by-products was organized to produce bakery meal (BM) to integrate it in the diets of fattening and growing pigs. Using Life Cycle Assessment (LCA) methodology, the environmental performance of 20% BM inclusion in pig diets was examined in comparison with the conventional feedstock. BM experimentally replaced corn, wheat, barley, and soya bean from conventional feedstock. The Life Cycle Inventory (LCI) was based on the yearly average values of feed and energy consumption to produce 1 kg of living weight of pig on the pig farm. Life Cycle Impact Assessment (LCIA) was conducted with SimaPro v3.5, using Recipe Midpoint Hierarchical v1.6. The LCIA calculations exhibited that BM inclusion in pig diets can lead to significant land occupation decrease, approximately 30%, which is mostly related to reduced wheat and soya beans. The reduction of cultivated croplands also led to reduced fertilizer and pesticide application, which improved marine eutrophication and freshwater ecotoxicity impact by 20% while it significantly reduced risks of human carcinogenic toxicity by 25%. Moreover, the Greek pig sector exhibited a 5% capacity for overall improvement of its environmental performance, which relies on minimizing logistics when the pig farm conducted collection and processing of by-products. A basic assumption of this study is the assessment of bakery by-product quantities in the wider region of the pig farm. The availability of by-products, based on the reported experience, was limited, and the reliability of the supply was frequently disrupted. As such, the supply chain model of the central hub for the collection and processing of bakery by-products is proposed as more efficient for regulating logistic challenges and availability.

In this paper, 15 farm-scale Green House Gas-based (GHG-based) decision support (DS) tools were evaluated based on a number of criteria (descriptive evaluation), as well as the parameters requested as inputs and the outputs, all of which are considered important for the estimation procedure and the decision support approach. The tools were grouped as emission calculators and tools providing indicators in terms of more than one pillar of sustainability. The results suggest an absence of automatic consultation in decision support in most of the tools. Furthermore, dairy and beef cattle production systems are the most represented in the tools examined. This research confirms a number of important functionalities of modern GHG-based DS tools.

To meet national and global air quality and climate ceilings, it is essential to provide farm-level decision support tools for mitigating gaseous emissions from agriculture. A major challenge is to develop reliable tools that can be adapted to country-specific conditions, particularly in countries where such tools are currently lacking, and support farmers in assessing emission mitigation measures. To address this challenge, a Prototype Decision Support Tool (PDST) for estimating and mitigating gaseous emissions at the livestock farm scale was developed based on the FarmAC whole-farm model. The PDST supports livestock farm-level assessment of carbon emissions, including CH₄ and CO₂, and nitrogen-related emissions, including N₂O and NH₃. Emissions were estimated using the IPCC 2006 Guidelines, their 2019 Refinement, and the EMEP/EEA 2023 methodology. The PDST was applied to two intensive pig farms in Greece, both with fully slatted housing and outdoor slurry tank storage, and two intensive dairy cattle farms, one in Greece and one in Poland, both using deep-litter housing with solid manure storage. For these farms, the PDST estimated total annual emissions of 1.58 and 1.54 kg CO₂eq per kg of pig live weight and 0.80 and 0.66 kg CO₂-eq per kg of raw milk, respectively. These estimates were consistent with values reported in the literature for comparable production systems and emission sources, supporting the preliminary consistency of the PDST outputs. The PDST can form the software basis to support stakeholders in choosing farm-level practices that specifically reduce emissions.

Globally, livestock production is a major source of greenhouse gas (GHG) emissions, which are the primary driver of climate change. To assess the expected needs for Decision Support Tools (DST) related to GHG emissions in global livestock production at the farm level, the perspectives of stakeholders were surveyed. Direct communication with stakeholder groups in various countries was established to explore their experiences with existing GHG-based DST at the farm scale. Collecting this information was crucial to understand the current demand for integrating GHG and ammonia emissions estimation into the decision-making process at the farm scale across different countries. Additionally, the study aimed to evaluate and present the potential for utilizing these DST at the farm scale in the near term. Understanding the requirements of potential users can offer valuable insights to developers of emissions-based decision support tools, enabling them to improve existing tools and align them better with users’ needs. The majority of respondents were livestock farm advisors (80 out of 116), followed by livestock farmers (23 respondents), inventory compilers (9 respondents), and authority officials/policymakers (4 respondents). The survey respondents represented various countries, including Greece, Poland, Germany, Austria, France, and Chile. While most stakeholders who responded were aware of software-based DS tools, less than half of them actually used such tools. Furthermore, even fewer respondents reported using software-based DS tools that estimate GHG and ammonia emissions at the livestock farm level to incorporate emission reduction in decision-making process. Although the adoption of farm-scale emission-based DST in livestock farming is currently limited, it is clear that farmers who embrace technological developments are aware of the potential environmental impact of their farms. In fact, 87.7% of respondents expressed interest in being informed about software-based DS tools that estimate and utilize GHG and ammonia emissions in decision-making. Moreover, 59.6% of stakeholders expressed a willingness to participate in a future process for developing software-based DS tools that estimate and incorporate GHG and ammonia emissions in decision-making. This highlights the need for continued development and promotion of standardized tools across all participating countries.