In recent decades there have been significant changes in land use and production orientation in certain marginal agricultural areas in the southwest of Spain. The abandonment of rainfed cereal crops and their change of use as natural pastures grazed by milk sheep, have led to an improvement in the profitability of the farms, greater industrialisation and a positive impact on rural development. This paper calculates the carbon footprint (CF) of farms in the context of life cycle assessment with the objective to identify the system that accounts for the lowest CF while maintaining adequate levels of profitability and revitalising the rural environment. The data were obtained through surveys carried out on dairy sheep farms of different typologies, ranging from the semi-intensive farms with small grazing areas, to the extensive farms with large areas of natural pastures. Findings could help farmers evaluate the environmental impact of their activities, while at the same time provide consumers with valuable evidence to be used in further marketing actions. Greenhouse gas emissions vary from 1.77 to 4.09 Kg CO2eq/kg of milk, where the lowest values correspond to the most intensive farms and the highest values to the most extensive and least productive farms. Enteric fermentation, followed by feeding, are the emissions with the greatest impact. Enteric fermentation reaches its maximum value (52.22 % of the total emissions) in the most extensive farms. On other hand, this study found that carbon sequestration varies between 0.09 and 2.04 kg of CO2eq/kg of milk, a figure that can considerably reduce the carbon footprint calculation and justifies its inclusion in the Life Cycle Assessment.
Keywords: Sheep farms | Extensive | Carbon footprint | Rangelands

This paper presents a cooperative multi-objective optimization for the networked microgrids energy management. We introduce the Independence Performance Index (IPI) for the MGs to reduce energy exchange with the main grid. The system losses, voltage drop, and greenhouse gas emissions are improved when the independence of MMG is increased. Besides, the MMG operator seeks to reduce its total daily costs. For this reason, MGs can participate in Demand Response Programs (DRPs). MGs have two types of loads, namely flexible and inflexible loads. The flexible loads can response to price signals and participate in the DR Programs. The uncertainty of renewable generation is modeled as a stochastic optimization that a scenario generation and reduction decision-making method is employed. This stochastic multi-objective optimization is solved by Compromised Program (CP) method that is used to combine non-homogeneous objective functions. This technique converts the original multi-objective problem into a single-objective problem. The proposed model is tested on a standard case study for two different conditions. The simulation results show the proposed model improves CO2 emission about 13.4 and 9.2% in the case studies. Besides, the proposed model brings 17 and 11.7% improvements for the independence of MMG in the case studies.
Keywords: Demand response programs | Independence performance index | Multi-objective optimization | Multi-microgrid

There has long been an understanding that to achieve meaningful progress against sustainability challenges, action is required at multiple levels. With regards to education initiatives, these levels range from macro-level international agreements and activities such as the United Nations Sustainable Development Goals (SDGs) and the United Nations Principles of Responsible Management Education, meso-level influences such as the role of national bodies supporting sustainability in higher education, and micro-level influences such as the commitment of individual universities or departments. However, decision makers are individuals and the development and delivery of such initiatives requires action at the level of the individual. This paper explores the impact of working within and across these different levels and how jointly they help to work towards addressing carbon reductions in a partnership setting between a business school and various organisations. In its centre is an educational initiative carried out in the United Kingdom in the core curriculum of Nottingham Business School where students conduct a carbon footprint of an organisation and recommend measures to reduce the companys greenhouse gas emissions. The total recommended greenhouse gas emissions savings from two years of the project were 507, 435 kg CO2e, averaging over 10 tonnes per organisation and 2 tonnes per student. If this project was extended over 5 years and taken on by an additional educator, the potential reductions increase to 2,562,418 kg CO2e. It demonstrates that action undertaken at the micro-level can result in significant impact at the macro-level when scaled up and provide sig- nificant benefits to actors across all levels from individuals though to all participating organisations. This initiative has proven very successful in delivering SDG 7, SDG 13 and SDG17; if taken up by more business schools the impacts on the targets of these SDGs and the climate change agreements could be significant.
Keywords: Climate mitigation | Responsible management education | Sustainable development goals | Education for sustainable development | Carbon | Business | Principles of responsible management | education

Incomplete combustion processes lead to the formation of many gaseous byproducts that can be challenging to monitor in flue gas released via chimneys. This study presents ground-based remote sensing approaches to make greenhouse gas (GHG) flux measurements of methane (CH4) and nitrous oxide (N2O) from a waste incineration chimney at distances of 150–200 m. The study found emission of N2O (corresponding to 30–40 t yr−1), which is a consequence of adding the reduction agent urea to decrease NOX emissions due to NOX regulation; a procedure that instead increases N2O emissions (which is approximately 300 times more potent as a GHG than CO2 on a 100-year time scale). CH4 emissions of 7–11 t yr−1 was also detected from the studied chimney despite the usage of a high incineration temperature. For this particular plant, local knowledge is high and emission estimates at corresponding levels have been reported previously. However, emissions of CH4 are often not included in GHG emission inventories for waste incineration. This study highlights the importance of monitoring combustion processes, and shows the possibility of surveying CH4 and N2O emissions from waste incineration at distances of several hundred meters.
keywords: Waste incineration | Greenhouse gas emissions | Methane | Nitrous oxide | Remote measurements| Hyperspectral imaging