Alessandro Chiodi

Integrating agriculture and energy to assess GHG emissions reduction: a methodological approach

Agriculture is responsible for approximately 25% of anthropogenic global GHG emissions. This significant share highlights the fundamental importance of the agricultural sector in the global GHG emissions reduction challenge. This article develops and tests a methodology for the integration of agricultural and energy systems modelling. The goal of the research is to extend an energy systems modelling approach to agriculture in order to provide richer insights into the dynamics and interactions between the two (e.g. in competition for land-use). We build Agri-TIMES, an agricultural systems module using the TIMES energy systems modelling framework, to model the effect of livestock emissions and explore emissions reduction options. The research focuses on Ireland, which is an interesting test case for two reasons: first, agriculture currently accounts for about 30% of Irelands GHG emissions, significantly higher than other industrialized countries yet comparable with global levels (here including emissions associated with other land-use change and forestation); second, Ireland is both a complete and reasonably sized agricultural system to act as a test case for this new approach. This article describes the methodology used, the data requirements, and technical assumptions made to facilitate the modelling. It also presents results to illustrate the approach and provide associated initial insights. Policy relevance Most of the policy focus with regard to climate mitigation targets has been on reducing energy-related CO2 emissions, which is understandable as they represent by far the largest source of emissions. Non-energy-related GHG emissions – largely from agriculture, industrial processes, and waste – have received significantly less attention in policy discourse. Going forward, however, if significant cuts are made in energy-related CO2 emissions, the role of non-energy-related GHG emissions will grow in importance. It is therefore crucial that climate mitigation analyses and strategies are not limited to the energy system. This article shows the value of using integrated energy and agriculture techno-economic modelling techniques to draw evidence for new comprehensive climate policy strategies able to discern between the full range of technical solutions available. It enables the production of economy-wide least-cost climate mitigation pathways.

Soft-Linking Exercises Between TIMES, Power System Models and Housing Stock Models

Soft-linking TIMES models with carefully selected complementary models can provide useful additional insights into the results from the TIMES model and can usefully scrutinize specific TIMES results in greater detail with another model. This multi-model approach can take advantage of the individual strengths of different modelling approaches. This chapter collates methodologies and results from a number of soft-linking exercises with TIMES. Two specific examples are given; firstly the soft-linking of TIMES to a power system model to investigate the TIMES results and provide additional insights into power system flexibility, reliability and market issues. The second example comprises the soft-linking of a TIMES model to a power system and a housing stock model to explore the impacts of increased electrification of residential heating on the power system and associated emissions from the residential sector. These examples show how a multi-model approach and soft-linking can provide a strong complementary analysis to TIMES modelling exercises and generate insights into results that otherwise would be difficult to achieve with a single model approach.

Energy Policies Influenced by Energy Systems Modelling—Case Studies in UK, Ireland, Portugal and G8

A key objective of IEA-ETSAP is to assist decision makers in robustly developing, implementing and assessing the impact of energy and climate mitigation policies. This chapter focuses on four case studies, in which there is clear evidence of a direct link between the use of MARKAL and TIMES scenario modelling activities and the resulting policy decisions. The case studies selected assess how the (i) UK MARKAL model informed the development of energy and climate mitigation policy in the UK, focusing on the Energy White Paper in 2003, the Energy White Paper in 2007 and the Climate Change Act in 2008; (ii) Irish TIMES model informed the development of climate mitigation legislation in Ireland in 2014 and Ireland’s negotiating position regarding the EU 2030 Climate Energy Package in 2014; (iii) TIMES_PT model informed climate policy in Portugal in the last 10 years and has supported the design of climate mitigation policies; (iv) IEA ETP Model informed the G8 in responding to the 2005 Gleneagles Plan of Action and has supported the work of the Major Economies Forum and Clean Energy Ministerial. This chapter collates methodologies and results from these different case studies and summarizes some key findings regarding (i) policy frameworks and goals; (ii) how policy makers have been intertwined with the modelling tool during the modelling process; (iii) the role of the economic stakeholders dialogue; (iv) main insights from the modelling exercises; (v) lessons learnt: from effective contributions to real limitations and (vi) recommendations.

Introduction: Energy Systems Modelling for Decision-Making

The role that energy modelling plays in improving the evidence base underpinning policy decisions is being increasingly recognized and valued. The Energy Technology Systems Analysis Program is a unique network of energy modelling teams from all around the world, cooperating to establish, maintain and expand a consistent energy/economy/environment/engineering analytical capability mainly based on the MARKAL/TIMES family of models, under the aegis of the International Energy Agency. Energy systems models like MARKAL/TIMES models provide technology rich, least cost future energy systems pathways and have been used extensively to explore least cost options for transitioning to an energy secure system and a low carbon future. This chapter presents an overview of ETSAP’s history and objectives, introduces the main principles of energy system modelling and summarizes the different chapters of the book.

A Global Renewable Energy Roadmap: Comparing Energy Systems Models with IRENA’s REmap 2030 Project

In 2014, the International Renewable Energy Agency (IRENA) published a global renewable energy roadmap—called REmap 2030—to double the share of renewables in the global energy mix by 2030 compared to 2010 (IRENA, A Renewable Energy Roadmap, 2014a). A REmap tool was developed to facilitate a transparent and open framework to aggregate the national renewable energy plans and/or scenarios of 26 countries. Unlike the energy systems models by IEA-ETSAP teams, however, the REmap tool does not account for trade-offs between renewable energy and energy efficiency activities, system planning issues like path dependency and investments in the grid infrastructure, competition for scarce resources—e.g. biomass—in the commodity prices, or dynamic cost developments as technologies get deployed over time. This chapter compares the REmap tool with the IEA-ETSAP models at two levels: the results and the insights. Based on the results comparison, it can be concluded that the REmap tool can be used as a way to explicitly engage national experts, to scope renewable energy options, and to compare results across countries. However, the ETSAP models provide detailed insights into the infrastructure requirements, competition between technologies and resources, and the role of energy efficiency needed for planning purposes. These insights are particularly relevant for countries with infrastructure constraints and/or ambitious renewable energy targets. As more and more countries are turning to renewables to secure their energy future, the REmap tool and the ETSAP models have complementary roles to play in engaging policy makers and national energy planners to advance renewables.

Modal Shift of Passenger Transport in a TIMES Model: Application to Ireland and California

Climate change mitigation clearly requires a focus on transport that should include improved representation of travel behaviour change in addition to increased vehicle efficiency and low-carbon fuels. Energy system models focus however on technology and fuel switching and tend to poorly incorporate travel behaviour. Conversely, transport demand modelling generally fails to address energy and climate policy trade-offs. This chapter seeks to make energy systems analysis more holistic by introducing modal choice within passenger transport in a TIMES model, to allow trade-offs between behaviour and technology choices explicit. Travel demand in TIMES models is typically exogenous—no competition exists between alternative modes. A simple illustrative TIMES model is described, where competition between modes is enabled by imposing a constraint on overall travel time in the system. This constraint represents the empirically observed travel time budget of individuals, constraining the model choosing between faster and more expensive modes (e.g. cars) and slower but cheaper mode (e.g. buses or rail). Further, a new variable is introduced, called travel time investment, which acts as a proxy for infrastructure investments to reduce the time associated with travel, to enable investment in alternative modes of transport as a means of CO2 mitigation.

Challenges Faced When Addressing the Role of Cities Towards a Below Two Degrees World

In order to achieve the goal of the Paris Agreement on Climate Change to limit average global temperature rise to well under 2 °C, concerted action will be needed in cities to manage energy consumption and reduce greenhouse gas emissions. But, what can be done at city level to move towards such a global ambitious target? The project InSMART (Integrative Smart City Planning) brought together four EU cities: Evora (Portugal), Cesena (Italy), Nottingham (UK) and Trikala (Greece), and scientific organizations in these countries in order to try and provide some answers to this question. A methodology was established for enhancing sustainable energy planning for future city needs through an integrative and multidisciplinary approach, including City Energy System Models (ESM), development of different scenarios with a participatory workshop approach, and a multi-criteria assessment for the final ranking of measures and the development of a Sustainable Energy Action Plan. It is important not to overestimate the contribution and the area of influence of city-agents to the global GHG target; but it is undoubted that municipalities are extremely well positioned for actions related to households, and their consumption in buildings and transport, for bridging locally the gap between what is perceived/known and what would be economically and technically feasible and for urban planning with a focus on significant benefits for GHG emissions reduction.