Consequential life cycle assessment of the Italian power system

Energy production and consumption contribute to 76% of the European greenhouse gas (GHG) emissions in 2018, and 90% of global GHG emissions with land use, land use change and forestation (LULUCF) in the same year. By applying energy efficiency (EE) and renewable energy (RE) technologies, the GHG emission intensity of the energy sector reduced by 1.3% in 2018 compared to the previous year. The current climate change policy aims at decarbonization, sustainable environment, economic prosperity and social equity. It requires the deep decarbonisation of the economies, meaning that the energy and power systems as well as other emission intensive sectors need to transform into zero-emission ones. It also requires the minimization of the environmental impacts while ensuring the economic development and meeting the need of the population growth. This thesis quantifies and evaluates the life cycle environmental impacts with focus on GHG emissions of the power sector, as consequences of changes in the environmental policy. Specifically, the thesis will answer five research questions: 1. What are climate change and energy/ power development policies in Italy? 2. What are changes in the energy/ power systems as consequences of energy climate policies? 3. What are the methods and approach for quantifying and evaluating life cycle environmental impacts as consequences of changes? 4. What are the life cycle environmental impacts of the Italian energy/ power system, with focus on GHG emissions, as consequences of changes in environmental and power policies? 5. The interactions between the energy climate policies and the environmental impacts/ GHG emissions of the Italian power system? The thesis is structured into six chapters, including two chapters of introduction and conclusion, and four chapters of answering five above-mentioned research questions. Chapter 2 provides the answers for two questions (Question 1 and Question 2) on climate and energy policies and changes in the Italian energy/power system due to climate and energy policies. Climate change and energy/ power development policy in Italy is presented in five main documents: FIT for 55, Integrated national energy and climate plan (NECP), national energy strategy (SEN), national energy efficiency action plan (PAEE), and national renewable energy action plan (NREAP). The four national documents set out the targets for EE and RE. Specifically, the targets of energy savings by 2030 include 43% reduction in primary energy consumption, 0.8% reduction in annually final energy consumption without transportation sector and 10 MTOE final energy consumption reduction. For RE, by 2030, the target is 28% ~ 30% of share of RE in total energy consumption, 55% of RE share in electricity consumption and 21% ~ 22% of RE share in transportation sector. It is expected that the electricity generation technology mix will change in order to meet the requirement on RE and EE targets set out in the Italian energy and climate policies. In this thesis, the energy scenarios called National Trend Italia (NT Italia) will be used. The NT Italia was developed by Terna and Snam, for the horizon years 2025, 2030 and 2040, using modelling tools for electricity demand, gas demand and market simulation. In these scenarios, the installed capacity of electricity by natural gas, which is slightly increased by 2040. The installed capacity of coal-based electricity and other fossil fuels-based electricity reduce from 7GW currently to 2GW by 2025, and will not change then. The scenarios also see a constant growth of electricity by RE, reaching 64 GW for solar and 25 GW for wind power (including 4.2 GW offshore) by 2040, while the installed capacity of hydropower and other renewable electricity will be stable. Chapter 3 and Chapter 4 of this thesis will deal with the research question 3, in which Chapter 3 is about the methodology and Chapter 4 focuses on the applied framework. In Chapter 3, the state of the art of consequential life cycle assessment (C-LCA) in the energy and power sectors has been reviewed. The review was conducted on 43 case studies of C-LCA in energy sector and 31 C-LCA papers in power sector. It was identified that economic models are frequently applied in combination with life cycle assessment (LCA) to conduct a C-LCA study in energy and power sectors. The identified economic models include equilibrium (partial and general equilibrium), input-output, and dynamic (agent based and system dynamic) models. Out of these, the equilibrium model is the most widely used, showing some strengths in availability of data and energy system modelling tools. The input-output model allows for describing both direct and indirect effects due to changes in the energy sector, by using publicly available data. The dynamic model is less frequently applied due to its limitation in availability of data and modelling tools, but has recently attracted more attention due to the ability in modelling quantitative and qualitative indicators of sustainability. The review indicates that the most suitable approach to conduct the study is combining one or several economic models and LCA to assess the consequential life cycle impacts of the power system. As each economic model has their own strengths and limitations, the choice of the applied models in combination with LCA largely depends on the goal of the study, the nature of the changes due to market mechanisms, economic or social origins, and the availability of data. In Chapter 4, a framework of combining Input Output Analysis (IOA) and process-based LCA for conducting the study was proposed. Moreover, this chapter provides detailed information on data collected for the model. There are several weighting points for proposing this framework. Firstly, the goal of the study is to assessing the consequential life cycle impacts of energy/ power systems. It requires the comprehensive overview of all economic sectors, as energy is connected all economic activities. The comprehensiveness will be ensured by applying IOA. At the same time, the process-based LCA will provide the detail of a sector/ a product system, which is normally a limitation of economic-wide tool such as IOA. Secondly, the change in the power system originates from economic activities (supply and demand of energy) as well as the environmental requirement to GHG emission reduction and zero carbon emissions. This change can be well modelled with an economic analysis tool (IOA) in combination with an environmental management tool (processed-based LCA). Finally, data for these tools is publicly available. The IOA depends on the input output tables (IOT), which is published every five years by the Italian Statistics (Istat). Data on energy sector is collected from Energy Balance Table, published annually by Ministry of Economic Development, the data from Terna and Snam, the database of the International Energy Agency (IEA), International Renewable Energy Agency (IRENA) and European Commission. Data on environmental aspects includes the National Accounting Matrix with Environmental Accounts (NAMEA), being collected from Istat. Data for process-based LCA is taken from ecoInvent 3. Some global database for IOA are available such as World Input Output Database (WIOD), EXIOBASE, and ect. Followings is the general framework for combining IOA and processed-based LCA to conduct a C-LCA. Consequential life cycle impact is the subtraction of the life cycle impact ‘after change’ and the life cycle impact ‘before change’. The life cycle impact ‘before change’ is quantified by applying IOA. The life cycle impact ‘after change’ depends on the change of pollutant amount, technological coefficient and the final demand due to the inclusion of renewable energy into the Italian energy system. In this thesis, multiregional input output (MRIO), a variant of IOA is used to cover several regions or countries. The application of hybrid MRIO and process-based LCA (hereinafter being called as H-MRIO) is described as followings: • First, two types of data, including MRIO and hybridization data are collected. MRIO data such as the Italian and multiregional IOTs and air emissions accounts are collected from Istat and EXIOBASE. Hybridization data is collected from Italian power/energy suppliers for power development scenarios, and from the ecoinvent database for direct air emissions of power generation technologies • From MRIO data, the MRIO model with two regions of Italy and Rest of the World (RoW) and 36 economic sectors will be constructed. • In combination with the power development scenarios, the Italian electricity sector is disaggregated into seven power generation technologies, for both intermediate flow matrices and final demand vectors in Italian IOT. Similarly, in the environmental burden matrices, the air emissions of electricity sector are disaggregated into those of seven power generation technologies, with data taken from ecoinvent. At this time, the H-MRIO model composes of 42 sectors (36 economic sectors - 1 electricity sector + 7 power technologies). • The model is calculated with historical data of 2010 and 2017 (reference scenario) and replicated for the future scenarios of 2025, 2030 and 2040. Chapter 5 focuses on applying the proposed H-MRIO framework on the Italian context, to obtained the answers for the last two research questions (Question 4 and 5). The total GHG emissions to meet global final demand in 2017 calculated in the study is at 47.69 GtCO2e, which is slightly higher than the global GHG emissions estimated by Climate Watch, at 47 GtCO2e excluding Land use change and forestation (LUCF). The difference in the obtained results of this model and other models is caused by the difference in scope of air emissions being studied. This model quantified actual anthropogenic emissions of CO2, CH4 and N2O, excluding emissions from LULUCF and biomass burning as a fuel. Meanwhile the Climate Watch’s model takes into account all GHGs (CO2, CH4, N2O, and F-gases such as HFCs, PFCs, and SF6), excluding LUCF. This causes a difference of around 1 GtCO2eq of F-gases and 2.8 Gt CO2eq of CH4. The exclusions of emissions from land use (mostly CH4), biogenic CO2 and F-gases in this model leads to an insignificant difference of around 0.69 GtCO2e (less than 1.5%). In order to look into details of the sources of the change in the air emission, a decomposition analysis has been conducted. With the change in final demand and electricity sector composition of Italy, consumption-based GHG emissions appear to decrease in the period 2010-2040. Specifically, due to changes in production structure, emission coefficients, and final demand, the annual CO2 emission reduction embodied in production activities during the period 2017- 2025 will be up to 7.1 MtCO2, which makes up 57.1 MtCO2 emission reduction in the whole period. The increased final demand of Italy causes an annual increase of 4.8 MtCO2. While the change in production structure, including electricity sector and corresponding change in other economic sectors, helps to reduce 6.1 MtCO2 annually. The change in emission flow coefficients brings an annual reduction credit of about 5.8 MtCO2. During the period of 2025-2030 and 2030-2040, the annual change in emission reduction will be much smaller, at 2.3 MtCO2 and 33.9 ktCO2 respectively. Due to the change in power supply technologies and power consumption, the future air emissions dramatically reduce in electricity sector. Most of the emissions of the domestic electricity production come from fossil fuel based electricity, e.g. electricity by coal and natural gas. A smaller part comes from other renewable electricity, including geothermal and biomass based electricity. The productions of solar and wind power do not generate any air-borne emission, and that of hydropower emits an amount of N2O. The reduction in electricity from fossil fuels such as coal and natural gas help to reduce the emissions of the domestic electricity production nearly four times from 97.5 MtCO2 in 2017 to 25.9 MtCO2 by 2040. Besides, the CO2 emission of final consumption of electricity is 34.9 MtCO2 in 2017, which reduces by more than half, at 13.7 MtCO2 by 2040. The CO2 emission of final electricity consumption is divided among technologies by their production structure. As it can be observed, low-carbon technologies such as solar and wind power technologies contribute to emissions, because of the manufacturing of their infrastructures. The emissions of final electricity consumption are smaller than that of domestic electricity production, as they are shared by other economic sectors as intermediates for production activities. The changes in electricity consumption induce changes in other economic sectors, which are clearly shown in coke and petroleum, pharmaceuticals, water transportation, education, and healthcare, either increase or decrease their emissions. Particularly, electricity sector accounts for 11.6% of the total CO2 emissions in 2017, which reduces to 5.9% by 2040. The CO2 emission shares of some other economic sectors also decrease during the period 2017-2040, such as construction and healthcare (reducing around 1 percent point). Meanwhile, the CO2 emission shares of some sectors increases, such as food and beverage (increasing less than 1 percent point). It should be noted that the CO2 emission contributions of these sectors to the national final consumption emissions do not show the correspondingly absolute increase (or decrease). Instead, they relatively present the changes in the identified ‘hotspot’ sectors over years. The absolute values of the CO2 emissions decrease in all economic sectors between 2017 and 2040. The decrease is clearly presented in economic sectors such as construction, decreasing from 20.99 MtCO2 in 2017 to 13.4 MtCO2 by 2040, at about 0.33 MtCO2 annually; or food and beverage, decreasing from 15 MtCO2 to 12.5 MtCO2, or 0.1 MtCO2 annually; or healthcare, decreasing from 17.7 MtCO2 to 11.43 MtCO2 or 0.27 MtCO2 annually in the same period. Five economic sectors holding larges shares out of total CO2 emission of final consumption includes: wholesale and retail, healthcare, food and beverage, electricity and construction (‘hotspot’ sectors). In 2017, wholesale and retail contribute to more than 12% of the total CO2 emission of the Italian final consumption. The four remaining sectors account for an average CO2 emission, from 6% to 10% of the total CO2 emissions. By 2040, the shares of emissions of these sectors remain in the same range. This emission pattern suggests that between 2017 and 2040, in order to reduce the national CO2 emissions, effort should be focused on these ‘hotspot’ sectors. Besides, the different contributions of domestic and import emissions to the total emissions suggest that Italy should have proper strategies to reduce its emissions in term of geographical effort. CO2 emissions of Italian trade partners for food and beverage, health, construction, and wholesale and retail should be taken into account because their emissions largely depends on import. The effort should be taken either to reduce their trade partners’ emission intensity, or to move away from trade partners that having high emission intensities. Meanwhile equal effort should be shared between local manufacturers and trade partners being relevant to renewable power technologies such as solar, wind and other renewable.