sustainability Article Tackling Energy Poverty through Collective Advisory Assemblies and Electricity and Comfort Monitoring Campaigns Joana Ortiz 1, * , Mariana Jiménez Martínez 2 , Alba Alegría-Sala 3 , Sergio Tirado-Herrero 4 , Irene González Pijuan 5,6 , Mònica Guiteras Blaya 5 and Lluc Canals Casals 2,3 1 Thermal Energy and Building Performance Group, Catalonia Institute for Energy Research (IREC), Jardins de les Dones de Negre 1, 2a, 08930 Sant Adrià de Besòs, Spain 2 Energy Systems Analytics Group, Catalonia Institute for Energy Research (IREC), Jardins de les Dones de Negre 1, 2a, 08930 Sant Adrià de Besòs, Spain; mcjimenez@irec.cat (M.J.M.); lluc.canals@upc.edu (L.C.C.) 3 Project and Construction Engineering Department, Polytechnic University of Catalonia, Avda. Diagonal 647, 08028 Barcelona, Spain; alba.94ras@gmail.com 4 Institute of Environmental Science and Technology (ICTA), Universitat Autònoma de Barcelona (UAB), 08193 Cerdanyola del Vallès, Spain; Sergio.Tirado@uab.cat 5 Enginyeria Sense Fronteres, Carrer Múrcia 24 Baixos, 08027 Barcelona, Spain; irene.gonzalez@esf-cat.org (I.G.P.); monica.guiteras@esf-cat.org (M.G.B.) 6 Centre for Regional Economic Social Research, Sheffield Hallam University, Howard St., Sheffield City Centre, Sheffield S1 1WB, UK * Correspondence: jortiz@irec.cat  Abstract: The present work aims to describe and analyze the results of the interventions carried out  in the Barcelona pilot site of the EmpowerMed project. The overall objective of EmpowerMed is to Citation: Ortiz, J.; Jiménez Martínez, tackle energy poverty and to help improve the health of people in coastal areas of Mediterranean M.; Alegría-Sala, A.; Tirado-Herrero, countries, with a particular focus on women. The main support approach implemented in Barcelona S.; González Pijuan, I.; Guiteras Blaya, is Collective Advisory Assemblies (CAA), in the framework of Alliance against Energy Poverty. M.; Canals Casals, L. Tackling Energy Poverty through Collective Advisory CAA is an innovative, collaborative empowering engagement tool that offers an alternative to the Assemblies and Electricity and more traditional one-off individual household advice and support approaches. CAAs take place Comfort Monitoring Campaigns. together with a monitoring campaign where: electricity consumption is analyzed to optimize the Sustainability 2021, 13, 9671. https:// supply contracts, and indoor environmental comfort to provide recommendations for wellbeing im- doi.org/10.3390/su13179671 provement. Through the different approaches, a characterization of the people that have participated in the Barcelona pilot site was completed, from a socioeconomic, energy, thermal comfort and air Academic Editor: quality perspective. Additionally, it was compared with a group of energy poverty non-affected Samuel Asumadu-Sarkodie households, which are involved in the monitoring campaign. Finally, the impact was quantified in terms of empowerment of energy poverty population and, potential economic savings. Received: 21 July 2021 Accepted: 24 August 2021 Keywords: energy poverty; collective advisory assembly; smart meters; thermal comfort; air qual- Published: 27 August 2021 ity; gender Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. 1. Introduction While the European Union is spearheading global action on the climate emergency, millions of Europeans are unable to access a sufficient level of domestic energy services for fully participating in the lifestyles, customs and activities that define membership Copyright: © 2021 by the authors. of society. This condition has become widely known as energy or fuel poverty (EP) in Licensee MDPI, Basel, Switzerland. the scientific and policy literature and is defined as the “inability to attain a socially and This article is an open access article materially necessitated level of domestic energy services” [1]. According to the European distributed under the terms and Energy Poverty Observatory (EPOV), tens of millions of Europeans suffer from high energy conditions of the Creative Commons expenses, cold homes and arrears on utility bills among other symptoms [2]. Spatial Attribution (CC BY) license (https:// differences in incidence rates signal Eastern and Southern Member States (including Spain) creativecommons.org/licenses/by/ as a “periphery” of EU countries displaying EP rates significantly higher than those in 4.0/). Sustainability 2021, 13, 9671. https://doi.org/10.3390/su13179671 https://www.mdpi.com/journal/sustainability Sustainability 2021, 13, 9671 2 of 28 the North-Western “core” of nations where just a small fraction of their populations are affected [3,4]. Low incomes, increasing energy prices, and poor energy performance of buildings have been identified as key drivers for EP in the EU context [5–8] As EP is a multifaceted prob- lem [9], studies identifying or characterizing EP-affected households from different perspectives are available for several European locations. These include socio-economic [10–13], energy consumption [12,13], energy expenses [10–13], thermal comfort [10,11], dwelling characteris- tics [10–13], physical health [14,15], mental health and social relations [16] and gender [15,17] dimensions. In order to provide a point of comparison, results from EP-affected households have been often compared against non-affected peers in previous research. This is the case of the statistical analysis carried out by Papada and Kaliampakos to measure EP levels in Greece [18]. Recently, the adoption of smart meters in some EU-member states has facilitated access to household energy consumption data to an unprecedented level of detail, pro- moting its usage in EP characterization studies, especially when electricity consumption is considered. Smart meter data are often complemented by quantitative or qualitative survey questions, and tend to include thermal comfort evaluations as they are not only related to energy usage but work as EP indicators themselves [19]. An example is the work by Gouveia et al. [12] that analyzed electricity consumption patterns and thermal comfort levels in 388 households from Évora, Portugal, using smart-meter data, survey responses and buildings energy use simulations, differentiating between EP-affected and non-affected consumers. Data retrieved from smart meters can also be used for the assessment of EP mitigation actions based on bill optimization, as Antepara et al. propose in their analysis of an intervention providing energy service advice to vulnerable households in the Basque Country [20]. To the best of our knowledge, no other research that combines smart meter, thermal comfort and indoor air quality measurement data to characterize EP has yet been carried out in the EU. Within the Mediterranean basin, the Metropolitan Area of Barcelona (which includes the city of Barcelona) is home to more than 3.2 million people and the eighth-largest metropolitan region in Europe. Its Mediterranean climate of mild winters and hot summers make the city vulnerable to wintertime forms of EP as well as to climate change-related heat waves in the summertime. In the years 2016–2017, 24.7% of the metropolitan population was at risk of poverty or social exclusion and 5.3% suffered severe material deprivation. Estimates based on EP indicators show that several hundred thousand people living in the metropolitan area experience difficulties in paying for their domestic water and energy are unable to keep their homes adequately warm in winter, reported arrears on utility bills or relied on insecure access to the supply of basic household utilizes (electricity, water and gas). These various forms of monetary and material deprivation affect women disproportionately as they have lower salaries and pensions, more precarious jobs, less access to stable, quality housing, and poorer health than men [21]. Gender inequality is a risk factor that increases the vulnerability and probability of suffering from EP [22]. Petrova and Simcock [23] have identified two ways in which EP is differentially experienced along gender lines: household practices of responding to and resisting EP, and the emotional labor of living with EP. Sánchez-Guevara et al. [17] look into the feminization of EP through an analysis of gender inequalities in EP incidence in the city of Madrid, while also highlighting the scarcity of available gender-disaggregated data re- ferred to EP. Other previous research [17,23,24] also suggests that one of the main problems to characterize and quantify the feminization of EP is the lack of gender-disaggregated data, since EP has typically been conceptualized and researched as a “household” issue. It is well established that the physical health and psychological and emotional well- being of people can be influenced by their environment [25]. Over the last decade, there has been an increase in scientific publications that establish the relationship between in- adequate housing and disease and mortality [26]. Studies such as the one conducted by Bonnefoy [27] explores the type of housing conditions that have a negative effect on occupants’ health, and their associated risks. In the case of EP, affected persons are more Sustainability 2021, 13, 9671 3 of 28 likely to suffer from poor health because of their precarious socioeconomic situation, inad- equate living conditions and limited opportunities and challenges in balancing strained household budgets. Critical drivers of ill-health in relation to EP are poor thermal and humidity conditions, inadequate dwelling quality, inability to afford domestic energy services and debt-related stress and social stigma, among others [28–32]. EP has severe direct and indirect impacts on the physical and mental health of those who suffer from it and these conditions have been associated with excess winter mortality and morbidity due to respiratory and cardiovascular diseases [33]; poor mental health and wellbeing [34]; and the exacerbation of existing health conditions. Furthermore, EP has been found to impact the ability of people to socially engage with others [16]. The recognition of EP as a distinct form of deprivation and as a policy issue of its own merit has triggered action in the EU at all levels over the last 10 years. Some of this action takes place under Horizon 2020-funded projects such as EmpowerMed (from which this pa- per stems) and cognate initiatives (such as REACH, ENPOR or STEP) that test approaches for addressing EP at small scales. These projects often include local interventions aimed at helping affected people save energy at home; an approach that often relies on changing habits and behavior under the assumption that people in EP use more energy than necessary due to the inefficiency of the dwelling or appliances and what has been labeled as “energy illiteracy” (i.e., “the lack of understanding of the nature and role of energy in our daily lives, and the inability to apply it to everything from making energy efficiency decisions to understanding energy bills” [35]). In many cases, interventions consist of household visits in which a rapid energy audit is conducted along with the provision of energy-saving and thermal comfort tips, and the installation of low-cost energy efficiency measures, e.g., LED bulbs, socket strips and simple windows weather-stripping. Such small-scale project-based interventions take place in parallel to more ambitious national and local level measures led by governmental actors to mitigate EP. For instance, Kyprianou et al. [6] have compared support policies implemented in five EU member states—Bulgaria, Cyprus, Lithuania, Portugal, Spain—Regarding consumer protection, financial interventions, energy savings, RES integration, and information provision. Initiatives led by non-governmental organi- zations have also been reviewed by Bouzarovski et al. [7] and Creutzfeldt et al. [36], for instance, the “CAF-Acció” initiative in Spain that lend EP-affected money to implement energy efficiency or retrofitting measures. Nonetheless, detailed information about their approaches, beneficiaries’ characteristics or impacts on affected households is often missing in national-level studies of this sort. In its Barcelona pilot site, the EmpowerMed project is testing and implementing collec- tive advisory assemblies (CAA) as an innovative, collaborative empowering engagement tool that offers an alternative to traditional one-off individual household advice and sup- port approaches. Inspired by right to energy principles, CAAs go beyond a symptomatic treatment of EP and aim to mobilize the potential of individual and collective agency for affected people—Especially women—To confront their “vulnerable consumer” status. They are based on a horizontal participatory methodology in which people affected by EP receive recurrent advice and support from an “assembly of peers”—A mix of activists and partici- pants who have been or still are in EP themselves. As part of the EmpowerMed project activities, CAAs take place together with related forms of support (Figure 1), namely: (1) an electricity and indoor environmental comfort monitoring campaign to optimize electricity supply contracts and provide recommendations for comfort improvement; and (2) mutual support workshops facilitated by a counselor for addressing the mental health and emotional wellbeing impacts of EP. In that context, the authors want to give an answer to the following research questions: • Who attends the CAAs and what is their socioeconomic profile? • What are the indoor environmental comfort conditions of EP participants in CAA, in terms of thermal comfort and air quality? What are the differences when compared to non-EP households? to non-EP households? • What electricity consumption patterns can be observed among EP-affected partici- pants in CAA? What are the differences when compared to non-EP households? • Are collaborative engagement tools such as CAA useful strategies to empower EP- affected persons and reduce the impact of EP? Sustainability 2021, 13, 9671 4 of 28 The present work characterizes the EP population that attends CAA, describes and analyzes the results of EmpowerMed interventions from a multi-perspective point of view (energy use, economic savings, thermal comfort and indoor air quality, and empower- • ment What electricitypopulation). of EP-affected consumptionThepatterns papercan beproduces also observedaamong EP-affected comparison of keyparticipants EP-related in CAA? variables What sample in a small are the differences when compared of EP households to non-EP households? and non-EP-affected households. The anal- • of ysis Are thecollaborative mutual supportengagement workshopstools such as the is outside CAA useful scope strategies of the to empower paper, and EP- only a short affected persons and reduce the description of the activity is included.impact of EP? Figure Figure 1.1.EmpowerMed EmpowerMed activities (left) (left) activities carried out in out carried Barcelona pilot site pilot in Barcelona and datasets site and(right) col- datasets lected in each of them: collective advisory assemblies, monitoring campaign of electricity and indoor (right) collected in each of them: collective advisory assemblies, monitoring campaign of electricity environmental comfort, and mutual support workshops. and indoor environmental comfort, and mutual support workshops. The The present present paper is divided intothe work characterizes theEPfollowing populationsections: Section CAA, that attends 2 describes the main describes and determinants of EP in Spain, followed by Section 3 that introduces analyzes the results of EmpowerMed interventions from a multi-perspective point of view the social movement Alliance against (energy use, Energy economic Poverty savings, (APE) comfort thermal in Catalonia, in collaboration and indoor air quality,with and which the Em- empowerment powerMed activities are carried out. Section 4 describes the materials of EP-affected population). The paper also produces a comparison of key EP-related and methods used in this research—in particular, data collection, tools and procedures. variables in a small sample of EP households and non-EP-affected households. The analysis Section 5 shows the results of the research of the mutual supportinworkshops relation to is socioeconomic characterization outside the scope of the paper,of CAA participants, and only a short indoor environmental comfort, description of the activity is included. electric consumption and costs, and the achievements of the CAAs carried out in the framework of APE’s actions; Section 6 discusses The present paper is divided into the following sections: Section 2 describes the main the results and relates theofmain determinants EP infindings to previous Spain, followed by studies Section and 3 thatis introduces followed bythe Section social7movement that states the main conclusions of the research. Alliance against Energy Poverty (APE) in Catalonia, in collaboration with which the EmpowerMed activities are carried out. Section 4 describes the materials and methods 2. Energy used Poverty in this Determinants research—in particular, in data Spaincollection, tools and procedures. Section 5 shows the results It is well established that the determinants of EPcharacterization of the research in relation to socioeconomic are a combination of CAA participants, of: (a) socioeco- indoor environmental comfort, electric consumption and costs, and nomic situation of the household; (b) poor housing energy efficiency; and (c) high energythe achievements of the CAAs prices carried [5]. To out in the contextualize framework the of APE’s Spanish situation inactions; relation Section 6 discusses to EP driving factors,thetheresults main and relates the of characteristics main the findings electricity to market previous studies and and is followed the residential by Section building stock are 7 that states described the main conclusions of the research. below. Household consumers in Spain have the option to get their electricity supply from a 2. Energy Poverty Determinants in Spain regulated or non-regulated company since the market liberalization process was com- pletedIt with is well theestablished enactment of thatthethe determinants Electricity ServiceofLaw EP are a combination in 2013 [37]. Althoughof: (a) onesocioe- of the conomic situation objectives of the of the market household; was liberalization (b) poor housing to offer energy efficiency; more competitive prices toand (c) high consumers, energy prices [5]. To contextualize the Spanish situation in relation to EP driving factors, the main characteristics of the electricity market and the residential building stock are described below. Household consumers in Spain have the option to get their electricity supply from a regulated or non-regulated company since the market liberalization process was completed with the enactment of the Electricity Service Law in 2013 [37]. Although one of the objectives of the market liberalization was to offer more competitive prices to consumers, electricity costs for Spanish households have followed an increasing trend in the past decade, even with the drop-in prices experienced in 2019 and 2020, as Figure 2-left shows. Spain is in fact one of the EU-27 countries with the highest electricity prices, especially when using Purchasing Power Standard (PPS) for comparison (Figure 2-right). The PPS is an artificial common reference currency unit used by Eurostat which eliminates the differences in price and income levels between countries. The prices shown in Figure 2 correspond to an average domestic consumer (2500–5000 kWh/year). However, when observing the same ade, even with the drop-in prices experienced in 2019 and 2020, as Figure 2-left shows. Spain is in fact one of the EU-27 countries with the highest electricity prices, especially when using Purchasing Power Standard (PPS) for comparison (Figure 2-right). The PPS is an artificial common reference currency unit used by Eurostat which eliminates the dif- Sustainability 2021, 13, 9671 ferences in price and income levels between countries. The prices shown in Figure 2 cor- 5 of 28 respond to an average domestic consumer (2500–5000 kWh/year). However, when observ- ing the same Eurostat data for different electricity consumption bands, it is observed that households with the lowest annual consumption (under 1000 kWh/year) pay up to two Eurostat data for different electricity consumption bands, it is observed that households times more in average per kilowatt-hour consumed than those in the upper consumption with the lowest annual consumption (under 1000 kWh/year) pay up to two times more in band (above 15,000 kWh/year), which suggests that tariff structures in Spain put a heavier average per kilowatt-hour consumed than those in the upper consumption band (above burden on low-income households as reported by Haar [38]. 15,000 kWh/year), which suggests that tariff structures in Spain put a heavier burden on Furthermore, the Spanish regulation considers not only the variable cost per kilo- low-income households as reported by Haar [38]. watt-hour consumedthe Furthermore, as Spanish shown above, butconsiders regulation also a capacity term not only charged cost the variable upon the per con- kilowatt- tracted hour power defined consumed by the user. as shown above,According but also atocapacity SmartEnterm [39], charged only Italy, the Netherlands, upon the contracted Norway, Portugal and Sweden had a similar tariff structure in the EU by 2019. UntilNorway, power defined by the user. According to SmartEn [39], only Italy, the Netherlands, June 2021, the capacity charge could represent over 75% of the consumers’ electricity Portugal and Sweden had a similar tariff structure in the EU by 2019. Until June 2021, bill de-the pending on their consumption habits, one of the highest in Europe [Indra/Eurelectric]. capacity charge could represent over 75% of the consumers’ electricity bill depending on their consumption habits, one of the highest in Europe [Indra/Eurelectric]. Figure 2. Electricity prices for household consumers in Spain and the European Union (27 countries), for a consumption Figure 2. Electricity prices for household consumers in Spain and the European Union (27 countries), for a consumption band DC (Medium): Annual consumption between 2500 kWh/year and 5000 kWh/year. The prices include taxes and levies. band DC (Medium): Annual consumption between 2500 kWh/year and 5000 kWh/year. The prices include taxes and lev- Electricity prices in Euro/kWh (left) and in PPS/kWh (right) [40]. The EU-27 countries included are: BE, BG, CZ, DK, DE, ies. Electricity prices in Euro/kWh (left) and in PPS/kWh (right) [40]. The EU-27 countries included are: BE, BG, CZ, DK, EE, DE, IE,IE, EE, GR, ES,ES, GR, FR, CRO, FR, IT,IT, CRO, CY,CY, LV,LV, LT, LT, LU,LU, HU,HU, MT,MT, NL,NL, AU,AU, PL, PL, PT, RO, SI, SK, PT, RO, SI, FI SK,and SE. SE. FI and To offer residential consumers an alternative from liberalized market supply contracts, To offer residential consumers an alternative from liberalized market supply con- the Spanish legislation allows low-voltage customers with contracted power under 15 kW tracts, the Spanish legislation allows low-voltage customers with contracted power under to undertake their electricity from a reference supply company (“Comercializadoras de 15 kW to undertake their electricity from a reference supply company (“Comercializado- referencia”, in Spanish), which are companies that can offer regulated tariffs under gov- ras de referencia”, in Spanish), which are companies that can offer regulated tariffs under ernment price controls [41]. Before June 2021, three regulated tariffs were available under government price controls [41]. Before June 2021, three regulated tariffs were available this scheme known as Voluntary Price for the Small Consumer (PVPC for its acronym in under this scheme known as Voluntary Price for the Small Consumer (PVPC for its acro- Spanish). Tariffs 2.0DHA and 2.0DHS could be classified as Time-of-Use (ToU) tariffs as nym in Spanish). Tariffs 2.0DHA and 2.0DHS could be classified as Time-of-Use (ToU) they have more than one pricing period as explained in Circular 3/2014 [42], while tariff tariffs as they have more than one pricing period as explained in Circular 3/2014 [42], 2.0A was a flat rate. New legislation introduced in June 2021 [41] eliminates these three while tariff tariffs, 2.0A only leaving was aone flatToU rate.tariff Newwithlegislation introduced three pricing periodsin (peak, June 2021 [41]flat) valley, eliminates available these three tariffs, leaving only for customers in the regulated market. one ToU tariff with three pricing periods (peak, valley, flat) available for customers in the regulated market. Regarding national EP support policies, the status of vulnerable consumers and the Regarding social national bonus (“Bono EP support Social policies, Eléctrico”) the status for domestic of vulnerable electricity consumers consumers and the were introduced social bonus in the late (“Bono 2000 s Social Eléctrico”) and regulated infor domestic 2017 electricity [43]. The social consumers bonus is a were socialintroduced benefit that in reduces the late 2000 the cost of electricity bill by 25% or 40% according to the level ofthat s and regulated in 2017 [43]. The social bonus is a social benefit reduces vulnerability theaccredited cost of electricity bill by 25% or 40% according to the level of vulnerability by the beneficiary. Having a contract with a reference supply company is a accredited byrequirement the beneficiary. Having to access thea social contract with The bonus. a reference supply household’s company is level vulnerability a requirement is assessed by the government considering a series of socioeconomic characteristics such as annual household income, number of children, and special circumstances such as disability, status as victims of terrorism or gender-based violence 43]. Regarding the energy performance of buildings in Spain, more than 50% of the existing housing stock is over 50 years old [44], showing poor energy performance compared to the current building standards. The most common typology are buildings constructed between 1961 and 1980, which represent 36% of the country’s dwellings (6.4 million dwellings) and imply around 32.5% of the heating consumption of Spain [45]. This building typology was built without energy efficiency criteria, so it does not guarantee comfortable indoor Sustainability 2021, 13, 9671 6 of 28 conditions to the occupants without an intense use of heating and cooling systems (no insulation materials, low window performance, high infiltration and thermal bridges, inefficient heating systems). Statistical data from Eurostat’s Survey on Income and Living Conditions (SILC) reflect these inadequate conditions of households, showing that as of 2019 around 7.5% of the Spanish population could not keep their home adequately warm in winter, 6.5% had arrears on utility bills or lived in a dwelling with a leaking roof, damp walls, floors or foundation, or rot in window frames of the floor. In addition, data from the EPOV indicate that 22.8% of the population lived in uncomfortable cool dwellings in the summer of 2012 and 14.2% had had a high share of energy expenditure relative to their income [46]. 3. Alliance against Energy Poverty in Catalonia The Alliance against Energy Poverty (APE, “Aliança contra la Pobresa Energètica” in Catalan), formed in Catalonia in 2014, is a social movement, constituted by EP-affected people and activists. APE advocates for universal access to water and energy services, pointing out the responsibility of the administrations, but also of the large companies that trade with these services. Among APE’s main battles is the prohibition of electricity, water and gas cuts in vulnerable households, the cancellation of debts incurred by these households with the utilities, the denunciation of the supply companies’ harassment suffered by families in debt, and a guaranteed minimum level of supply for households in precarious housing conditions as a consequence of being forced to live in irregularly occupying properties. A significant milestone of APE in Catalonia is Law 24/2015 [47] that prohibits supply cuts in “services of general interest” (i.e., water, gas and electricity) to vulnerable families, which was initially launched as a popular legislative initiative co-led by the Alliance. Since 2015, APE has been demanding big utility companies to cancel the accumulated debts of vulnerable families. Debt write-off was achieved for households indebted to the dominant water utility in the Metropolitan Area of Barcelona (Agbar) in 2018 and the dominant electricity company in Catalonia (Endesa) in 2021. A primary tool in APE’s action are CAAs, through which attendees share their own EP experience and receive the support and advice of the assembly. CAAs function as a transformative, self-support engagement methodology that helps participants facing often overwhelming EP conditions get rid of the fear, shame and sense of failure associated with EP. CAAs are held twice a month, followed by coordination meetings where political and strategic issues are discussed. In cases where it is deemed necessary, affected people are “accompanied” in the process of claiming their supply rights against utilities and public authorities. Non-violent direct actions and/or communication campaigns are also carried out within the framework of APE’s political action strategy. In CAAs, affected people (i.e., with unpaid rent or utility bills, or facing supply disconnection, foreclosure or eviction) share concerns and grievances in a safe and trusted space without feeling judged or examined. These meetings follow a collective intelligence methodology: As new cases arrive, knowledge accumulates and practical solutions to specific cases are jointly crafted by assembly participants, who also provide support and advice about, e.g., how to renegotiate a mortgage with a financial institution, or how to deal with utility providers and social services. Assemblies have an explicit gender dimension as they are mostly attended by affected women. Even if assemblies are facilitated by non-affected activists, they purposely have no explicit formal leadership to ensure that everyone feels equally entitled to contribute with their knowledge and skills about, e.g., how to deal with utility companies, social services or how to change a supply contract to reduce bills (but not consumption). The individual household cases addressed in the CAA serve for advocacy purposes too. They allow disseminating the right to energy approach among the media and the wider public thus helping to insert this perspective into social imaginaries. Sustainability 2021, 13, 9671 7 of 28 4. Materials and Methods 4.1. Data Collection Data collection was carried out within the framework of CAAs between October 2019 and May 2021. Consequently, a non-probabilistic sampling is used, where APE’s participants were invited to voluntarily participate in the data collection process. Further- more, social networks and email were used to engage non-EP-affected persons in order to compare their living conditions to the EP-affected ones. Different levels of participation were proposed to CAA attendees, resulting in three datasets. A brief overview is presented and more details are provided in the next Sections 4.2 and 4.3: • CAA monitoring tool: collects general information about each CAA. Information from 34 CAAs were registered during the studied period. • CAA survey: Gathers information on socioeconomic and energy from all new CAA participants. 74 questionnaires were completed by assembly participants that attended a CAA for the first time. • Monitoring campaign: detailed information is collected from 27 voluntary participants of the monitoring campaign, some of which were recruited during CAAs. This dataset contains thermal comfort, indoor air quality and electricity consumption data from 27 voluntarily surveyed households that include 14 EP-affected and 13 non-EP- affected households. However, due to specific characteristics of 8 of the 27 households (explained below), not all were included in the comparative analysis of electricity consumption. As a result, only 19 households are included in the electricity use assessment (10 EP-affected and 9 non-affected). 4.2. Collective Advisory Assemblies (CAAs) Two different EmpowerMed tools for data collection are used in each CAA: The CAA monitoring tool and the CAA survey. The CAA monitoring tool is used during the assemblies to obtain data in a non- intrusive way, as direct interactions that might disturb the session are avoided. This tool is formed by two simple tables through which an EmpowerMed project member takes notes of ongoing events and commentaries that take place during CAAs. The first table presents a general overview of the CAA by registering the number of persons (gender sensitive) that attend each session, present a case, speak out or inform of health affectations. The second table collects the characteristics of each individual case presented during the session. Specifically, the registered data are: Type of electricity contract (regulated or liberalized), contracted power, cost of the utility bill, active social bonuses for electricity and/or gas and other situations (e.g., water leaks, irregular connections or accumulated debts). In addition, the estimated potential savings of each form of support or advice provided by the assembly to the participant is included in the table. Once the session finishes, data are transposed to an Excel spreadsheet that automatically reports the expected and confirmed savings per session—See results in Section 5.4. An example of this tool is available at the website of the EmpowerMed project [48]. Regarding the CAA survey, all new participants to CAA, affected and non-affected, are invited to voluntarily fill in an online questionnaire that collects general socioeconomic and EP information of the households. The 74 household data are used to provide a descriptive analysis of EP-affected populations that participate in CAAs. Additionally, a correlation test is run on key survey variables using the Pearson correlation tool to find relevant statistical associations among variables—See results in Section 5.1. 4.3. Monitoring Campaign: Electricity and Indoor Environmental Comfort A monitoring campaign is offered to CAAs’ participants, addressed to EP-affected and non-effected. The monitoring campaign consists of four main parts, as Figure 3 shows: volunteer engagement, detailed monitoring survey, electricity and indoor environmental comfort monitoring campaign, individual and collective feedback. relevant statistical associations among variables—See results in Section 5.1. 4.3. Monitoring Campaign: Electricity and Indoor Environmental Comfort A monitoring campaign is offered to CAAs’ participants, addressed to EP-affected Sustainability 2021, 13, 9671 and non-effected. The monitoring campaign consists of four main parts, as Figure 3 shows: 8 of 28 volunteer engagement, detailed monitoring survey, electricity and indoor environmental comfort monitoring campaign, individual and collective feedback. Figure 3. Monitoring campaign process: volunteer engagement, detailed monitoring survey, elec- Figure 3. Monitoring campaign process: volunteer engagement, detailed monitoring survey, electric- tricity and indoor environmental comfort monitoring campaign, individual and collective feedback. ity and indoor environmental comfort monitoring campaign, individual and collective feedback. Thefirst The firststep stepisistotoinvite invitevoluntary voluntaryparticipants participantstototake takepart partininthe themonitoring monitoringcam-cam- paign. This process is performed at two moments paign. This process is performed at two moments of the CAA: of the CAA: •• At Atthe thebeginning beginning ofof thethe assembly, assembly, when when the the monitoring monitoring campaign campaign is introduced is introduced to theto the participants with the objective to involve them participants with the objective to involve them in the process. in the process. •• At Atthe theend endofofthe theassembly, assembly, when when previous previous volunteers volunteers thatthat have have finished finished the the moni- monitor- toring process share their experience with the group, providing ing process share their experience with the group, providing collective feedback and collective feedback and encouraging encouraging other other people people to participate to participate in thein the monitoring monitoring campaign. campaign. InInthe thesecond secondstep, step,volunteers volunteersproceed proceedtotocomplete completeaadetailed detailedmonitoring monitoringsurvey survey[49]. [49]. Thequestionnaire The questionnairecollects collects information information fromfrom different different fields: fields: Demographic Demographicand andsocioeco- socioe- nomic data, conomic data,household householdinformation, information,comfort comfort perception, perception, energy energysupply supply contracts, EPEP contracts, in- dicators and energy awareness. A Google Form survey is used to deliver indicators and energy awareness. A Google Form survey is used to deliver the question- the questionnaire and is naire andfilled in in-person is filled or online, in in-person depending or online, dependingon the volunteer’s on the availability volunteer’s and availability also and be- also cause ofofthe because theCOVID-19 COVID-19pandemic pandemicrestrictions. restrictions. Duringthe During thethird thirdstep, step,the themonitoring monitoringprocess processisiscarried carriedout outby bycollecting collectingelectrical electrical andindoor and indoorenvironmental environmental comfort comfort data. AAdetailed detailedexplanation explanationofofboth bothprocedures procedures is is in- troduced ininSections introduced Sections4.3.1 4.3.1and and4.3.2. 4.3.2. Thefourth The fourthstep stepconsists consistsofofproviding providingfeedback feedbackofofthe theresults resultsand andisisperformed performedonce once bothmonitoring both monitoringprocesses processesare arefinished: finished: •• Individualfeedback: Individual feedback:Volunteers Volunteersreceive receiveananexplanation explanationabout aboutthe theresults resultsofofthe themoni- mon- toring, itoring, which whicharearesummarized summarizedinintwo twopersonalized personalizedreports. reports.Some Somerecommendations recommendations are areprovided providedininterms termsofofthe thepower powersupply supplycontract contractand andpotential potentialeconomic economicsavings, savings, asaswell wellas, as,thermal thermalcomfort comfortandandairairquality qualityimprovements improvementsthrough throughbasic basicbehavioral behavioral changes. changes. •• Collective Collectivefeedback: feedback:Volunteers Volunteersexplain explaintheir theirexperience experienceduring duringthe themonitoring monitoringcam-cam- paign paign process at the CAA, highlighting the usefulness of the results andthe process at the CAA, highlighting the usefulness of the results and theeasiness easiness ofofits itsimplementation. implementation. 4.3.1. 4.3.1.Indoor IndoorEnvironmental EnvironmentalComfort ComfortMonitoring Monitoring The The environmental comfort monitoringevaluates environmental comfort monitoring evaluatesthe thethermal thermalcomfort comfortand andair airquality quality through a measurement campaign of 10–15 days. Two sensors are given to each volunteer, through a measurement campaign of 10–15 days. Two sensors are given to each volunteer, with indications to place them in their living room and the main bedroom to record indoor air temperature, humidity and CO2 concentration. Data are recorded every 2–5 min, depending on the storage capacity of data loggers. Information about the sensors used in the monitoring process is detailed in Table 1. The sensors are provided to volunteers completely configured along with simple instructions to place the sensors in their houses. The use of battery-powered sensors is prioritized, but plug-in sensors are provided to non- affected volunteers when several households are monitored simultaneously. In general, the sensors are delivered during the CAA; however, a post-delivery service was available if needed to facilitate the participation of EP-affected people attending virtually to the CAA. Weather data are collected for the same monitoring periods from weather stations located in the vicinity of monitored households. Sustainability 2021, 13, 9671 9 of 28 Table 1. Characteristics of the sensors used in the monitoring process. Sensor Variables Power Supply Location Comet-U3430 Temperature Battery or Humidity Living room Wöhler CDL 210 CO2 concentration Plug-in Elitech RC-5 USB Temperature Battery Bedroom The monitored data together with the information from the detailed monitoring survey are used to analyze the indoor environmental comfort conditions of each household. The following aspects were used from the survey: • Building characteristics: year of construction, state of conservation, level of energy efficiency and characteristics of the heating and cooling systems. • Household size and usage of the dwelling: number of occupants, use of heating and cooling systems, use of natural ventilation and solar shading devices. • Indoor environmental comfort perception: local discomfort issues in winter and summer, and satisfaction with indoor environmental comfort levels. The monitored data were used to calculate the comfort and air quality indicators, in order to be compared with the users’ comfort perceptions obtained from surveys. The indicators are described following and comfort ranges are detailed in Table 2: • Operative Temperature (Top , ◦ C) is a thermal comfort index for adaptive method [50], that relates acceptable temperature ranges to weather conditions. The adaptive com- fort method is applied in occupant-controlled naturally conditioned spaces. Top = A · Ti + B · Trm (1) where, Ti is the indoor air temperature, Trm is the radiant mean temperature, and A and B are parameters that depends on the indoor air velocity (va ) (if va < 0.2 m/s, then A = B = 0.5; if 0.2 < va < 0.6 m/s, then A = 0.6 and B = 0.4, if va > 0.6 m/s, then A = 0.7 and B = 0.3, which method for obtaining the operative temperature is described in ASHARE 55 [51]). Indoor air temperature is the only parameter measured, to simplify the campaign and do not disturb households’ occupants, therefore the following assumptions were made: Trm = Ti , and va <0.2 m/s, and consequently the parameters A and B are 0.5. These simplifications may underestimate the thermal discomfort of the users, as situations like radiant temperature asymmetry or draft are not completely reflected by the indoor air temperature parameter. However, a balance must be struck between the representativeness of the measurements and avoid inconvenience to users. • CO2 concentration (CO2 , ppm) is used as a tracer of human occupancy and allows to determine if the household has appropriate ventilation rates to guarantee acceptable indoor air quality. As Table 2 shows, there are four comfort categories, from the highest to the lowest level of expectation, IEQI to IEQIV , respectively. The thermal comfort range is defined by a minimum and maximum comfortable operative temperature, which is established according to outside temperature conditions (To,rm , running mean outdoor temperature of the daily mean outdoor air temperature). The measured operative temperature should be inside the corresponding comfort category, depending on the requirements of the users. For households, the expected comfort range would be IEQII for new buildings and IEQIII for existing buildings. The last comfort category, IEQIV should be avoided and is only acceptable for short periods of time. The air quality comfort ranges are based on the CO2 concentration, defining a maximum CO2 concentration above the outdoors for each category, being the outdoors CO2 concentration around 350–500 ppm. Sustainability 2021, 13, 9671 10 of 28 Table 2. Comfort range for the different comfort indexes: Operative temperature and CO2 concentration [50]. Top CO2 (1) Comfort Range Level of Expectation [◦ C] [ppm] High. Occupants with special needs (children, Top = 0.33 · To,rm + 18.8 + 2 (2) IEQI 550 elderly, persons with disabilities, etc.). Top = 0.33 · To,rm + 18.8 − 3 Top = 0.33 · To,rm + 18.8 + 3 IEQII Medium. Standard level. 800 Top = 0.33 · To,rm + 18.8 − 4 Moderate. It will not provide any health risk but Top = 0.33 · To,rm + 18.8 + 4 IEQIII 1350 may decrease comfort. Top = 0.33 · To,rm + 18.8 − 5 Low. Acceptable only for very short periods of IEQIV - >1350 time throughout the year. (1) Corresponding CO2 concentration above outdoors (350–500 ppm). (2) To,rm is the running mean outdoor temperature of the daily mean outdoor air temperature. 4.3.2. Electricity Monitoring Tool The electricity monitoring tool consists of a Python script that calculates and compares the estimated annual electricity expenses considering different tariff options with the purpose of identifying the one that represents the least cost for the user and analysing whether they can opt for a social benefit to reduce their energy expenses or not. To do so, the tool requires information about the user’s hourly electricity consumption, contracted power, maximum demanded power over the last year, current electricity supplier and tariff, as well as socioeconomic data. The user’s hourly electricity consumption data are downloaded as CSV files from their personal page at the distributor’s website [52]. To create an account, the only requirements are being the electricity contract holder and having an official identification to validate their identity. The validation process takes over one day, so data are not immediately available. Aside from the hourly consumption data, the website indicates the name of the company supplying electricity to the user, their current tariff and contracted power. It also permits the visualization of the maximum demanded power registered each month since the electricity contract started. The detailed monitoring survey is used to gather the users’ socioeconomic data linked to social bonus granting. The annual electricity expenses are calculated considering avail- able tariffs from the regulated and liberalized markets. To calculate the annual electricity expenses for the three tariff schemes available in the regulated market, the hourly ac- tive energy price for each PVPC tariff (PVPCEPh , in EUR/kWh) is downloaded from the database of the Spanish Transmission System Operator (TSO), “Red Eléctrica Española” (REE) through their Advance Programming Interface (API) service [53]. The obtained values are multiplied by the corresponding hourly electricity consumption (ECh , in kWh) as shown in the following equation, to get the total energy cost (TEC, in EUR): TEC = ∑ PVPCEPh · ECh (2) h The cost of the PVPCEP is formed by the transmission and distribution costs—Fixed per each pricing period—and the electricity production costs that vary every hour. Both concepts include other series of costs as explained in the Royal Decree 216/2014 [54]. Nonetheless, all of them are already considered in the PVPCEP value given by REE service. The total power cost [TPC] is obtained by multiplying the user’s contracted power (UCP, in kW) per the sum of the annual contracted power cost (ACPC), set at 38.043426 EUR/kW/year by the Order IET/107/2014 [55], plus an annual commercializa- tion margin (ACM) of 4 EUR/kW/year [56]: TPC = UCP · ACPC · ACM (3) Sustainability 2021, 13, 9671 11 of 28 The 5.1127% tax on electricity usage (EUT) is calculated upon the sum of the TEC and TPC values [56]. Afterward, the rental price of the smart meter (SMRP) is added, considering a monthly cost of 0.84 EUR/month as stated by the Spanish Ministry of Energy, Tourism and Digital Agenda. Finally, the total annual electricity bill [TAEB] is obtained by calculating the value-added tax (VAT)—21%—Upon the resulting amount [56] as shown in Equation (3). TAEB = VAT · [ EUT · ( TEC + TPC ) + SMRP] (4) For unregulated tariffs, it is not possible to obtain the same degree of accuracy because there are multiple options available and their costs change with time. Thus, the price paid by one customer might not be the same as another even if they hired the same option from the same company depending on when the contract was signed. For this reason, a benchmarking analysis is conducted obtaining the prices offered by 11 private companies for the concept of energy consumption (equivalent to the PVPCEP) and contracted power (equivalent to the sum of ACPC and ACM). These were obtained from the companies’ websites throughout June 2020 and can be consulted in Appendix A. The rest of the concepts are handled similarly to the PVPC scheme. The resulting TAEB for each tariff—Regulated and non-regulated—Are compared by the tool, selecting the one that offers the minimum value. Additionally, the tool analyzes the user’s responses to the detailed monitoring survey to establish the annual income threshold and the level of vulnerability applicable following the guidelines stated in the Royal Decree 897/2017 [43]. If the users’ reported annual income is below the established threshold, the tool calculates the estimated annual savings they can achieve if the social bonus is applied, considering the discount percentage applicable for each case. When a user indicates to be a social bonus beneficiary, the tool applies the discount directly over the TAEB values. In all cases, the discount is applied only to the regulated market options. The monitoring tool also compares the reported contracted power against the max- imum demanded power. If the latter value is lower than the contracted power, the tool suggests contracting a power equivalent to 1.05 times the maximum demanded power. When the maximum demanded power is higher, the tool does not suggest changing their contracted value as it is assumed that users are not willing to pay more for their electricity services and prefer to deal with minor adjustments in their energy usage. 4.4. Mutual Support Workshops The mutual support workshop is a group established by APE to tackle the emotional and mental health dimensions of EP. Not being able to keep the home at an adequate temperature, pay the bills or, at least, secure regular access to basic supplies, generates strong feelings of anxiety, impotence and guilt in families. Moreover, these families are forced to deal with these issues individually and often feel stigmatized and unsupported. The purpose of the mutual support workshop is to address those situations collectively and politically, with the main objective of alleviating the responsibility that families currently feel, based on the idea that accessing basic supplies is a right and should never depend on the ability to pay. The mutual support workshop is an empowerment tool focused on health issues, based on an exchange of experiences and worries. It is carried out in the form of the gathering of a reduced group of people, building trust and a secure environment and that allows establishing strong relationships between participants. The purpose of the group is to jointly deal with some of the main inequity axes that accompany the EP: material and economic situations, gender, age, functional diversity, and health, among others. Mutual support sessions are usually made up of a round on “How are we?” to open up into experiences that generate anxiety, pain, sadness, depression, anger that cannot be easily dealt with in the CAA. It follows a peer support dynamic through which participants have already experienced or felt the same situation/feeling and can empathize with others. That connection helps generate encouragement, support and positive reinforcement. Addi- tionally, at the moment where a situation of human rights violation is shared, recognition Sustainability 2021, 13, 9671 12 of 28 and visibility take place because the situation is given voice and value. At the same time, the sessions act as a tool to take care of the group members’ health. Self-organized care and monitoring mechanisms are established for group members that need it, or whatever roles need to be established to guarantee such support. 5. Results 5.1. Socioeconomic Characterization of the Participants People attending CAAs in Barcelona constitute a severely affected EP population as in- dicated by the responses of the 74 assembly participants collected through the CAA survey between January 2020 and May 2021. As shown in Table 3, 82% of survey respondents are registered in the social services system and 36% are at risk of housing exclusion as per the criteria of municipal social services. The latter means that they have an IRER (“Informe de Risc d’Exclusió Residencial”, in Catalan), a socioeconomic vulnerability certificate issued by social services that protect vulnerable households from utility supply disconnections and evictions in accordance with Catalan Law 24/2015 [47]. Most people live in rented properties (49% of the total) and almost one-third of the respondents inhabit irregularly occupied dwellings (35%). Such numbers suggest high levels of housing insecurity as these cases refer to families at risk of eviction and with other difficulties associated with their irregular housing circumstances, e.g., being denied an official utility supply contract. More than half of the respondents (54%) experienced poor thermal comfort conditions at home and all reported issues related to access or affordability of basic utility supplies (water, electricity, natural gas–and butane gas in a few cases as well). Most respondents acknowledge that they struggle with two (28%) or three (50%) of those supplies. Still, only a few of them have access to social bonuses to reduce their expenditures on water, electricity or gas (16%, 22% and 23%, respectively). Our analysis found a significant correlation between having the social bonus for electricity and the social bonus for water (r = 0.78, p < 0.01). Regarding gender, more women (64%) than men (35%) seek support through CAA, which speaks of gender inequalities in the incidence of severe EP and also of gender dif- ferences in the way men and women respond to precarious living conditions. In addition, 43% of the respondents that attended the assemblies have children at home, while other vulnerable groups such as persons with disabilities are present in 24% of the households. Based on the correlation analysis, no strong associations between gender and other vari- ables are found in the survey data, which might be due to the fact that all people answering the survey are affected by EP at some level. The gender factor, however, is present in the higher number of female respondents in comparison with their male counterparts. The most significant issues reported by CAA participants are indebtedness with utility providers, supply disconnections and irregular connections to the supply (often associated with living in an irregularly occupied dwelling). These problems are acknowledged by as many as 45% of survey respondents (for any of the three supplies) and they are more likely to appear in relation to electricity (35% of all cases) and water supply (27%)—See Table 4. It is observed that having an electricity supply contract is strongly positively correlated with having a water contract (r = 0.84, p < 0.01) whereas having a gas supply contract positively correlates to having a water contract (r = 0.52, p < 0.01), and an electricity contract (r (72) = 0.65, p < 0.01). This is not surprising as the water supply is usually the most important utility service that household secure as it covers its most basic needs. Therefore, families that have other regular utility services like electricity or natural gas usually have access to a regular water supply as well. On the contrary, not all people that have a water contract manage to regularize their access to the supply of gas or electricity, especially when they live in an irregularly occupied property. The resulting correlation coefficients show that there are significant negative associations between living in an irregularly occupied home and having a water supply contract (r = −0.51, p < 0.01), having an electricity supply contract (r = −0.67, p < 0.01), and having a gas supply contract (r = −0.59, p < 0.01). This is expected as people in this situation face more challenges to regularize access to utility Sustainability 2021, 13, 9671 13 of 28 services. Finally, a positive correlation is found between having electricity debts and having water debts (r = 0.52, p < 0.01), as well as, having electricity debts and gas debts (r = 0.59, p < 0.01). Table 3. Characteristics of participants in collective advisory assemblies (CAA survey, n = 74) in January 2020–May 2021. Characteristics n (N = 74) % of n Woman 47 64% Gender Man 26 35% Non-binary 1 1% Children in the household 32 43% People with disabilities in the household 18 24% Owned 6 8% Housing tenure Rented 36 49% Irregularly occupied 26 35% Other 6 8% Yes 61 82% Registered in social services No 9 12% Does not know 2 3% Yes 27 36% At risk of housing No 25 34% exclusion (IRER) Did not qualify 2 3% Does not know what 20 27% IRER is Water 12 16% Access to Social Bonus Electricity 16 22% Gas 17 23% Thermal comfort at Uncomfortable 40 54% home in winter Comfortable 28 38% Water 63 85% Electricity 56 76% Reports EP related issues with utility Gas 42 57% supplies Butane 3 4% One supply 14 19% Two 21 28% Three 37 50% Table 4. EP-related issues reported by participants in collective advisory assemblies (n = 74) in January 2020–May 2021. Percentage of Participants Water Electricity Natural Gas Irregular connection to the supply 11% 16% 4% Outstanding debt with provider 11% 18% 12% Had supply disconnection 8% 7% 1% Any of the above 27% 35% 16% Sustainability 2021, 13, 9671 14 of 28 EmpowerMed data also allow for comparison among EP and non-EP-affected people. Table 5 presents the results of the detailed monitoring survey of a subsample of 27 house- holds (14 assembly participants affected by EP vs. 13 voluntary households not affected by EP) that took part in the EmpowerMed monitoring campaign between September 2020 and June 2021. Results indicate significantly higher levels of wintertime thermal discomfort among those affected by EP (93% vs. 46%) but otherwise similar levels of summertime thermal discomfort (57% vs. 54%). More than half (64%) of the EP-affected households de- clare arrears on utility bills in the last 12 months whereas zero non-EP households face this situation. EP-affected also displays a range of well-known coping behaviors such as cutting on food, medication or clothing expenditures; reducing water consumption, limiting the usage of appliances and white goods or indoor heating and lighting. In contrast, practically all non-EP households declare that they do not need to resort to any of these adaptive mechanisms to ensure they can pay utility bills. All in all, these values reflect broader socioeconomic inequalities between EP and non-EP-affected households as evidenced by the fact that the equivalised monthly income of non-EP households (EUR 1816) is more than three times higher than the equivalised income of EP-affected (EUR 515). Note that these equivalisation factors from the OECD-modified equivalence assign a value of 1 to the household head, of 0.5 to each additional adult member and of 0.3 to each child. Table 5. Comparison of households affected (EP) and non-affected (non-EP) of a subsample of 27 households that take part in the EmpowerMed monitoring campaign. EP Non-EP EUR EUR Monthly income (EUR/equivalent person) 515 1816 Cannot keep home adequately warm in winter 93% 46% Cannot keep home adequately warm in summer 57% 54% Arrears on utility bills 64% 0% To make sure you could pay utility bills, have you had to . . . ? cut on food expenditure 43% 0% reduce hot water consumption 29% 0% reduce water consumption 36% 0% cut on heating 64% 8% reduce natural gas consumption 43% 0% cut on indoor lighting 64% 0% reduce expenditure on medication or clothing 57% 0% shorten house ventilation time 21% 0% reduce the usage of appliances or white goods 43% 0% none of the above 21% 92% Participation in Collective Advisory Assemblies Yes, more than 3 sessions 64% 31% Yes, less than 3 session 36% 8% No, never - 62% 5.2. Indoor Environmental Comfort Evaluation Based on the data collected in the detailed monitoring survey (n = 27, 14 EP-affected and 13 non-affected), 74% of the households live in buildings constructed without any or with poor energy efficiency criteria (before 1979), including both EP and non-EP households. Additionally, 75% of the respondents report inadequate housing conditions, such as mold and dampness (48%), water leaks (11%), cracks in walls (26%) or air leakage in windows 5.2. Indoor Environmental Comfort Evaluation Based on the data collected in the detailed monitoring survey (n = 27, 14 EP-affected and 13 non-affected), 74% of the households live in buildings constructed without any or with poor energy efficiency criteria (before 1979), including both EP and non-EP house- Sustainability 2021, 13, 9671 holds. Additionally, 75% of the respondents report inadequate housing conditions, such 15 of 28 as mold and dampness (48%), water leaks (11%), cracks in walls (26%) or air leakage in windows and doors (63%). Figure 4 indicates that butane heaters (36%) and electric radi- ators (29%) are the most common heating systems in EP-affected households, and that and doors electric (63%).(54%) radiators Figure 4 indicates and thatboilers natural gas butane (38%) heatersdominate (36%) and inelectric non-EPradiators (29%) households. are the most non-EP Additionally, commonhouseholds heating systems tend toinhave EP-affected households, more than andsystem one heating that electric (30% radiators of non- EP(54%) and natural households), gas boilers (38%) in comparison dominate with the in non-EP(one EP households households. household, Additionally, non-EP 7%). In summer, most households do not use any mechanical cooling system (50% in EP-affected house-in households tend to have more than one heating system (30% of non-EP households), comparison holds, and 38% with the EP households in non-EP), 21% and 31% (oneuse household, fans and 7%). 29% andIn summer, 31% air most households conditioning in do not some userooms of the any mechanical cooling for at their household, system (50% EP and in EP-affected non-EP households, households, andIn38% respectively. bothin non-EP), seasons 21% and and 31% groups, theuse fans and heating and29% and systems cooling 31% air conditioning are used only in when some ofit the rooms at is cold/hot their household, for EP and non-EP households, respectively. In both and mainly in some rooms. Additionally, almost all households use natural ventilationseasons and groups, in the heating and cooling systems are used only when it is cold/hot and mainly winter for cleaning the air (1.3 h/day on average), and in summer for refreshing the house- in some rooms. hold (more Additionally, than 5 h/day). almost all households use natural ventilation in winter for cleaning the air (1.3 h/day on average), and in summer for refreshing the household (more than 5 h/day). Figure Figure 4.4. Heating Heating (left) (left) and and cooling cooling (right) (right) systemsused systems usedininEPEPand andnon-EP non-EPhouseholds. households. After describing the main features of the households and their heating and cool- After describing the main features of the households and their heating and cooling ing systems, indoor environmental comfort is evaluated using the participants’ personal systems, indoor environmental comfort is evaluated using the participants’ personal per- perception and the monitored data. Figure 5 shows the indoor environmental comfort ception and the monitored data. Figure 5 shows the indoor environmental comfort per- perceptions of EP and non-EP respondents, with 10 representing the best comfort percep- ceptions of EP and non-EP respondents, with 10 representing the best comfort perception tion and 1 the worst. In general, non-EP households have higher satisfaction with the and 1 the worst. In general, non-EP households have higher satisfaction with the indoor indoor environmental comfort (air quality, thermal, visual and acoustic comfort) of their environmental comfort (air quality, thermal, visual and acoustic comfort) of their homes homes with an average of 8, in comparison with the average value of 5.4 for EP households. with an average of 8, in comparison with the average value of 5.4 for EP households. In In terms of thermal comfort, the satisfaction is low in both groups, and worst for the EP terms of thermal persons, comfort, especially the satisfaction in winter. is lowexpresses The EP-affected in both groups, and dissatisfaction an average worst for the EPof per- 3.6 in sons, especially in winter. The EP-affected expresses an average dissatisfaction winter and 5.3 in summer, while non-EP results in 5.7 and 6.3, respectively. In relation of 3.6 into winter visualand 5.3 infor comfort, summer, whileand daylighting non-EP results artificial in 5.7 comfort lighting, and 6.3, perception respectively. In relation is around 7 into EP visual comfort, for daylighting and households, and around 8 for non-EP. artificial lighting, comfort perception is around 7 in EP households, Figures 6 and and around 8 for 7 analyze thenon-EP. operative temperature of the living room from EP (left) and non-EP (right) households. In Figure 6, the operative temperature of each household is represented together with the mean outdoor temperature (grey dots), showing when the indoor conditions provide comfort to the users based on the adaptive model categories presented in Table 2. Additionally, the average operative temperature of the monitored period is represented (purple and yellow dots). It is possible to observe that, most of the time, EP and non-EP-affected are at least in Category III (IEQIII ). However, two EP households (those at the bottom of Figure 6-left) were monitored during an extreme weather conditions period (Filomena Storm, 8–10 January 2021) and most of their monitored operative temperature data are outside category III (IEQIII ), providing an average operative temperature around 15 ◦ C. Sustainability 2021, 13, x FOR PEER REVIEW 16 of 28 Sustainability 2021, 13, 9671 16 of 28 Figure 5. Indoor environmental comfort perception of EP (left) and non-EP (right) affected persons, being 1 discomfort and 10 comfort. Grey dots represent the answers of each person, and purple/yellow dots are the average value of EP and non-EP, respectively. Figures 6 and 7 analyze the operative temperature of the living room from EP (left) and non-EP (right) households. In Figure 6, the operative temperature of each household is represented together with the mean outdoor temperature (grey dots), showing when the indoor conditions provide comfort to the users based on the adaptive model categories presented in Table 2. Additionally, the average operative temperature of the monitored period is represented (purple and yellow dots). It is possible to observe that, most of the time, EP and non-EP-affected are at least in Category III (IEQIII). However, two EP house- holds (those at the bottom of Figure 6-left) were monitored during an extreme weather conditions period (Filomena Storm, 8–10 January 2021) and most of their monitored op- erative Figure 5. Indoor environmental temperature comfort data perception of are outside EP (left) and category III (IEQ non-EP (right) III), providing an average operative affected persons, being 1 discomfort Figure 5. comfort. and 10 temperature Indoor environmental comfort Grey dots represent aroundof15 theperception answers °C.(left) ofeach EP person,and non-EP and (right) affected purple/yellow dots arepersons, beingvalue the average 1 discomfort of EP and and 10 comfort. Grey dots represent the answers of each person, and purple/yellow dots are the average value of EP and non-EP, respectively. non-EP, respectively. Figures 6 and 7 analyze the operative temperature of the living room from EP (left) and non-EP (right) households. In Figure 6, the operative temperature of each household is represented together with the mean outdoor temperature (grey dots), showing when the indoor conditions provide comfort to the users based on the adaptive model categories presented in Table 2. Additionally, the average operative temperature of the monitored period is represented (purple and yellow dots). It is possible to observe that, most of the Sustainability 2021, 13, x FOR PEERtime, EP and non-EP-affected are at least in Category III (IEQIII). However, two EP house- REVIEW 17 of 28 holds (those at the bottom of Figure 6-left) were monitored during an extreme weather conditions period (Filomena Storm, 8–10 January 2021) and most of their monitored op- erative temperature monitored dataoperative time with are outside category IIIin temperatures (IEQ III), providing an average operative Category IV (IEQIV), which is only ac- temperature around 15 °C. ceptable for very short periods of time. Comparing the monitored temperature of the liv- ing room and the bedroom, there is a difference between both (0.5–2 °C), with living room Figure 6. Figure Indooroperative 6. Indoor operativetemperature temperature of of EP (left) (left) and and non-EP non-EP (right) (right) households as as aa function function of of running running mean mean outdoor outdoor temperaturesEP being higher for most of households the households. temperature. Thermal temperature. Thermal comfort comfort categories categories (IEQ) (IEQ) based based onon adaptive adaptive model. model. Figure 7 represents the percentage of time when the operative temperature is inside each comfort category, confirming that there are not many differences between both groups of households. Around 3–5 households of each group spend more than 20% of the Figure 7. Percentage Figure 7. Percentage of of time time in in each each thermal thermal comfort comfort category category based based on on an an adaptive adaptive model model for for each each EP EP (left) (left) and and non-EP non-EP (right) (right) households. households. Monitored Monitored households households are are srted srted by by mean mean outdoor outdoor temperature, temperature, represented represented by by a a holed holed dot dot (right (right axes). axes). Figure 6. Indoor operative temperature of EP (left) and non-EP (right) households as a function of running mean outdoor temperature. Thermal comfort categories (IEQ) based on adaptive model. Figure 7 represents the percentage of time when the operative temperature is inside Figure 8 represents the air quality of the monitored households, EP and non-EP (left each comfort category, confirming that there are not many differences between both groups andFigure right,7respectively). represents theThe air quality percentage of is evaluated time when thethrough the temperature operative CO2 concentration and is inside of households. Around 3–5 households of each group spend more than 20% of the moni- the comfort each percentage of time confirming category, when households are inare that there each notairmany quality category. There differences are both between signif- tored time with operative temperatures in Category IV (IEQIV ), which is only acceptable for icant differences groups between of households. both Around groups, 3–5 with the households EP-affected of each households group spend reporting more than 20% ofpoorer the very short periods of time. Comparing the monitored temperature of the living room and air quality: nine EP households spend more than 20%◦ of the time in Category III (IEQIII) the bedroom, there is a difference between both (0.5–2 C), with living room temperatures or worse, in comparison with only five non-EP households. One possible reason could be being higher for most of the households. that around 86% of the EP-affected households are occupied almost the entire day, in com- parison with just 46% of non-EP households with this dwelling usage regime. Addition- ally, a clear relationship can be observed between heating systems and air quality: house- holds using butane heaters that were monitored in cold periods present very low air qual- ity, being around 60–80% of the time in IEQIII or worse (households A05, A07 and A08). Figure 7.2021, Sustainability Percentage 13, 9671 of time in each thermal comfort category based on an adaptive model for each EP (left) and non-EP17 of 28 (right) households. Monitored households are srted by mean outdoor temperature, represented by a holed dot (right axes). Figure 8 represents the air quality of the monitored households, EP and non-EP (left Figure and right, 8 represents respectively). Thetheairair quality quality of the monitored is evaluated throughhouseholds, EP and non-EP the CO2 concentration and (left the and right,ofrespectively). percentage The air quality time when households are iniseach evaluated through air quality the CO category. 2 concentration There are signif- anddifferences icant the percentage of time between bothwhen households groups, with the are in each air EP-affected quality category. households reportingThere are poorer significant differences between both groups, with the EP-affected air quality: nine EP households spend more than 20% of the time in Category III (IEQIII) households reporting orpoorer worse,air in quality: comparison ninewith EP households only five non-EPspendhouseholds. more than 20% Oneof the time possible in Category reason could beIII (IEQ that III ) or worse, around 86% of thein comparison EP-affected with only five households arenon-EP occupied households. almost theOne possible entire day, in reason com- could be parison that with around just 46% of86% of the non-EP EP-affected households households with this dwellingare occupied almostAddition- usage regime. the entire day,a in ally, comparison clear relationship with just can be46% of non-EP observed households between heating with thisand systems dwelling usagehouse- air quality: regime. Additionally, a clear relationship can be observed between heating systems holds using butane heaters that were monitored in cold periods present very low air qual- and air quality: households ity, being around using butaneofheaters 60–80% the time that in were IEQIIImonitored in cold periods or worse (households A05,present A07 and very low A08). air quality, being around 60–80% of The remaining households with butane heaters (A09,the time in IEQ or worse (households A05, A07 IIIA14, N07, N12, N13) do not reflect and A08). the same The remaining behaviour households probably due towith butane warmer heaters weather (A09, A14, conditions of N07, N12, N13)period the monitored do not reflect that the same require behaviour less use probably due to warmer weather conditions of the monitored of heating. period that require less use of heating. Percentageofoftime Figure8.8.Percentage Figure timeinineach eachair airquality qualitycategory categorybased basedononCO CO 2 concentration 2 concentration forfor each each EPEP (left) (left) and and non-EP non-EP (right) (right) household. Monitored households are sorted by mean outdoor temperature, represented by a holed dot household. Monitored households are sorted by mean outdoor temperature, represented by a holed dot (right axes). (right axes). 5.3.Electricity 5.3. ElectricityConsumption Consumptionand andCost Cost Forthe For theassessment assessmentofofthe theelectricity electricityconsumption consumptionmonitoring monitoringcampaign, campaign,1919outoutofofthe the 27 households participating in the monitoring 27 households participating in the monitoring campaign are campaign are evaluated using the electricity the electric- itymonitoring monitoring tool. Eight tool. are Eight areexcluded excluded from from this thispart of of part thethe study studydue to to due thethe lack of of lack sufficient suffi- datadata cient caused caused by by smart-meter smart-meter malfunction, malfunction,shorter shortercontract contract validity periodor validity period orirregular irregular electricitysupply electricity supply access access conditions. conditions. FromFrom thethe 19 evaluated 19 evaluated households, households, 10 participate 10 participate in in CAAs and are affected by EP, while the remaining 9 are non-EP-affected CAAs and are affected by EP, while the remaining 9 are non-EP-affected households households whose data are collected with the purpose of comparing their consumption and electricity expenses against EP-affected users. Relevant characteristics of the electricity contract held by each household are pre- sented in Table 6. Most EP-affected households have a regulated tariff contract as this is a requirement to access the social bonus discount, a form of support from which 70% of the evaluated nine EP households already benefit. According to the survey responses, 80% of the monitored EP group have also already applied and obtained the IRER. The detailed monitoring survey responses show that EP users with regulated tariff contracts and social bonuses had attended at least three CAAs, whereas those new to the APE are more likely to have an unregulated supply company contract and none of them had the social bonus by the time they first come to a CAA. Notably, none of the non-EP households have a regulated tariff contract even considering it is usually cheaper [57], but otherwise, they have ToU tariffs in a slightly higher percentage than EP users. monitoring survey responses show that EP users with regulated tariff contracts and social bonuses had attended at least three CAAs, whereas those new to the APE are more likely to have an unregulated supply company contract and none of them had the social bonus by the time they first come to a CAA. Notably, none of the non-EP households have a Sustainability 2021, 13, 9671 regulated tariff contract even considering it is usually cheaper [57], but otherwise, 18 of 28 they have ToU tariffs in a slightly higher percentage than EP users. Table 6. Characteristics of the electricity contract held by EP and non-EP households. Table 6. Characteristics of the electricity contract held by EP and non-EP households. Metric EP Non-EP Metricwith a regulated utility company EP Percentage of households [%] Non-EP 90.0% 0% Percentage of households Percentagewith of ahouseholds regulated utility withcompany [%][%] ToU tariff 90.0% 60.0%0% 66.7% Percentage Percentageof of households withToU households with thetariff social[%]bonus discount 60.0% [%] 70.0% 66.7% 0% Average contracted power [kW] Percentage of households with the social bonus discount [%] 70.0% 3.19 0% 4.17 Average contracted power [kW] 3.19 4.17 Regarding the analysis of the households’ annual electricity consumption, Figure 9- left, shows some differences between EP and non-EP households. First, the average an- Regarding the analysis nual consumption of the in per household households’ the EP groupannual electricity isconsumption, (2451 kWh/year) 3% lower than the Figurevalue 9-left, shows some differences between EP and non-EP reported for the non-EP group (2535 kWh/year). When households. First, calculating the the an- average average annual nual consumption consumption per household per equivalent in the person theEP group (2451 differences kWh/year) between both is 3% lower groups rise up to than the value reported for the non-EP group (2535 kWh/year). When calculating 8%, but remain lower for the EP group (1443 kWh/year) as compared to the non-EP the (1575 average annual consumption per equivalent person the differences between both groups kWh/year). It should be noted that for both indicators there is a higher variation among rise up to 8%, but remain lower for the EP group (1443 kWh/year) as compared to the the EP group’s values. The higher electricity consumption values in both subsamples cor- non-EP (1575 kWh/year). It should be noted that for both indicators there is a higher respond to 3–5-member families. This households’ values get closer to the group’s median variation among the EP group’s values. The higher electricity consumption values in both when looking at the equivalent-person metric. Figure 9-right represents the distribution subsamples correspond to 3–5-member families. This households’ values get closer to the of contracted power for each household, showing significant differences among EP and group’s median when looking at the equivalent-person metric. Figure 9-right represents non-EP. The EP households have on average a contracted power of 3.2 kW, while non-EP the distribution of contracted power for each household, showing significant differences households tend to have higher contracted power, with an average of 4.2 kW. among EP and non-EP. The EP households have on average a contracted power of 3.2 kW, while non-EP households tend to have higher contracted power, with an average of 4.2 kW. Figure 9. Box plots showing the annual consumptions per household and equivalent person (left) and contracted power (right) Figure 9. Box for EP and plots households. non-EP showing theDescription annual consumptions per household of the box plot parameters:and equivalent mean person by square; (left) median by and contracted horizontal line;power (right) for EP and non-EP households. Description of the box plot parameters: mean by square; median by horizontal line; 25–75% percentile by box; 10% and 90% by whiskers; 1% and 99% percentile by cross; minimum and maximum by dash. 25–75% percentile by box; 10% and 90% by whiskers; 1% and 99% percentile by cross; minimum and maximum by dash. A significant difference between groups can be observed when analyzing electricity consumption by season. Figure 10 represents the monthly electricity consumption per equivalent person of each household (grey lines) and the average for EP and non-EP households (purple and yellow dotted lines, respectively). In general terms, the average electricity consumption for the EP curve is flatter than for non-affected households, and indicates similar monthly values in winter than in summer. On the other hand, the values of non-EP households reveal an important variation of consumption between winter and summer, being higher in winter and lower between May and November. As it happens with annual values, households in the EP group show higher diversity among individual consumption patterns than in the non-EP group. households (purple and yellow dotted lines, respectively). In general terms, the average of non-EP households electricity consumption reveal an EP for the important curve isvariation of consumption flatter than between for non-affected winter and households, and summer, indicates similar monthly values in winter than in summer. On the other hand,itthe being higher in winter and lower between May and November. As happens values with annual of non-EP values, households households reveal an in the EP group important showofhigher variation diversitybetween consumption among winter individual and consumption patterns than in the non-EP group. summer, being higher in winter and lower between May and November. As it happens Sustainability 2021, 13, 9671 19 of 28 with annual values, households in the EP group show higher diversity among individual consumption patterns than in the non-EP group. Figure 10. Monthly electricity consumption per equivalent person for EP and non-EP households. To better understand the seasonal impact on the consumption habits, the households. hourly elec- Figure 10. Monthly Figure 10. Monthly electricity electricity consumption consumption per per equivalent equivalent person person for for EP EP and and non-EP non-EP households. tricity consumption per equivalent person for two average days representing summer and winter Toseasons better understand are calculated. the seasonal impact To this end, the on the consumption monitored consumption habits, theregistered data hourly elec- in To better understand the seasonal impact on the consumption habits, the hourly elec- tricity the consumption months of January per(winter) equivalent and person July for two average (summer) are days used, as representing Figure 11 summer shows. The and av- tricity consumption per equivalent person for two average days representing summer and winterwinter erage seasons day are calculated. reveals large To To this end,between differences the monitored consumption non-EPconsumption and EP households, data registered having in a winter seasons are calculated. this end, the monitored data registered in the months similar shape of January but with a (winter) lower and July (summer) magnitude. The non-EPare used, householdsas Figure have 11ashows. more The pro- the months of January (winter) and July (summer) are used, as Figure 11 shows. The av- average winter nounced peakday indaythe reveals morning large differences between non-EPtheirandworking EP households, having erage winter reveals largeand in the evening, differences between reflecting non-EP and time schedule. EP households, having a a In similar shape both groups, but with the with maximum a lower magnitude. consumption The non-EP households have a more pro- similar shape but a lower magnitude.is The registered non-EP at households 22 h, with a value have aofmore 0.42 kWhpro- nounced for non-EP peak in the households morning and 0.31and in kWh the evening, forevening, reflecting EP-affected. their Night-hoursworking time consumption schedule. is veryIn nounced peak in the morning and in the reflecting their working time schedule. both similargroups, the maximum consumption is registered at 22 h, with a value of 0.42 kWh for In both in non-EP both groups. groups, households the and Looking maximum 0.31 kWh at the entireis groups’ consumption for EP-affected. registered average h,consumption at 22consumption Night-hours with a value in of July, is very 0.42 it is kWh similar observed forboth non-EP that non-EP-affected households and consumption 0.31 kWhgroups’ remains for EP-affected. mostly flat during Night-hours in the day, consumption while EP- is very in affected groups. households Looking show at the entire a consumption average peak groups’ around 10 consumption h, 16 hconsumptionJuly, it is observed and after 21 h.inHowever, similar that in both groups. non-EP-affected Looking consumption atremains the entire mostly flat average during the day, while July, it is EP-affected as a difference observed that of the winter non-EP-affected day, the consumptionvariation remainsbetween mostly EP and flat non-EP during the households day, while EP-is households show a consumption peak around 10 h, 16 h and after 21 h. However, as smaller. a affected households difference of the winter show day, a consumption peak around the variation between EP and10 h, 16 h and non-EP after 21 h.isHowever, households smaller. as a difference of the winter day, the variation between EP and non-EP households is smaller. Figure 11. Hourly energy consumption per equivalent person for an average day in winter (left) and summer (right) seasons based on monitored data by EP and non-EP household for the months of January and July, respectively. Regarding electricity expenses, Table 7 summarizes the obtained results through the electricity monitoring tool, and is not based on actual electricity bills. Electricity expenses from the non-EP households are found to be 26% higher than for EP households, and 63% if the social bonus is taken into consideration (only applied if a user meets the previously mentioned requirements). This is due to the more expensive contracts and higher contracted power in an average non-EP-affected group as compared to EP-affected households. In general terms, it is observed that affected households prefer regulated tariff contracts as they are less costly per kWh and give them access to the social bonus. In comparison, non-affected users value other aspects such as the possibility to consume Sustainability 2021, 13, 9671 20 of 28 electricity from renewable energies, that are offered by non-regulated companies (reported by 55% of non-EP households). Table 7. Comparison of electricity expenses metrics between EP and non-EP households. Electricity Expenses Metrics 1 EP Non-EP Average household electricity expenses without social bonus [EUR/yr] 413.0 521.7 Average household electricity expenses considering social bonus [EUR/yr] 2 320.7 521.7 Average percentage of electricity bill corresponding to contracted power [%] 52% 57% Average cost reduction per household implementing changes suggested [EUR/yr] 42.0 126.2 N◦ of users recommended to change to a regulated contract 1 9 N◦ of users recommended to change from a flat to a ToU regulated tariff 4 9 N◦ of users recommended to lower their contracted power 1 0 1Calculated using the electricity monitoring tool described in Section 4.3.2 and not based on actual electricity bills. 2 The social bonus discount is applied only if a user meets the previously mentioned requirements. The monitoring campaign indicates that there are opportunities to reduce electricity expenses in both groups; however, on average, the cost-saving potential is higher for the non-EP group (24% vs. 12% savings) as they tend to have costlier contracting conditions. The most common suggestion is changing from a free-market contract to a regulated tariff contract as the latter is the cheapest option for all analyzed users. As all non-affected households have unregulated contracts, the EmpoweMed tool suggests this option for more users in this category than in the EP, as only one household in it has this type of contract. In all cases, the recommendation also includes contracting a regulated ToU tariff. Regarding contracted power, only one of the households in the EP-affected group has a contracted value above their needs and, therefore, an opportunity to save money by lowering it. On average, the cost associated with the contracted power represents a larger share of the electricity bill for non-EP consumers as they tend to contract higher power values at a costlier rate. It might be possible for some users to reduce their contracted power by implementing some changes in their consumption habits, but this analysis is not part of the study. Another result of the analysis is that the flat regulated tariff (2.0 DA) is not found to be optimal for any of the evaluated households. For this reason, the EmpowerMed tool recommends users with a flat regulated tariff changing to a ToU alternative—Until the change in legislation occurred in June 2021 (see Section 2). In general, the ToU tariff has lower prices at night (valley period) and higher prices during day-time (peak period), as represented in Figure 12-right. Moreover, the numbers obtained show in Figure 12-left that all households (no matter if they are affected or not) have a relatively balanced con- sumption with none of them having more than 57% of the consumption in a given period (peak or valley). Sustainability 2021, 13, x FOR PEER REVIEW 21 of 28 Sustainability 2021, 13, 9671 that all households (no matter if they are affected or not) have a relatively balanced 21 con- of 28 sumption with none of them having more than 57% of the consumption in a given period (peak or valley). Figure 12. Distribution of annual consumption for each ToU tariff period (valley and peak) before the change legislation Figure 12. Distribution of annual consumption for each ToU tariff period (valley and peak) before the change legislation in in June June 2021. 2021. Left: The bar Left: The bar graph graph shows shows the the average average values values per per EP EP and and non-EP non-EP households households and and the the dots dots each each household. household. Right: ToU Right: ToU tariff tariff periods periods definition definition in in winter winter and and summer. summer. 5.4. APE’s Achievements through CAAs: Results of the CAA Monitoring Tool Tool The EmpowerMed CAA monitoring tool reports 789 participants participants and and 308 308 cases cases pre- sented during 34 CAA held between October 2019 and May October 2019 and May 2021: 2021: an average of 23 persons and 99 cases cases per perassembly. assembly.Women Womenare area amajority majorityininterms terms ofof CAA’s CAA’s participation participation (58% (58% of of attendees attendees and and 61% 61% ofof cases).They cases). Theyalso alsoreport reportmore moreoften oftenthan than men men being the contract contract holder of the energy supply service (67%) and be facing health health impacts impacts (74%). (74%). The overall The overallexpected expectedsavings savingsobtained obtained through throughthe the participation in CAAs participation is estimated in CAAs is esti- at EUR 17,472, about EUR 514 per assembly. Most of these savings mated at EUR 17,472, about EUR 514 per assembly. Most of these savings (EUR 12,037)(EUR 12,037) come from debt waives with four cases representing 49.7% of the total savings obtained come from debt waives with four cases representing 49.7% of the total savings obtained through this action (one of these cases sums EUR 4200 while the rest represents between through this action (one of these cases sums EUR 4200 while the rest represents between EUR 2000 and EUR 1000 EUR 2000 each). and EUR Around 1000EUR each).2500 in savings Around EURwere 2500 achieved in savings bywere informing achievedandbyempowering informing CAA participants to apply available support mechanisms, primarily and empowering CAA participants to apply available support mechanisms, primarily the social bonus. the Advice social bonus. Advice for the reduction in the contracted power and change from a flattariff for the reduction in the contracted power and change from a flat rate to a ToU rate (48 to a cases) is estimated ToU tariff (48 cases)toisresult in economic estimated to result savings in economicof about EUR savings of 1000. about The EURrest 1000.of The the savings come from supply regularization (51 cases, from which 36 were rest of the savings come from supply regularization (51 cases, from which 36 were led by led by women) or claims for maintenance refunds and not because of active energy saving women) or claims for maintenance refunds and not because of active energy saving sug- suggestions. gestions. 6. Discussion Activities carried out by APE in Barcelona, and in particular, CAAs and the monitoring 6. Discussion campaign performed in the framework of the EmpowerMed project were analyzed in Activities carried out by APE in Barcelona, and in particular, CAAs and the monitor- the present work. They allow a detailed characterization of EP-affected persons that participated inperformed ing campaign in theand these activities framework of the EmpowerMed provide evidence of CAAs andproject wereconsumption electricity analyzed in the present work. They allow a detailed characterization of EP-affected and indoor environmental comfort monitoring as support tools to tackle energy poverty. persons that par- ticipated in these activities and provide evidence of CAAs and electricity Data collected through the CAA survey (n = 74) indicate that people attending CAAs consumption and constitute aenvironmental indoor comfort population severely monitoring affected by EP:as they support tools show to tackle higher energy levels poverty. of housing in- Data collected through the CAA survey (n = 74) indicate that people security (49% rented and 35% irregularly occupied dwellings), precarious material attending CAAs liv- constitute a population ing conditions severely (75% of the people affected reportsbyinadequate EP: they show higher housing levels of at conditions housing home,inse- e.g., curity (49% rented and 35% irregularly occupied dwellings), precarious mold, humidity, leaky windows, etc.), low incomes (average monthly income around material living conditions (75% of theperson), 500 EUR/equivalent people reports inadequate high levels housing of thermal conditions discomfort (93%atarehome, e.g., unable tomold, keep humidity, their homeleaky windows, adequately warm etc.), low incomes in winter) and of (average arrears onmonthly income utility bills around (64%). Around500 EUR/equivalent 60% of participants person), high levels are women, of thermal 43% have discomfort children at home,(93% are unable and persons with todisabilities keep their are present in 24% of the households. Comparing those characteristics with the sample data from non-EP-affected persons, the insecurity of their living conditions becomes more evident: the average equivalised income of an EP household is 3 times lower than for a non-EP household. Consequently, EP-affected persons have the need to reduce their Sustainability 2021, 13, 9671 22 of 28 expenditure in a variety of basic services and essential goods to pay for utility bills, very much unlike non-EP households. Previous work by Yoon and Saurí [58] also based on collected data from APE’s participants during 2015–2016 shows similar patterns about socioeconomic characteristics of the EP participants. In this earlier study, most participants in APE CAAs were persons at risk of social exclusion. There was a high concentration of female participants (61%) and single-parent households, which on average have larger families (3.1 members) compared to the Catalan average of 2.1 members per household. Furthermore, 64% lived on monthly household incomes of less than EUR 750, and 36% lived on less than EUR 450. Single-parent (mother) families were especially vulnerable, as 21% of them did not have any income. Similar patterns were observed in other Spanish cities like Madrid, where Sanchez-Guevara et al. [17] observed that the income of single- person households with women over 65 tends to be significantly lower than the income in single-person households of men over 65. Additionally, women tend to be responsible for caregiving tasks and have higher rates of unemployment or part-time jobs, meaning they spend more hours at home, and are therefore exposed for longer times to inadequate temperatures when the household experiences EP conditions. Figures about indebtedness with utility providers, supply disconnections and irreg- ular connections to the supply presented in Table 4 are confirmed by a previous semi- quantitative assessment of domestic energy-related problems faced by CAA participants. Canals et al. [59] report significant difficulties related to the security and stability of basic utility services supply (45% of survey respondents). In this earlier work, a many as 25% of the 286 households mentioned in APE’s 78 “energy poverty chronicles” (i.e., short sum- maries of bimonthly CAA held by the APE in Barcelona) collected between November 2014 and March 2018 referred to utility-enforced electricity supply disconnections (versus 3% of natural gas and 13% of water). They also reported high rates of arrears or failed payments (23% for electricity, 8% for natural gas and 12% for water). These percentages, as well the figures reported in this paper, are well above incidence rates reported for these EP issues in Barcelona, Catalonia and Spain, which on average affect only a small fraction (below 5%) of the overall population [60]. The monitoring campaign carried out with the voluntary participation of 27 house- holds has also allowed comparing the EP and non-EP-affected households in terms of thermal comfort, indoor air quality, electricity consumption and costs. These results clearly illustrate the benefits of taking part in APE’s CAAs. The analysis of the monitored thermal comfort data for the 27 households suggests minor differences between EP and non-EP households. However, if wintertime thermal comfort perceptions are compared, a sig- nificant difference between groups emerge, as EP-affected persons report worse thermal conditions at home (an average of 3.6/10 thermal comfort perception, compared to 5.7/10 for non-EP persons; 93% of EP households cannot keep home adequately warm in winter, compared to 46% of non-EP households). The discrepancy between monitored temperature data and thermal comfort perception could be explained by considering that thermal com- fort depends both on physical parameters (environmental and architectural characteristics of the building) and the sociocultural characteristics of the person and household. In that case, the physical parameters are reasonably similar between groups (74% with low energy efficiency in buildings and 75% inadequate housing conditions for both) and thanks to the social bonus, EP-affected households are able to maintain the temperature of the household in at least Category III most of the time, similarly to non-EP households. Nevertheless, the main difference appears to be related to the group’s socioeconomic situation as EP-affected persons report high levels of dissatisfaction in relation to thermal comfort as well as very low incomes, arrears on utility bills, deprivation of basic services and essential goods, health conditions. This dissatisfaction could be related to a strong association between EP and the emotional burden of living in EP. Some examples of mechanisms and pathways through which EP affects emotional wellbeing may be constant worries about energy bills or about falling into debt and the absence of any solution or sense of control over the prob- lem [15]. Additionally, another aspect that could influence the thermal comfort perception Sustainability 2021, 13, 9671 23 of 28 is that 86% of EP-affected persons spend most of the day at home, in comparison with just 46% of non-EP households. On the contrary, the perception of thermal comfort in summer is quite similar between groups (6/10 on average for both) but then the monitored periods do not cover this season to make the comparison using sensor data. Regarding indoor air quality, EP-affected households present worse levels despite the adequate natural ventilation habits of the occupants. Two main reasons could cause that situation: 86% of the EP-affected households are occupied almost all day, and 36% use butane heaters. Further data would be needed to evaluate additional air quality indicators in those households where butane heaters are used, as CO2 concentration is a tracer of human occupancy and of indoor open fire combustion as well. In these cases it would be necessary to track the presence of other pollutants that can derive from the combustion of butane gas, such as CO or PM. A limitation of the indoor environmental comfort campaign is that all households are not monitored during the same period of time, complicating direct comparison. To partially solve this limitation, average outdoor temperatures were taken into account for the analysis, in order to relate monitored thermal comfort with weather conditions. Furthermore, there is only one household monitored in summer weather conditions, and the comparison between comfort perception and monitored data in the summertime cannot be made. The analysis of the electricity consumption based on data retrieved from the smart meters of 19 households that participated in the monitoring campaign also demonstrates small differences across EP and non-EP households. The EP-affected report consumption levels 8% lower than non-EP, when comparing the electricity consumption per equivalent person. Such a small difference between the two groups could be due to the social bonus discount on electricity bills, which 70% of EP households had at the time of the monitoring campaign and likely helps them maintain adequate electricity consumption levels. Focusing on the seasonal variation, the main difference is observed in the winter period, where the electricity consumption of EP-affected households is lower than non-affected; however, the trend is opposite in summer, manifesting smaller variations between groups. The wintertime behavior could respond to EP-affected households’ need to reduce their basic services expenditures for economic reasons, despite the access to social bonuses. As a comparison, the study of Gouveia et al. [12] in Portugal observed how similar energy subsidies (social tariff) were provided for EP households minimizing the high-energy costs, even if as a support mechanism it did not provide a sustainable long-term solution addressing the root causes of the thermal performance gap. While differences in electricity consumption are relatively small, the variation on estimated annual electricity costs is substantially higher: non-EP households pay around 18% more than EP households, and 46% if the social bonus is considered. Electricity is more expensive for non-EP households because of a combination of effects: only EP- affected households have regulated tariff contracts, with cheaper prices; the contracted power (which represents around 50–60% of the electricity bill) is lower in EP households; and, thanks to the social bonus, the EP group can reduce the electricity expenses by an average of 20%. Consequently, the electricity monitoring tool reported potential savings nearly 2 times higher (around 100 EUR/year) for non-affected households than for EP- affected households, meaning that EP-affected households participating in APE’s CAAs are definitely aware of the costs of electricity and apply most of the available strategies. The most common suggestion to reduce the electricity bill provided by the electricity monitoring tool is to change from a free market to a regulated tariff contract under a ToU tariff. A similar approach to the electricity monitoring tool was used by Antepara et al. [20] for an initiative addressing energy poverty in two municipalities in the Basque Country. The project also evaluated the electricity contracts of vulnerable customers, suggesting changes to minimize their costs based on their current contracting conditions and consumption profile, which is registered by the users’ smart-meter and accessed through the distribution system operator’s (DSO) website. The potential savings estimated by Antepara et al. are between 10% and 40% of the user’s annual electricity expenses. Sustainability 2021, 13, 9671 24 of 28 For the electricity monitoring campaign, two main limitations are identified. The first is that the sample of households was reduced from 27 to 19 due to several situations (lack of sufficient data caused by smart-meter malfunction, shorter contract validity period or irregular electricity supply access conditions) resulting in a smaller sample. Second, the annual consumption data collected for each household do not always cover the same period of time, meaning that weather conditions or the COVID-19 pandemic may have a different impact on the households’ electricity consumption patterns depending on the accessed period. Finally, these data show that CAAs do empower vulnerable customers, allowing them to reduce their electricity costs by selecting the most suitable tariffs and enabling them access to the social bonus. This effect is observed when comparing EP-affected households that have recently joined the CAA against those that have participated for several months. Data are from the CAA monitoring tool. Debt write-off was possible due to the agreement between the Catalan Government and dominant water and electricity companies in Catalonia, which were achieved in 2018 and 2021, respectively, in response to the advocacy campaign carried out by APE since 2015. 7. Conclusions The present work characterizes the EP population that attends to APE’s CAAs, a col- laborative empowering engagement tool based on a horizontal participatory methodology in which people affected by EP receive advice and support from an “assembly of peers”. Furthermore, the paper describes and analyzes the results of EmpowerMed interventions offered to CAA participants, consisting of an electricity and indoor environmental comfort monitoring campaign to optimize electricity supply contracts and provide recommenda- tions for comfort improvement. Finally, a comparison of a small sample of EP households with non-EP-affected households is provided. CAA participants represent a population severely affected by EP that experiences and report high levels of housing insecurity, precarious material living conditions, low incomes, high levels of thermal discomfort and arrears on utility bills. Around 60% of participants are women, 43% have children at home, and persons with disabilities are present in 24% of the households. These characteristics are found in previous studies of APE, which confirm that CAAs are a useful and necessary space to give support to the most vulnerable groups of the population. The environmental comfort analysis demonstrates that in general terms, EP-affected households report worst thermal comfort and indoor air quality conditions than non-EP households. However, some differences are highlighted. The thermal comfort indexes, obtained from the monitored data in winter do not reveal significant differences in indoor temperatures measured through sensors between groups; nevertheless, reported thermal comfort perception in the wintertime is considerably worse than in EP households than non-EP. This variation between monitored data and thermal comfort perception could be explained by the subjectivity behind thermal comfort and the strong association between EP and emotional wellbeing. In terms of indoor air quality, the worst conditions are found in EP households with butane heaters. Further monitoring campaigns would be needed to assess thermal comfort conditions in summer and monitoring additional pollutants to evaluate the impact of use butane heaters. In terms of electricity consumption, data retrieved from smart meters indicate a small difference between EP and non-EP households, with EP-affected households reporting just 8% less electricity usage per equivalent person. The difference is primarily explained by the social bonus discount on electricity bills and their empowerment through the participation of APE’s CAAs, which allows EP households to keep adequate electricity consumption levels. The analysis of electricity expenses also revealed that EP-affected households have lower electricity costs compared to non-EP households, demonstrating that EP-affected households participating in APE’s CAAs are definitely aware of the costs of electricity and capable to be in control and optimize their electricity supply contracts. In addition to Sustainability 2021, 13, 9671 25 of 28 the social bonus, the other two mechanisms through which EP-affected households have lower electricity bills than non-EP are having a regulated tariff contract and having a lower contracted power in their supply contract. In conclusion, the data collected by the EmpowerMed project in Barcelona demonstrate that CAAs as a community-based engagement methodology devised and put in practice by APE serve to empower and provide material support to persons severely affected by EP. They do so through the provision of information about their rights, of administrative and legal support, of specific recommendations about tariffs and utility contracts, by the accompaniment’ EP-affected households by activists and people dealing with similar EP issues, and also thanks to APE’s intense advocacy activity targeting utility companies and public authorities. Recently, APE has also identified the necessity to accompany EP-affected persons from a health point of view. To this aim, the mutual support workshops were launched with the objective of covering that emotional wellbeing dimension of EP. All in all, CAAs stand out as a powerful communitarian alternative for tackling energy poverty beyond the provision of individualized forms of support to vulnerable customers. Author Contributions: Conceptualization, J.O., M.J.M., S.T.-H., I.G.P., M.G.B. and L.C.C.; method- ology, J.O., M.J.M., S.T.-H. and L.C.C.; software, M.J.M. and L.C.C.; validation, M.J.M. and L.C.C.; formal analysis, J.O., M.J.M., A.A.-S., S.T.-H. and L.C.C.; investigation, J.O., M.J.M., A.A.-S., S.T.-H. and L.C.C.; writing—Original draft preparation, J.O., M.J.M., A.A.-S., S.T.-H. and L.C.C.; writing— Review and editing, J.O., M.J.M., S.T.-H. and L.C.C.; visualization, J.O. and M.J.M.; supervision, J.O.; project administration, J.O. All authors have read and agreed to the published version of the manuscript. Funding: The research conducted in this paper is part of the EmpowerMed project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 847052. All researchers from IREC have been partially supported by the Generalitat de Catalunya (2017 SGR 1219). Institutional Review Board Statement: Ethical review and approval were waived for this study due to no action on humans was done in the study. The study only collects information from subjects and treats it in anonymized way. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The data are not publicly available due to confidential reasons. Acknowledgments: The researchers of this project thank Aliança contra la Pobresa Energètica—APE for their collaboration, as well as the volunteers that participate in the monitoring campaign. Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Appendix A Table A1. Prices per kilowatt-hour during peak, valley and supervalley periods, and per kilowatt of contracted power used for the calculation of electricity costs in the liberalized market (June 2020). Peak Valley Super-Valley Contracted Power Company Tariff Name [EUR/kWh] [EUR/kWh] [EUR/kWh] [EUR/kW] Bassols Hogar 24 Horas 0.132690 - - 0.123069 EDP Luz Máximo Ahorro 0.127947 - - 0.116302 Electracomercial Centellas Tarifa 2 0.130568 - - 0.106023 Endesa One Luz 0.119893 - - 0.114323 Estabanell Energia Plan Premium 0.139755 - - 0.121649 Sustainability 2021, 13, 9671 26 of 28 Table A1. Cont. Peak Valley Super-Valley Contracted Power Company Tariff Name [EUR/kWh] [EUR/kWh] [EUR/kWh] [EUR/kW] Factor Energía Tarifa Fija 0.139406 - - 0.105676 Iberdrola Plan Estable 0.114656 - - 0.125000 Naturgy EcoEasy Luz 0.106000 - - 0.125000 Nexus Energía Luz Clásica 0.127000 - - 0.104200 PEUSA 24 h 0.152400 - - 0.132500 Som Energia 2.0 A SOM 0.139000 - - 0.103944 Bassols Hogar Noche 0.157284 0.07851 - 0.123069 EDP Fórmula Luz 0.154797 0.08631 - 0.116302 Electracomercial Centellas 2.0 DH 0.150366 0.072869 - 0.106023 Endesa One Luz Nocturna 0.158614 0.07942 - 0.114323 Estabanell Energia Plan Luz Día y Noche 0.164646 0.08811 - 0.121649 Iberdrola Plan Noche 0.134579 0.067519 - 0.125000 Nexus Energía Luz Clásica 2H 0.144000 0.07600 - 0.104200 PEUSA Nocturna 0.184800 0.08250 - 0.132500 Som Energia 2.0 DHA SOM 0.161000 0.08200 - 0.103944 Bassols Hogar Ahorro 0.155854 0.088473 0.070335 0.123069 Bassols Hogar Movilidad 0.155854 0.088473 0.068304 0.123069 Electracomercial Centellas 2.0 DHS 0.150802 0.075006 0.058982 0.106023 Endesa Tempo Verde Supervalle 0.154701 0.088909 0.076377 0.126181 Estabanell Energia Plan Vehículo Eléctrico 0.157067 0.091912 0.075394 0.121649 PEUSA Mobilitat 0.198700 0.116800 0.085500 0.132500 Som Energia 2.0 DHS SOM 0.160000 0.091000 0.073000 0.103944 References 1. 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