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Article

Factors That Contribute to Changes in Local or Municipal GHG Emissions: A Framework Derived from a Systematic Literature Review

Institute of Science and Innovation in Mechanical and Industrial Engineering (INEGI), Faculty of Engineering of the University of Porto (FEUP), Rua Dr. Roberto Frias, 400, 4200-465 Porto, Portugal
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Author to whom correspondence should be addressed.
Energies 2020, 13(12), 3205; https://doi.org/10.3390/en13123205
Submission received: 15 April 2020 / Revised: 15 June 2020 / Accepted: 16 June 2020 / Published: 19 June 2020
(This article belongs to the Special Issue Energy Saving at Cities)

Abstract

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The changes observed in a municipal or local energy system over a period of time is due a number of concurrent dynamics such as the local social and economic trends, higher-level policies (e.g., national), and the local policies. Thus, a thorough identification and characterization of the many factors of change is key for an adequate assessment of the effectiveness of policies adopted at the local level, as well as for future planning. Such thorough identification and characterization of the factors that are determinant for the evolution of the local energy system is the content of this paper. The identification is performed through a systematic literature review, followed by a synthesis process. The factors identified are grouped into the categories of local context, local socio-economic and cultural evolution, higher-level governance framework, and local climate change mitigation actions. They are represented through a set of measurable variables. The factors and respective variables can be used to improve the disaggregation of changes in the local energy system into individual causes, leading to a better assessment of the evolution over time.

1. Introduction

Local actions are crucial for the achievement of global climate change mitigation goals. Both the physical characteristics of the local energy systems and the regulatory competences of local authorities prompt local level as an appropriate level for action [1]. Moreover, local actions are becoming more common, due to the increasingly active role of local authorities and to the recognition of their importance by policy makers at higher governance levels. Thus, there is an increasing need to assess their contribution towards climate change mitigation, and to the achievement of global targets.
However, given the universal scope of climate policy and the link between the local energy system and local context, it is currently very difficult to properly assess the actual contribution of local policy actions. Indeed, the local energy system is influenced by numerous factors, of which only some are related with actions promoted by local authorities. The changes in the economic activity or on population are two examples. The assessment difficulties are amplified by the fact that local policies and actions are implemented as a part of a complex multi-level governance framework.
Previous studies have already highlighted the importance of considering external factors when evaluating local actions. Within the studies reviewed in [2], several factors were identified as key in the link between observed changes and actual effects of local climate change mitigation actions. For instance, the evolution of local socio-economic features (structure of local economy, demographic and economic conditions of local population, etc.), prompted by economic, social, and technological changes, is one of the aspects that are commonly considered relevant for the observed variation in local GHG emissions. However, within existing studies, a comprehensive analysis of all the relevant factors that influence the local energy system and the corresponding GHG emissions was not found.
Moreover, the analysis of empirical studies focusing on assessing the effects of local actions has emphasized this need to thoroughly identify all the factors that contribute to changes in local GHG emissions [3,4,5]. For instance, in [3], Millard-Ball performed a quantitative analysis on the effects of city climate policy, without considering any external factors; although some scattered evidence of climate plans effects was found, the findings are not sufficiently robust (which could be partly explained by the non-consideration of other relevant factors). The evidence for impact of local climate plans in the different sectors is not demonstrated with the empirical analysis, which does not provide a coherent result across the different models that were tested. Similarly, in [5], the conclusions drawn were also insufficient to prove the causal link between local actions and GHG emissions. Within the results from the linear regression analysis with panel data, the coefficient associated with the effect of local actions is not statistically significant for any of the countries that were included in the study. However, in the same analysis, the relevance of municipality specificities as well as of higher-level context (i.e., country) for the assessment of local GHG emissions and their evolution over time was confirmed (resulting in coefficients that are statistically significant). Both these studies show the need for a comprehensive consideration of the different factors that impact local GHG emissions to ensure a robust and meaningful assessment of the specific impact of local climate change mitigation actions.
Thus, the identification of the factors of change of local GHG emissions is a crucial step towards a more complete understanding of the observed changes within the local energy system and assessment of the actual effects of local climate change mitigation actions. Indeed, to develop a model that is able to adequately represent the evolution of the local energy system, identifying the links between the changes in local GHG emissions and the different explanatory factors, it is necessary to first identify all the factors that may have an impact on local GHG emissions (factors of change). Herein, factors of change refer to all features and events that lead to changes in the local energy system and respective GHG emissions. These include factors related with local climate change mitigation actions as well as external factors (i.e., factors that are not directly influenced by actions promoted by local authorities). For instance, local demographic evolution—size and structure of local population—may lead to significant changes in the local energy system and, consequently, on the respective GHG emissions.
This paper attempts to perform a systematic identification and characterization of the factors of change of local GHG emissions. This comprises the identification of all factors that may potentially influence local emissions, even if their specific effects in the local energy system are not quantifiable or even relevant (depending on the local system being studied). In order for this to be applicable in the future, it is necessary not only to identify the relevant factors of change, but also to characterize them with indicators. Therefore, that is also covered by this paper. The work is presented in five sections. Section 2 describes the methodological approach that was used to identify the factors of change of local GHG emissions and the review process, including the documents used as reference to this analytical framework, as well as the presentation of the final list of factors identified. Section 3 is dedicated to the presentation of the results, including the description of the identified factors of change and the listing of the respective quantifiable indicators. Section 4 presents a brief discussion of the obtained results, focusing on their potential contribution for improved planning and evaluation of local climate change mitigation actions. The paper ends with some final remarks regarding the results obtained (Section 5).

2. Methodology

Considering the extensive research that has already been done on this topic, a wide literature review was considered an adequate methodological approach to identify and characterize the factors of change of local GHG emissions. More specifically, the method used consisted in a systematic literature review, using content analysis—which allowed reviewing, assessing, and aggregating a body of literature utilizing pre-specified standardized techniques to all the documents reviewed [6]. The definition of the specifications for data collection and analysis beforehand and respective use as a guide for performing the process aimed to avoid bias in the review.
A systematic literature review process consists of these four sequential steps: (i) definition of the objective; (ii) definition of the specifications to be followed; (iii) the retrieval and assessment of the information; and (iv) synthesis of the results obtained. In what concerns the specifications defined a priori as guidelines for the review, these consist in three types of rules/criteria: (1) the eligibility criteria to retrieve the literature; (2) the rules to retrieve information from literature; and (3) the rules for the analysis and screening of the obtained information. Table 1 presents the details of these three types of criteria.
The selection of relevant research covered the following keywords: “Energy system characterization”; “Energy system modelling”; “Energy system planning”; “Energy system scenarios”; “Energy policy evaluation”; and “Local climate change mitigation”. The keyword selection was based on the different contexts within which this discussion has been raised, including planning, policy evaluation, and energy management.
To guarantee the reliability of the results, the documents considered in the review were restricted to peer-reviewed articles published in scientific journals or conference journals, reports or working papers published by internationally reputed entities (as e.g., International Energy Agency and European Union), and PhD theses. The reviewed documents were published between 1999 and 2017. A list of the documents with a description of their main focus of research is presented in Table 2.
The information collected from the documents comprised three types of relevant information: (1) factors of change of GHG emissions; (2) variables that may be helpful to characterize the factors of change identified; and (3) information on the relation between the different factors of change and local GHG emissions.
In regard to the identification of the factors of change, Figure 1 presents a schematic representation of the whole process. The analysis of these documents resulted in a list composed of 511 variables with an impact on GHG emissions. The full list, as well as the reference to the documents where each variable has been referred, is presented in Table A1 (Appendix A).
Then, to reduce the list to the essential, both the eligibility criteria (Box 2 in Figure 1) and the screening filters (Box 3 in Figure 1) were applied successively. The following paragraphs describe this process in detail.
The eligibility criteria were defined to guarantee the applicability of the framework to the assessment of local climate change mitigation actions. Firstly, it was assumed that the respective change must be associated with energy-related GHG emissions, excluding, e.g., the emissions from crops and livestock. Then, the associated effect on the energy system should also be on Scope 1 and 2 emissions—GHG emissions that can be attributed to each municipality (i.e., that local inhabitants can be made accountable for). For instance, with this condition, changes in aviation and international commerce emissions are excluded, since typically an airport serves an area much larger than the municipality. Finally, it was also defined that factors should either change over time and/or influence the effect of the other factors identified. As the goal is to decouple the observed changes in a specific local energy system into effects of the different factors of change, it makes sense that factors that are constant over time (even if determinant for local energy use) must be disregarded. For example, topography of the local territory can have significant implications for local energy use, but it cannot be considered a factor of change as it cannot lead to changes of a specific local energy system over time.
The implementation of this step corresponded to the exclusion of variables that do not comply with at least one of the three eligibility criteria. The first eligibility criteria led to the exclusion of variables such as the “existence of strategies for landfill methane capture” and “changes in cattle production or fertilization strategies”. Moreover, the constraint that implies that each factor must influence local GHG emissions led to the removal of variables such as “level of international trade” and “trade allowances between regions”. Lastly, the criteria that exclude variables that do not change over time nor have an impact on policy outcomes implied the exclusion of factors “latitude”, “topography”, and others. Overall, with the application of the eligibility criteria, 73 variables were excluded from the list. The full list of the non-eligible variables is presented in the Appendix (Table A2).
Furthermore, a screening process was defined and implemented to reduce the list of identified factors to the essential. This screening process is composed by three main steps that correspond to the application of three distinct filters: (1) explicit repetition; (2) implicit repetition; and (3) redundancy. The screening of the list of variables led to the exclusion of 331 variables. The full list of the excluded variables and the identification of the filters that led to their exclusion are presented in the Appendix A (Table A3, Table A4 and Table A5).
The filter of explicit repetition refers to the removal of duplicates, i.e., factors that were identified by more than one document. For example, the number of inhabitants (or overall local population) and GDP were two of the variables that appeared more than once in the list.
Implicit repetition refers to factors that, even if not literally in duplicate, if withdrawn from the list do not imply an information loss. This includes factors that are a combination of other two or more factors that are also listed. For instance, average household area per capita can be considered as implicit repetition if both overall population and built area for residential purposes are already listed. This led to the exclusion of variables such as average household area per person (as total household area and overall population were also listed) and sectorial GDP (as GDP per subsector was also included).
Finally, the redundancy filter corresponds to the screening for dependent factors, whose relation has already been identified by literature. With this filter, for instance, average income per capita was excluded, considering that changes in private consumption (also linked to average income) would imply the exact same impact on local GHG emissions.
Once the variables with an impact on local GHG emissions have been identified and screened, a final list that is consistent with the goal of this work was obtained. The application of the eligibility criteria and the screening filters led to a final list of 107 variables that were grouped into 40 factors of change. This was done through an aggregation process, distinguishing policy-based factors from the ones that occur naturally, and factors related to actions implemented at local level from factors associated with governance actions at higher-levels. This grouping process is detailed in Table 3.
Finally, to complete the theoretical framework, each individual factor was characterized with (preferably quantifiable) indicators. For most of the factors, the documents where they were extracted from also mentioned possible indicators. When more than one indicator was available, the choice fell back on the indicators whose data are more commonly available. When the documents did not mention possible indicators, these were searched for in national statistical agencies and policy reports from national or international governments. Within this step, there was an effort to choose indicators that use data that are commonly available for the municipality level, or equivalent scale, to avoid the need for downscaling.

3. Factors of Change of Local or Municipal GHG Emissions and Respective Characterization

This section presents the results obtained by the systematic literature review process described in the previous section. This includes discussion detailed description and an analysis of the final list of factors of change that were identified as well as the listing of the characterizing indicators for each factor of change.
To better understand the relation between the different factors of change and prompt a more fulfilling discussion, the 40 factors of change identified in the review were grouped into four distinct sets. Three of these groups correspond to three sources of change: local socio-economic and cultural changes; higher-level governance framework; and local climate change mitigation actions. The fourth group (herein referred to as local context) comprises variables that, despite not leading directly to changes of local GHG emissions, have influence on how the different sources of change impact local GHG emissions (e.g., climate awareness). A schematic representation of the relation between these sources of change and the observed changes in local GHG emissions, considering the local context, is presented in Figure 2.

3.1. Local Context

Local context refers to the local characteristics that, despite not leading directly to changes on the local energy system, influence the outcomes of both local and higher-level policies. On the one hand, this comprises the local inhabitants’ characteristics, as education level, cultural diversity, and awareness towards the problematic of climate change. On the other hand, local context also includes characteristics referring to the local authority as an entity, including human and financial resources as well as legal competences. In general, the characteristics here referred as local context do not change significantly in the medium-term.
A complete list of the factors of change considered as local context is presented in Table 4, along with the respective characterizing indicators.
A summarized description of each of the factors of change associated with local context is presented below.

3.1.1. Local Inhabitants’ Characteristics

Education level refers to the average level of education of the local population, e.g., whether the majority of local citizens have completed high school, or even a bachelor degree. Here, it was assumed that the distribution of local population per education level could be a good indicator.
Cultural diversity refers to the heterogeneity of local population in terms of cultural background. This is mostly linked with the scale of immigration to the city, currently but also in the last decades. Culture is associated with daily habits and, thus, with specific patterns of energy use and reaction towards certain policy actions/incentives. One of the possibilities to assess this diversity could be through the number of residence permits by reason (or by country of origin).
Willingness to act refers to the level of motivation of the local citizens in having an active role towards climate change mitigation, which is highly associated with their level of awareness to the problem and their civic involvement in the community. For instance, the level of awareness of local population on environmental and climate change issues can have a huge influence on the outcome of any related policy independently on the level of implementation. Even if waste associated emissions are not considered within this work, it is assumed that the share of waste separation could be a good indicator of the local population awareness on climate change issues. Moreover, the degree of civic involvement may be assessed by the number and scale of environmental nonprofits that were created at the local level.

3.1.2. Local Authorities’ Characteristics

Legal competences refers to the regulatory competences of local authorities regarding climate change mitigation, i.e., their scope of action. These may vary significantly from country to country and are determinant for the type of actions that are promoted at the local level. The level of autonomy of local authorities can be seen as a good indicator of their scope of action.
Qualified personnel corresponds to the technical competences of the municipal staff for developing and implementing actions targeting climate change mitigation. This can be assessed through the existence of a dedicated agency or municipal department to climate change mitigation, and from past experiences with these issues.
Economic situation translates the economic capacity of the local authority in financing and promoting actions towards climate change mitigation. This can be assessed by the relation between income and expenses of the local authority, which provides a characterization of their yearly profit or debt. Moreover, the ability to obtain funding, through private partnerships or public tenders, is also a relevant indicator.

3.2. Local Socio-Economic and Cultural Changes

Local socio-economic and cultural changes refer to the group of changes that result from local demographic, social, and economic changes, thus not directly caused by energy-related policies. In planning terms, this would correspond to the “business as usual” or “reference” scenario, i.e., the potential evolution of the system between two distinct moments in time, considering that no policies would be implemented in this timeframe. This comprises demographic, social, and economic changes, as well as climate variability.
The full list of factors of change associated with the local socio-economic and cultural changes that have been identified is presented in Table 5, along with the respective characterizing indicators.

3.2.1. Demographic Evolution

Demographic changes include the population growth (due to migration and natural growth) and also changes in the age pyramid and in the share of population living in urban and rural areas. All these variations imply changes in the local energy system—in the overall energy use as well as in the structure of this use. For example, energy use in urban areas differ from that in rural areas, due to the differences in heating options available (natural gas vs. traditional wood) and the different household conditions (housing type and size). A summarized description of each of the factors of change associated with demographic changes is presented below.
Population growth refers to the changes regarding the size of local population that occur within the studied timeframe. This is assessed through the number of local inhabitants and their evolution over time.
Migration to urban areas translates the level of urbanization of a municipality and its evolution over time. A change in the level of urbanization has an impact in the local energy system, in terms of preferred transportation modes, average distances traveled, and even in the type of housing. The changes in the level of urbanization can be assessed through the share of local population living in rural/urban areas.
Age pyramid refers to the distribution of the population according to their age. A change in this distribution implies changes in the local energy system, caused by the distinct energy service needs. The differences are more significant between active and inactive citizens. Thus, it is assumed that this factor of change can be assessed by the quantification of the share of active population.

3.2.2. Social Evolution

Social changes refer to the lifestyle changes of local inhabitants that occur naturally, not promoted by energy-related policies. These may include e.g., the increase of appliances ownership per capita and changes in the number of persons per household, in the residential sector, and a change in the average distance between home and work or school, in the transportation sector. Each of the factors of change associated with social evolution are described below.
Household conditions refer to lifestyle changes associated with the residential building. This includes changes in the average number of people per household (usually also linked with the evolution in families’ typology) and changes in the average size of the household. These changes can imply significant changes in the energy use for space heating and cooling, lighting, and even cooking. Moreover, changes in appliances ownership must also be considered.
Commuting needs reflect the distance between home and work/school for the local inhabitants. A variation in this distance implies also a change in the daily transportation needs, and often even a change in the transportation modes that are used for commuting. It is assumed that this factor can be assessed through the average distance traveled per person per day, for commuting purposes.
Transportation habits refer to changes in the preferences for daily traveling, for both commuting and leisure purposes. These characteristics may change over time for multiple reasons—economic, social or other. It is assumed that a large share of these changes can be estimated based on the changes in car ownership of local population.

3.2.3. Economic Evolution

Economic evolution refers to the economic situation of local inhabitants and also to the evolution of local economic activities. The effect of these changes on local energy system may be affected, even if not in a very significant way, by local context. For instance, the increase in average income of local population leads to an increase in energy use; however, the growth rate may depend on the level of awareness of the local inhabitants towards climate change issues. The factors of change associated with the economic evolution at the local level are described below.
Overall growth of local economy refers to changes in the level of activity, i.e., the overall value of the local economy. Changes in the local gross domestic products (GDP) are a good indicator for the variation in the level of activity.
Structure of local economy refers to the weight that different economic sectors (or subsectors) represent to the overall local economy. Describing the structure of economy of a specific municipality would consist on identifying the sectors responsible for a larger share of gross value added or for employing more workers and which sectors are less relevant.
Economic situation of households translates the financial situation of individuals. This includes the employment situation, which has a significant impact in the local energy system given the difference in the daily habits between employed and unemployed citizens, and the individuals purchase power. On the latter, there are several studies that demonstrate the relation between private purchase power and energy use.

3.2.4. Climate Variability

Finally, the effects of differences in climate conditions have also been included in the natural evolution of the local energy system. These vary from year to year, and temperature differences lead to changes in energy needs (mostly for heating and cooling), which must be considered. It is assumed that these changes can be assessed through the variations in annual heating and cooling degree days.

3.3. Higher-Level Governance Framework

Higher-level governance framework refers to the characteristics of international, national, and regional governance frameworks existing within the studied timeframe and focusing on energy and climate issues. Considering the variables identified in the review, it is assumed to be appropriate to separate technology evolution from specific energy and climate policies.
The full list of factors that characterize higher-level governance framework is presented in Table 6, along with the respective characterizing indicators.

3.3.1. Technology Evolution

Technology evolution can be prompted by energy related policies (targeting energy efficiency and others) but it may also be market driven (following industry needs or an attempt to reduce costs). The evolution of the energy supply sector can be seen as a mix between natural technology evolution and an effect of energy and climate policies. The energy efficiency improvement on conversion plants is an example of the former, while the preference for renewable energy sources to produce electricity, due to fee-in tariffs in the technological maturation phase, is an example of the latter.
Technical evolution refers to the technology development that occurs naturally, i.e., excluding development that is promoted by energy efficiency policies and other related instruments. This evolution can be assessed by the variation in the energy intensity for each activity sector, at national or even international level.
Market evolution corresponds to the changes in the market that lead to changes in the technology choices by both individuals and companies. This can be translated into changes in technology costs, as well as the presence of market barriers that hamper the shift towards more efficient solutions. The variation in technology costs can be characterized by, e.g., the over cost of A++ appliances compared to a B equivalent. The presence of market barriers and respective evolution over time can be assessed by the quantification of the energy efficiency gap in different moments in time.
Energy supply sector represents the changes in the national and regional energy transformation and transport activities. It includes the evolution in electricity and heat production and transport, as well as the changes in the refinery of fossil fuels. Thus, it comprises the changes in the fuel-mix of electricity and heat generation, i.e., the increase/decrease in the share of renewable energy sources that are used in electricity production, as well as the changes in the efficiency of the energy supply sector (electricity and heat production, but also oil products transformation).

3.3.2. National and International Energy-Related Policies

On what concerns the factors of change associated to energy and climate policies, two distinct groups of factors were found: the ones that characterize the existing energy and climate related policies, e.g., in terms of implementation and specific targets, and the ones that characterize the existing institutional framework regarding the promotion and support of local actions towards climate change mitigation. It is also important to mention the influence that the local context may have on the overall effect of these factors of change on the local energy system. The effects of national and international policies depend on the reaction of targeted actors to the policy instruments put in place. In turn, their reaction depends on their level of education and awareness as well as cultural habits and financial situation. All the identified factors associated with energy and climate policies are briefly described below.
Existing policies correspond to the policies that are implemented at regional, national, and international level that have a climate and/or energy purpose. These may impact positively or negatively local GHG emissions, depending on the coherence between local policies and the ones defined at higher levels of governance. Here, it is assumed that the public and private investments on environmental management and protection could be a good indicator of the scale of existing policies at governance levels other than local.
Energy costs refer to the changes in the average cost of the different energy products and the impact that these may have in the local energy system. Energy prices are usually established at the national and/or regional level, and thus are included within the changes associated with the higher-level governance framework. The average unitary price per energy product in the consumer sector, as well as the respective evolution over time, is considered a good indicator to characterize this factor of change.
Coherence with local policies refers to whether national and regional policy objectives are aligned with those that were defined at the local/municipal level. Here, the quantification of this alignment is not feasible, thus a yes or no question is suggested.
Support of local action refers to the existence of initiatives promoted at national and international level that promote actions taken at the local level. This may include technical support for the development of action plans, and energy dedicated actions, and economic incentives and support (as low-rate loans). A possible indicator to characterize the level of support could be the number of initiatives promoted at higher levels of governance that support local action.

3.4. Local Climate Change Mitigation Actions

Finally, local climate change mitigation actions include any policy actions that are promoted at the local level, by (or with the support of) local authorities, with the aim of reducing local GHG emissions. These include actions taken under a formal and wider plan and also isolated actions with a very specific target (e.g., the improvement of energy efficiency in public lighting). Here, the factors of change that have been identified are mostly related with the characterization of these actions, in terms of objectives and targeted actors as well as in what concerns implementation procedures. The factors that were identified as important for the characterization of local climate change mitigation actions are briefly described below and presented in Table 7.
Actors’ involvement refers to the group of actors that were/are involved in the local climate change mitigation actions. A distinction is made between the actors that are involved in the planning process (where actions are defined) and the ones involved in the implementation stage. The involvement of different stakeholders in the planning and implementation of climate and energy actions is considered to be beneficial for the respective acceptance and adherence by local citizens. The characterization of this involvement may be achieved by the identification of the groups of actors that were involved (e.g., local authority, local/regional energy agency, external consultant, local NGOs, citizens, etc.) and their level of involvement (co-creation, draft version public consultation, etc.).
Timeframe refers to the time span of the actions being planned/implemented. Throughout the review, the consideration of the time span of the ex-ante planning exercise (when existing) was also noted as relevant for the assessment of the outcomes of local actions. This is translated into the beginning and end years of the actual (or projected) action implementation.
Targets refer to the objectives that were defined at the local level. These include the level of GHG emissions reductions that is aimed, the wider vision concerning the local energy system, and whether there are other goals besides GHG emissions (such as creation of jobs or decrease in energy costs).
Current implementation status refers to the degree of implementation of the wider action plan (if existing) and of the different individual actions that are projected. It can be assessed as a percentage of the overall implementation target. For instance, considering an action that implied the installation of solar thermal systems for water heating in 100 residential buildings, the degree of implementation would correspond to the identification of the share of systems that were already installed.
Estimated impact corresponds to the projected outcome of the proposed actions, in terms of both energy use and GHG emissions. When a mid-term assessment is also performed, the quantification of the already achieved reductions could also be performed.
Budget refers to the level of investment needed to implement the proposed actions. Here, it is important to distinguish between the overall projected budget and the investments made thus far.
Financing sources correspond to the entities responsible for financing the actions’ implementation. This may comprise different entities, both public and private. The characterization of the financing sources could be performed by the identification of the type of entities financing the local actions (local authority’s own resources, national funds and programs, EU funds and programs, other), and the level of investment of each of the different entities.
Actions characterization corresponds to the characterization of the individual actions planned and/or implemented at the local level, in terms of: (1) area of intervention; (2) type of technical measure; and (3) policy instrument. Area of intervention is the sector and subsector of the local energy system which will be impacted by the action (residential, services, transports, etc.). Then, the technical measure refers to the type of change that is aimed at, as well as the degree of change that is intended. For instance, the shift of 10% of private cars passenger-kilometers to soft modes of transportation could be seen as a technical measure. Finally, the choice of policy instrument corresponds to the type of mechanism that is used to achieve the desired changes in the system. Using the same example, this could comprise the creation of dedicated bike lanes and/or the implementation of a congestion charge. When assessing the policy instruments, it is also useful to identify the level of financial support that is provided to the adopters of the measures (i.e., if there are economic incentives to change) and which actors are involved in their implementation.
Similar to what was said regarding the effects of higher-level policies, the influence of local context on the contribution of local actions cannot be disregarded. Local inhabitants’ characteristics may influence the outcomes of policy actions in a significant manner. Moreover, local authorities’ characteristics are an important feature on the definition and implementation of local actions. Thus, even if local actions are similar in their characteristics, their outcome can be very different if the context in which they are implemented is not the same.

4. Discussion

There are several studies that analyze the changes in local GHG emissions and potential explanatory factors. However, it was noted throughout the review that existing work is usually constrained to the consideration of a specific set of factors of change, disregarding others that may also have a significant impact on local emissions. For instance, it is common to narrow the focus to the actions that are being taken at the local level, disregarding the influence of higher-level governance framework in which they are being implemented and that may have confounding effects.
Such non-consideration of other potential factors of change hinders the accuracy of the results, as the effects calculated and associated with the considered factors may turn out to be either under- or overestimated. Indeed, the evaluation of the effects of local climate change mitigation actions will not lead to accurate results unless the remaining factors of change are taken into account. For example, in [5], the impact of local climate actions was inconclusive, partly due to the non-consideration of factors associated with the changes in local socio-economic and cultural conditions. Moreover, a better understanding of all potential factors of change of local GHG emissions can lead to better planning at local as well as regional and national levels. The interaction between the policies implemented at different governance levels could be improved by a comprehensive consideration of all factors of change and their interactions.
It is worth noting the overly simplified consideration of the local context in most of the existing work. Some of the reviewed documents refer to its importance, and how the local context specificities can be determinant for the success of local actions implementation, yet quantification methods tend to be overlooked. The systematic identification of the factors of change associated with local context may thus be a step forward for their consideration in future empirical ex-post evaluation studies and/or ex-ante planning exercises.

5. Conclusions

This paper is dedicated to a comprehensive and systematic identification and characterization of the factors that are relevant for the assessment of the observed changes in GHG emissions associated with local energy systems. This is an important contribution for the assessment of the actual effects of local climate change mitigation actions, by establishing the bases for developing analytical frameworks.
The identification was performed through a systematic literature review process. The complete list of variables encountered in the review was reduced using eligibility criteria, as well as three screening filters (explicit repetition, implicit repetition, and dependent variables). A list of 107 variables that were grouped into 40 factors of change was finally obtained.
The factors of change were grouped into four subsets, corresponding to three sources of change plus the local context. The sources of changes subsets are: local socio-economic and cultural changes; higher-level governance framework; and local climate change mitigation actions. The local context corresponds to a group of variables that, despite not leading directly to changes in local GHG emissions, have influence on how the remaining factors impact the local energy system—e.g., local inhabitants’ level of awareness and commitment towards environmental problems or local authorities’ legal scope of action.
Even if the identification of the major categories has been previously accomplished in academic studies, the major advancement of this work corresponds to their disaggregation into individual factors of change and respective characterization.
The factors identified correspond to all the factors that may potentially lead to changes in local GHG emissions. The relevance of the effects associated with each factor of change will depend on the local system in question, as well as on the timeframe addressed. Moreover, even acknowledging the difficulty of empirical validation (and quantification) of each factor individually, the obtained results comprise an advancement from what was possible thus far, providing a basis for more accurate models and analyses of the evolution of the energy systems at the local level.
These results can be used to build an analytical framework to characterize and model the evolution of a local energy system, assessing the individual effect of each of the different explanatory factors. This will allow for more accurate energy planning at the local level, taking into account the potential interactions with the external factors of change (i.e., the factors that are not controlled by local authorities). For instance, it may be used for ex-post evaluation of local climate change mitigation actions, allowing for the disaggregation of the observed changes in local GHG emissions into the causes and the isolation of the effects that were solely associated to local policies and actions.
The outcome of this work can be seen as a fundamental step towards a comprehensive assessment of the evolution of local energy systems. Such assessment is crucial for a better evaluation of the actual contribution of local climate-related policies and actions towards climate change mitigation.

Author Contributions

Conceptualization, I.A. and V.L.; Formal analysis, I.A. and V.L.; Funding acquisition, I.A.; Investigation, I.A.; Methodology, I.A.; Supervision, V.L.; Validation, I.A. and V.L.; Visualization, I.A.; Writing—original draft, I.A.; and Writing—review and editing, I.A. and V.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Fundação para a Ciência e Tecnologia (FCT—Portugal), grant number PD/BD/105862/2014, in the frame of the MIT Portugal Program. INEGI (LAETA—Grupo de Energia e Ambiente) provided financial support with the article processing charges.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

This appendix presents in detail the process of identification and screening of the factors of change that are relevant for local GHG emissions. Table A1 presents the full list of variables identified in the literature. The four following tables are dedicated to the screening process: Table A2 presents the variables that were excluded for non-applicability; Table A3 and Table A4 present the variables that were eliminated due to explicit and implicit repetition, respectively; and Table A5 presents the variables that were excluded to avoid dependent variables.
Table A1. Full list of variables identified in the systematic literature review process and respective sources.
Table A1. Full list of variables identified in the systematic literature review process and respective sources.
DocumentCodeVariable
Auld et al. (2014)1.001Agenda setting processes
1.002Favorable public opinion
1.003Favorable party platform
1.004Recent change in government
1.005Presence of champions
1.006Social appeal
1.007Availability of technology
1.008International processes
1.009Focusing events
1.010Action of feedback mechanism
1.011Timeframe
1.012Reporting nature
1.013Policy instruments
1.014State of activity
1.015Target of policy (actors)
1.016Source of authority at different stages (Hybrid or Government)
1.017Presence of flexibility mechanisms
Boonekamp (2004)2.001GDP growth
2.002Structure, main sectors
2.003Structure, subsectors
2.004Structure, final demand
2.005Savings, final demand
2.006Conversion efficiency end-users
2.007Co-generation end-users
2.008Fuel mix end-users
2.009Export
2.010Structure electricity production sectors
2.011Co-generation electricity production sectors
2.012Import
2.013Fuel mix electricity production sectors
Boonekamp (2005)3.001Energy statistics (statistical figures)
3.002Corrected statistics (corrections from trend breaks, etc.)
3.003Climate (degree-days and fraction room heating)
3.004GDP growth (GDP growth rate)
3.005Structure, main sectors (growth rate main sectors)
3.006Structure, subsectors (growth rate per subsector)
3.007Structure, final demand (Reference final demand per subsector)
3.008Savings, final demand (Actual final heat/electricity demand)
3.009Conversion efficiency end-users (Actual efficiency boilers, etc.)
3.010Cogeneration end-users (actual CHP figures)
3.011Fuel-mix end-users (Actual energy use)
3.012Export (Actual energy exports)
3.013Structure energy transformation sectors (reference use refineries/gas supply)
3.014Cogeneration energy transformation sectors (actual cogeneration figures)
3.015Efficiency energy transformation sectors (actual conversion efficiencies)
3.016Import (actual energy imports)
3.017Fuel-mix electricity production sectors (actual energy use)
Broto and Bulkeley (2013)4.001Country
4.002Urban area
4.003Population
4.004Density
4.005GDP
4.006GDP per capita
4.007World City Rank
4.008Annual population rank
4.009Location
4.010Dates
4.011Urban character
4.012Type of experiment
4.013Objectives
4.014Type of innovation
4.015Institutional factors
4.016Sector specific information
4.017Actors involved
4.018Funding
4.019Mode of governance
4.020Environmental justice
4.021Action targeted sectors
4.022Action type of schemes
CoM (2010)5.001Overall CO2 reduction target
5.002Vision
5.003Coordination and organizational structures created/assigned
5.004Staff capacity allocated
5.005Involvement of stakeholders and citizens
5.006Overall estimated budget for the Sustainable Energy Action Plan implementation
5.007Foreseen financing sources for the implementation
5.008Monitoring process
5.009Year
5.010Population
5.011Final energy consumption per sector and carrier
5.012Energy supply sources
5.013CO2 emissions per sector and carrier
5.014Date of approval
5.015Decision body approving the plan
5.016Business-as-usual projections
5.017Area of intervention
5.018Policy instrument
5.019Origin of the action (local or other)
5.020Responsible body
5.021Implementation timeframe
5.022Estimated implementation cost
5.023Energy savings
5.024Renewable energy production
5.025CO2 reduction
5.026Newest inventory year
5.027Population
5.028Final energy consumption per sector and carrier
5.029Energy supply sources
5.030CO2 emissions per sector and carrier
5.031Status implementation
5.032Implementation cost spent so far
5.033Renewable energy production from actions implemented so far
5.034CO2 reduction from actions implemented so far
Corfee-Morlot et al. (2009)6.001Coherent multi-level policy framework (vertically and horizontally)
6.002Existence of a dedicated institution/agency to deal with climate change mitigation actions/plans
6.003Local authority’s capacity and expertise on climate change mitigation
6.004Local authority’s ability to obtain funding
6.005Local authority’s responsibility and competences
6.006Support from central governments to local policies
Farla and Blok (2000)7.001Total dwelling area
7.002Average number of inhabitants
7.003Number of appliances per type
7.004Number of vehicle-kilometers of personal cars per fuel
7.005Number of passenger-kilometers per mode (except car)
7.006Number of vehicle-kilometers of freight road transportation
7.007Number of ton-kilometers per mode (other freight transportation)
7.008Number of employee-years
7.009Production of goods per type (piece, kg or m2)
7.010Cultivated land area
7.011Raising of cattle, pigs and chickens
7.012Volume index of production
Fortes et al. (2014)8.001Gross domestic product (GDP)
8.002Population
8.003Private consumption
8.004Gross value-added Agriculture
8.005Gross value-added Services
8.006Gross value-added Transports
8.007Gross value-added Industry
Fortes et al. (2015)9.001Annual growth rate of the socio-economic indicator
9.002Demand elasticity
9.003Autonomous efficiency improvement factor (industrial sectors)
9.004Energy and environmental policies
9.005Energy and environmental policy instruments
9.006Technical and costs evolution
9.007Availability and capacity limits
9.008Other information (discount rate, etc.)
9.009Endogenous resources potential and prices
9.010Import/export prices and boundaries
Gustavsson et al. (2009)10.001Actors involved in local Climate Change mitigation
10.002Formulation of the climate-policy strategy
10.003Results in terms of GHG emissions reduction
10.004Geography
10.005Business structure
10.006Physical circumstances
10.007Actors involvement
Gysen et al. (2002)11.001Objectives
11.002Instruments
11.003Means—Societal
11.004Means—Policy process
11.005Policy output
11.006Policy outcome
11.007Policy impact
IAEA (2006)12.001Total population
12.002Average annual growth rate of population
12.003Share of urban population
12.004Average household size in urban areas
12.005Average household size in rural areas
12.006Share of population of age 15–64 in total population
12.007Share of potential labor force actually working
12.008Share of population living in large cities
12.009GDP
12.010Average annual growth rate of GDP
12.011Distribution of GDP formation by kind of economic activity
12.012Distribution of sector gross value-added by subsectors
12.013Energy intensities in industry
12.014Penetration of energy carriers into useful thermal energy demand of the different sectors
12.015Average efficiencies of fuels for thermal uses per sector
12.016Share of transportation modes in the total demand for freight transportation
12.017Energy intensity of freight transportation modes
12.018Average intracity distance traveled per person per day
12.019Average load factor of intracity passenger transportation mode(s)
12.020Share of transportation mode(s) in the total demand for intracity passenger transportation
12.021Energy intensity of transportation mode(s) in intracity travel
12.022Average intercity distance traveled per person per day
12.023Inverse of car ownership ratio
12.024Average intercity distance driven per car per year
12.025Average load factor of intercity transportation mode(s)
12.026Share of car type(s) in the intercity transportation mode(s)
12.027Share of public transportation mode(s) in the intercity passenger travel by public modes
12.028Energy intensity of transportation mode(s)
12.029Fraction of urban dwellings in areas where space heating is required
12.030Degree days for urban dwellings
12.031Fraction of urban dwellings per type
12.032Average size of urban dwellings by type
12.033Fraction of floor area that is actually heated in urban areas per dwelling type
12.034Specific heat loss rate by urban dwelling type
12.035Share of urban dwellings with air conditioning, by dwelling type
12.036Specific cooling requirements by urban dwelling type
12.037Specific energy consumption for cooking in urban dwellings
12.038Share of urban dwellings with hot water facilities
12.039Specific energy consumption per urban dwelling for electric appliances
12.040Electricity penetration for appliances in urban households
IAEA (2006)12.041Specific fossil fuel consumption per urban dwelling for lighting and non-electric appliances
12.042Penetration of various energy forms into space heating in urban households
12.043Efficiency of various fuels use, relative to that of electricity use, for space heating in urban households
12.044Coefficient of performance of heat pumps for space heating in urban households
12.045Penetration of various energy forms into water heating in urban households
12.046Efficiency of various fuels use, relative to that of electricity use, for water heating in urban households
12.047Coefficient of performance of heat pumps for water heating in urban households
12.048Approximate share of water heating demand in urban households that can be met with solar installations
12.049Penetration of various energy forms into cooking in urban households
12.050Efficiency of various fuels use, relative to that of electricity, for cooking in urban households
12.051Approximate share of cooking demand in urban households that can be met with solar installations
12.052Share of air conditioning demand of urban households that can be met with electricity
12.053Coefficient of performance of electric air conditioning in urban households
12.054Coefficient of performance of non-electric air conditioning in urban households
12.055Fraction of rural dwellings in areas where space heating is required
12.056Degree days for rural dwellings
12.057Fraction of rural dwellings per type
12.058Average size of rural dwellings by type
12.059Fraction of floor area that is actually heated in rural areas per dwelling type
12.060Specific heat loss rate by rural dwelling type
12.061Share of rural dwellings with air conditioning, by dwelling type
12.062Specific cooling requirements by rural dwelling type
12.063Specific energy consumption for cooking in rural dwellings
12.064Share of rural dwellings with hot water facilities
12.065Specific energy consumption per rural dwelling for electric appliances
12.066Electricity penetration for appliances in rural households
12.067Specific fossil fuel consumption per rural dwelling for lighting and non-electric appliances
12.068Penetration of various energy forms into space heating in rural households
12.069Efficiency of various fuels use, relative to that of electricity use, for space heating in rural households
12.070Coefficient of performance of heat pumps for space heating in rural households
12.071Penetration of various energy forms into water heating in rural households
12.072Efficiency of various fuels use, relative to that of electricity use, for water heating in rural households
12.073Coefficient of performance of heat pumps for water heating in rural households
12.074Approximate share of water heating demand in rural households that can be met with solar installations
IAEA (2006)12.075Penetration of various energy forms into cooking in rural households
12.076Efficiency of various fuels use, relative to that of electricity, for cooking in rural households
12.077Approximate share of cooking demand in rural households that can be met with solar installations
12.078Share of air conditioning demand of rural households that can be met with electricity
12.079Coefficient of performance of electric air conditioning in rural households
12.080Coefficient of performance of non-electric air conditioning in rural households
12.081Share of service sector in the total active labor force
12.082Average floor area per employee in the Service sector
12.083Share of Service sector floor area requiring space heating
12.084Share of Service sector floor area requiring space heating that is actually heated
12.085Specific space heat requirements of Service sector floor area
12.086Share of air-conditioned Service sector floor area
12.087Specific cooling requirements in the Service sector
12.088Energy intensity of motor fuel use per Services’ subsector
12.089Energy intensity of electricity specific uses per Services’ subsector
12.090Energy intensity of thermal uses (except space heating) per Services’ subsector
12.091Penetration of various energy forms into space heating in Service sector
12.092Penetration of various energy forms into other thermal uses in the Service sector
12.093Efficiency of various fuels use, relative to that of electricity use, for thermal uses in Service sector
12.094Coefficient of performance of heat pumps in space heating in Service sector
12.095Share of low-rise buildings in the total Service sector floor area
12.096Approximate share of thermal uses in the Service sector that can be met by solar installations
12.097Share of air-conditioning that can be met with electricity
12.098Coefficient of performance of electric air conditioning in Service sector
12.099Coefficient of performance of non-electric air conditioning in Service sector
IEA (2014)13.001Population
13.002Floor area per capita
13.003Persons per household
13.004Appliances ownership per capita
13.005Heat per floor area
13.006Domestic how water energy per capita
13.007Cooking energy per capita
13.008Electricity for lighting per floor area
13.009Energy per appliance
13.010Passenger-kilometers
13.011Share of total passenger-kilometers by mode
13.012Energy per passenger-kilometer by mode
13.013Tons-kilometers
13.014Share of total ton-kilometers by mode
13.015Energy per ton-kilometer by mode
13.016Services value-added
13.017Energy per value-added (services)
13.018Industry subsectors value-added
13.019Share of total value-added by subsector
13.020Energy per value-added by subsector
13.021Agriculture value-Added
13.022Share of total value-added by subsector
13.023Energy per value-added by subsector
13.024Changes in CO2 intensity
13.025Changes in input coefficients
13.026Changes in the composition of final demand
13.027Changes in the level of final demand (economic growth)
Jovanovic et al. (2010)14.001Population growth
14.002Persons per household
14.003Share of the potential labor force
14.004Share of the population outside the community
14.005Share of rural population
14.006GDP
14.007GDP growth rate
14.008Monetary values per capita of the major sectors and subsectors
14.009Efficiency of appliances/vehicles
14.010Buildings insulation
Kasperson et al. (1995)15.001Population growth
15.002Migration
15.003Natural growth
15.004Irrigation development
15.005Mechanization
15.006Fertilization
15.007Pasture improvement
15.008Industrialization infrastructure
15.009Agricultural intensification
15.010Urbanization
15.011Poverty
15.012International market
15.013National market
15.014State policy
15.015Shift to commodity production
15.016Foreign debt, balance of trade
15.017Resource allocation rules and institutions
15.018Capital extraction
15.019Political corruption
15.020Frontier development
15.021Ethnic/religious views
15.022Mass-consuming view of nature
15.023Acceptance of corruption
Lin et al. (2010)16.001Population
16.002Population growth rate
16.003Size of households
16.004Number of households
16.005GDP
16.006Growth rate of GDP
16.007Measures and policies already promulgated
16.008Measure/Action
16.009Intensity of measure (degree of implementation)
16.010Competences of local authorities in implementation fields
16.011Investment costs
16.012Implementation experiences
Millard-Ball (2012)17.001Population
17.002Employment
17.003Average income
17.004Education
17.005Environmental voting
17.006Civic
17.007Non-residential building
17.008Latitude
17.009Ped/bike mode share
17.010Time
17.011Number of certified buildings
17.012Share of renewable energy sources electricity microgeneration
17.013Street lighting expenditure
17.014Use of soft modes
Morlet and Keirstead (2013)18.001City power (EU, 2007)
18.002City size (population)
18.003Legal structure and status
18.004Spending power
18.005Control over income
18.006Civic involvement (voting patterns)
18.007Herfindahl–Hirschman index (degree of competition in the national electricity system)
18.008Degree of electricity generated in combined heat and power systems
18.009City’s population
18.010Wealth (GDP per capita)
18.011Climate (Heating Degree Days)
18.012Price of energy (gas and electricity) and relative share of any taxes or levies—energy costs
18.013Carbon intensity of fuels
18.014Targets set by each city for GHG emissions reductions
18.015Annual energy demand
18.016Policy type (Financial/Non-financial)
Murphy et al. (2012)19.001Policy instrument combinations
19.002Obligating/Incentivizing balance
19.003Long-term program
19.004Non-generic instruments
19.005Primacy to energy efficiency
19.006Whole house/deep retrofit
19.007Energy sufficiency
19.008Policy theory associated with instruments applied
19.009Description of the impact of instruments (secondary sources and interviews)
Nassen (2014)20.001Total consumption
20.002Household size
20.003Age of occupants
20.004Education of occupants
20.005Dwelling type
20.006Urbanity
Neji and Astrand (2006)21.001Changes in knowledge
21.002Awareness and behavior of important actors
21.003Technology performance
21.004Price development
21.005Sales data
21.006Market share
21.007Changes in manufacturers assortment
Praznik et al. (2013)22.001Surface area to volume ratio
22.002Orientation of the facades’ transparent elements
22.003Thermal zoning of the building and the separation of its unheated parts from the thermal envelope
22.004Heated area per occupant
Rai and Robinson (2015)23.001Attitude factors
23.002Economic factors
23.003Social factors (impact on agents’ attitude)
Schipper et al. (2001)24.001Population
24.002Floor area per capita
24.003Persons per household
24.004Appliances ownership per capita
24.005Intensity for different uses
24.006Total passenger-kilometers
24.007Distribution of passenger-kilometers per mode
24.008Energy/passenger-kilometer per mode
24.009Distribution of value-added per subsector
24.010Average energy/value-added per subsector
Sobrino and Monzon (2014)25.001Carbon intensity of road transport
25.002Energy intensity of road transport
25.003Use intensity
25.004Motorization rate
25.005Job intensity
25.006Workers income intensity
25.007GDP
Spyridaki and Flamos (2014)26.001Electricity market structure and design
26.002Interconnection of domestic electricity markets in Europe
26.003Primary factor: labor, capital, conventional and non-conventional resources
26.004Supply and demand parameters
26.005Incumbent policy framework included in the reference scenario
26.006Different renewable energy sources penetration levels
26.007Renewable energy source potential
26.008Efficiency of the whole electricity system
26.009Emissions of other air pollutants
26.010Discount rate for investments
26.011Firm behavior
26.012Allowance trade patterns among regions
26.013Socio-demographic and lifestyle trends
26.014Interconnection of domestic electricity markets in Europe
26.015Political context in which policy instruments are imposed
26.016Supply and demand parameters
26.017Firm behavior
26.018Simplification in technology production options and load segments of electricity production
26.019Limited analysis of constraints in output
26.020Slope of demand and supply curves
26.021Electricity market structure and design
26.022Technology market failures and other externalities related to electricity generation design
26.023Trading options
26.024Banking of emissions
26.025Alternative compliance payments
26.026Distinctions between price based or quantity-based policy instruments with variations in prices and quotas for commodities
26.027Uniform/Differentiated feed in tariff rate
26.028Phase in of Renewable Portfolio Standard
26.029Annual digression rate of feed in tariff rate
26.030Limitation of the payment period
26.031Tariff reduction due to inflation
26.032Distinctions between price based or quantity-based policy instruments with variations in prices and quotas for commodities
26.033International emissions trading
26.034Uniform and unilateral imposition of carbon taxes across all EU-ETS regions
26.035Lump-sum treatment of additional tax revenues
26.036Stringency levels
26.037Different application scope
26.038Nature of targets, the target groups, the policy-implementing agents, the available budget, the available information on the initially expected energy-savings impact, and the cost effectiveness of the instrument
Spyridaki and Flamos (2014)26.039Distinctions between price-based or quantity-based policy instruments
26.040Different renewable energy sources and support design elements
26.041Variable scenarios in the short and long run for key policy parameters such as price of certificate, level of obligation, level of sales tax and the level of penalty
26.042Fixed-price policies and endogenous price policies
26.043Technology specific hurdle rates reflecting market barriers, consumer preferences and risk factors limiting purchase of new energy technologies
26.044Conditions for implementation and proper utilization of saving options (technology equipment availability, familiarity with the policy, overcoming barriers, motivation to invest)
26.045Specific implementation of policy instruments with regard to their funding
26.046Transaction costs
26.047Stability and credibility in policy regime
26.048Implementation period of the policy instrument
26.049Circumstances in which to apply a policy instrument (challenges in addressing different target groups, challenges in addressing different scopes, addressing a financial, knowledge barrier, internalizing externalities, addressing market competition, conditions under which a policy combination is required, conditions of policy redundancy)
26.050Implicit and explicit assumptions in the policy implementation process and mapping the cause-impact relationships
26.051Transaction costs related to the combined policy cycle
26.052Regulatory decisions on the additionality of energy savings from individual projects
Tang et al. (2010)27.001Political will
27.002State-level mandates concerning climate change (national)
27.003Wealth
27.004Coastal distance
27.005Population density
27.006Hazard damage
27.007Energy consumption
27.008Light transportation (soft modes and public transportation)
27.009Average commuting time
27.010Vehicular emission
27.015Concept of climate change or global warming
27.016Concept of GHG emission
27.017Effects and impact of climate change
27.018Long-term goals and detailed targets for GHG emissions
27.019Emissions inventory
27.020Base year emissions
27.021Emissions trend forecast
27.022Vulnerability assessment
27.023Cost estimates for GHG emissions reduction
27.024Using analysis tools
27.025Public awareness, education, and participation
Tang et al. (2010)27.026Inter-organizational coordination procedures
27.027GHG emissions reduction fee
27.028Establish a carbon tax
27.029Disaster resistant land use and building code
27.030Mixed use and compact development
27.031Infill development and reuse of remediated brownfield sites
27.032Green building and green infrastructure
27.033Low-impact design for impervious surface
27.034Control of urban service/growth boundaries
27.035Alternative transportation strategies
27.036Transit-oriented development and corridor improvements
27.037Parking standards adjustment
27.038Pedestrian/resident friendly, bicycle friendly, transit-oriented community design
27.039Renewable energy and solar energy
27.040Energy efficiency and energy stars
27.041Landfill methane capture strategies
27.042Zero waste reduction and high recycling strategy
27.043Creation of conservation zones or protected areas
27.044Watershed-based and ecosystem-based land management
27.045Vegetation protection
27.046Establish implementation priorities for actions
27.047Financial/budget commitment
27.048Identify roles and responsibilities among sectors and stakeholders
27.049Continuous monitoring, evaluation and update
27.050Overall energy efficiency gains
27.051Final intensity
27.052Primary intensity
27.053Energy efficiency gains
27.054Energy intensity (industry, manufacturing, chemicals, European Union structure)
27.055Specific consumption (steel, cement, paper)
27.056Energy efficiency gains
27.057Consumption per unit of traffic (road car equivalent, freight, air)
27.058Car efficiency (fleet average, new cars)
27.059Mobility in transport (public transport, freight)
27.060Energy efficiency gains
27.061Consumption per dwelling (total, electricity, scaled to European Union climate)
27.062Heating consumption (per dwelling, per m2)
27.063Energy consumption per employee (total, electricity)
27.064Energy intensity (total, electricity)
Table A2. Variables excluded for non-applicability in the systematic literature review process.
Table A2. Variables excluded for non-applicability in the systematic literature review process.
CodeVariable
1.004Recent change in government
1.005Presence of champions
1.008International processes
1.009Focusing events
1.010Action of feedback mechanism
4.007World City Rank
4.009Location
9.002Demand elasticity
9.009Endogenous resources potential and prices
9.010Import/export prices and boundaries
10.003Results in terms of GHG emissions reduction
10.004Geography
10.005Business structure
10.006Physical circumstances
11.005Policy output
11.006Policy outcome
11.007Policy impact
12.008Share of population living in large cities
12.037Specific energy consumption for cooking in urban dwellings
12.039Specific energy consumption per urban dwelling for electric appliances
12.041Specific fossil fuel consumption per urban dwelling for lighting and non-electric appliances
12.063Specific energy consumption for cooking in rural dwellings
12.065Specific energy consumption per rural dwelling for electric appliances
12.067Specific fossil fuel consumption per rural dwelling for lighting and non-electric appliances
15.006Fertilization
15.007Pasture improvement
15.015Shift to commodity production
15.016Foreign debt, balance of trade
15.017Resource allocation rules and institutions
15.018Capital extraction
15.019Political corruption
15.020Frontier development
15.023Acceptance of corruption
17.007Non-residential building
17.008Latitude
17.011Number of certified buildings
17.013Street lighting expenditure
18.007Herfindahl–Hirschman index (degree of competition in the national electricity system)
18.013Carbon intensity of fuels
18.015Annual energy demand
20.001Total consumption
21.007Changes in manufacturers assortment
22.001Surface area to volume ratio
22.002Orientation of the facades’ transparent elements
22.003Thermal zoning of the building and the separation of its unheated parts from the thermal envelope
22.004Heated area per occupant
26.001Electricity market structure and design
26.002Interconnection of domestic electricity markets in Europe
26.003Primary factor: labor, capital, conventional and non-conventional resources
26.004Supply and demand parameters
26.005Incumbent policy framework included in the reference scenario
26.007Renewable energy source potential
26.009Emissions of other air pollutants
26.011Firm behavior
26.012Allowance trade patterns among regions
26.014Interconnection of domestic electricity markets in Europe
26.016Supply and demand parameters
26.017Firm behavior
26.019Limited analysis of constraints in output
26.020Slope of demand and supply curves
26.049Circumstances in which to apply policy instrument (challenges in addressing different target groups, challenges in addressing different scopes, addressing a financial, knowledge barrier, internalizing externalities, addressing market competition, conditions under which a policy combination is required, conditions of policy redundancy)
26.050Implicit and explicit assumptions in the policy implementation process and mapping the cause-impact relationships
26.051Transaction costs related to the combined policy cycle
26.052Regulatory decisions on the additionality of energy savings from individual projects
27.004Coastal distance
27.006Hazard damage
27.007Energy consumption
27.019Emissions inventory
27.020Base year emissions
27.022Vulnerability assessment
27.024Using analysis tools
27.062Heating consumption (per dwelling, per m2)
27.063Energy consumption per employee (total, electricity)
Table A3. Variables excluded for explicit repetition in the systematic literature review process.
Table A3. Variables excluded for explicit repetition in the systematic literature review process.
CodeVariable
1.011Timeframe
1.013Policy instruments
1.015Target of policy (actors)
1.016Source of authority at different stages (Hybrid or Government)
2.002Structure, main sectors
2.003Structure, subsectors
2.004Structure, final demand
2.005Savings, final demand
2.006Conversion efficiency end-users
2.007Co-generation end-users
2.008Fuel mix end-users
2.009Export
2.010Structure electricity production sectors
2.011Co-generation electricity production sectors
2.012Import
2.013Fuel mix electricity production sectors
3.004GDP growth (GDP growth rate)
4.003Population
4.004Density
4.005GDP
4.010Dates
4.011Urban character
4.017Actors involved
4.020Environmental justice
5.010Population
5.027Population
7.002Average number of inhabitants
9.001Annual growth rate of the socio-economic indicator
9.008Other information (discount rate, etc.)
11.001Objectives
11.002Instruments
12.009GDP
12.010Average annual growth rate of GDP
12.011Distribution of GDP formation by kind of economic activity
12.013Energy intensities in industry
13.001Population
13.002Floor area per capita
13.003Persons per household
13.004Appliances ownership per capita
13.016Services value-added
13.018Industry subsectors value-added
13.021Agriculture value-Added
14.006GDP
16.001Population
16.002Population growth rate
16.003Size of households
16.005GDP
16.006Growth rate of GDP
16.011Investment costs
17.001Population
17.006Civic
17.010Time
17.014Use of soft modes
18.002City size (population)
18.009City’s population
18.010Wealth (GDP per capita)
18.016Policy type (Financial/Non-financial)
20.004Education of occupants
20.006Urbanity
24.001Population
24.003Persons per household
24.006Total passenger-kilometers
24.007Distribution of passenger-kilometers per mode
24.008Energy/passenger-kilometer per mode
24.009Distribution of value-added per subsector
25.007GDP
26.008Efficiency of the whole electricity system
26.048Implementation period of the policy instrument
27.008Light transportation (soft modes and public transportation)
27.023Cost estimates for GHG emissions reduction
27.047Financial/budget commitment
27.049Continuous monitoring, evaluation and update
27.059Mobility in transport (public transport, freight)
27.061Consumption per dwelling (total, electricity, scaled to European Union climate)
Table A4. Variables excluded for implicit repetition in the systematic literature review process.
Table A4. Variables excluded for implicit repetition in the systematic literature review process.
CodeVariable
1.003Favorable party platform
1.007Availability of technology
1.012Reporting nature
3.005Structure, main sectors (growth rate main sectors)
3.006Structure, subsectors (growth rate per subsector)
4.001Country
4.002Urban area
4.006GDP per capita
4.008Annual population rank
4.013Objectives
4.016Sector specific information
4.022Action type of schemes
5.005Involvement of stakeholders and citizens
5.009Year
7.001Total dwelling area
7.003Number of appliances per type
7.004Number of vehicle-kilometers of personal cars per fuel
7.005Number of passenger-kilometers per mode (except car)
7.006Number of vehicle-kilometers of freight road transportation
7.007Number of ton-kilometers per mode (other freight transportation)
7.008Number of employee-years
8.002Population
9.003Autonomous efficiency improvement factor (industrial sectors)
10.002Formulation of the climate-policy strategy
10.007Actors involvement
11.003Means—Societal
12.001Total population
12.002Average annual growth rate of population
12.004Average household size in urban areas
12.005Average household size in rural areas
12.006Share of population of age 15–64 in total population
12.016Share of transportation modes in the total demand for freight transportation
12.017Energy intensity of freight transportation modes
12.020Share of transportation mode(s) in the total demand for intracity passenger transportation
12.021Energy intensity of transportation mode(s) in intracity travel
12.027Share of public transportation mode(s) in the intercity passenger travel by public modes
12.028Energy intensity of transportation mode(s)
12.029Fraction of urban dwellings in areas where space heating is required
12.030Degree days for urban dwellings
12.031Fraction of urban dwellings per type
12.032Average size of urban dwellings by type
12.033Fraction of floor area that is actually heated in urban areas per dwelling type
12.034Specific heat loss rate by urban dwelling type
12.036Specific cooling requirements by urban dwelling type
12.038Share of urban dwellings with hot water facilities
12.055Fraction of rural dwellings in areas where space heating is required
12.056Degree days for rural dwellings
12.057Fraction of rural dwellings per type
12.058Average size of rural dwellings by type
12.059Fraction of floor area that is actually heated in rural areas per dwelling type
12.060Specific heat loss rate by rural dwelling type
12.062Specific cooling requirements by rural dwelling type
12.064Share of rural dwellings with hot water facilities
13.019Share of total value-added by subsector
13.022Share of total value-added by subsector
13.024Changes in CO2 intensity
13.025Changes in input coefficients
13.026Changes in the composition of final demand
13.027Changes in the level of final demand (economic growth)
14.005Share of rural population
14.007GDP growth rate
14.008Monetary values per capita of the major sectors and subsectors
14.009Efficiency of appliances/vehicles
15.009Agricultural intensification
15.010Urbanization
16.004Number of households
16.010Competences of local authorities in implementation fields
17.009Ped/bike mode share
17.012Share of renewable energy sources electricity microgeneration
18.001City power (EU, 2007)
18.008Degree of electricity generated in combined heat and power systems
18.011Climate (Heating Degree Days)
18.014Targets set by each city for GHG emissions reductions
19.001Policy instrument combinations
19.002Obligating/Incentivizing balance
19.003Long-term program
19.004Non-generic instruments
19.005Primacy to energy efficiency
19.006Whole house/deep retrofit
19.007Energy sufficiency
20.002Household size
21.001Changes in knowledge
21.002Awareness and behavior of important actors
21.003Technology performance
21.006Market share
25.001Carbon intensity of road transport
25.002Energy intensity of road transport
25.003Use intensity
25.006Workers income intensity
26.018Simplification in technology production options and load segments of electricity production
26.023Trading options
26.024Banking of emissions
26.025Alternative compliance payments
26.026Distinctions between price based or quantity-based policy instruments with variations in prices and quotas for commodities
26.027Uniform/Differentiated feed in tariff rate
26.028Phase in of Renewable Portfolio Standard
26.029Annual digression rate of feed in tariff rate
26.030Limitation of the payment period
26.031Tariff reduction due to inflation
26.032Distinctions between price based or quantity-based policy instruments with variations in prices and quotas for commodities
26.033International emissions trading
26.034Uniform and unilateral imposition of carbon taxes across all EU-ETS regions
26.035Lump-sum treatment of additional tax revenues
26.036Stringency levels
26.037Different application scope
26.038Nature of targets, the target groups, the policy-implementing agents, the available budget, the available information on the initially expected energy-savings impact, and the cost effectiveness of the instrument
26.039Distinctions between price-based or quantity-based policy instruments
26.040Different renewable energy sources and support design elements
26.041Variable scenarios in the short and long run for key policy parameters such as price of certificate, level of obligation, level of sales tax and the level of penalty
26.042Fixed-price policies and endogenous price policies
26.043Technology specific hurdle rates reflecting market barriers, consumer preferences and risk factors limiting purchase of new energy technologies
26.044Conditions for implementation and proper utilization of saving options (technology equipment availability, familiarity with the policy, overcoming barriers, motivation to invest)
26.045Specific implementation of policy instruments with regard to their funding
27.002State-level mandates concerning climate change (national)
27.010Vehicular emission
27.018Long-term goals and detailed targets for GHG emissions
27.021Emissions trend forecast
27.025Public awareness, education, and participation
27.026Inter-organizational coordination procedures
27.027GHG emissions reduction fee
27.028Establish a carbon tax
27.029Disaster resistant land use and building code
27.030Mixed use and compact development
27.031Infill development and reuse of remediated brownfield sites
27.032Green building and green infrastructure
27.033Low-impact design for impervious surface
27.034Control of urban service/growth boundaries
27.035Alternative transportation strategies
27.036Transit-oriented development and corridor improvements
27.037Parking standards adjustment
27.038Pedestrian/resident friendly, bicycle friendly, transit-oriented community design
27.039Renewable energy and solar energy
27.040Energy efficiency and energy stars
27.041Landfill methane capture strategies
27.042Zero waste reduction and high recycling strategy
27.043Creation of conservation zones or protected areas
27.044Watershed-based and ecosystem-based land management
27.045Vegetation protection
27.048Identify roles and responsibilities among sectors and stakeholders
27.050Overall energy efficiency gains
27.053Energy efficiency gains
27.054Energy intensity (industry, manufacturing, chemicals, European Union structure)
27.055Specific consumption (steel, cement, paper)
27.057Consumption per unit of traffic (road car equivalent, freight, air)
27.058Car efficiency (fleet average, new cars)
27.060Energy efficiency gains
Table A5. Variables excluded to avoid the presence of dependent variables in the systematic literature review process.
Table A5. Variables excluded to avoid the presence of dependent variables in the systematic literature review process.
CodeVariable
1.002Favorable public opinion
1.006Social appeal
3.001Energy statistics (statistical figures)
3.007Structure, final demand (Reference final demand per subsector)
3.008Savings, final demand (Actual final heat/electricity demand)
3.009Conversion efficiency end-users (Actual efficiency boilers, etc.)
4.015Institutional factors
4.019Mode of governance
7.009Production of goods per type (piece, kg or m2)
7.010Cultivated land area
7.011Raising of cattle, pigs and chickens
7.012Volume index of production
8.001Gross domestic product (GDP)
11.004Means—Policy process
12.014Penetration of energy carriers into useful thermal energy demand of the different sectors
12.018Average intracity distance traveled per person per day
12.019Average load factor of intracity passenger transportation mode(s)
12.022Average intercity distance traveled per person per day
12.024Average intercity distance driven per car per year
12.025Average load factor of intercity transportation mode(s)
12.026Share of car type(s) in the intercity transportation mode(s)
12.035Share of urban dwellings with air conditioning, by dwelling type
12.040Electricity penetration for appliances in urban households
12.042Penetration of various energy forms into space heating in urban households
12.043Efficiency of various fuels use, relative to that of electricity use, for space heating in urban households
12.044Coefficient of performance of heat pumps for space heating in urban households
12.045Penetration of various energy forms into water heating in urban households
12.046Efficiency of various fuels use, relative to that of electricity use, for water heating in urban households
12.047Coefficient of performance of heat pumps for water heating in urban households
12.048Approximate share of water heating demand in urban households that can be met with solar installations
12.049Penetration of various energy forms into cooking in urban households
12.050Efficiency of various fuels use, relative to that of electricity, for cooking in urban households
12.051Approximate share of cooking demand in urban households that can be met with solar installations
12.052Share of air conditioning demand of urban households that can be met with electricity
12.053Coefficient of performance of electric air conditioning in urban households
12.054Coefficient of performance of non-electric air conditioning in urban households
12.061Share of rural dwellings with air conditioning, by dwelling type
12.066Electricity penetration for appliances in rural households
12.068Penetration of various energy forms into space heating in rural households
12.069Efficiency of various fuels use, relative to that of electricity use, for space heating in rural households
12.070Coefficient of performance of heat pumps for space heating in rural households
12.071Penetration of various energy forms into water heating in rural households
12.072Efficiency of various fuels use, relative to that of electricity use, for water heating in rural households
12.073Coefficient of performance of heat pumps for water heating in rural households
12.074Approximate share of water heating demand in rural households that can be met with solar installations
12.075Penetration of various energy forms into cooking in rural households
12.076Efficiency of various fuels use, relative to that of electricity, for cooking in rural households
12.077Approximate share of cooking demand in rural households that can be met with solar installations
12.078Share of air conditioning demand of rural households that can be met with electricity
12.079Coefficient of performance of electric air conditioning in rural households
12.080Coefficient of performance of non-electric air conditioning in rural households
12.081Share of service sector in the total active labor force
12.082Average floor area per employee in the Service sector
12.083Share of Service sector floor area requiring space heating
12.084Share of Service sector floor area requiring space heating that is actually heated
12.085Specific space heat requirements of Service sector floor area
12.086Share of air-conditioned Service sector floor area
12.087Specific cooling requirements in the Service sector
12.088Energy intensity of motor fuel use per Services’ subsector
12.089Energy intensity of electricity specific uses per Services’ subsector
12.090Energy intensity of thermal uses (except space heating) per Services’ subsector
12.091Penetration of various energy forms into space heating in Service sector
12.092Penetration of various energy forms into other thermal uses in the Service sector
12.093Efficiency of various fuels use, relative to that of electricity use, for thermal uses in Service sector
12.094Coefficient of performance of heat pumps in space heating in Service sector
12.095Share of low-rise buildings in the total Service sector floor area
12.096Approximate share of thermal uses in the Service sector that can be met by solar installations
12.097Share of air-conditioning that can be met with electricity
12.098Coefficient of performance of electric air conditioning in Service sector
12.099Coefficient of performance of non-electric air conditioning in Service sector
13.009Energy per appliance
13.013Tons-kilometers
13.014Share of total ton-kilometers by mode
13.020Energy per value-added by subsector
14.001Population growth
14.004Share of the population outside the community
15.004Irrigation development
15.005Mechanization
15.008Industrialization infrastructure
15.011Poverty
15.014State policy
15.022Mass-consuming view of nature
16.007Measures and policies already promulgated
16.012Implementation experiences
17.003Average income
17.005Environmental voting
18.003Legal structure and status
18.004Spending power
18.005Control over income
20.003Age of occupants
20.005Dwelling type
21.004Price development
21.005Sales data
23.001Attitude factors
23.002Economic factors
23.003Social factors (impact on agents’ attitude)
24.010Average energy/value-added per subsector
25.004Motorization rate
25.005Job intensity
26.006Different renewable energy sources penetration levels
26.010Discount rate for investments
26.013Socio-demographic and lifestyle trends
26.015Political context in which policy instruments are imposed
26.046Transaction costs
26.047Stability and credibility in policy regime
27.001Political will
27.003Wealth
27.005Population density
27.051Final intensity
27.052Primary intensity

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Figure 1. Schematic representation of the systematic literature review process.
Figure 1. Schematic representation of the systematic literature review process.
Energies 13 03205 g001
Figure 2. Framework of the sources of change and the observed changes in local GHG emissions.
Figure 2. Framework of the sources of change and the observed changes in local GHG emissions.
Energies 13 03205 g002
Table 1. Systematic literature review specifications.
Table 1. Systematic literature review specifications.
ObjectiveIdentify and Characterize Factors of Change of Local Energy Systems
Documents Selection
Search expressions“Energy system characterization”
“Energy system modeling/modelling”
“Energy system planning”
“Energy system scenarios”
“Energy policy evaluation”
“Local climate change mitigation”
Type of documentsPeer-reviewed articles
Reports and working papers from internationally reputed entities
PhD theses
Type of contentFactors that lead to changes in GHG emissions
Characterizing variables of those factors
Information on the relation between factors of change and local GHG emissions
Table 2. Characterization of the documents used for the identification of the factors of change.
Table 2. Characterization of the documents used for the identification of the factors of change.
CodeStudyAuthorsYearTopic/ThemeDoc. TypeRef.
1“Evaluating the effects of policy innovations: Lessons from a systematic review of policies promoting low-carbon technology”Auld, G., Mallet, A., Burlica, B., Nolan-Poupart, F., Slater, R.2014Policy EvaluationJP[7]
2“Energy and emission monitoring for policy use—Trend analysis with reconstructed energy balances”Boonekamp, P.G.M.2004Policy EvaluationJP[8]
3“Improved methods to evaluate realized energy savings”Boonekamp, P.G.M.2005Policy EvaluationPhD[9]
4“A survey of urban climate change experiments in 100 cities”Broto, C.B., Bulkeley, H.2013Multilevel governanceJP[10]
5“Reporting Guidelines on Sustainable Energy Action Plan and Monitoring”Covenant of Mayors (European Union)2010Policy EvaluationPR[11]
6“Cities, Climate Change and Multilevel Governance”Corfee-Morlot, J., Kamal-Chaoui, L., Robert, A., Teasdale, P.J.2009Multilevel governanceWP[12]
7“The use of physical indicators for the monitoring of energy intensity developments in the Netherlands, 1980–1995”Farla, J.C.M., Blok, K.2000Energy useJP[13]
8“Long-term energy scenarios: Bridging the gap between socio-economic storyline and energy modeling”Fortes, P., Alvarenga, A., Seixas, J., Rodrigues, S.2015Energy planningJP[14]
9“Integrated technological-economic modelling platform for energy and climate policy”Fortes, P., Pereira, R., Pereira, A., Seixas J.2014Energy planningJP[15]
10“Multilevel governance, networking cities, and the geography of climate-change mitigation: two Swedish examples”Gustavsson, E., Elander, I., Lundmark, M.2009Multilevel governanceJP[16]
11“Evaluating the effectiveness of environmental policy: A analysis of conceptual and methodological issues”Gysen, J, Bachus, K., Bruyninckx, H.2002Policy evaluationCP[17]
12“Model for Analysis of Energy Demand (MAED-2)—Computer Manual Series N° 18”International Atomic Energy Agency2006Energy useTR[18]
13“Energy Efficiency Indicators: Essentials for Policy Making”International Energy Agency2014Energy planningPR[19]
14“An analytical method for the measurement of energy system sustainability in urban areas”Jovanovic, M., Afgan, N., Bakic, V.2010Energy useJP[20]
15“Regions at Risk: Comparisons of Threatened Environments”Kasperson, J.X., Kasperson, R.E, Turner, B.L.1995Policy EvaluationBk[21]
16“Evaluating the effectiveness of urban energy conservation and GHG mitigation measures: The case of Xiamen city, China”Lin, J., Cao, B., Cui, S., Wang, W., Bai, X.2010Policy evaluationJP[22]
17“Do city climate plans reduce emissions?”Millard-Ball, A.2012Policy evaluationJP[3]
18“A comparative analysis of urban energy governance in four European cities”Morlet, C., Keirstead, J.2013Multilevel governanceJP[23]
19“A qualitative evaluation of policy instruments used to improve energy performance of existing private dwellings in the Netherlands”Murphy, L., Meijer, F., Visscher, H.2012Policy evaluationJP[24]
20“Determinants of greenhouse gas emissions from Swedish private consumption: Time-series and cross-sectional analyses”Nassen, J.2014Energy useJP[25]
21“Outcome indicators for the evaluation of energy policy instruments and technical change”Neij, L., Astrand, K.2006Policy evaluationJP[26]
22“Simplified evaluation method for energy efficiency in single-family houses using key quality parameters”Praznik, M., Butala, V., Senegacnik, M.Z.2013Energy useJP[27]
23“Agent-based modeling of energy technology adoption: Empirical integration of social, behavioral, economic, and environmental factors”Rai, V., Robinson, S.A.2015Energy planningJP[28]
24“Indicators of Energy Use and Carbon Emissions: Explaining the Energy Economy Link”Schipper, L., Unander, F., Murtishaw, S., Ting, M.2001Energy useJP[29]
25“The impact of the economic crisis and policy actions on GHG emissions from road transport in Spain”Sobrino, N., Monzon, A.2014Policy evaluationJP[30]
26“A paper trail of evaluation approaches to energy and climate policy interactions”Spyridaki, N.A., Flamos, A.2014Policy evaluationJP[31]
27“Moving from agenda to action: evaluating local climate change action plans”Tang, Z., Brody, S.D., Quinn, C., Chang, L., Wei, T.2010Policy evaluationJP[32]
28“Global change in local places: How scale matters”Wilbanks, T.J., Kates, R.W.1999Multilevel governanceJP[33]
Legend: JP, peer-reviewed journal article; WP, working paper; CP, conference paper; Bk, Book; PhD, PhD thesis; PR, policy report; TR, technical report.
Table 3. Final list of variables and respective grouping into factors of change.
Table 3. Final list of variables and respective grouping into factors of change.
Factor of Change Variables Identified in the Literature Review
Statistical differences3.002Corrected statistics
Local inhabitants’ characteristicsEducational level17.004Education
Cultural diversity15.021Ethnic/religious views
Willingness to act18.006Civic involvement (voting patterns)
27.015Concept of climate change (awareness of)
27.016Concept of GHG emissions (awareness of)
27.017Effects and impact of CC (awareness of)
Local administration characteristicsCompetences6.0005Local authority’s responsibilities and competences
Qualified personnel6.002Existence of a dedicated institution/agency to deal with CC mitigation actions/plans
6.003Local authority’s capacity and expertise on CC mitigation
Economic situation6.004Local authority’s ability to obtain funding
Ratio between income and expenses
Climate variability3.003Climate (degree-days)
Demographic evolutionPopulation growth/change15.002Natural growth
15.003Migration
Migration to urban areas12.003Share of urban population
Age pyramid14.003Share of potential labor force
Social evolutionHousehold conditions14.002Persons per household
24.002Floor area per capita
24.004Heat per floor area
13.005Appliances ownership per capita
13.006DWH energy per capita
13.007Cooking energy per capita
13.008Lighting per floor area
Commuting needs and transportation habits13.010Pkm
12.023Inverse of car ownership ratio
13.011Share of total pkm by mode
27.009Average commuting time
Economic evolutionOverall local economy2.001GDP growth
Structure of local economy8.004GVA agriculture
8.005GVA services
8.006GVA transports
8.007GVA industry
12.012Distribution of sectors GVA by subsectors
Economic situation of individuals17.002Employment
8.003Private consumption
Technology evolutionMarket drivers/barriers26.022Technology market failures and other externalities related to electricity generation design
9.006Technical and costs evolution
9.007Availability and capacity limits (technology)
Technical evolution12.015Average efficiencies of fuels for thermal uses per sector
27.064Energy intensity
Technical evolution (Buildings)14.010Buildings insulation
24.005Intensity for different uses
13.017Energy per value-added (services)
Technical evolution (Transports)13.012Energy per pkm by mode
13.015Energy per tkm by mode
Technical evolution (Agriculture)13.023Energy per value-added by subsector
Electricity generation and other energy transformation processes3.010Cogeneration end-users
3.011Fuel-mix end-users (actual energy use)
3.012Export (actual energy exports)
3.013Structure e-sectors (reference use refineries/gas supply)
3.014Cogeneration e-sectors
3.015Efficiency e-sectors (actual conversion efficiencies)
3.016Import (actual energy imports)
3.017Fuel-mix e-sectors
State and international governance frameworkExisting policies9.004Energy and environmental policies
15.012International market
15.013National market
Energy costs18.012Price of energy and relative share of any taxes or levies (energy costs)
Synergies with local-level actions6.001Coherent multi-level policy framework (vertically and horizontally)
6.006Support from central governments to local policies
Actors involvedSEAP preparation5.015Decision body approving the plan
5.003Coordination and organizational structures created/assigned
5.004Staff capacity allocated
SEAP implementation10.001Actors involved in local CC mitigation
5.019Origin of the action (local or other)
5.020Responsible body
Timeframe5.014Date of approval
5.021Implementation timeframe
Targets5.001Overall CO2 reduction target
5.002Vision
Current implementation status1.014State of activity
5.026Newest inventory year
5.031Status implementation
5.006Overall estimated budget for the SEAP implementation
Estimated impactBase year inventory5.011Final energy consumption per sector and carrier
5.012Energy supply sources
5.013CO2 emissions per sector and carrier
BAU projections5.016BAU projections
Overall estimated impact5.023Energy savings
5.024Renewable energy production
5.025CO2 reduction
Mid-term inventory5.028Final energy consumption per sector and carrier
5.029Energy supply sources
5.030CO2 emissions per sector and carrier
Mid-term estimated impact5.033Renewable energy production from actions implemented so far
5.034CO2 reduction from actions implemented so far
5.009Description of the impact of instruments
BudgetOverall5.022Estimated implementation costs
Spent so far5.032Implementation cost spent so far
Financing sources4.018Funding
5.007Foreseen financing sources for the implementation
Actions characterizationArea of intervention5.017Area of intervention
Technical measure4.021Action targeted sectors
16.008Measure/action
16.009Intensity of measure (degree of implementation)
Instruments4.012Type of experiment
4.014Type of innovation
1.017Presence of flexibility mechanisms
19.008Policy theory associated with instruments applied
5.018Policy instrument
Other process characteristics1.001Agenda setting process
27.046Establish implementation priorities for action
5.008Monitoring process
Table 4. Factors of change associated with local context with corresponding indicators.
Table 4. Factors of change associated with local context with corresponding indicators.
Factor of ChangeCharacterizing (and Quantifiable) IndicatorUnit
Local inhabitants’ characteristicsEducation levelDistribution of local population per education levelDimensionless (%)
Cultural diversityValid permits by reason per 1000 inhabitants# permits/1000 inhab.
Willingness to act
AwarenessShare of waste that is separated previous to collection (recycling)Dimensionless (%)
Civic involvementNumber of environmental nonprofits per 1000 inhabitants# groups/1000 inhab.
Local authority characteristicsLegal competencesLevel of autonomy (High, Medium, Low)Nominal variable
Qualified personnel
Dedicated institution/agency for CC mitigationY/N (or Number of people assigned to CC mitigation issues)# people
Previous experiences related with CC mitigationY/Nn.a.
Economic situation
Ability to obtain fundingGlobal ranking of the municipalities’ financial situationDimensionless
Relation between income and expensesRatio between income and expensesDimensionless
Table 5. Factors of change associated with local socio-economic and cultural changes with corresponding indicators.
Table 5. Factors of change associated with local socio-economic and cultural changes with corresponding indicators.
Factor of ChangeCharacterizing (and Quantifiable) IndicatorUnit
Climate variability Heating Degree DaysHDD
Cooling Degree DaysCDD
Demographic evolutionPopulation growthChange of overall population# inhabitants
Migration to urban areasShare of rural populationDimensionless (%)
Age pyramidShare of active populationDimensionless (%)
Social evolutionHousehold conditionsPersons per householdPerson/household
Floor area per personm2/cap
Commuting needsAverage commuting needskm/person.day
Transportation habitsCar ownershipcars/cap
Economic evolutionOverall growth of local economyLocal GDP change
Structure of local economyGVA per sector (or number of employees)
Economic situation of households:
EmploymentUnemployment rateDimensionless (%)
Private consumptionPrivate Purchase Power€/cap
Table 6. Factors of change related to higher-level governance framework with corresponding indicators.
Table 6. Factors of change related to higher-level governance framework with corresponding indicators.
Factor of ChangeCharacterizing (and Quantifiable) IndicatorsUnit
Technology EvolutionTechnical evolutionNational average energy intensity per sectorkWh/€
Market evolution:
Technology costsOver cost of A++ appliances compared to B equivalent
Market barriersEnergy efficiency gap
Energy supply sector:
Fuel-mix of electricity and heat generationShare of renewable energy sources (RES)Dimensionless (%)
Efficiency of energy transformation sectorOverall efficiency and lossesDimensionless (%)
National and international energy-related policiesExisting policiesPublic and private investments on environmental management and protection per economic activity (cumulative values)
Energy costsAverage energy cost for final consumer€/kWh
Coherence with local policiesAlignment between different scales objectives?(Y/N)
Support of local actionInitiatives to promote local action (Number)# initiatives
Table 7. Factors of change associated with local climate change mitigation actions with corresponding indicators.
Table 7. Factors of change associated with local climate change mitigation actions with corresponding indicators.
Factor of ChangeCharacterizing (and Quantifiable) IndicatorsUnit
Actors involvementAction plan preparationGroups of actors involvedNominal variable
Action plan implementationGroups of actors involvedNominal variable
TimeframeStudyBase Year and Time HorizonYear
Action plan implementationBeginning and End of action plan implementationYear
TargetsVisionOther goals besides GHG emissions reduction(Y/N)
GHG emissions reduction ton CO2 eq.
Current implementation statusOverallShare of the overall plan already implementedDimensionless (%)
Per actionShare of the individual measure already implementedDimensionless (%)
Estimated impactBase year inventoryIn terms of final energy and GHG emissions reduction (measured)GWh/a
ton CO2 eq./a
BAU projectionsIn terms of final energy and GHG emissions reduction (predicted)GWh/a
ton CO2 eq./a
Latest inventoryIn terms of final energy and GHG emissions reduction (measured)GWh/a
ton CO2 eq./a
BudgetOverall
Spent so far
Financing sourcesEntity(s) responsibleEntities financing local actions (per category)Nominal variable
Share of overall investment costsFraction of overall investment that is financed by each entityDimensionless (%)
Actions characterizationArea of interventionSector and subsector targeted
Technical measure:
MeasureBuilding retrofit, modal shift in transports, led street lights, etc.Nominal variable
Level of implementationShare of the sector/subsector impacted by the actionDimensionless (%)
Estimated impactIn terms of final energy and GHG emissions reductionGWh/a
ton CO2 eq./a
Policy instrument:
TypeRegulation, incentive, education, etc.Nominal Variable
Level of supportShare of financing provided by the instrumentDimensionless (%)
Stakeholders involvement Nominal variable

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MDPI and ACS Style

Azevedo, I.; Leal, V. Factors That Contribute to Changes in Local or Municipal GHG Emissions: A Framework Derived from a Systematic Literature Review. Energies 2020, 13, 3205. https://doi.org/10.3390/en13123205

AMA Style

Azevedo I, Leal V. Factors That Contribute to Changes in Local or Municipal GHG Emissions: A Framework Derived from a Systematic Literature Review. Energies. 2020; 13(12):3205. https://doi.org/10.3390/en13123205

Chicago/Turabian Style

Azevedo, Isabel, and Vítor Leal. 2020. "Factors That Contribute to Changes in Local or Municipal GHG Emissions: A Framework Derived from a Systematic Literature Review" Energies 13, no. 12: 3205. https://doi.org/10.3390/en13123205

APA Style

Azevedo, I., & Leal, V. (2020). Factors That Contribute to Changes in Local or Municipal GHG Emissions: A Framework Derived from a Systematic Literature Review. Energies, 13(12), 3205. https://doi.org/10.3390/en13123205

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