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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Environ. Sci.</journal-id>
<journal-title>Frontiers in Environmental Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Environ. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-665X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">985340</article-id>
<article-id pub-id-type="doi">10.3389/fenvs.2022.985340</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Environmental Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Modeling energy governance index for the adequacy of policy, legal, and institutional response measures for climate compatible development</article-title>
<alt-title alt-title-type="left-running-head">Iqbal et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fenvs.2022.985340">10.3389/fenvs.2022.985340</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Iqbal</surname>
<given-names>Kanwar Muhammad Javed</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1896791/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Waheed</surname>
<given-names>Farah</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1896563/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Azhar</surname>
<given-names>Urooj</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Akhtar</surname>
<given-names>Nadia</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1976740/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Khan</surname>
<given-names>Muhammad Irfan</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1925391/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>National Institute of Maritime Affairs</institution>, <institution>Bahria University</institution>, <addr-line>Islamabad</addr-line>, <country>Pakistan</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Management Studies Department</institution>, <institution>Bahria Business School</institution>, <institution>Bahria University</institution>, <addr-line>Islamabad</addr-line>, <country>Pakistan</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Environmental Science</institution>, <institution>International Islamic University</institution>, <addr-line>Islamabad</addr-line>, <country>Pakistan</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1455825/overview">Vishal Dagar</ext-link>, Great Lakes Institute of Management, India</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1844149/overview">Sumit Dagar</ext-link>, Delhi Technological University, India</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1819814/overview">Sakshi Malik</ext-link>, O.P. Jindal Global University, India</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Farah Waheed, <email>fwaheed.buic@bahria.edu.pk</email>; Kanwar Muhammad Javed Iqbal, <email>kanwar.javediqbal@gmail.com</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Environmental Economics and Management, a section of the journal Frontiers in Environmental Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>12</day>
<month>09</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>10</volume>
<elocation-id>985340</elocation-id>
<history>
<date date-type="received">
<day>03</day>
<month>07</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>26</day>
<month>07</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Iqbal, Waheed, Azhar, Akhtar and Khan.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Iqbal, Waheed, Azhar, Akhtar and Khan</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Climate compatible and sustainable expansion of energy resources is a major global challenge. Developing countries, with inadequate resources and incoherent policies, and legal and institutional frameworks must strive hard to achieve targets set by the Sustainable Development Goals (SDGs) while keeping track of Nationally Determined Contributions for Greenhouse Gas (GHG) emissions abatement. Inclusive governance is quite complex due to the interplay of informal and formal systems, rules-based to rights-based approaches, and arrangements in national to local scenarios <italic>vis-&#xe0;-vis</italic> methodological limitations. In this context, this study aims at developing a governance index for assessing climate compatible development (CCD) by taking case of the energy sector in Pakistan. The study adopted a two-step approach to develop and validate a methodological framework for assessing the adequacy of governance. In the first step, a multivariate analysis model was developed using principle (CP-1), criteria (09), and 43 indicators (PCIs) through stakeholder involvement. In the second step, the model was deployed by combining the Multi Criteria Decision Analysis method with statistical analysis of the dataset. Data were collected from federal and provincial capitals as well as ten districts through a structured scoring matrix consisting of all 43 indicators. The sample population was based on key informant interviews (340), and experts (17) who were engaged through focus group discussion at federal, provincial, and district levels. Respondents were asked to score against each indicator on a ratio scale, which was then aggregated to develop a governance index score. The findings reveal the dearth of a preemptive and comprehensive governance to address climate compatible development in the energy sector in all tiers of constituencies in Pakistan. There is a need for coherent and inclusive policy, and a legal and institutional framework. This study&#x2019;s outcome authenticates the findings of United Nations SDGs Report 2020 that efforts to achieve sustainable energy targets are not up to scale and stresses the need to speed up the efforts and development of the associated governance framework for renewable energy to achieve climate compatible and SDGs.</p>
</abstract>
<kwd-group>
<kwd>energy sector</kwd>
<kwd>climate compatible development (CCD)</kwd>
<kwd>sustainable development</kwd>
<kwd>governance index</kwd>
<kwd>principles, criteria and indicators</kwd>
<kwd>MCDA</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>The cascading effects of the climatic phenomenon are attributed to all sectoral economies through its convergent evidences and manifestation in everyday life (<xref ref-type="bibr" rid="B8">Carvalho and Peterson 2009</xref>; <xref ref-type="bibr" rid="B35">H&#xf6;&#xf6;k and Tang 2013</xref>; <xref ref-type="bibr" rid="B78">Reser, Bradley, and Ellul 2014</xref>; <xref ref-type="bibr" rid="B40">IPCC 2018</xref>; <xref ref-type="bibr" rid="B43">Iqbal and Khan 2018</xref>; <xref ref-type="bibr" rid="B6">Blunden and Arndt 2019</xref>; <xref ref-type="bibr" rid="B94">WMO 2019</xref>). The energy sector is no exception, where a strong interplay of fossil fuel consumption, lifestyle changes, and growing concerns about environmental security and sustainable development makes the development of this sector more challenging (<xref ref-type="bibr" rid="B2">Ali and Iqbal 2017</xref>; <xref ref-type="bibr" rid="B17">Eleftheriadis and Anagnostopoulou 2017</xref>; <xref ref-type="bibr" rid="B45">Iqbal et al., 2020</xref>; <xref ref-type="bibr" rid="B33">Hassan et al., 2021</xref>). The United Nations&#x2019; SDGs Report of 2020 highlighted the unsustainable use of energy resources worldwide, as the anticipated target (3%) of energy efficiency is not yet achieved. Consequently, the global temperature is anticipated to rise (3.2&#xb0;C) by 2100. Annual global GHG emissions reduction targets are lagging behind (about 7.6%), mainly due to an injudicious use of energy resources (<xref ref-type="bibr" rid="B87">UN Statistics Division, United Nations, 2020</xref>). Sustainable and climate compatible energy development is among the major global challenges, particularly in the governance context of countries with a lack of adequate and coherent policies, and legal and institutional arrangements (<xref ref-type="bibr" rid="B49">Jiang et al., 2017</xref>; <xref ref-type="bibr" rid="B60">L&#xf3;pez-Ballesteros et al., 2020</xref>; <xref ref-type="bibr" rid="B66">Naseer, Iqbal, and Khan 2020</xref>; <xref ref-type="bibr" rid="B68">Nwedu 2020</xref>; <xref ref-type="bibr" rid="B91">Waheed, Fischer, and Khan 2021</xref>).</p>
<p>In order to address policy, and legal and institutional arrangements for energy security and sustainability, conformance between SDGs 7 and 13 is a prerequisite and foremost important element. SDG-7 aims at ensuring clean, affordable, accessible, and modern energy for all, while SDG-13 calls for climate action (<xref ref-type="bibr" rid="B52">Kaygusuz 2012</xref>; <xref ref-type="bibr" rid="B4">Armin Razmjoo, Sumper, and Davarpanah 2020</xref>; <xref ref-type="bibr" rid="B85">Swain and Amin 2020</xref>; <xref ref-type="bibr" rid="B15">Elavarasan et al., 2021</xref>). In theory, these two goals go hand in hand and form a synergistic relationship. Understanding the linkages between various aspects of SDGs may aid in developing a cross-sectoral program and policies that could lead to a synergistic functioning for developing and promoting renewables (<xref ref-type="bibr" rid="B95">Xu et al., 2019</xref>; <xref ref-type="bibr" rid="B92">Wei et al., 2020</xref>). However, the developing countries are facing challenges in shifting towards effective, sustainable, and climate compatible renewable energy (RE) solutions while fulfilling their rapidly growing energy demand. A lack of understanding of the linkages, flexible behavior about trade-offs, and poorly designed sectoral synergies have resulted in incoherent policies, adverse impacts of development on different sectors, lost opportunities for sustainable solutions, and a delayed outcome to progress. Overall, major challenges include high financing costs; insufficient infrastructure; inadequate skills for production and transmission; policy, legal, and regulatory barriers; lack of political will and institutional effectiveness; ownership problems; and poor understanding (<xref ref-type="bibr" rid="B22">Galera 2017</xref>; <xref ref-type="bibr" rid="B57">Liu et al., 2019</xref>; <xref ref-type="bibr" rid="B5">Asante et al., 2020</xref>; <xref ref-type="bibr" rid="B61">Mahama, Derkyi, and Nwabue 2020</xref>; <xref ref-type="bibr" rid="B89">Usman, Khalid, and Mehdi 2021</xref>).</p>
<p>Most important among the aforementioned factors is the issue of an ineffective policy and institutional framework to adapt to clean energy sources (<xref ref-type="bibr" rid="B22">Galera 2017</xref>; <xref ref-type="bibr" rid="B81">Sen and Ganguly 2017</xref>; <xref ref-type="bibr" rid="B99">Zafar et al., 2018</xref>; <xref ref-type="bibr" rid="B18">Erdiwansyah et al., 2019</xref>). The highly centralized system that depends on few actors often becomes hostile and non-hospitable for innovative technologies and suppliers. Many countries in the world still have their policies designed around the interests and monopoly of these giant inhospitable suppliers, acting as a policy barrier (<xref ref-type="bibr" rid="B16">Eleftheriadis and Anagnostopoulou 2015</xref>; <xref ref-type="bibr" rid="B37">Hu et al., 2018</xref>). Thus, modification of the existing laws is an imperative priority to make the industry and the stakeholders open to the idea of a clean energy mix. Overcoming inconsistent standards, compliance requirements, and regulations regarding RE buy-back schemes and feed-in tariffs could help in mainstreaming the RE forms in the developing world (<xref ref-type="bibr" rid="B72">Qazi et al., 2017</xref>; <xref ref-type="bibr" rid="B80">Seetharaman et al., 2019</xref>; <xref ref-type="bibr" rid="B50">Kamran, Fazal, and Mudassar 2020</xref>). This complex interplay of energy markets, technology, policies, social norms, and consumer preferences has affected, and will continue to affect, energy production and consumption and low carbon development, which ultimately links with a climate compatible and sustainable development (<xref ref-type="bibr" rid="B39">Ike et al., 2020</xref>). Besides, a lack of clarity and priorities with the crosscutting and rather conflicting nature of institutions also impede the progress on climate compatible energy sector development.</p>
<p>As of 2019, the global installed capacity of RE reached more than 200&#xa0;GW, with a significant share by the developing countries (<xref ref-type="bibr" rid="B38">IAEA 2020</xref>). At present, 17% of the total energy share is RE and this needs a boost, as 789 million people around the globe still lack access to electricity (<xref ref-type="bibr" rid="B4">Armin Razmjoo et al., 2020</xref>; <xref ref-type="bibr" rid="B87">UN Statistics Division, United Nations, 2020</xref>), provision of which raises serious concerns about its compatibility with climate mitigation targets. In the current scenario, SDGs serve as the primary driving instruments for the international community to set their policies and practices in line with the set and agreed targets. However, under the current policy arrangement status, many countries are lagging behind. For the Association of Southeast Asian Nations (ASEAN), the target (23%) for renewables seems ambitious unless comprehensive reforms in strategies are ensured (<xref ref-type="bibr" rid="B53">Khuong, McKenna, and Fichtner 2019</xref>). Similarly, the Nationally Determined Contribution (NDC) Statement (2016) of Pakistan also provided an ambitious commitment of reducing GHG emissions (26%) which will cost 40 billion US$ (<xref ref-type="bibr" rid="B88">UNFCCC 2016</xref>). Like Pakistan, many nations are still far behind in achieving SDG targets due to policy gaps and an ineffective implementation mechanism (<xref ref-type="bibr" rid="B53">Khuong et al., 2019</xref>; <xref ref-type="bibr" rid="B87">UN Statistics Division, United Nations 2020</xref>).</p>
<p>The sustainability goals for CCD require realizing the milestones of SDG-7 and SDG-13 together, which necessitates an inclusive governance mechanism. The mechanism should be able to put into practice a set of coherent and widely accepted policies, and legal and institutional arrangements with cross-sectoral integrations at all levels. However, the matter of inclusive energy governance is quite complex. It encompasses informal to formal systems and rules-based to rights-based approaches for policies. It will also require rearrangements in national, sub-national, and local institutional setups <italic>vis-&#xe0;-vis</italic> methodological procedures to assess and review the policies systematically and periodically. The informal governance concept is based on practices and processes without observing formal rules and procedures, and does not provide voting rights to the weak actors. The &#x201c;formal governance&#x201d; concept normally revolves around rules. Rules-based approaches are linked with the application of a top-down model, which raises concerns pertaining to stakeholders&#x2019; participation. Right-based approaches revolve around the rights, participation, and active engagement of all kind of relevant actors and the political economy (<xref ref-type="bibr" rid="B21">Follesdal, Christiansen, and Piattoni 2004</xref>; <xref ref-type="bibr" rid="B90">Visseren-Hamakers and Glasbergen 2007</xref>; <xref ref-type="bibr" rid="B79">Saunders and Reeve 2010</xref>; <xref ref-type="bibr" rid="B84">Stone 2011</xref>; <xref ref-type="bibr" rid="B54">Kleine 2014</xref>; <xref ref-type="bibr" rid="B70">Pierre and Peters 2020</xref>). Besides, the &#x201c;triple-win&#x201d; notion of CCD is participatory in nature and involves multi-sector and multi-actor approaches (<xref ref-type="bibr" rid="B65">Mitchell and Maxwell 2010</xref>). Thus, adopting traditional governance frameworks is unable to address the challenges faced by the energy sector. These challenges necessitate a proper methodological framework for periodic review about the adequacy, performance, and decision-making process at all levels of the energy governance mechanism in a country. However, a widely acknowledged model for analysis of governance framework for CCD is tenuous in the literature (<xref ref-type="bibr" rid="B71">Pyone, Smith, and van den Broek 2017</xref>). The frameworks proposed in the past have limitations and ambiguities due to a lack of clarity about the subject, principles, criteria, and indicators (<xref ref-type="bibr" rid="B13">Douxchamps et al., 2017</xref>; <xref ref-type="bibr" rid="B20">FAO 2017</xref>; <xref ref-type="bibr" rid="B32">Ha et al., 2018</xref>; <xref ref-type="bibr" rid="B69">Oliveira and Hersperger 2018</xref>). The concept of CCD is still evolving, and there are no specified principles, criteria, and indicators for sectoral governance for national, sub-national, and local reference scenarios.</p>
<p>As aforesaid, this study aims at evolving a framework based on a governance index for assessing the compatibility of the government&#x2019;s policies, legal instruments, institutional strategies, and management of CCD by taking the case of the energy sector in Pakistan. It comes under the scope of a basic response mechanism which is the first component of overall governance framework (i.e., GC-1). It is extracted from an extensive study regarding the development of a climate governance assessment framework based on mixed-method modeling of PCIs for CCD in different sectors of the economy (<xref ref-type="bibr" rid="B41">Iqbal et al., 2022</xref>). In this study, the assessment of energy governance for CCD was done against the first climate response principle, that is, &#x201c;respect climate policies, processes, strategies, law and the institution.&#x201d; It provides a methodological framework for periodic assessment of the efficacy of energy governance for CCD in terms of the contents of the policies, legal instruments, and institutional setup to promote a state&#x2019;s sustainable and climate compatible energy initiatives.</p>
<p>The research query undertaken for GC-1 was &#x201c;whether the existing architecture of policies, legal instruments and institutional setup has essential ingredients for emerging CCD needs in energy sector, and is inclusive for national, sub-national and local reference scenarios.&#x201d; The null hypothesis of this research query revolved around the absence of an inclusive governance mechanism.</p>
</sec>
<sec id="s2">
<title>Methodological framework</title>
<p>The study employed a PCI-based methodological framework for developing a governance index, employing six climate principles which were formulated by the first author as part of his PhD study in relation to six governance components (see <xref ref-type="table" rid="T1">Table 1</xref>) of the published article in <xref ref-type="bibr" rid="B41">Iqbal et al. (2022</xref>). A similar framework was previously used to study the actor&#x2019;s capacity in the energy sector, which was also extracted from the same major study as applicable for this article (<xref ref-type="bibr" rid="B41">Iqbal et al., 2022</xref>). The research design for the board study is reflected in the <xref ref-type="sec" rid="s11">Supplementary Appendix SI</xref>. The methodological framework for the limited scope of the present research to the first governance component (GC-1) and Climate Principle (CP-1) is shown in <xref ref-type="table" rid="T1">Table 1</xref> and <xref ref-type="fig" rid="F1">Figure 1</xref>. The analysis is based on mixed-method modeling by combining various quantitative and qualitative tools and techniques including the application of MCDA (Multi Criteria Decision Analysis) along with SMART (Simple Multi Attribute Rating Technique) scoring, and clumping the rules and rights-oriented model approaches of the governance (<xref ref-type="bibr" rid="B11">Daim et al., 2009</xref>; <xref ref-type="bibr" rid="B3">Amer and Daim 2011</xref>; <xref ref-type="bibr" rid="B10">Costa, Gomes, and de Barros 2017</xref>; <xref ref-type="bibr" rid="B48">Ishtiaque et al., 2019</xref>; <xref ref-type="bibr" rid="B62">McIntosh and Austin 2020</xref>). During the course of developing and finalizing the methodological framework for CCD, three consultative sessions with climate change and energy sector experts were conducted, by following the previous practices as reported in the literature (<xref ref-type="bibr" rid="B93">Wellman 1983</xref>; <xref ref-type="bibr" rid="B7">Borgatti et al., 2009</xref>; Ingie Hovland 2005). The model was logically organized for CCD and the energy sector. The framework provides flexibility to be applied as unabridged or sectional for a governance component and/or climate response principles. Its architecture is simple, and application is easy. The present study used the framework in partial form by using CP-1 and GC-1 (<xref ref-type="bibr" rid="B41">Iqbal et al., 2022</xref>) for developing a governance index to gauge the adequacy of the government&#x2019;s policies, and legal and institutional strategies and management for CCD. The logical structure adopted for the multivariate governance model is portrayed in <xref ref-type="fig" rid="F1">Figure 1</xref>. The analysis was carried out through a two-step procedure, that is, the first step involved the formulation of a measuring tool, while the second step was a practical application for the determination of a governance index for a basic response mechanism through a case study of the energy sector in Pakistan.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Climate response principles and components of the basic governance mechanism (<xref ref-type="bibr" rid="B41">Iqbal et al., 2022</xref>).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Code</th>
<th align="left">Climate response principle</th>
<th align="left">Corresponding governance component</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">CP1</td>
<td align="left">Respect climate policies, processes, strategies, law, and the institution</td>
<td align="left">Policy, legal, and institutional arrangements (GC1)</td>
</tr>
<tr>
<td align="left">CP2</td>
<td align="left">Ensure climate competence, capacity, and active role of the line government departments</td>
<td align="left">Role and capacities of the line government departments (GC2)</td>
</tr>
<tr>
<td align="left">CP3</td>
<td align="left">Promote vibrant and influential role of the civil society stakeholders with climate competence and capacity</td>
<td align="left">Role and capacities of CSOs and academia (GC3)</td>
</tr>
<tr>
<td align="left">CP4</td>
<td align="left">Maintain active engagement of the community-based stakeholders towards climate endeavors</td>
<td align="left">Role and capacities of community-based organizations (GC4)</td>
</tr>
<tr>
<td align="left">CP5</td>
<td align="left">Dynamic role of the private sector stakeholders for best climate solutions</td>
<td align="left">Role and capacities of corporate/private sector stakeholders (GC5)</td>
</tr>
<tr>
<td align="left">CP6</td>
<td align="left">Achieve and maintain participatory sustainable climate compatible performance</td>
<td align="left">Practice and performance system (GC6)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Source: PhD dissertation of the first author.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>GC1 CCD assessment model for energy governance.</p>
</caption>
<graphic xlink:href="fenvs-10-985340-g001.tif"/>
</fig>
<sec id="s2-1">
<title>Determination of key variables and primary data collection</title>
<p>The study demands diverse sets of variables to address the newly developed governance model by integrating PCIs. A careful narrowing-down procedure was followed in determining the set of 43 composite indicators against 9 CCD criteria, governance component 1 (GC1), that is, basic response mechanism, CP1, and 6 World Bank good governance principles (<xref ref-type="bibr" rid="B51">Kartodihardjo et al., 2013</xref>), as illustrated in <xref ref-type="fig" rid="F2">Figure 2</xref>. For the purpose, a widely practiced scenario-based learning and situational analysis technique (<xref ref-type="bibr" rid="B12">Dey 2012</xref>; <xref ref-type="bibr" rid="B36">Hovland 2005</xref>; <xref ref-type="bibr" rid="B67">Norris et al., 2012</xref>; <xref ref-type="bibr" rid="B82">Serrat 2017</xref>) was employed, using flip charts in three consultative meetings with experts in Islamabad. The consultative meetings concluded a set of nine criteria (i.e., Energy C-1.1 &#x3d; Disaster Risk Reduction, Vulnerability and Spatial Mapping; Energy C-2.1 &#x3d; Regulation of Rights; Energy C-3.1 &#x3d; Climate Smart Practices; Energy C-4.1 &#x3d; Technological Innovation; Energy C-5.1 &#x3d; Climate Organization; Energy C-6.1 &#x3d; Institutional Effectiveness; Energy C-7.1 &#x3d; Climate Infrastructure; Energy C-8.1 &#x3d; Agriculture, Water, and Energy Nexus; and Energy C-9.1 &#x3d; Sustainability) and 43 indicators (see <xref ref-type="sec" rid="s11">Supplementary Appendix SII</xref>). The indicators focused on established and in-practice policies, strategies, legal and institutional mechanism targeting climate vulnerability assessment, renewable energy proliferation, and grievance redressal mechanisms against nine criteria.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Criteria wise governance index for Governance Component-1 at provincial and federal level.</p>
</caption>
<graphic xlink:href="fenvs-10-985340-g002.tif"/>
</fig>
<p>MCDA&#x2019;s SMART was employed with a ratio scale presented as 0 &#x3d; not applicable or no response for CCD yet; 0.01 to 1.99 &#x3d; very poor response for CCD; 2.00 to 3.99 &#x3d; poor response for CCD; 4.00 to 4.99 &#x3d; considerable response for CCD; 5.00 to 5.99 &#x3d; fair response for CCD; 6.00 to 7.49 &#x3d; good response for CCD; 7.50 to 8.99 &#x3d; very good response for CCD; and 9.00 to 10.0 &#x3d; excellent response for CCD. The responses against each indicator were aggregated for scoring and weighting (<xref ref-type="bibr" rid="B14">Edwards 1977</xref>; <xref ref-type="bibr" rid="B56">Leskinen and Kangas 2005</xref>; <xref ref-type="bibr" rid="B23">G&#xe4;rtner et al., 2008</xref>; <xref ref-type="bibr" rid="B34">Heinrich et al., 2011</xref>) the CCD criteria. For SMART scoring, a structured questionnaire-cum-scoring matrix comprising 9 criteria and 43 indicators of energy governance was used. To validate and normalize the tool, pilot testing was carried out in Islamabad. A purposive sampling plan was designed by keeping in view the geographical requirement and attaining a representative size of the sample from each jurisdiction, including federal and provincial capitals and 10 districts throughout the country (i.e., Khuzdar and Jhal Magsi from the Balochistan province, Rajanpur and Bahawalpur from the Punjab province, Badin and Sanghar from the Sindh province, Ghizer from Gilgit-Baltistan, and Muzaffarabad from Azad Jammu and Kashmir). The existence of climate-related initiatives was duly considered during the selection of the geographical locations under the scope of this study. Data were collected through interviews of key experts/informants (KIIs) and FGD (focus group discussion) sessions. For each location, data through one FGD and 20 KIIs were collected, resulting in a purposive sample of a total of 357 responses. For FGDs and KIIs, experts were selected from energy departments including power generation, transmission, distribution, regulating authorities, as well as allied organizations like National Energy Efficiency and Conservation Authority (NEECA), Provincial Energy Efficiency and Conservation Authority (PEECA), Alternative Energy Development Board (AEDB), and Pakistan Council for Renewable Energy Technology (PCRET). Besides that, for FGD, experts from climate change-related departments including the Ministry of Climate Change, provincial environmental departments, and the Global Change Impact Studies Center (GCISC) were also invited. Flashcards were used to keep the discussion interactive and focused. Besides responses, the discussion of experts was also recorded, which helped in understanding different aspects of the findings.</p>
</sec>
<sec id="s2-2">
<title>Analysis of data</title>
<p>MS Excel 2016 was used for tabulating, cleaning, and processing the data and calculating the governance index of GC1 for the energy sector. The results were validated using IBM SPSS Statistics 25 by employing three statistical tests: linear regression, the non-parametric H-test, that is, Kruskal&#x2013;Wallis (KW) hypothesis testing, and 1-tailed Pearson Correlation. The H- test helped in understanding and characterizing the sample groups from district, provincial, and federal levels. The tests were preordained to ensure the originality of the sample and to understand the association of the different interlocking variables.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<p>The present study analyzed the adequacy of the current governance framework for the energy sector in relation to the CCD principles at the vertical levels with the constituencies at national (federal), sub-national (all provinces), and local (districts) levels. The responses were collected from the key informants using a structured questionnaire as well as through FGD with the experts in the energy and climate change sectors. The GC-I index was calculated by averaging the individual rating scores against each criterion. <xref ref-type="table" rid="T2">Table 2</xref> shows the criteria-wise itemization of the GC-1 index for CCD in relation to the energy sector in Pakistan. The overall results depict the highest score (6.02) for EC-1.1. For other criteria, the score was variable: the EC-2.1 index score of 4.05; EC-3.1 index score 5.90; EC-4.1 score 5.85; EC-5.1 index score 5.81; EC-6.1 index scores 5.85; EC-7.1 index score 5.64; and EC-8.1 index score 5.68. The lowest score is reported for EC-9.1 (average score 3.17). Constituency-wise index scores were highest for the federal (8.50), then the provincial (5.17), and lowest (2.31) for the district levels, signifying poor governance in districts. The overall GC-1 index remained 5.33. With reference to the constituency-wise GC-1 index, the federal area scored (8.50) good (see <xref ref-type="fig" rid="F2">Figure 2</xref>). <xref ref-type="fig" rid="F3">Figure 3</xref> portrays the constituency-wise index score in the form of a radar to show constituency-wise comparison of the index scores. <xref ref-type="fig" rid="F4">Figure 4</xref> shows the GC-1 index at district level. The lowest GC-1 index score was from the district of Balochistan&#x2014;Jhal Magsi and Khuzdar, while the highest score was from Muzaffarbad.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Governance index for Governance Component-1 for the energy sector of Pakistan.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Constituency level</th>
<th colspan="11" align="left">CCD criteria</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left"/>
<td align="left">Energy C-1.1</td>
<td align="left">Energy C-2.1</td>
<td align="left">Energy C-3.1</td>
<td align="left">Energy C-4.1</td>
<td align="left">Energy C-5.1</td>
<td align="left">Energy C-6.1</td>
<td align="left">Energy C-7.1</td>
<td align="left">Energy C-8.1</td>
<td align="left">Energy C-C9.1</td>
<td align="left">Average score</td>
<td align="left">Ranking</td>
</tr>
<tr>
<td align="left">National</td>
<td align="left">9.31</td>
<td align="left">7.53</td>
<td align="left">9.22</td>
<td align="left">9.21</td>
<td align="left">9.19</td>
<td align="left">8.95</td>
<td align="left">8.52</td>
<td align="left">9.28</td>
<td align="left">5.30</td>
<td align="left">
<bold>8.50</bold>
</td>
<td align="left">Very Good</td>
</tr>
<tr>
<td align="left">Sub-national (all provinces)</td>
<td align="left">6.16</td>
<td align="left">3.02</td>
<td align="left">5.91</td>
<td align="left">5.79</td>
<td align="left">5.69</td>
<td align="left">6.04</td>
<td align="left">5.85</td>
<td align="left">5.21</td>
<td align="left">2.90</td>
<td align="left">
<bold>5.17</bold>
</td>
<td align="left">Fair</td>
</tr>
<tr>
<td align="left">Local level (all districts)</td>
<td align="left">2.60</td>
<td align="left">1.59</td>
<td align="left">2.55</td>
<td align="left">2.55</td>
<td align="left">2.54</td>
<td align="left">2.55</td>
<td align="left">2.55</td>
<td align="left">2.54</td>
<td align="left">1.30</td>
<td align="left">
<bold>2.31</bold>
</td>
<td align="left">Poor</td>
</tr>
<tr>
<td align="left">Average score</td>
<td align="left">
<bold>6.02</bold>
</td>
<td align="left">
<bold>4.05</bold>
</td>
<td align="left">
<bold>5.90</bold>
</td>
<td align="left">
<bold>5.85</bold>
</td>
<td align="left">
<bold>5.81</bold>
</td>
<td align="left">
<bold>5.85</bold>
</td>
<td align="left">
<bold>5.64</bold>
</td>
<td align="left">
<bold>5.68</bold>
</td>
<td align="left">
<bold>3.17</bold>
</td>
<td align="left">
<bold>5.33</bold>
</td>
<td align="left">Fair</td>
</tr>
<tr>
<td align="left">Ranking</td>
<td align="left">Good</td>
<td align="left">Considerable</td>
<td align="left">Fair</td>
<td align="left">Fair</td>
<td align="left">Fair</td>
<td align="left">Fair</td>
<td align="left">Fair</td>
<td align="left">Fair</td>
<td align="left">Poor</td>
<td align="left">Fair</td>
<td align="left">-</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Bold indicates that the average values.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Radar graph of governance index for Governance Component-1 in the energy sector.</p>
</caption>
<graphic xlink:href="fenvs-10-985340-g003.tif"/>
</fig>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>GC-1 index at district level.</p>
</caption>
<graphic xlink:href="fenvs-10-985340-g004.tif"/>
</fig>
<p>The inferential statistics, that is, KW Hypothesis Test, was performed to test the null hypothesis; that is, <italic>the distribution of governance index score is the same across all nine criteria, constituency- and gender-wise.</italic> It rejects the null hypothesis with an asymptotic significance level 0.05 (against N &#x3d; 357) for the overall sample of GC-1 in the energy sector. The Pearson correlations (1-tailed) significantly indicate a strong co-relation among all CCD criteria (<xref ref-type="table" rid="T3">Table 3</xref>), whereas for the multivariate regression analysis (see <xref ref-type="table" rid="T4">Tables 4</xref>&#x2013;<xref ref-type="table" rid="T7">7</xref>), the CCD criteria &#x201c;Energy C-9.1, that is, Sustainability for GC-1,&#x201d; was taken as the dependent variable. The retrieved R and R Square values were 0.936 and 0.876 respectively. The results of the T-test (values above &#xb1;2) inferred a significant relationship of sustainability criteria with other criteria, except EC-1.1, EC-4.1, and EC-5.1. However, the collinearity diagnostics for all correlations (tolerance &#x3c;0.10, VIF &#x3e;10) is not indicative of significance, though all criteria showed zero-order correlation with the sustainability criteria.</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Correlation between energy sector GC-1&#x2019;s CCD criteria (EC1.1-EC9.1).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="10" align="left">Pearson correlations</th>
</tr>
<tr>
<th align="left">CCD criteria</th>
<th align="left">Energy C-1.1</th>
<th align="left">Energy C-2.1</th>
<th align="left">Energy C-3.1</th>
<th align="left">Energy C-4.1</th>
<th align="left">Energy C-5.1</th>
<th align="left">Energy C-6.1</th>
<th align="left">Energy C-7.1</th>
<th align="left">Energy C-8.1</th>
<th align="left">Energy C-C9.1</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Energy C-1.1</td>
<td align="left">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Energy C-2.1</td>
<td align="left">0.914<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Energy C-3.1</td>
<td align="left">0.994<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.924<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Energy C-4.1</td>
<td align="left">0.993<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.927<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.997<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Energy C-5.1</td>
<td align="left">0.992<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.931<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.996<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.996<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Energy C-6.1</td>
<td align="left">0.995<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.911<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.995<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.994<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.993<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">1</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Energy C-7.1</td>
<td align="left">0.993<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.906<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.996<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.995<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.993<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.995<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">1</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Energy C-8.1</td>
<td align="left">0.982<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.951<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.988<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.990<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.991<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.982<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.983<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">1</td>
<td align="left"/>
</tr>
<tr>
<td align="left">Energy C-9.1</td>
<td align="left">0.893<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.911<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.897<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.895<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.894<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.895<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.882<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">0.893<sup>&#x2a;&#x2a;</sup>
</td>
<td align="left">1</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>&#x2a;&#x2a;1-tailed significance level of correlation &#x3d; 0.01.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>Summary of regression model for GC-1 in the energy sector.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="5" align="left">Model summary<xref ref-type="table-fn" rid="Tfn2">
<sup>b</sup>
</xref>
</th>
</tr>
<tr>
<th align="left">Model</th>
<th align="left">R</th>
<th align="left">R square</th>
<th align="left">Adjusted R square</th>
<th align="left">Std. eror of the estimate</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">1</td>
<td align="left">0.936<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
<td align="left">0.876</td>
<td align="left">0.873</td>
<td align="left">0.47057</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn1">
<label>a</label>
<p>Predictors: (Constant), Agriculture, Water, and Energy Nexus, Climate Infrastructure, Institutional Effectiveness, Regulation of Rights, DRR, Vulnerability and Spatial Mapping, Climate Smart Practices, Technological Innovation, and Climate Organization.</p>
</fn>
<fn id="Tfn2">
<label>b</label>
<p>Dependent variable: Sustainability.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T5" position="float">
<label>TABLE 5</label>
<caption>
<p>Summary of ANOVA for GC-1 in the energy sector.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="7" align="left">ANOVA<xref ref-type="table-fn" rid="Tfn3">
<sup>a</sup>
</xref>
</th>
</tr>
<tr>
<th colspan="2" align="left">Model</th>
<th align="left">Sum of squares</th>
<th align="left">Df</th>
<th align="left">Mean square</th>
<th align="left">F</th>
<th align="left">Sig</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="3" align="left">1</td>
<td align="left">Regression</td>
<td align="left">543.019</td>
<td align="left">8</td>
<td align="left">67.877</td>
<td align="left">306.535</td>
<td align="left">0.000<xref ref-type="table-fn" rid="Tfn4">
<sup>b</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">Residual</td>
<td align="left">77.059</td>
<td align="left">348</td>
<td align="left">0.221</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Total</td>
<td align="left">620.078</td>
<td align="left">356</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn3">
<label>a</label>
<p>Dependent variable: Sustainability.</p>
</fn>
<fn id="Tfn4">
<label>b</label>
<p>Predictors: (Constant), Agriculture, Water, and Energy Nexus, Climate Infrastructure, Institutional Effectiveness, Regulation of Rights, DRR, Vulnerability and Spatial Mapping, Climate Smart Practices, Technological Innovation, and Climate Organization.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T6" position="float">
<label>TABLE 6</label>
<caption>
<p>Criteria wise summary of regression coefficients for GC-1 in the energy sector.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="10" align="left">Coefficients<xref ref-type="table-fn" rid="Tfn5">
<sup>a</sup>
</xref>
</th>
</tr>
<tr>
<th/>
<th rowspan="2" colspan="2" align="left">Model</th>
<th colspan="2" align="left">Unstandardized coefficients</th>
<th align="left">Standardized coefficients</th>
<th rowspan="2" align="left">t</th>
<th rowspan="2" align="left">Sig</th>
<th rowspan="2" align="left">Correlations zero-order</th>
<th colspan="2" align="left">Collinearity statistics</th>
</tr>
<tr>
<th colspan="2" align="left"/>
<th align="left">B</th>
<th align="left">Std. error</th>
<th align="left">Beta</th>
<th align="left">Tolerance</th>
<th align="left">VIF</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="9" align="left">1</td>
<td align="left">(Constant)</td>
<td/>
<td align="left">0.340</td>
<td align="left">0.050</td>
<td align="left"/>
<td align="left">6.763</td>
<td align="left">0.000</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">DRR, Vulnerability, and Spatial Mapping</td>
<td/>
<td align="left">0.094</td>
<td align="left">0.103</td>
<td align="left">0.189</td>
<td align="left">0.916</td>
<td align="left">0.360</td>
<td align="left">0.893</td>
<td align="left">0.008</td>
<td align="left">118.671</td>
</tr>
<tr>
<td align="left">Regulation of Rights</td>
<td/>
<td align="left">0.605</td>
<td align="left">0.056</td>
<td align="left">0.799</td>
<td align="left">10.904</td>
<td align="left">0.000</td>
<td align="left">0.911</td>
<td align="left">0.067</td>
<td align="left">15.037</td>
</tr>
<tr>
<td align="left">Climate Smart Practices</td>
<td/>
<td align="left">0.417</td>
<td align="left">0.166</td>
<td align="left">0.800</td>
<td align="left">2.518</td>
<td align="left">0.012</td>
<td align="left">0.897</td>
<td align="left">0.004</td>
<td align="left">282.546</td>
</tr>
<tr>
<td align="left">Technological Innovation</td>
<td/>
<td align="left">0.208</td>
<td align="left">0.155</td>
<td align="left">0.394</td>
<td align="left">1.345</td>
<td align="left">0.180</td>
<td align="left">0.895</td>
<td align="left">0.004</td>
<td align="left">240.670</td>
</tr>
<tr>
<td align="left">Climate Organization</td>
<td/>
<td align="left">&#x2212;0.259</td>
<td align="left">0.142</td>
<td align="left">-0.486</td>
<td align="left">&#x2212;1.824</td>
<td align="left">0.069</td>
<td align="left">0.894</td>
<td align="left">0.005</td>
<td align="left">198.697</td>
</tr>
<tr>
<td align="left">Institutional Effectiveness</td>
<td/>
<td align="left">0.487</td>
<td align="left">0.131</td>
<td align="left">0.940</td>
<td align="left">3.725</td>
<td align="left">0.000</td>
<td align="left">0.895</td>
<td align="left">0.006</td>
<td align="left">178.443</td>
</tr>
<tr>
<td align="left">Climate Infrastructure</td>
<td/>
<td align="left">&#x2212;0.411</td>
<td align="left">0.148</td>
<td align="left">&#x2212;0.759</td>
<td align="left">&#x2212;2.776</td>
<td align="left">0.006</td>
<td align="left">0.882</td>
<td align="left">0.005</td>
<td align="left">209.529</td>
</tr>
<tr>
<td align="left">Agriculture, Water, and Energy Nexus</td>
<td/>
<td align="left">&#x2212;0.514</td>
<td align="left">0.102</td>
<td align="left">&#x2212;0.928</td>
<td align="left">&#x2212;5.056</td>
<td align="left">0.000</td>
<td align="left">0.893</td>
<td align="left">0.011</td>
<td align="left">94.366</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn5">
<label>a</label>
<p>Dependent variable: Sustainability.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T7" position="float">
<label>TABLE 7</label>
<caption>
<p>Regression&#x2019;s residual statistics for GC-1 in the energy sector.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th colspan="6" align="left">Residuals statistics<xref ref-type="table-fn" rid="Tfn6">
<sup>a</sup>
</xref>
</th>
</tr>
<tr>
<th align="left"/>
<th align="left">Minimum</th>
<th align="left">Maximum</th>
<th align="left">Mean</th>
<th align="left">Std. deviation</th>
<th align="left">N</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Predicted value</td>
<td align="left">0.2587</td>
<td align="left">5.7091</td>
<td align="left">2.1038</td>
<td align="left">1.23504</td>
<td align="left">357</td>
</tr>
<tr>
<td align="left">Residual</td>
<td align="left">&#x2212;1.16587</td>
<td align="left">1.35976</td>
<td align="left">0.00000</td>
<td align="left">0.46525</td>
<td align="left">357</td>
</tr>
<tr>
<td align="left">Std. predicted value</td>
<td align="left">&#x2212;1.494</td>
<td align="left">2.919</td>
<td align="left">0.000</td>
<td align="left">1.000</td>
<td align="left">357</td>
</tr>
<tr>
<td align="left">Std. residual</td>
<td align="left">&#x2212;2.478</td>
<td align="left">2.890</td>
<td align="left">0.000</td>
<td align="left">0.989</td>
<td align="left">357</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn6">
<label>a</label>
<p>Dependent variable: Sustainability.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>The normal P-P plot (<xref ref-type="fig" rid="F5">Figure 5</xref>) illustrates relatively low deviation, and upward and downward variations. <xref ref-type="fig" rid="F6">Figure 6</xref> (scatter plot) indicates four clusters, of which two clusters are submerged to each other while the remaining two are trivial with overall results within the (&#xb1;3) boundaries. The inferential statistics determine that all nine criteria of the GC-1 index impact each other. Thus, convincingly the null hypothesis cannot be rejected, suggesting the absence of a preemptive and comprehensive response mechanism to govern CCD in the energy sector for its environmental security at federal, provincial, and district levels in Pakistan.</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption>
<p>Regression&#x2019;s P-P plot for CCD index under GC1 in the energy sector.</p>
</caption>
<graphic xlink:href="fenvs-10-985340-g005.tif"/>
</fig>
<fig id="F6" position="float">
<label>FIGURE 6</label>
<caption>
<p>Regression&#x2019;s scatter plot for CCD index under GC1 in the energy sector.</p>
</caption>
<graphic xlink:href="fenvs-10-985340-g006.tif"/>
</fig>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>Pakistan, with a population (213 million) growing at the rate of 2%, ranks the sixth-most populous country of the world. With a growing population, the energy demand is also increasing from 5% to 7% per year (<xref ref-type="bibr" rid="B47">Irfan et al., 2020</xref>; <xref ref-type="bibr" rid="B73">Qiu et al., 2022a</xref>; <xref ref-type="bibr" rid="B74">Qiu et al., 2022b</xref>). As a result, the annual total GHG emissions reached 408 million tons of CO<sub>2</sub> in 2015, with the major share (45.5%) from the energy sector. <xref ref-type="bibr" rid="B100">Zhang et al. (2021a)</xref>, <xref ref-type="bibr" rid="B101">Zhang et al. (2021b)</xref>, and <xref ref-type="bibr" rid="B102">Zhang et al. (2021c)</xref> demonstrated that the major reason is reliance on fossil fuels as the major energy source. Among the major contributors of GHG emissions from the energy sector, electricity generation adds 49.065&#xa0;Gg of CO<sub>2</sub> annually (<xref ref-type="bibr" rid="B31">GoP 2018</xref>). The current energy reliance is still on thermal power generation (61%), with renewables contributing only 1% in the total energy mix (<xref ref-type="bibr" rid="B47">Irfan et al., 2020</xref>). However, the government targeted to increase reliance on renewables (solar, wind, waste to energy) to 5% of the total energy by 2030 (<xref ref-type="bibr" rid="B44">Iqbal et al., 2018</xref>). <xref ref-type="bibr" rid="B9">Chen et al. (2022)</xref> indicated that the current electricity production in Pakistan is less than demand, with a supply&#x2013;demand gap of more than 3,000&#xa0;MW. The resultant pressure forced the government to encourage short-term energy supply projects, including importing oil for thermal power generation (<xref ref-type="bibr" rid="B63">Miao et al., 2018</xref>; <xref ref-type="bibr" rid="B97">Yin et al., 2022a</xref>; <xref ref-type="bibr" rid="B64">Miao et al., 2022</xref>).</p>
<p>Pakistan&#x2019;s geographical location provides opportunities to harness 2900&#xa0;GW of solar energy (<xref ref-type="bibr" rid="B75">Rafique et al., 2020</xref>). Similarly, Pakistan&#x2019;s multifarious terrain includes coastal and hill areas that provide excellent potential for wind energy (<xref ref-type="bibr" rid="B83">Shami et al., 2016</xref>). Being an agricultural country, Pakistan also has the potential to utilize agricultural biomass as fuel. Sixty percent of the population reside in rural areas. An estimated 230 billion tons of biomass, 652&#xa0;M&#xa0;kg of manure, and 230 thousand tons of agricultural residues are produced every year. Besides that, an estimated 60,000 tons of solid waste per day is produced (<xref ref-type="bibr" rid="B47">Irfan et al., 2020</xref>). However, all these researches emphasized the need to adapt a comprehensive governance framework to tap the potential of renewable resources to achieve the low-carbon development goals for CCD (<xref ref-type="bibr" rid="B44">Iqbal et al., 2018</xref>; <xref ref-type="bibr" rid="B46">Irfan et al., 2019</xref>, <xref ref-type="bibr" rid="B47">2020</xref>).</p>
<p>The global installed capacity of RE reached more than 200&#xa0;GW in 2019, with a significant share by the developing countries (<xref ref-type="bibr" rid="B38">IAEA 2020</xref>). <xref ref-type="bibr" rid="B19">Fang et al. (2022)</xref>, <xref ref-type="bibr" rid="B76">Rahman and Islam (2020)</xref>, and <xref ref-type="bibr" rid="B103">Fofack and Derick (2020)</xref> indicated that the largest share of renewables is contributed in the electricity sector; however, the heat and transportation sectors are still far from the desired goals. The heat and transportation sector contributes 80% of the total energy consumption. Similarly, the United Nations SDG Report 2020 also stressed the need for additional efforts to achieve the energy efficiency targets. An enhancement in installation capacity and the spread of RE systems provided clean electricity and cooking fuel to the areas that lacked access to energy resources, especially in many developing nations. The actions helped to achieve access to the energy targets, while ensuring commitment pertaining to the global drive to diversify and shift to cleaner energy sources. However, progress is not the same across the nations; many nations are far behind in achieving a sustainable level of energy production and in meeting the SDG requirements, mainly due to policy gaps and effective implementation. ASEAN nations also lag behind in achieving the 23% renewable energy target by 2025, unless drastic adjustments in strategies are guaranteed (<xref ref-type="bibr" rid="B53">Khuong et al., 2019</xref>).</p>
<p>Pakistan is no exception. The renewable energy targets were set as a 20% share of renewables in energy generation by the year 2025 and further enhancement to 30% by the year 2030, while reducing GHG emissions seems ambitious in absence of an inclusive governance mechanism. The emission reduction targets become more challenging, particularly in the case of increasing energy demands under the &#x201c;China Pakistan Economic Corridor (CPEC)&#x201d;-related expansion needs and scope of activities (<xref ref-type="bibr" rid="B88">UNFCCC 2016</xref>; <xref ref-type="bibr" rid="B42">Iqbal and Haider 2020</xref>). At the same time, the United Nations SDGs Report 2020 reflects that international financing in renewable energy has accelerated, reaching up to $21.4 billion in 2017.</p>
<p>The findings revealed gaps in governance for the GC-1 related energy sector&#x2019;s CCD response measures at federal, provincial, and district level in Pakistan. The preparedness of federal level developments for CCD is better than that at the provincial and district levels (<xref ref-type="table" rid="T1">Table 1</xref>). When comparing the province and district levels, the provinces were rated &#x201c;fair,&#x201d; but scores for the district level context are not promising transversely in Pakistan (<xref ref-type="table" rid="T2">Table 2</xref>). The findings corroborate that the energy sector had a strong foundation in the federal region for being a federal subject till the year 2010. Late in 2010, the 18th Amendment in the Constitution of Pakistan, 1973 devolved its powers, by giving autonomy to the provinces for the progression of energy sources. Subsequently, diversification in the energy resources started targeting wind, solar, and waste to energy projects. The private sector was invigorated to invest in an independent power producer (IPP). The system was restructured to provide a net-metering facility that created prospects for harnessing solar energy at a domestic as well as a commercial scale in Pakistan. Accordingly, the relevant energy sector policies and strategies at the federal level were aligned to have all the mandatory provisions to fulfill the NDCs. However, the findings revealed that the progress in the provincial and local contexts sits far behind the national level development, due to the governance gaps.</p>
<p>Some of the key steps taken at the federal level include the launching of the Clean Development Mechanism (CDM) in August 2005. The CDM cell (<xref ref-type="bibr" rid="B24">Ghumman 2007</xref>) promoted clean energy and energy efficiency projects which aimed at reducing GHG emissions. The Local Adaptation Plan for Action (LAPA) started in 2012 as part of a 5-year project without any linkage to policies in the context of nexus of energy, water, and agriculture. During the project, six LAPAs for six districts were initiated, but the mechanism remained informal. So far, there is absence of concrete measures to link up LAPAs for the nexus of energy, water, and agriculture, which is critically important for CCD in the energy sector. Similarly, the Alternative Energy Development Board (AEDB) was established which in 2006 formulated a Renewable Energy Policy to diversify energy sources, stimulate renewable energy projects, and shun dependence on fossil fuels (<xref ref-type="bibr" rid="B25">GoP 2006</xref>). The Renewable Energy Policy 2006 was the first policy that intended to increase to a 10% share of renewables in the energy generation mix by the year 2015. Particular attention was given to micro-hydel, solar, and wind power projects. Consequently, renewable energy-based IPPs for selling the produced electricity were given incentives. Later on, the Power Generation Policy 2015 (<xref ref-type="bibr" rid="B28">GoP 2015</xref>) also announced incentives and a simplified <italic>modus operandi</italic> for approval and installation of power generation projects to meet the demand-supply gap for the socioeconomic lift of the economy. Vision 2025 of Pakistan also envisages the promotion of RE technologies in the goals to curtail the future upsurge of GHG emissions proportionately to growing energy demands. Later on, the Alternative and Renewable Energy Policy of Pakistan 2019 (ARE Policy 2019) augmented the target (<xref ref-type="bibr" rid="B1">AEDB 2019</xref>) to 20% of renewable mix by the year 2025 and 30% by the year 2030 in overall energy generation. It is anticipated that the targeted energy mix will provide environmentally sound, accessible, and affordable solution at the grassroots level while encouraging the stakeholders (<xref ref-type="bibr" rid="B1">AEDB 2019</xref>).</p>
<p>Among other important steps at the federal level, the establishment of the National Energy Efficiency and Conservation Authority (NEECA) is a major milestone. NEECA initially started as a project of USAID in 1985 which later become an authority after promulgation of NEECA Act in 2016 (<xref ref-type="bibr" rid="B30">GoP 2016b</xref>). Since its inception, NEECA has initiated projects to ensure energy efficiency and conservation in transport, manufacturing, and domestic sectors including energy auditing, building codes, and energy labeling of products (<xref ref-type="bibr" rid="B29">GoP 2016a</xref>).</p>
<p>Similarly, the National Climate Change Policy of Pakistan (<xref ref-type="bibr" rid="B26">GoP 2012</xref>) also stipulates commitment to GHG emission abatement as targeted in the NDCs. However, the policy also envisions that provisions related to the growth of RE technologies such as the promotion of distributed grid solutions, deployment of hydropower generation, utilizing rooftops for solar power generation, and installation of more waste to energy projects need to be in line with energy sector planning. Subsequently, the Framework for Implementation of Climate Change Policy (FICCP) further elaborates strategies and engagements for the advancement of RE-based energy diversification to control GHG emissions (<xref ref-type="bibr" rid="B27">GoP 2014</xref>). The strategies comprise the preferment of hydel power projects, the installation of more power plants based on municipal waste, and provision of incentives for desirable projects to gear progress towards low-carbon energy sources. However, all these steps also require institutional reforms for the transmission and distribution of the energy produced, tariff setting, and other fiscal reforms to promote RE technologies.</p>
<p>The role of the government in the progression of RE is crucial in any nation. RE brings opportunities such as the creation of a large number of jobs, energy security, and improved quality of life. Globally, governments are implementing policies to stimulate the utilization of RE sources and technologies (<xref ref-type="bibr" rid="B86">Sweetnam et al., 2013</xref>). Currently, the feed-in tariff (FIT) mechanisms are widely practiced across the globe, particularly in the developing nations (<xref ref-type="bibr" rid="B77">REN21, 2011</xref>). Pakistan adopted the FIT mechanism to promote renewable energy in connection with net-metering policies in 2015. The scheme set remuneration for a solar power project of up to 10&#xa0;MW for 25&#xa0;years in accordance with capacity and region. Ostensibly, 19 solar power generation projects with more than 50&#xa0;MW of capacity gained licenses during 2020&#x2013;21. Besides that, 8,417 net metering licenses of above 145&#xa0;MW capacity were issued during the same year. However, Pakistan is facing deterrence pertaining to insecurity for FITs in relation to high capital investment, and investors&#x2019; and consumers&#x2019; interests (<xref ref-type="bibr" rid="B86">Sweetnam et al., 2013</xref>). Other challenges include financial obstacles, a dearth of competition, institutional obstructions, and a lack of access to technology (<xref ref-type="bibr" rid="B96">Yazdanie and Rutherford 2010</xref>). Consequently, setting FITs high by the National Electric Power Regulatory Authority (NEPRA) will maximize the profits of the investors. In such case, the consumers will suffer from high costs of RE. Likewise, setting FITs to a lower rate will result in benefitting consumers while investors bear high capital investment costs. These challenges compromise the desired results that can be achieved by implementing the FIT framework in Pakistan. The analysis of respondents&#x2019; feedback reveals that sustainability under GC-1 is fair at the federal level, while in the range of very poor to poor at the provincial and district levels respectively. However, the vertical coherence of policies and legal instruments is necessary for the sustainability of the federal level commitments. In this context, the role of the provincial governments is critical to complement all the provincial policies and plans with the federal endeavors. The findings also reveal that the development of compulsory mechanisms to strengthen the institutional capabilities and capacities is important. However, such a roadmap is non-existent in strategies, policies, and planning documents resulting in the low governance index score.</p>
<p>The energy sector requires intensive investment which is necessary to boost the economy, ensure social well-being, and strengthen the technology base and thus the overall development of a country. Awareness and the capacity building of relevant institutions remain a major hurdle in the inclusive development energy sector in the developing world. Most of the current initiatives are project based, temporary, and thus inadequate for capacity building and training of human resources (<xref ref-type="bibr" rid="B55">Lawonski et al., 2018</xref>). Consequently, gaps in innovation, management, analytical research base, and general awareness need to be overcome in order to achieve the 20&#x2013;30% contribution of RE in the overall energy mix to achieve the NDCs (<xref ref-type="bibr" rid="B59">Lo et al., 2019</xref>). This can be achieved by decommissioning policies that revolve around conventional energy forms, and the promotion of RE-based initiatives adopting cross-sectoral approaches.</p>
<p>Awareness and relevant capacity-building remain a major hurdle in the inclusion of RE in the developing world, as the current efforts have project-based orientation rather than context-dependent and long-term efforts envisaged (<xref ref-type="bibr" rid="B55">Lawonski et al., 2018</xref>). Perspective gaps in innovation, management, analytical research base, and general awareness need to be understood well in order to assess the effectiveness and demand of RE from the bottom up (<xref ref-type="bibr" rid="B59">Lo et al., 2019</xref>), by rationalizing and decommissioning the shortcomings of the policies that revolve around conventional energy forms and their promotion in the business-as-usual scenario. This is greatly needed in the context of Pakistan where policy coherence and overlaps have created great confusion, particularly for the trickle-down effect from federal to the provincial and local contexts.</p>
</sec>
<sec sec-type="conclusion" id="s5">
<title>Conclusion</title>
<p>Study of the Governance Component-1 (the basic response mechanism for policy, legal, and institutional arrangements), intended for first climate response principle 1 in the energy sector at federal, provincial, and district levels, showed that the model proved well in developing, validating, and interpreting the governance index against the basic research query. The developing countries including Pakistan have great potential and prospects for renewable and sustainable energy development. However, they have several challenges due to the lack of an adequate and coherent policy, and legal and institutional arrangements which are necessary for devising strategies as well as planning and execution processes. This occurs due to the complex governance mechanism. The results of this study reveal that climate response is more visible at the federal level. The relevant sectoral policies and strategies have all the essential provisions that are obligatory for CCD in the energy sector. However, the provincial and local contexts sit far behind the national level development, due to governance gaps, thus it shows a very strong disconnect and does not appeal to the audience. After the 18th Amendment in the Constitution of Pakistan, 1973, provinces were given autonomy to develop their energy resources. Private sector companies were given the choice to become independent power producer (IPP); particularly, the net-metering facility created the opportunity to tap the solar energy potential in Pakistan. A poor uptake was found in provinces. However, all nine criteria of GC-1 influence each other; in totality, the null hypothesis could not be excluded for the case of GC-1 in the energy sector. So, GC-1 index scores are indicative of the lack of a preemptive and inclusive governance framework to ensure climate compatible development in the energy sector at the federal, provincial, and district levels in Pakistan. The study reveals that the governance mechanisms pertaining to energy generation, distribution and regulation of the consumption, and efficiency lack clarity in their objectives as well as in their execution. Due to the energy crises in the past few years, the predominant goal of the energy sector was to bridge the gap between supply and demand, irrespective of the commitments made under climate change policy and action plan. Consequently, Pakistan&#x2019;s energy mix skewed towards thermal power generation from imported fuel, posing a risk for climate as well as energy security and accessibility issues. The study also revealed a lack of coordination among the vertical hierarchy of governance, that is, federal, provincial, and district level departments.</p>
<p>The findings of the study pave the way to restructure the energy sector policies, strategies, and institutions in line with the principle, criteria, and indicators stipulated in the study to ensure environmental security and sustainable development. The study recommends aligning the energy sector development objectives in line with climate change and SDGs. This reflects rethinking the agreements of imported fuels as well as the diversification of existing energy resources. For this purpose, policies and strategies should support technological innovation in all segments of the energy sector.</p>
<p>As far as the limitation of the study is concerned, all aspects related to the basic response mechanism comprising policy, legal, and institutional measure to feature CCD in the energy sector have been covered well. However, it has been carried out by involving a large dataset based on indictors and constituencies, due to which it required more time and resource input. Data recording from the respondents was a difficult process, due to poor understanding of the subject, particularly at provincial and district levels. The outcome of the study could have been even better if adequate financial resources had been available for 1) increasing the number of districts and 2) having a comparative analysis by adding a few more developing countries under the scope of this study (<xref ref-type="bibr" rid="B98">Yin et al., 2022b</xref>).</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s6">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s11">Supplementary Material</xref>. Further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s7">
<title>Ethics statement</title>
<p>Ethics review and approval/written informed consent were not required as per local legislation and institutional requirements.</p>
</sec>
<sec id="s8">
<title>Author contributions</title>
<p>All the authors contributed substantially to the entire work reported in this article. They read and approved the final manuscript, which was extracted from a novel and original research dissertation of the first author submitted to the International Islamic University, Islamabad, for partial fulfillment of his PhD degree. KI extracted and shaped the basic idea, methodology, results, discussion, and conclusion. MK supervised the work by reviewing and editing the overall paper, technically and academically. NA helped in drafting the introduction, discussion, and abstract sections. FW complemented in discussion, logical conclusion, proofreading, and processing the paper with Frontiers in Environmental Science. UA assisted in referencing and formatting.</p>
</sec>
<ack>
<p>The authors would like to thank the referees for their very useful suggestions.</p>
</ack>
<sec sec-type="COI-statement" id="s9">
<title>Conflicts of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s10">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s11">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fenvs.2022.985340/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fenvs.2022.985340/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet2.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="DataSheet1.docx" id="SM2" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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