An Empirical Analysis of Sustainable Energy Security for Energy Policy Recommendations

Abstract

This study presents a framework for assessing Pakistan’s sustainable energy security (SES) between 1991 and 2020 by estimating its composite index, termed “SESi”, and three sub-indices. The SES has three dimensions: economic, social, and environmental. A total of 26 indicators were chosen and normalized using the Z-score approach before being weighted using principal component analysis (PCA) or equal weighting. The findings associated with the indices point to a declining tendency between 1991 and 2020. The highest degree of sustainable energy security (SES) was reported in 1991, with the lowest levels recorded in 2004 and 2007. Between 1991 and 2020, 9% of SESi regressed. Economic dimensions regressed among the dimension indices between 1991 and 2004, followed by steady performance, while the other two dimensions, social and environmental, fell by 30% and 26%, respectively, during the study period. Further analysis indicates that the objectives of the policies implemented throughout the study period were only partially achieved due to the country’s heavy import dependence, energy expenditures, falling reserves and forest area, and inefficiencies in the power sector.

1. Introduction

Sustainability is related with the term “sustainable development”, which is additionally consolidated to “clean energy”, which corresponds to energy use [1]. It is also concerned with reducing emissions, with a focus on non-fossil-based and naturally restored energy. This term came into use during the 1970s and is still extremely relevant, since there is no better way to portray “sustainability” [2]. Likewise, with the idea of “energy security”, there is still no generally agreed upon definition, despite the fact that it is referred to as complex [3]. With the introduction of the “Sustainable Development Goals (SDGs)”, efforts to alleviate poverty and improve basic livelihoods have intensified [4]. As a result, policymakers have been synthesizing their impact on energy security and sustainability. In this regard, studies have shown a strong correlation between energy consumption per capita and the human development index (HDI) [5].

In the last two decades, the global population has grown at a rate of 1.20% per year [6], contributing to an annual increase in energy consumption of 2.8% per year [7]. The present system of primary energy sources cannot satisfy the rising demand on a global scale [8]. This is due to the environmental complications caused by the direct combustion of fossil and nuclear fuels. Additionally, growing patterns in fossil fuel consumption will contribute to deposit depletion in the near future [9]. In these circumstances, the literature emphasizes the importance of having a long-term vision for refocusing on both the sustainability and security components of energy [10]. Likewise, it must account for the dimensions of sustainable development for energy planners to establish policies for transitioning to energy security and energy sustainability in order to explicitly implement public acceptability [11]. As a result of mounting concerns about the greenhouse effect, global warming, biodiversity loss, progressive pollutant growth, and human health degradation in the last two decades, the goalpost has shifted beyond sustainability and energy security [12,13].

In virtue of the multidimensional significance of the terms “sustain”, “support”, and “conserve” with respect to the sustainability paradigm, not only must harmonization and sustainability of energy, economic, social, and environmental development be considered, but also efficiency and diversity [14]. The combination of energy security and sustainability has its own significance, as achieving energy security alone can cause irreparable damage to reserves and the environment, and on the other hand, sustainability alone ignores the high cost of extracting clean energy resources while focusing on the environmental impact of energy to use [15]. To counter, an integrated idea has been described as “Sustainable Energy Security (SES)” [3], which seeks to provide energy services to meet society’s current and future developmental needs without affecting economic growth and the environment [3,16]. Furthermore, attempts have also been made to enable quantification of SES to capture certain characteristics of a country, which are aptly referred to as “Energy Indicators for Sustainable Development (EISD’s)” [17,18]. These EISD’s have been developed by the United Nations Department of Economic and Social Affairs along with other organizations such as the International Energy Agency and International Atomic Energy Commission [19]. The EISDs are transparent and simple, founded on a philosophical basis, reflecting the idea of sustainable energy, taking into account interconnections within the set, and focusing on stakeholder feedback [20]. EISDs may be able to overcome the conundrum of designing indicators that are methodologically valid, observable, and meaningful at the global level while still being helpful to policymakers at the national level [4,18].

The literature implies that an indicator-based method is an elegant technique [4,12]. It avoids complexity [21,22] because the system has interlinkages with economic, social, and environmental components of development that might be difficult to grasp [22,23]. However, the literature also suggests that indicators may give conflicting results, their relative importance is unknown, and they may measure similar characteristics. Notwithstanding this, the literature likewise recommends that indicators might give clashing outcomes, their overall significance is obscure, and they might quantify similar attributes [24]. To circumvent these constraints and give a simple figure, an attempt was made to construct an “index” from the set of energy indicators [25]. Furthermore, an index aids in the presentation of a country’s performance over time as well as associated important trends that might not be visible otherwise [26].

In order to ensure SES, an instrument (index) based analysis is covered by a few of the studies. For example, Narula (2014) considered four dimensions of SES, namely, Availability, Acceptability, Affordability, and Efficiency and their corresponding indicators to represent SES [13]. The study’s limitations were that the ESID’s were not taken into account, and an aggregated index was not developed, instead opting for an ad hoc trend analysis that was not statistically robust. On the other hand, K. Narula et al. (2016), in another study, presented dimensional and sectoral indices and the aggregated SES index based on the weights derived from an interview and the perception of respondents [16]. However, the absolute values of the index fell short of the ideal index value of 1.0, which indicates that there is further room for improvement. Moreover, J. Martchamadol, S. Kumar, (2014) utilized the EISD for Thailand and produced the aggregated index [18]. The shortcoming was that they focused on the aggregated index for the country and provinces and did not produce indices across three dimensions of sustainability. In addition, considering regional context, many other studies have also been considered. For example, Shadmane et al. (2021) formalized indicators through a mapping process to quantify the energy security of Malaysia [27]. Their mapping considered the 4A’s dimensions to facilitate policymakers and energy analysts with energy outlooks to design data-driven energy security policies. Erahman et al. (2016) estimated the individual indices across five dimensions with outlier detection [28]. Only GDP and intensity indicators were used to present the social and economic issues of Indonesia. Notably, only six years of data were analyzed, and as a result, Principal component Analysis (PCA) failed in three dimensions. Similarly, Tongsopit et al. (2016) utilized individual indices across four dimensions [29]. However, they focused mainly on import indicators and applied equal weights to indicators for the Association of Southeast Asian Nations (ASEAN). To this end, the literature suggests that application of equal weight is inappropriate as different economies have different agendas to improve energy security in their respective states [30]. Moreover, in the case of Pakistan, four different studies contributed towards the energy security assessment, such as Abdullah et al. (2020), who strategized five dimensions but did not consider the sustainability dimensions for the assessments [31,32]. Malik et al. (2019) also considered energy security across 4A’s dimensions, but they focused on imports and financial aspects in indicator selection rather than the sustainability of the energy sector [33]. Shahzada et al. (2018) focused only on solar and wind in the power sector of Pakistan without the fossil fuel resources [34]. However, indicator selection was presented and how the weight of indicators was estimated was not presented.

In sum, the dimensions and indicators chosen for this study were broadly similar to those addressed in energy security research. However, a few insights can be drawn from a survey of the literature’s proposed national energy security or energy sustainability indicators and indices. To begin, economic, environmental, and social elements were addressed to provide a comprehensive review [35]. Energy security challenges from a national perspective would revolve around the economic competitiveness of its sector, the environmental impact of emissions from the energy system, and social issues associated with energy, such as energy poverty and affordability. Second, the studies differ in a variety of ways, including the recommended frameworks for organizing the indicators and the indicators themselves. The key factors of these were the study’s purpose as well as a country’s unique national energy circumstances, such as its reliance on energy imports and energy infrastructure. The implication is that in order to build a sustainable energy security measuring framework, the country’s circumstances and policies must be thoroughly studied. Finally, there is a significant disparity in the number of indicators employed. As a result, there is no agreement on how data-intensive a sustainable energy security index should be and how this would affect the outcomes. As a result, the goal of this study is to establish an energy security indexing framework for Pakistan. The concept has EISD’s distributed across three energy security dimensions: economic, social, and environmental. It is intended to offer Pakistan’s Sustainable Energy Security Index, denoted as “SESi”, as well as three sub-indices, one for each dimension. The framework identifies weaknesses in the energy supply chain while also taking into account what are known as a country’s energy concerns, i.e., balancing the three competing ends of energy security, economic competitiveness, and environmental sustainability in providing reliable, affordable, and clean energy solutions. Weight estimations will also be made using dimensionality reduction techniques after an aggregation methodology is chosen. Next, standardization will be performed, followed by a determination of the impact of the indicator on the index. Aggregation processes such as inverse, scaling, and summation would then be used to arrive at the final index (SESi). Notably, indices in the social, economic, and environmental aspects will be estimated using a similar approach.

The value of such an approach is multi-fold. To start, proposing a comprehensive methodology to evaluate sustainable energy security performance will drive energy policy and improve institutional capacity not only in Pakistan, but also in other developing countries such as India and Bangladesh. Second, analytical tools like SESi may allow analysts and regulators to identify the correct energy alternatives in the range of options available. Third, the index allows this output to be associated with the implementation of new, transformative energy policies or innovations. Fourth, dimensional wise indices allow for the understanding of complementarities between components such as availability, affordability, performance, and environmental quality. Finally, SESi will also identify energy security vulnerabilities and problems that can inspire regional collaboration by providing an opportunity for countries to work together to solve common energy security concerns.

2. Materials and Methods

In the literature, 5 different sets of sustainable energy indicators have been published [35]. The majority of indicator sets were created utilizing some form of conceptual framework. I. Gunnarsdottir et al. (2020), on the other hand, investigated the appropriateness of existing indicator sets for SES. The study selected established indicator sets for SES, as indicated in

Table 1. SES indicators reported.

Indicator—Set 1 [19]	Indicator—Set 2 [3]	Indicator—Set 3 [37]	Indicator—Set 4 [16]	Indicator—Set 5 [13]
1. Population: total; urban	1. Per capita electricity generated annually	1. Sectoral energy consumption	1. Energy import dependence (net % energy use)	1. Total energy import exposure
2. GDP per capita	2. Average energy deficit and Average peak energy deficit	2. Proven fossil fuel reserves (oil, gas, coal)	2. Diversity of total primary energysupply (Herfindahl index)	2. Electricity diversity
3. End-use energy prices with and without tax/subsidy	3. Shortfall from targets at end of 12th five year plan for length of Tx lines	3. Per capita fossil fuel reserves (oil, gas, coal)	3. Diversification of import Herfindahl index)	3. GDP per capita
4. Shares of sectors in GDP value added	4. Shortfall from targets at end of 12th five year plan for transformer capacity	4. Per capita production of energy (only commercial) from domestic sources	4. Electrification rate (% of population)	4. Security of world oil, gas, coal reserves
5. Distance travelled per capita: total, by urban public transport mode	5. Shortfall from targets at end of 12th five year plan for T&D infrastructure	5. Net energy import dependence	5.% of population using solid	5. Security of world oil, gas, coal production
6. Freight transport activity: total, by mode	6. Percentage of technical and commercial losses	6. Shannon–Wiener Index	6. Fuels for cooking (%)	6. Petroleum, gas, coal import exposure
7. Floor area per capita	7. Fresh water use for electricity generation	7. Per capita energy consumption	7. Quality of electricity supply	7. Energy consumption per capita
8. Manufacturing value added by selected energy intensive industries	8. Land used for electricity conversion in coal plants	8. Lack of access to modern energy	8. Cost of energy imports (% GDP)	8. Transportation energy per capita
9. Energy intensity: manufacturing, transportation, agriculture, commercial & public services, residential sector	9. Weighted average of CO2 emission intensity of fossil fuel fired plants	9. Total and per capita CO2 emissions	8. Distortion to gasoline pricing (index)	9. World oil refinery utilization
10 Final energy intensity of selected energy intensive products	10. Average volume of waste water discharged from coal plants	10. CO2 emission intensity (monetary or physical)	10. Electricity prices for industry	10. Fossil fuel import expenditures per GDP
11. Energy mix: final energy, electricity generation, and primary energy supply	11. Utilization of fly ash generated from coal plants	11. Share of non-carbon and modern RE	11. Distortion to diesel pricing (index)	11. Retail electricity prices
12. Energy supply efficiency: fossil fuel efficiency for electricity generation	12. Weighted average efficiency of fossil fuel fired plants	12. % change in retail prices of energy	12. Energy exports (% GDP)	12. Energy expenditure volatility
13. Status of deployment of pollution abatement technologies: extent of use, average performance	13. Efficiency of transmission and distribution of electricity	13. Energy subsidy in US$	13. Alternative and nuclear energy (% of total energy use)	13. Crude oil price volatility
14. Energy use per unit of GDP	14. Average efficiency of conversion, T&Dof electricity	14. % share of household income spend on lighting and cooking	14. CO2 emissions from electricity production	14. Crude oil prices
15. Expenditure on energy sector: total investments, environmental control, hydrocarbon exploration & development, RD&D, net energy import expenses	15. Per capita crude oil refined annually	15. Energy intensity for country’s economy	15. Methane emissions in energy sector	15. Energy expenditures per capita
16. Energy use per capita	16. Excess (shortfall) refining capacity	16. Thermal efficiency and T&D loss	16. Nitrous oxide emissions in energy sector	16. Non-CO2 emitting share of electricity generation
17. Indigenous energy production	17. Spare pipeline capacity of major pipelines		17. PM10, country level	17. Energy-related CO2 emissions intensity
18. Net energy import dependence	18. Average gross refining margin		18. Energy intensity	18. CO2 emissions trend
19. Income inequality	19. Average fresh water consumption in oil refineries		19. Average fuel economy for passenger cars	19. Energy-related CO2 emissions per capita
20. Ratio of daily disposable income/private consumption per capita of 20% poorest population to the prices of electricity and major household fuels	20. Average land used for refining			20. Energy intensity
21. Fraction of disposal income spent on fuels (total population, 20% poorest)	21. Concentration of air pollutants			21. Transportation energy intensity
22. Fraction of households: heavily dependent on non-commercial energy; without electricity	22. Average waste water generation in oil refineries			22. Petroleum intensity
23. Quantities of air pollutant emissions (SO2, NOx, particulates, CO, VOC)	23. Solid pollutants (volume and concentration)			23. Energy expenditure intensity
24. Ambient concentration of pollutants in urban areas: SO2, NOx, suspended particulates, CO, ozone	24. Average conversion efficiency of oil refineries
25. Land area where acidification exceeds critical load.	25. Average conversion efficiency of transportation
26. Quantities of greenhouse gas emissions	26. Average efficiency of conversion and transportation
27. Radionuclides in atmospheric radioactive discharges	27. Average per capita electricity consumption per year
28. Discharges into water basins: waste/storm water, radionuclides, oil into coastal waters	28. Average per capita LPG consumption per year
29. Generation of solid waste	29. % of population with access to electricity
30. Accumulated quantity of solid wastes to be managed	30. % of population using LPG/PNG for cooking
31. Generation of radioactive waste	31. % of expenditure on fuel and light by households
32. Quantity of accumulated radioactive wastes awaiting disposal	32. Weighted sum of price distortion score due to subsidies for cooking
33. Land area taken up by energy facilities and infrastructure	33. Weighted sum of price distortion score due to subsidies for lighting
34. Fatalities due to accidents with breakdown by fuel chains	34. Annual CO2 emissions per household
35. Fraction of technically exploitable capability of hydropower currently not in use	35. Average lighting efficacy
36. Proven recoverable fossil fuel reserves	36. Average cook stove efficiency
37. Life time of proven fossil fuel reserves	37. Average appliance efficiency
38. Proven uranium reserves	38. Number of hours of electricity supply in a day
39. Life time of proven uranium reserves	39. Weighted sum of price distortion score due to subsidies in energy sources used in sector
40. Intensity of use of forest resources as fuelwood	40. CO2 emission intensity of industrial sector
41. Rate of deforestation	41. Energy intensity of industrial sector
	42. Energy intensity of service sector
	43. % share of electrified pump sets in sector
	44. Energy intensity of agriculture sector
	45. Energy intensity of transport sector
	46. O2 emission intensity of transport sector

, and generated indicator set assessment criteria [36]. The criteria were based on features such as (1) indicator transparency, (2) conceptual framework, (3) representativeness, (4) linkages, and (5) stakeholder engagement. The study’s authors determined that the “Energy Indicators for Sustainable Development (EISD)” was the only indicator set that matched all criteria and could thus be considered comprehensive and robust. The EISD’s were transparent and clear, representative of SES, considered interconnections within the set, and based on stakeholder input. Therefore, this study selects the EISD’s which are divided into three categories: social, economic, and environmental [19].

In the context of Pakistan, however, 26 EISD’s were formed (

Table 2. Sustainable energy indicators for Pakistan.

List of Indicators (EISDs)	Themes	Dimension
1 Total primary energy supply (TPES) per capita	Overall Use	Economic
2 Electricity per capita	Overall Use
3 Total primary energy intensity	Productivity
4 Final energy intensity	Productivity
5 Loss in Transmission	Efficiency
6 Loss in Transformation	Efficiency
7 Reserve Production ratio (RPR) Crude oil	Production
8 Reserve Production ratio (RPR) Natural Gas	Production
9 Reserve Production ratio (RPR) Coal	Production
10 Final energy consumption (FEC) per capita	End Use
11 Industrial Energy Intensity	End Use
12 Agriculture Energy Intensity	End Use
13 Commercial Energy Intensity	End Use
14 Household energy per capita	End Use
15 Household electricity per capita	End Use
16 Transportation Energy Intensity	End Use
17 Share of capacity of renewable energy/total electricity generation	Diversifiation
18 Share of Non-carbon energy per TPES	Diversifiation
19 Share of Renewable energy per FEC	Diversifiation
20 Net Energy Import Dependency (NEID)	Imports
21 CO2 emission per capita	Climate Change	Environment
22 CO2 emission per GDP	Climate Change
23 Forest area to Land area ratio	Forest
24 Household access to electricity	Accessibility	Social
25 Share of income spent on electricity	Affordability
25 Residential Energy/Household	Disparity

) based on a framework (Figure 1) (Appendix A). The exclusion criterion for ignoring the indicators was data non-availability (Appendix B). The time series data was derived from the Ministry of Finance’s Pakistan Economic Survey, the Hydrocarbon Development Institute of Pakistan’s (HDIP) Pakistan Energy Yearbook, the World Bank (WB), the Asian Development Bank (ADB), the Energy Information Administration (EIA), or the International Energy Agency (IEA). Data on water quality, soil quality, solid waste, and nuclear waste were not available and were thus neglected (Appendix B). Based on the framework, there are some phases involved in developing the indices, which are as follows.

Standardization, Weighting and Aggregation of Indicators

While indicators are associated with multiple units, transformation (normalization) is required prior to the aggregation phase in order to determine an index [17]. The indicators of energy security have been standardized in a variety of ways [38,39,40,41]. The Z-score is employed in this study to offer new values to the indicators, resulting in a “standard deviation” of 1 and a “mean” of 0 (Supplementary file). For weight estimation, the indicator’s data necessitates the employment of a dimensional reduction approach. There have been 13 documented dimensional approaches [41], with Principal Component Analysis (PCA) being the most commonly used [42]. Notably, V.D. Maaten et al. (2009) stated that PCA has outperformed all other dimensional reduction techniques [41]. As a result, PCA was chosen as the analytical method for this investigation, and KMO (Kaiser Meyer Olkin) tests were obtained using IBM’s SPSS Version 22. KMO is required for PCA to validate data adequacy (acceptable limit is 0.5 or more [17]). The KMO for SESi was 0.728 (greater than 0.5 required) and the significance of Bartlett’s Test was 0.000 (lower than 0.05 required). Therefore, this confirms that the data were adequate for PCA testing. The results of PCA based on eigen values of more than 1 are shown in

Table 3. Principal Component Analysis (PCA) results for SESi.

Rotated Component Matrix
	Group
	1	2	3	4
FEC/Capita	0.921
NEID	−0.915
Reserves/Production (Gas)	−0.908
TPES/Capita	0.899
Renewable Share (Non-Hydro)	0.883
Household Energy/Capita	0.870
Electricity/Capita	0.863
Residential Energy/Household	0.856
Forest/Land Ratio	0.897
% Income spent	0.842
CO2/Capita	0.840
Transformational Losses	−0.819
Access to Energy	0.793
Agricultural Intensity	−0.786
Electricity/Household	0.776
CO2/GDP	−0.755
Commercial Intensity	0.751
Reserves/Production (Coal)	−0.679
Reserves/Production (Oil)	0.658
Share of Non-Carbon/TPES		−0.898
Renewable Share/FEC		−0.839
Transport Intensity			0.930
TD Losses			0.651
FEC/GDP				0.868
Industrial Intensity				0.849
TPES/GDP				0.725

Source: Author’s own estimation.

. It may be difficult to identify the list of indicators in each group since certain indicators may have medium values of factor loading for more than one group. As a result, the factor rotation method, such as “Varimax”, was used to solve this problem (Table 3). The rotation provides the list of indicators in each group. Notably, the results of PCA provide the “% of variance (Vark)“ and “ cumulative % of variance (ΣVark)” as shown in

Table 4. Weight estimations based on PCA extraction.

Component
	Total	% of Variance	Cumulative %	${\mathit{w}}_{\mathit{k}}$
1	13.137	54.337	54.337	W1 = 54.337/89.497 = 0.607
2	3.309	12.571	66.908	W2 = 12.571/89.497 = 0.140
3	2.963	11.401	78.309	W3 = 11.401/89.497 = 0.127
4	2.876	11.188	89.497	W4 = 11.188/89.497 = 0.125

Source: Author’s own estimation.

. These results are also used to determine the weighting factor for the list of indicators in each group.

An indicator’s impact on an index might be both positive and negative. In counteract, negative signs must be inversed as the starting step, whilst positive indicators are to be handled directly via Equation (1). The next step is the scaling (${\phi }_i)$ function, which converts the indicator in a range of 1 to 10 by identifying the maximum value in a set (Equation (2)).

$$Ma{x}_{ij}=\left\{Y_{ij}\dots \dots \dots .Y_{in}\right\}$$

(1)

And

$${\phi }_i=\raisebox{1ex}{$\left[10X_{ij}\right]$}\!\left/ \!\raisebox{-1ex}{$Ma{x}_{ij}$}\right.$$

(2)

where ${\phi }_i$ is the relative indicator i of year j, Xij and $Y_{ij}$ are the value of positive indicator i of year j, $Ma{x}_{ij}$ is the maximum value of the indicator i, and i is indicator i.

Following the scaling, the group index ($G{I}_{kj})$ is to be calculated through estimating the root mean square of all scaled indicators (${\phi }_i)$ for both positive and negative indicators (Equation (3)).

$$G{I}_{kj}=\sqrt{\sum \frac{{\phi }_{ij}{}^2}{m}}$$

(3)

where $G{I}_{kj}$ is the group index ‘k’ of year j, ${\phi }_{ij}$ is the relative positive and negative indicator i of year j, and m is the number of indicators in each group.

To compute “m”, take into account the factor loading value that is near to 1 (or −1). It specifies whether this indicator belongs to one group (component) or the other. For example, two indicators belong to groups 2 and 3, while three and nineteen indicators belong to groups 4 and 1, respectively (Table 3). The final index is to be aggregated via equation 4 based on group indices (Supplementary file). Notably, the “$w_k$” for each group was estimated with the total value of “Cumulative%”. The value in this case is 89.497, and it will be used to estimate the weighting factor for each group of indicators, as shown in Table 4. The same approach was used to calculate indices for the social, economic, and environmental dimensions.

Table 5. Results of PCA & weighting factor across dimensions.

Index Name	KMO & Bartlett’s Test	Decision	% of Variance	Cumulative %	Weight ${\mathit{w}}_{\mathit{k}}$	Components Extracted
Economic	0.681 sig 0.000	Passed	50.351 15.169 12.840 11.305	50.351 65.520 78.360 89.665	0.561 0.169 0.143 0.126	4
Social	0.693 sig 0.000	Passed	82.547	82.547	Equal	1
Environment	0.497 sig 0.000	Failed	85.612	85.612	Equal	1

Source: Author’s own estimation.

displays the PCA and weight factor results. Aside from the environment dimension, all other indices passed the test. For index development, equal weight was assigned to the environment dimension (Supplementary file).

$$SESi=\frac{\sum \left\{w_k\times G{I}_{kj}\right\}}{\sum w_k}$$

(4)

where $SESi$ is the Aggregated Indicator of year j, $G{I}_{kj}$ is the group index ‘k’ of year j, and $w_k$ is the weighting factor of group index ‘k’.

3. Results and Discussion

Based on the equations and aggregation process, the aggregated index and dimension wise indices were produced as shown in

Table 6. Sustainable performance indices.

Year	SESi	ECO Index	Soc Index	Env Index
1991	8.33	7.97	6.74	9.48
1992	8.14	7.81	6.31	9.49
1993	7.93	7.59	6.04	9.36
1994	7.87	7.54	6.01	9.27
1995	7.65	7.29	5.85	9.22
1996	7.74	7.42	5.94	9.15
1997	7.63	7.34	5.79	8.95
1998	7.45	7.15	5.79	8.95
1999	7.39	7.12	5.72	8.55
2000	7.52	7.27	5.58	8.71
2001	7.46	7.27	5.30	8.71
2002	7.44	7.25	5.29	8.66
2003	7.38	7.12	5.55	8.66
2004	7.17	6.95	5.31	8.20
2005	7.26	7.10	5.18	8.33
2006	7.42	7.32	5.09	8.05
2007	7.17	7.02	5.22	7.69
2008	7.35	7.20	5.25	7.99
2009	7.36	7.18	5.46	7.94
2010	7.46	7.27	5.31	8.20
2011	7.35	7.20	5.12	8.23
2012	7.52	7.41	4.99	8.29
2013	7.63	7.47	5.37	8.43
2014	7.65	7.56	5.11	8.23
2015	7.59	7.51	4.90	8.00
2016	7.48	7.38	4.63	8.05
2017	7.37	7.31	4.44	7.62
2018	7.42	7.37	4.74	7.78
2019	7.48	7.45	4.72	7.75
2020	7.56	7.55	4.69	7.75

Source: Author’s own estimation.

.

3.1. Sustainable Security Index (SESi)

During the study period, the aggregated index “SESi” decreased, as shown in Figure 2. The highest score was 8.33 in 1991, and the lowest was 7.17 in 2007, with steady performance through 2020 (Table 6). The SESi index continued to increase from 2006 to 2020, but it did not reach the 1991 peak. Between 1991 and 2020, almost 9% of the sustainable index fell. Furthermore, between 1991 and 2020, all of the sustainable dimensions deteriorated. The most significant loss was seen in the social dimension, which fell by 30%, followed by the environment dimension, which fell by 18%. The economic dimension had seen the smallest reduction of 5% (Figure 2). According to PCA, the social and environmental aspects belong to the first group of principal components (PC) of SESi and thus have a weightage of 9% each. SESi’s remaining three PCs are based on economic indicators (Supplementary file). Between 1991 and 1995, the SESi followed the same trajectory as the economic index, although the social index also played a role in lowering the score. During this time, the environmental index was slightly squeezed but had a minor impact on SESi. Furthermore, between 1996 and 2000, the economic index improved marginally, but the social and environmental indices deteriorated, influencing the SESi. SESi was not influenced by the economic index between 2001 and 2010, but the social index and the environmental index converged to lower SESi’s performance, whereas in the previous decade, SESi was unaffected by the economic index and was reduced by the social index, which was followed by the environmental index. This implies that, during the last decade or two, the economic position has improved, but social equity has been jeopardized, as has environmental degradation.

The government restructured the power sector between 2006 and 2010, and other programs such as energy conservation were planned [31,32]. As a result, the SESi and economic aspects remained largely stable, while the social dimension increased by 4%. Furthermore, the environmental dimension increased by 1.8%, owing to CO2/GDP (which decreased by 7.6%). As in the previous period, the indicator “%age of income toward energy” contributed to the social dimension. Additionally, import reliance “(NEID)” has played a role in this, falling from 80% to 60% from 1996–2000. Risks involved with imports are mostly associated with quantity and price. Both can be addressed by decreasing import dependence, which can be accomplished by policies that increase domestic energy supply, improve energy efficiency, diversify fuel supplies, and maximize fuel mix. Since 2005, the government of Pakistan has prioritized the physical availability of supplies to meet demand for economic and social sustainability (

Table 7. List of policies and initiative by governments.

Period	Policy Objectives and Government og Pakistan (GoP) Initiatives
1990–1995	Three distinct sets of policies were announced, including “1991-Petroleum Policy”, “1994-Power Policy”, and “1995-Hydel Policy [44]”. The Private Power Infrastructure Board (PPIB) and the National Electric Power Regulatory Authority (NEPRA) were constituted as separate boards (NEPRA) [44]. The major purpose was to attract private investment through a one-stop shop. Other goals included increasing indigenous oil and gas output as well as refining capacity. Its goal was to eliminate load-shedding by increasing capacity in the power sector. Adding Hydel sources, in particular, to reduce tariffs [45]. The use of other renewables, as well as the reduction of lead-based fuel, was also encouraged. Energy conservation measures were created in tandem with transportation sector efficiency improvements [44].
1996–2000	The “Pakistan Council of Renewable Energy Technologies (PCRET)” was formed, and compressed natural gas (CNG) was introduced into the transportation industry [44]. In addition, 325 MW of nuclear electricity was added to the national grid [46].
2001–2005	The “2002-Power Policy” was announced with the goal of increasing capacity in the power sector while also pursuing low-cost and indigenous oil and gas production [47]. During this time, electricity imports began, and the usage of other renewables was also encouraged in order to protect the environment [46]. The “Alternate Energy Development Board (AEDB)” was established, and a long-term “Energy Action Plan-2030” for capacity expansion at a 10% growth rate by 2030 was introduced. The “Oil & Gas Regulatory Authority (OGRA)” was established to oversee the oil industry. “Karachi electric supply corporation (KESC)” was privatised to create “K-Electric” in order to bring about reform in the power sector [44].
2006 -2010	The “2006-Renewable Policy” was announced with the goal of focusing on Mainstreaming and Decentralized Renewable Energy in the power sector [48]. The “2010-Energy Policy” was also unveiled, with the goal of improving “access to modern energy”. Furthermore, extensive reforms were implemented, including the establishment of “Water & Power Development Authority (WAPDA)”, “Pakistan Electric Power Company (PEPCO)”, “Generation Companies (GENCOs)”, and “Distribution Companies (DISCOs) [49]”. Despite this, a problem of circular debt arose, reaching Rs. 584 billion [50]. CNG load management was implemented in the taransport sector to increase the reserve to production ratio of gas [51]. The energy saving programme was also improved with initiatives such as two days off per week in the public and private sectors, as well as a prohibition on the use of neon lights [52].
2011–2015	Four sets of policies were announced: “2012-Petroleum Policy”, “2012-National Climate Change Policy”, “2013-Power Policy”, and “2015-Generation Policy [53]”. The power policy emphasised affordable electricity, improved bill collection, and increased self-sufficiency through exploratory activities. The efficiency of the power sector was also prioritised, along with improving governance and reducing energy transmission losses through technological innovations [54]. Environment sustainability was also developed in order to address the difficulties of climate change and assure long-term economic growth. Capacity increases in the electricity industry based on Thar coal have also begun as part of the “China-Pakistan Economic Corridor (CPEC) [55]”. Other energy projects worth $28 billion were also fast-tracked under CPEC, with 100 MW of solar energy and 325 MW of nuclear power added to the grid. LNG imports began, and substantial efforts were made to exploit local resources [56].
2015–2020	In 2016, a 6000 MW electricity gap was recorded, and RLNG imports for the transportation sector commenced to reduce demand [49]. NEPRA and OGRA took control of various government ministries [57]. “In 2017, the Ministry of Climate Change was founded”. The Thar Coal-based power capacity of 660 MW was added to the grid. A total of 7285 villages were electrified, with a total of 5,387,641 connections provided [52]. The “2019-Alternative & Renewable Energy Policy (ARE)” was introduced with the goal of providing affordable electricity, increasing self-sufficiency, and ensuring energy security [32]. The policy also prioritised environmental conservation and distributed generation in order to improve social equality.

). As a result, imports decreased drastically between 2003 and 2020. Notably, NEID was just 38% in 2020, but oil and gas reserves were more exhausted since no major new recoveries were recorded between 2003 and 2020 [43]. This reflects the fact that the power policy (2002) and power policy (2009) resulted in increased indigenous output and reduced disruption risks, while the petroleum policy (1991) did not perform as expected between 1991 and 2002.

The electricity sector also did not perform as predicted, with generation and usage both increasing by 6.3 % between 1991 and 1995 [43], but load shedding was observed due to massive transmission losses of 31% during this time. Only hydel resources were used for clean energy, and their production rose by just 2.6%. SESi fell by 2.8% between 1996 and 2000, relative to the previous period. During this time frame, the social and environmental dimensions both contributed dramatically, with a 6.06% and 4.8% decrease reported in both. During this time, the electricity market was restructured in order to meet the previous period’s targets [47]. To this end, energy supplies improved at a rate of 2.8% annually and consumption decreased by 2.4% from 1996–2000. Interestingly, the social and environmental dimensions decreased as a result of “energy per household” and “forest/land ratio”. During this time, “energy per household” rose by 7.5%, while “forest ratio” decreased by 7.4%. This suggests that the goals of the petroleum policy (1991) and power policy (1994) were not met (Table 7). Furthermore, three indicators, namely, “reserves”, “T&D loses”, and “NEID”, helped to balance the sustainability index. Oil reserves rose to 12 years from 8 years in the previous period, while NEID remained relatively stable at 79% during this period. This suggests that the utilization of renewables in the energy mix was also not achieved, as the hydro share of supplies steadily declined from 5% in the previous period to 3.5% by the end of this period (1996–2000). Notably, the target of improving efficiency was reached when “Electricity/Capita (kwh)” rose by 5%, owing to “T&D losses”. “T&D losses” were reduced from 45% to 34% in 1997, while “Transformation losses” were also reduced from 43% to 34%.

During the period 2001–2010, the SESi fell by 1.3%, with the environmental dimension outweighing the economic and social dimensions. The environmental dimension fell by 5.8%, while the economic and social dimensions remained fairly stable. The new power policy (2002) was also revealed, as were the two boards in charge of managing alternative energies and controlling the oil and gas sectors (Table 7). In order to make further progress, the Energy Security Action Plan 2030 was also announced. Surprisingly, past efforts to boost the transportation industry have yielded results, as transportation intensity has decreased significantly by 8.3% during this period. However, the tradeoff was observed here, as the introduction of CNG in the transport industry added substantially to the reduction of gas reserves. The gas reserves were estimated to be 22 years by 2001, but had decreased to 18 years by 2010, representing an 18% decrease. Furthermore, due to imports “(NEID)” and “percentage of income towards energy”, the social and economic dimensions remained constant during this time period. The NEID decreased by 25.5%, while the “percentage of income towards energy” remained relatively steady (Appendix A).

Between 2011 and 2020, the “Ministry of Climate Change” [45] and three distinct policies (Table 7) were announced in response to emerging issues such as collection and payments and environmental sustainability. Surprisingly, the SESi increased by 2.7% over this time frame due to economic factors alone. The economic dimension increased by 4.6%, while the social and environmental aspects decreased by 8.3% and 5.8%, respectively. From 2013–17, the country experienced severe load shedding, and the gap between supply and demand rose to 6000 MW [58]. Surprisingly, the measures “Supply/Capita” and “FEC/Capita” were balancing each other out as they both increased by 12% during this time. Furthermore, the indicators “T&D loses”, “Industrial Intensity”, and “commercial intensity” were driven by the economic dimension and SESi because they encountered substantial fluctuations during this period. The “T&D losses” decreased to 25.8% from 34% in the previous period, while the “industrial and commercial intensities” improved by 14.4% and 9%, respectively. Notably, the economic dimension was improved due to the prices of gasoline, and diesel prices were kept to Rs. 100/Liters during 2015–16 [59]. Moreover, the other two dimensions were lowered due to “percentage of income towards energy”, “Forest/Land ratio”, and “CO2/Capita”. During this time, the “percentage of income towards energy” and “CO2/Capita” rose by 8.8% and 10.8%, respectively, while the “forest/land ratio” declined by 23%. This demonstrates that the goals of the “national climate change policy (2012)” and the “Ministry of Climate Change” to address the threats posed by climate change had not been met.

Nonetheless, SESi and dimensional indices exhibit annual trends and are capable of analyzing varied collections of policies and programs, making the development of a long-term strategic energy plan to address potential energy demands and supply routes feasible. The findings indicate that SESi fell to a moderate level and that related dimensions regressed between 1991 and 2020. The policies and initiatives, as shown in Table 7, had assisted in maintaining performance but had not been adequate to raise it to a level comparable to 1991 due to the following priority concerns:

• The use of renewables fell between 1991 and 2000, indicating a partial failure of the petroleum policy (1991), although indigenous production increased. However, the tradeoff was that oil and gas resources were greatly exhausted.
• Despite the fact that capacity growth was focused on in virtually every power strategy, the nation faced an energy shortage of up to 5000 MW [58]. The explanation for this is that the “Electricity/Capita (KWh)” rose by 36%, indicating the collapse of the power policy (1994), power policy (2002), power policy (2004), and power policy (2013).
• The industrial and commercial intensities rose by 2% and 33%, respectively, demonstrating that the energy production and conservation goals stressed in the petroleum policy (1991), electricity policy (2010), and power policy (2013) did not produce results.
• Significant progress was made when “T&D Losses” were reduced from 45% in 1998 to 22% in 2020. They should ideally be no more than 5% [60]. To that end, partial failures of the power policy (2013) and petroleum policy (2012) priorities were observed.
• Over the study period, import dependency “(NEID)” declined substantially. The NEID accounted for 40 percent of production in 2020, suggesting that indigenous demand, as per the petroleum policy (2012), showed signs of progress, but “income towards energy” show that the Oil & Gas Regulatory Authority (OGRA) neglected to set short-term goals based on constant monitoring of international prices at regular intervals.
• The country’s projected capacity for “Use of Renewables (Non-Hydro)” could not be realized until 2013. This suggests that the renewable policy (2005) and the “Pakistan Council of Renewable Energy Technologies (PCRET)” failed to achieve the necessary results.
• Over the study period, “CO2/Capita” rose by 5%, while the “Forest/Land ratio” decreased by 19%. The country still has the lowest forest cover in the region [61], indicating that the national climate change policy (2012), power policy (2013), and Ministry of Climate Change are out of alignment with the country’s environmental challenges.

3.2. Economic Index

The economic index assesses how energy consumption and production patterns, as well as the quality of energy services, affect economic development progress. What is the state of all sectors of an economy that demand energy—residential, industrial, commercial, transportation, service, and agriculture? These energy services, in turn, support local economic and social development by increasing productivity and promoting local income production [62]. Energy availability has an impact on jobs, productivity, and development. Hence, the main themes of the economic index are “End Use”, “Productivity”, “Diversification”, and “Efficiency”. For Pakistan, the decrease in the economic dimension between 1991 and 2004 is illustrated by Figure 2. Since 2005, the index has improved with fluctuation until 2020. PCA assigned six indicators to each of components 2, 3, and 4, accounting for 42% of the weightage in the economic index (Supplementary file). The indicator “Transport Intensity” earned the most weight (12.6%), followed by “Renewable share/FEC” and “Non-Carbon share/TPES”. They each account for 8% of the total weightage. In addition, 4.7% of the weightage was assigned to “TPES/GDP” and “FEC/GDP”. There were variations during the studied time. The transport intensity was 70.49 kgoe/$, with a high of 77.92 kgoe/$ in 1999 and a steady fall to 61.04 kgoe/$ in 2006. It continued to grow until it peaked in 2017, followed by a 13% decline in 2020 (Figure 2). As a result, the economic index fluctuated throughout, with the transportation sector accounting for 34% of total final energy consumption (FEC) [63]. Notably, the upward and downward trend was triggered by two important government policies. CNG was introduced to the transportation market in 1997, but gas supplies were soon exhausted, triggering the 2007 introduction of CNG load control to reduce gas demand (Table 7) (Appendix A). This shows that transportation industry reforms did not work during the study period. We observed that the petroleum policy (1991) struggled to achieve the sustainability target, as “FEC/GDP” rose by 6.4% in 2000 relative to 1991. Furthermore, it rose by 2.7% between 2001 and 2010, and then remained relatively unchanged until 2020. As a result, “Supply/GDP” had to rise, following the same pattern as demand intensity. Both of these indicators caused fluctuations because they account for 9.4% of the economic index’s weight (Figure 2). Energy consumption per unit of economic output (FEC/GDP or Supply/GDP) is more useful for comparing energy efficiency to economic activity, but reductions in intensities translate into more efficient use of energy capital and lower negative environmental impacts. As a result, improvements in intensities have been observed only in the last decade, indicating the energy policy (2010) and other programs have shown results since their inception (Table 7).

The use of renewables was the focus of three separate policies over the last three decades, but the only main renewable energy source used was hydro source. Notably, indicators belonging to the same principal component (PC) were weighted at 8% in the economic index and 7% in the SESi through PCA. The “Renewable or Non-carbon share/FEC” encourages climate efficiency, energy resource diversification, and environmental sustainability. During the period 1991–2020, the “Renewable share/FEC” averaged 6.9% and the “Non-Carbon share/TPES” averaged 4.5%. However, the use of renewable energy sources other than hydro, such as wind and solar, did not become prominent until 2013. These indicators suggest that the establishment of the Alternate Energy Development Board (AEDB), the Pakistan Council of Renewable Energy Technologies (PCRET), and the Renewable Policy 2006 did not yield the desired results. As a result, the government unveiled the Alternative & Renewable Policy (2019), with the aim of decentralizing renewable energy sources to promote energy equity and accessibility [48] (Table 7).

3.3. Social Index

The social index focuses on factors such as accessibility, cost, and disparities in energy supply and demand [63]. The availability of energy services may have consequences for poverty, community development, and culture. Indicators such as “Residential Energy per Household” and “Income Towards Energy” are examples that reflect a population may have a high per capita GDP, but its income distribution may be so skewed that a significant part of the population is unable to meet their household energy needs at current energy prices and private income levels. As a result, in order to promote social and economic development, the burden of expenditure on fuel and electricity in household budgets for the lower-income sector must be reduced. During the study period, the social dimension regressed by 30% in the case of Pakistan (Figure 2). One component of PCA extraction had three indicators and was given equal weight. Notably, there are significant differences between the indicators “Residential Energy per Household” and “Income towards Energy”. Aside from that, “Access to Energy” improved by only 1.7% between 1991 and 2000 and then remained relatively stable until 2020 (Figure 2). As a result, it is clear that the major role was played by “Residential Energy per household” and “Income towards energy” to the social index and, overall, to SESi. The aim of the “Income towards energy” is to assess the extent of accessibility and availability of energy supplies for lower-income classes of the population in order to reduce poverty and foster social and economic growth [17]. It was found that it rose dramatically by 11% between 1991 and 2000, followed by an increase of 8%, respectively, between 2001 and 2010 and 2011 and 2020 (Figure 2). One such example is the spike in 2013 (Figure 2), when income levels fell by 9% and residential shares fell by 5%. This suggests that policymakers in Pakistan struggled to decrease the strain of expenditures on fuel and energy for the lower-income classes of the population. On the other hand, the indicator “Residential energy per household” has risen approximately 50% since 1991, suggesting that the allocation was distorted and that a significant majority of the population failed to meet their needs for household energy due to energy prices and private income levels. As a result, we can see that several priorities of various policies, such as the petroleum policy (1991), the hydel policy (2005), the oil policy (2010), and the power policy (2013), have failed to perform.

3.4. Environment Index

The creation, delivery, and consumption of energy impose strain on the environment. These environmental effects vary depending on how energy is produced and consumed, as well as on energy regulatory measures and pricing structures [64]. Climate change, air pollution and degradation, and deforestation are among the major environmental concerns confronting Pakistan. The climate domain deteriorated 18% from 1991–2020, as shown by the environmental index of Pakistan (Figure 2). During the study period, the index sharply declined between 2013–17, driven by “CO2/Capita” and “Forest/Land ratio”. During the study period, “CO2/Capita”, for example, has increased by more than 26% since 1991, driven by combustion of fossil fuels and deforestation. In comparison, “CO2/GDP” remained relatively steady owing to GDP growth of 3.9% per year [6]. The “forest/land ratio”, on the other hand, regressed by 49% between 1991 and 2020, with a noticeable decrease of 23% observed in the last decade. Notably, the country already accounted for the lowest forest-cover in the world, caused by arid and semi-arid climate in many parts of the country [61]. As a result, the country has been witnessing more severe weather events, such as increased flooding, landslides, rainfall, and drought in some regions. The emissions are also linked with energy consumption (FEC/Capita), which is reported to have increased by 38% from 1991–2020. This reflects that the petroleum policy (1991) and energy policy (2010) did not work along with other initiatives to promote the use of renewables and sustainability. Consequently, the new “ARE policy (2019)” was announced to aim for sustained energy security and environmental protection [49].

The use of coal in power and commercial sectors in the country has contributed a growth rate of 20%; however, “CO2/Capita” remained fairly stable in the last five years [46]. The major share was driven by the power sector as four new coal-based plants have been added to the grid since 2018. These plants are technologically advanced and produce lower emissions. Therefore, much of their impacts on the environment in this study are not analyzed due to the lack of data, but we hope to include them in future studies.

4. Implications

Apart from the methodology considerations, this study intends to help Pakistan policy makers to develop future pathways. So, as predicted, people’s lifestyles in Pakistan may change in the future as they emerge from poverty [65]. This in turn may affect growth in energy demand [66]. The results can be disclosed via the economic index as it has increased steadily (about 7% in 2020) since 2007. As a result, energy demand in Pakistan will be 240 MTOE by 2030, compared to 54 MTOE, currently, at a growth rate of 6.5 per cent [46,67]. Therefore, there is no exemption from the exploitation of the coal and hydro resources [68]. Notably, with wind and solar technologies, Pakistan must wait a few years as the international market is not yet open and within an affordable range [69]. However, 1500 MW of wind, solar, and bagasse (a biowaste) facilities have been built, with plans to increase this to 3500 MW by 2025 [52]. Moreover, the country has introduced, and may encourage even more, solar power to rural villages [70]. The World Bank has supported approximately 0.2 million solar residential systems and larger grid-connected devices [57]. To that end, Pakistan must leverage the experience of private enterprises in commercializing solar home systems and mini-grids, similar to those operating in the South Asian and East African regions, in order to make further progress [61,71]. Likewise, the government should encourage banks to finance these projects and promote collaboration between solar system suppliers and regional distributors [72,73]. The best model is Bangladesh, where the public–private partnership model proved successful in attracting $500 million for the widespread deployment of off-grid solar photovoltaic systems [74].

As a result of quasi-fiscal deficits and low efficiency, Pakistan’s power sector was unable to attract the capital and funding required to satisfy rising electricity demand [75]. It is suggested that gas and clean energy must be given priority since they all seem commercially competitive and can draw private equity and debt funding [76]. With rapid urbanization coupled with lower efficiencies, we found that “residential energy/household” increased by 44% in the period 1991–2020. Conservation schemes must then be used by building envelopes, devices, and HVAC system requirements, as well as offering incentives for building owners to engage in new energy conservation systems [77]. Furthermore, the exploration policy (2012) is oriented toward low-cost oil and does not account for high-cost oil [57]. As estimated, “R/P ratios” of oil and gas imply that activity in this area has been at a low level during the last decade or so (Appendix A) [69]. In order to entice international firms to engage in exploration operations, high-priced activities will be offered up to $50 to $60 as an alternative [56,78]. It may also be beneficial to receive guidance from a consulting firm in this regard [78].

Additionally, an analytical framework such as SESi can assist stakeholders in synthesizing energy imports (NEID) from other countries in order to realize the genuine local energy potential and reduce reliance on outside sources. The country has already achieved major reductions in oil generation, particularly through natural gas replacement, and has cut its import costs by more than $2 billion [79]. In addition, preference may be given to nuclear production in the energy mix as the country has a wide pool of scientific staff in this sector. However, the cost per KW of nuclear power plants has not yet been feasible due to high capacity factors [46,78]. Further on the strategic front, Pakistan, similar to India, has not signed the “Nuclear Non-Proliferation Treaty” and would preferably not wish to have an association program with the IAEA to guarantee the insurance and security of new plants [74]. Consequently, with lower “R/P ratio-gas” and due to significant price fluctuations in the future [9], the country secured a gas (LNG) import contract with Qatar in 2015 [57]. As a result, Pakistan has purchased LNG facilities, comprising two floating storage regasification units (FSRU), to handle 14 million metric tons of imports per year [80]. Additionally, Pakistan should continue to diversify its Central Asian oil and gas imports, foster diplomatic relations, and boost economic growth. Approximately, electricity imports from Iran are around 130 MW, although this can be surpassed by as many as 3000 MW to Pakistan, based on the US sanctions [81].

Additionally, the sectoral intensities have contributed to the economic index significantly between 1991–2004 (Figure 2). A nearly 13% decrease in the index is observed (Appendix A). Here, agricultural intensities decreased by 65%, driven by reforms and use of efficient equipment [56]. However, the commercial intensity increased by 33%, driven by rapid urbanization. This reveals that energy efficient options remain largely unexploited in this domain. To counter, a vigorous campaign could enhance the awareness among the commercial sector of the substantial economic benefits of energy efficiency. Holistically, the country needs a robust strategy to launch a sustainable long-term energy efficiency program integrated with incentive mechanisms across industrial, commercial, and transport sectors [82].

Another significant finding stated by SESi is that “T&D losses” still have a long way to go, notwithstanding recent gains in comparison to the 1990s [81]. In this context, tougher controls on electricity theft and leakage must be implemented, as well as the restoration of ageing transmission and distribution facilities [80]. Another result is that hydropower has decreased its share of supplies due to poor water levels and the prospect of further impacts due to climate change in the future [83]. To this end, the “Indus River basin” should be considered for irrigation and as a water source to major urban centers throughout the nation [84]. Since the basin is prone to frequent floods and cyclones, with nearly 5.4% of GDP contributed as losses in 2010 [79], three large dam projects should be completed, which may add up to 2580 MW of hydropower by 2040 [49].

In the social dimension, the index decreased by 30% between 1991 and 2020. The key criterion is that the “per capita income” in Pakistan is very low, and about 6% of the income goes into energy spending [49]. The supply and affordability of clean cooking fuels and access to electricity is closely linked to wages [85]. The use of solid fuels for cooking is a potential cause of indoor air pollution-related mortality and morbidity [15]. The best strategy to avoid indoor air pollution is to move from conventional cooking and heating methods to more contemporary, cleaner ones [86]. The use of natural gas, ethanol, or even electric technology should be allowed, for example. On the other hand, access to electricity had been keeping pace with population growth and has been constant at 70% throughout the studied period (Appendix A). For access to electricity, a nation needs an alternative to the centralized energy supply [77]. One example is distributed generations that are better suited to off-grid remote applications in rural areas where demand is limited and the distance to the delivery center is high [87]. This will improve the mindset of the society towards efficient energy production and use [83].

The climate domain has been reverted, as shown by the Environmental Index (Figure 2), to the lower per capita emissions of developing countries such as Pakistan (Appendix A) [55]. This research reveals that there has been a growing pattern since 1991 and the rate of change is greater than expected (nearly 27% in 2020 compared to 1991). Furthermore, findings also reveal that “Forest/land ratio” has regressed 49% since 1991 as compared to 2020 (Appendix A). Likewise, Pakistan is known to have one of the world’s lowest forest covers, owing primarily to the arid and semi-arid climate in most regions of the country [55]. With this rate of degradation, the country is approaching having “no forest cover” [45]. As a responsible member of the global community, Pakistan must therefore increase its mitigation efforts in sectors such as energy, forestry, transportation, industry, urban planning, agriculture, and livestock [15]. As a result, this study proposed the following prospective factors for the development of the country’s or region’s climate domain:

8.

For coal-based power generation of nearly 10,000 MW by 2022 [88], the country must focus on importing ultra-super-critical coal-fired power technologies. Imports may be purchased from China when it transitions from coal, at which point it will have a surplus of this technology [70].

9.

Massive afforestation and reforestation efforts should be pursued in order to increase the country’s forest cover and develop forest regions as effective carbon sinks [61]. Along the way, suitable forest legislation, regulation, and incentives to encourage sustainable forest management will be developed, and policy input from experts and inter-national agencies will be sought for capacity building [77].

10.

“Sustainable forest management (SFM)” may be promoted by establishing applicable criteria and indicators to maintain the social and environmental principles and services of forests [88]. Establishing the manuals and procedures to track progress toward SFM may be suitable.

11.

Identify and incorporate essential forest fragments to establish natural transport routes for plant and wildlife species for ecosystem functioning [15]. Encourage farm forestry and agro-forestry methods by planting multipurpose and fast-growing tree species to suit the needs of the local community for fuel, lumber, and cow feed.

12.

Since 1995, access to energy has remained stable at 70% (Appendix A). Developing programs to provide alternate fuels and livelihood options may be accelerated to assist forest-dependent people in compensating for deforestation.

5. Final Remarks

While the proposed structure and assessment methods in this study have significant advantages compared to those presented by J. Martchamadol, S. Kumar [18] and K. Narula, B.S. Reddy [3], J. Martchamadol presented the holistic performance based on aggregated indicators across three dimensions. Their aggregated indicators are capable of presenting the performance in the past as well as in the future. However, criteria for selection of indicators were not presented, and their index may also be limited in its scope as it was not suitable for undertaking an international comparison, whereas K. Narula and B.S. Reddy presented the methodology to consider SES as a function of all primary energy sources, energy carriers, and sectors. Furthermore, a thematic framework was presented to select the sustainable indicators followed by vector matrices to form an index. However, the authors utilized their own judgement to develop the themes for the system and sub-systems. Additionally, their index was only for a single country assessment and not for international comparison. Apart from the advantages, there are several limitations to this analysis, which are described below to help steer future research on SES domain.

5.1. Future Projections

This research is based on historical time series data. Future energy security projections can also be developed using various energy system development paths [89]. Data might be gathered, and forecasts can be made utilizing the arrangement of indices since the procedure of the lists laid out in this study is fit for taking care of future projections that might be valuable in energy strategy revisions or upgrades.

5.2. Data Collection Efforts:

More work is required in light of the fact that various indicators were disregarded because of an absence of data, in spite of the way that SESi might have the option to give better understanding when applied to a bigger dataset. Furthermore, additional data sources may be necessary for the comparability of statistics used in index creation. Tracking performance, preferably at regular intervals, may be beneficial.

5.3. Regional Context

The SESi is helpful for various urban cities and states inside a country, as well as with respect to looking at other nations in the region. However, some of the metrics included in this study may be irrelevant in other nations or may indicate different issues in various countries. In the future, the advancement of a regional-index ought to be examined.

5.4. Weighting Methods

Other approaches for estimating indicator weights, such as “Data Enveloping”, “Benefit of Doubt”, “Unobserved Components Model”, “Budget Allocation Process”, “Analytic Hierarchy Process”, and “Conjoint Analysis”, may be investigated [17]. The PCA is utilized; however, the PCA has some drawbacks [90]. For example, the relationships in the PCA may not precisely address the underlying impact of the different indicators on the deliberate phenomenon. [42]. The PCA is particularly due to the concentration of outliers, factor extraction, and rotation methods [41]. Moreover, data revisions and updates may change the set of weights (estimated-loadings) used in the composite score [90].

5.5. Governance and Corruption

This study has not considered the governance and corruption indicators in the SESi. These two indicators may significantly contribute to the socio-economic characteristics of the country [91]. Developing countries, such as Pakistan, are marred with governance and corruption issues [32,76]; therefore, future research must explore the effect of these indicators for better interpretation of results.

The primary goal of this analysis is to identify a modern way to assess energy security that is consistent with the concepts of sustainability, pragmatism, and applicability. Specifically, most previous interventions were supply-oriented, with no consideration for environmental or social dimensions, whereas the concept of energy security implies that energy security can provide adequate energy for people’s social well-being while having no negative environmental consequences. Since there is no systematic way of choosing indicators, our research proposed a way to address this obstacle and offers sufficient flexibility such that researchers can select different indicators based on their applicability. However, SESi and three-dimensional indices may not be strictly objective; they are constrained by their sample size and non-qualitative process, but they have helped us to be more rigorous in our evaluation of sustainable energy security. We accept that the use of indicators will still have this conflict between comprehensiveness and comprehensibility, but that the most critical features of SESi and the indices are clear, relevant, and accessible. Thus, the goal of this study was to suggest a new approach to energy security and sustainability and to offer a realistic approach to enhancing calculations through current perceptions of sustainability and energy security.

The findings associated with the indices reveal a declining trend between 1991 and 2020 in Pakistan. The highest degree of sustainable energy security was reported in 1991, with the lowest levels recorded in 2004 and 2007. During the study period, the overall SESi fell by 9%, the economic index by 5%, the social index by 30%, and the environment by 18%. Pakistan must work to use energy to reduce poverty, boost economic growth, and promote social development. It is also important to consider that when energy use increases, stress is exerted on the environment at the local level. To protect the environment without delaying socioeconomic growth, Pakistan must seek technology solutions to transform unsustainable patterns of consumption and production in order to achieve sustainable development goals in the least expensive way possible. Analytical tools such as SESi can help locate optimal solutions. SESi and related indices can be used as benchmarks to analyze the state of energy security and illustrate a country’s past and future energy performance due to their robust methodology. SESi, in particular, can be used to analyze energy consumption and sustainable energy policy objectives (SDGs), as well as for indirect monitoring of energy conservation performance, energy demands, and energy subsidies. Moreover, SESi can also direct policy makers to reflect on target areas and improvement alternatives, as well as to map, control, and review the energy policies/measures. Finally, there are still visible gaps in energy security and sustainability in relation to open innovation ecosystems. An ecosystem in the energy industry is a collection of interactions in which interaction between government, suppliers, investors, and project developers supports decision-making, idea generation, value creation, and commercialization [92]. Innovation ecosystems are often built on openness, which attracts knowledge and capabilities from all businesses in the energy sub-sector. The primary benefit of establishing open innovation ecosystems may be seen in lower engineering procurement and energy asset construction costs, lower project development costs, conservation regimes, and tariff reductions. When examining small- and medium-sized enterprises (SMEs) or independent power producers (IPPs), most competitiveness characteristics have no substantial impact. One plausible clarification is that business decisions in SMEs are generally receptive and feature innovation benefits that originate from numerous players such as government, regulators, and different enterprises, whereas in the public policy realm, there is no entrepreneurial approach to developing innovation ecosystems. This is particularly the case in underdeveloped countries, where financial authorities have been short of funds and have been unable to complete all upgrades, maintenance, network extension, and rehabilitation. SESi and the proposed framework may assist with defining the role of institutions, regulators, and public policy in creating a favorable environment in this context. Nevertheless, by embracing an open innovation procedure in the energy business, it is possible to give more through increased openness to permit ecosystem creation—for example, an umbrella funding structure or increment capacity—and finally to further develop affordability through cost investment funds.