A Systems Perspective on the Sustainable Development of Qatar

Abstract

Sustainable development is a critical component of the Qatar National Vision 2030 and of the national strategy implementing it. The State of Qatar is developing policies aimed at protecting the environment, sustaining economic prosperity, and developing a knowledge-based society. The three pillars of sustainability—environment, economy, and society—are closely interlinked and need to be treated as such by policymakers. In this chapter, we first discuss the systemic nature of the sustainability challenges of Qatar, particularly focusing on the complex transition the country is facing as it moves away from the current rentier economic model, with its social and environmental implications, towards a new model where new, knowledge-based industries develop in areas such as climate-tech and services. We then discuss systems analysis frameworks and tools at the disposal of governments to support sustainability policy design, and we illustrate one tool in particular that we are developing at QEERI: an energy systems model. We conclude with recommendations on equipping Qatar with an analytical toolkit to support sustainability policymaking.

8.1 Introduction

All main definitions of sustainability explicitly recognize its multiple dimensions: environmental, social, and economic (Brundtland, 1987; United Nations, 2015; United Nations General Assembly, 2005). Sustainable development is one where environmental protection goes hand in hand with social development and economic prosperity. The Qatar National Vision 2030 (General Secretariat for Development Planning, 2008) clearly reflects this, identifying the need for action to address these dimensions simultaneously. In particular, Qatar aims to protect its environment, promote the development of a knowledge-based society and diversify its economy away from the fossil fuel sector. The QNV 2030 is operationalized through a national strategy (General Secretariat for Development Planning, 2011, 2018) and implemented through a range of sector-specific policies. Addressing the different dimensions of sustainability simultaneously, however, is necessary but not sufficient: policymakers need to also understand and account for the complex interconnections among the different dimensions and sectors—in other words, they need to take a whole-systems approach to sustainability.

Before discussing the systemic nature of sustainability problems though, it is worth briefly touching on the notions of sustainability and sustainable development. In this chapter, we have so far used the two terms without distinguishing between them—which is not uncommon—however in the literature they are typically associated with different meanings. The notion of sustainable development has its roots in research work from the 1970s, such as the report “The Limits to Growth” (Meadows et al., 1972), showing how unconstrained economic growth based on a business-as-usual scenario would eventually lead to mankind overshooting the planet’s carrying capacity and facing a subsequent collapse in population and industrial capacity. The first formal definition of sustainable development can be found in the Report “Our Common Future” (Brundtland, 1987), which articulates it as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs”. Since then, the concept of sustainable development has become pervasive; however, it has also been widely criticized for being vaguely defined and, by some, for implying that economic growth could be pursued indefinitely.

More recently, the notion of sustainability has emerged as distinct from sustainable development and decoupled from the idea of sustained economic growth, possibly also encompassing the perspective of pursuing economic “degrowth” in favour of social and environmental gains. In other words, sustainability can be pursued through transitioning away from development models where economic capital increases at the expenses of environmental and social capital, and overall capital degrades, to one where such total capital is preserved or increased in a durable manner. While conceptually sound, such definitions are obviously difficult to operationalize due to the uncertain and possibly subjective nature of any measurement of social and environmental capital. Moreover, different schools of thought still exist and the debate around the different notions of sustainability is still very open. For a more detailed discussion, we refer interested readers to a recent critical review of sustainability concepts (Ruggerio, 2021).

The problem of which sustainability notions and frameworks are more appropriate for Qatar is very interesting—particularly considering the country’s economic dependence on the exploitation of its fossil hydrocarbon endowment—however, we will not be addressing it in this chapter. Instead, we will focus on the systemic nature of the sustainability problem—which remains critical irrespective of the particular framework one may want to adopt—and how it can best be addressed by policymakers. Scholars and practitioners have long recognized that the different dimensions of the sustainability problem are interconnected through a complex set of relationships, and that balancing them cannot be reduced to seeking tradeoffs. Therefore, from a policy perspective, these dimensions should certainly not be treated in isolation and a whole system approach should be adopted instead (Senge, 1990). Systems thinking in sustainability, while not new, is drawing increasing attention from academics and practitioners (Future Earth, 2019; Gallopin, 2003) and we believe that such as approach can be particularly valuable for Qatar.

Other chapters in this book focus on specific environmental, social, and economic challenges that affect the State of Qatar today. In this chapter, we want to reflect on how these dimensions are intimately interconnected in the particular case of Qatar, and how policies introduced to address challenges in each of them can best be designed with a system perspective in mind. Failing to do this risks substantially limiting the efficiency and effectiveness of such policies, and possibly leads to unintended consequences. A set of tools are available to support systems analysis that are increasingly being used by policymakers and other stakeholders worldwide. We recommend that these are applied to the sustainability challenges of Qatar as well.

In the remainder of this chapter, we provide a qualitative discussion of the main systemic problems that the sustainability transition in Qatar is faced with (Sect. 8.2), then we provide an overview of the main tools available to support systems analysis (Sect. 8.3), and we focus on one tool in particular—i.e. an energy systems model—that we are developing at QEERI to support policymaking in the area of energy policy and climate change (Sect. 8.4). We conclude with recommendations on how systems thinking and analysis can further be built into sustainability policymaking in Qatar (Sect. 8.5).

8.2 The Systemic Nature of the Sustainability Challenges of Qatar

In this chapter, we do not aim to provide a comprehensive treatment of all systemic problems associated with the sustainability transition of Qatar. Instead, we will limit ourselves to outlining the main ones and illustrating how the different dimensions are closely interconnected. A more comprehensive analysis is in fact a step we would recommend for future research aimed at better informing sustainability policy in Qatar, as discussed in Sect. 8.5. Let us first begin by briefly discussing how the different dimensions of environmental, economic and social sustainability are interconnected in the case of Qatar and, more broadly, the countries of the Gulf Cooperation Council (GCC).

Since the second half of the twentieth century, the State of Qatar has experienced dramatic economic and social development, driven by the extraction and commercial exploitation of its vast hydrocarbon resources, and has achieved great prosperity—its GDP per capita ranking 4^th in the world in 2020 (World Bank, 2022). However, the rentier state¹ economic model of Qatar and other GCC countries—where most of the country’s revenues originate from international sales of fossil fuels—is coming under increasing pressure due to environmental reasons, particularly global climate change. In a post-Paris Agreement world that seeks to limit global average temperature rise to 1.5 degrees above pre-industrial times, and where use of unabated fossil fuels will need to rapidly reduce (IEA, 2021), the rents associated with them are bound to decrease.

This means that Qatar and other GCC countries will need to rapidly transition away from the current economic model and create new, more sustainable industries that can at least in part make up for the revenue gap from fossil fuel exports. Indeed, such transformation is already evident in the GCC, where countries such as Saudi Arabia and the United Arab Emirates in particular are taking substantial steps towards the development of a domestic climate-tech sector, focusing on technologies such as renewable energy and carbon capture, utilization and storage that both complement and support the fossil fuel sector. Developing new industries, however, requires substantial investments, clear strategies, and careful planning, especially in view of a future where fossil fuel rents may decrease while the scale of investment needed to replace existing infrastructure with a more sustainable one increases. Such strategies and plans need to be informed by system-level analysis, or else they risk being ineffective or inefficient, possibly jeopardizing the future economic prospects of the country.

The current economic model of Qatar and the GCC has also led to the development of an informal social contract based on the redistribution of fossil fuel rents to citizens through various mechanisms. One such mechanism is the provision of free or highly subsidized energy services, such as lighting, cooling, transport, and water, the latter mostly coming from energy-intensive seawater desalination due the lack of renewable freshwater resources. This, combined with the harsh climate of the region, has resulted in the GCC countries having among the highest energy consumption per capita in the world. Such high consumption, satisfied primarily through the use of fossil fuels, has added pressure on the already fragile natural environment and ecosystems of the Arabian Peninsula. To compound the problem, increasing energy demand tends to bring additional water use, and vice versa. This situation has been described as the energy-water nexus or, taking a broader perspective, the energy-water-food nexus. The systemic nature of the nexus and the importance for policymakers of considering the multiple dimensions it spans are being increasingly stressed by both scholars and practitioners (Borgomeo et al., 2018).

The strong interdependence between the economic and environmental dimensions of sustainability in Qatar and the GCC also deeply intersects with the social sustainability dimension. The rentier state economic model of the past has allowed GCC citizens to benefit from well-remunerated and secure public sector jobs, and generally enjoy high levels of social prosperity and stability on a scale that is not known in other countries of the Middle East and North Africa (MENA). The environmental pressures that are forcing the transition away from the current model will also entail substantial social changes. Developing new sectors of the economy is a highly complex process that requires, inter alia, a transformation of the national innovation system, duly supported by an education system that produces graduates with the necessary skills to match the new sectors that the country seeks to develop. Economic diversification will also require the private sector to grow in size and to improve its productivity, so as to be able to compete on international markets. As Qatar and other GCC countries move away from a planned economy to a market-based economy, labour productivity will, therefore, need to increase and wages reduce, and a complete social transformation will be required to maintain prosperity and stability.

GCC countries have long been aware of the risks of relying on the revenues generated from fossil fuel exports. Economic diversification and social transformation policies have therefore been on the agenda of GCC countries for some time, and yet results achieved so far are generally modest. Over the last few years, however, the rapidly accelerating pace of international climate action has made economic diversification an ever more pressing issue. As the GCC countries commit to the rapid and drastic changes required, the complexity of decisions that policymakers are facing grows exponentially, and with it the importance of tackling economic, social, and environmental sustainability challenges from a systems perspective.

The following section provides an overview of the main systems analysis tools that are at the disposal of scholars, policymakers, and other stakeholders and that can support the generation of evidence necessary to inform effective and efficient policy decisions.

8.3 Systems Analysis Tools to Support Sustainability Policy

Due to the complex nature of sustainability challenges, no single framework exists that is used to tackle all sustainability policy problems—in Qatar or elsewhere—across all dimensions (environmental, social, and economic) and all sectors of the economy. However, a wide range of tools exist that have been applied to policy analysis in several countries worldwide and that can be beneficial to Qatar as well. Different categorizations are possible, however at a high level we can distinguish between essentially two types of tools:

• a. Theoretical frameworks that can be operationalized through qualitative and quantitative indicators

• b. Computer-based models that cover different domains and use different approaches such as optimization and simulation.

Within these two categories, very many different tools exist and a systematic discussion of them is outside the scope of this chapter. Instead, in order to provide the reader with a basic understanding of sustainability policy research and practice, we will focus on selected tools that are particularly well-known globally and relevant to Qatar in particular.

Each of these tools is designed to address specific sets of questions and therefore needs to be used for the intended purpose, taking their relative strengths and weaknesses into due consideration. It is also important to keep in mind that none of these tools can be used off the shelf and that substantial work is needed to adapt them to the study of specific problems in a given context, which requires relevant expertise. Lastly, none of these tools should be intended as offering an accurate representation of reality, but rather simplified representations that focus on particular problems and allow us to better understand them for the purpose of deriving policy-relevant insights.

For this reason, a solid approach to studying policies to promote the sustainability transition—in Qatar or elsewhere—is one that is driven by specific questions, recognizes the complex, systemic nature of the challenge, and combines the use of multiple tools, carefully chosen to complement one another and ensure robustness of the insights so derived. Here follows a brief discussion of theoretical frameworks and computer-based models in turn.

8.3.1 Theoretical Frameworks that Can Be Operationalized for Policy Analysis

Sustainability problems are often described as those where current practices are unsustainable and need to be replaced by new ones. This may involve the development and adoption of new technology, and the social, institutional and behavioural changes that goes with it. Transitioning to more sustainable technologies is certainly of critical importance to Qatar, as outlined in Sect. 8.2. A number of frameworks have been developed over the last decades that aim to describe the mechanisms underlying technological and social transitions—also referred to as socio-technical transitions—around sustainability problems. Stemming from the fields of technology studies and evolutionary economics (Nelson, 1985), a theory of socio-technical transitions has started to emerge in the late 1980s (Freeman et al., 1987; Lundvall et al., 1988) which has developed into multiple strands (Savaget et al., 2019). The transitions literature is complex and we will not discuss it in detail. However, we will briefly discuss two particularly notable frameworks that have found many applications in sustainability-related problems: the Multi-Level Perspective (MLP) on Socio-Technical Transitions (Geels, 2002) and the Functions of Innovation Systems (Hekkert et al., 2007). Both frameworks treat sustainability transitions as systemic problems, characterized by multiple dimensions and actors. Both start from the premise that current paradigms owe their stability to reinforcing feedback loops linking technology, institutions, users, regulation, markets, and infrastructure, and that targeted policy interventions are required to overcome systemic barriers to change and effect the desired transition.

The MLP in particular focuses on the processes required for a transition to occur that involve interactions at different levels, defined as “landscape” (the external context, which in the case of Qatar can be international climate change policy), the “socio-technical regime” (the technology, in a broad sense, that needs to be replaced with a more sustainable one) and the “niche” (the new technology as it emerges from research, development, and early markets). The MLP describes technological transitions as a process where landscape pressures contribute to destabilizing dominant technologies (“regimes”) and therefore create a window of opportunity for new technologies to emerge. The three levels and the overall process of technological transition postulated by the MLP are schematically illustrated in Fig. 8.1.

Fig. 8.1

Illustration of the multi-level perspective on socio-technical transitions (Geels, 2011)

In the MLP, which can be applied to the study of any technological transition, the process of technological substitution does not happen spontaneously but is essentially driven by policy. Therefore, the MLP provides a useful tool for both ex-ante and ex-post policy analysis. The MLP is particularly popular among scholars and practitioners, and has been applied to a vast number of cases across many countries worldwide, including the GCC where one instance of its use is in the study of the transition to renewable energy in Saudi Arabia (Alrashoud, 2020). The MLP has also strongly influenced policy thinking however its direct use in policymaking processes to date remains limited.

The Functions of Innovation Systems framework, on the other hand, draws on a longer tradition of national and sectoral innovation systems analysis that has been directly used to inform government policy in many instances. The strong correlation between rates of technological innovation and economic growth is known since the 1960s, and the early models depicting innovation processes as linear have been replaced by a system approach already in the early 1990s (Lundvall, 1992). There is clear evidence of the use of national innovation systems frameworks for innovation policymaking aimed at creating knowledge-based economies since at least the late 1990s (OECD, 1997). In this context, the functions of innovation systems framework represent a development of the national innovation systems framework: while the latter focuses on studying innovation systems from the point of view of their structure—hence providing a static and institution-centred picture—the former focuses on the processes—or functions—that an innovation systems need to perform (Hekkert et al., 2007)—hence capturing systems dynamics and agency. Figure 8.2 below provides a schematic representation of such functions and how the link with one another.

Fig. 8.2

Illustration of the main functions of technological innovation systems (Hekkert et al., 2007)

The national innovation systems and functions of innovation systems frameworks can be seen as complementary approaches to the study of innovation systems, and their distinctive elements can also be combined as appropriate. Compared with the MLP, innovation systems frameworks are also easier to operationalize, which explains their more extensive use in policymaking.

To summarize, both MLP and innovation systems frameworks have been extensively applied by scholars and practitioners and, considering the importance that the State of Qatar places on sustainable technological innovation and the need to transition to a knowledge-based economy, we recommend their use to support policymaking. The frameworks are self-standing and can be operationalized and used on their own. However, they can also be used alongside the formal computer-based models that we will discuss in the next sections, and offer very valuable complements to them.

8.3.2 Computer-Based Models that Are Used to Explore and Design Different Policies

The recognition of the complexity of the sustainability problems under study has brought to the realization that computer-based tools are necessary in order to capture the multitude of elements and the dynamics linking them, in a way that the human brain alone is not able to. A range of computer-based models have, therefore, been developed to address different kinds of policy problems, which have found many applications at national, regional, and global scales. Here we will not provide a comprehensive overview of these tools, but rather we will discuss the main categories of models and their intended applications, as well as some of their main limitations, and their relevance to the sustainability challenges of Qatar.

When discussing the main types of models, we can make a first distinction among economic, engineering, and natural systems models. Economic models are built based on mathematical representations of economic theory and use real economic data as inputs. They are best used to study economic policies—such as pricing reforms, subsidies, and taxes, to name a few—and assess their likely impacts on the performance of the economic system under study or of specific sectors within it. Engineering models, on the other hand, are built based on mathematical representations of physical technical systems—such as power generation plants, buildings—and allow to test the effects of policies supporting the deployment of certain technologies on the energy consumption, emissions, and overall costs and performance of the system under study. Lastly, models of natural systems—of which very many exist, operating at different scales and representing physical as well as living elements of the natural environment—allow us to test the impact of anthropogenic activities on environmental quality, ecosystems, and global climate.

It is important to note that each of the model types discussed above can be used independently; however, they can also be used jointly, by either soft-linking or hard-linking them. In addition, there are also models that combine engineering and economic approaches—such as the TIMES energy systems model we are developing for Qatar that we will discuss in Sect. 8.4. Moreover, models that combine engineering and economic approaches can be further coupled with models of the natural environment, resulting in so-called Integrated Assessment Models (IAMs); these models are typically used to study climate change policy at the global level.

Another useful distinction is between models that optimize and those that forecast or simulate. Optimization models are useful to identify and characterize optimum pathways to reaching certain policy targets; the type of analysis these models lend themselves to is often referred to as “back-casting”, because it works backwards from the desired end state and identifies all those policies, technologies, and infrastructures that need to be deployed at different points in time in order to achieve it at the least cost to society. Optimization models typically represent the system they study in terms of neoclassical economic theory, i.e. economic actors have perfect foresight, fully rational behaviours, and markets can adjust instantaneously so they are constantly in equilibrium. However, optimization models can also be made more realistic by introducing constraints to the knowledge and rationality of the economic actors, which allows to identify optimum pathways that are also potentially easier to implement practically.

Forecasting or simulation models on the other hand allow testing the real-world impact of different policies based on the behaviour of economic actors such as firms, governments, and consumers, as well as of the man-made and natural environment in which they operate. These models project into the future using different techniques, including econometrics, agent-based, and system dynamics modelling, each of which has its own strengths and limitations. In particular, agent-based techniques allow exploring future dynamics—which could be unexpected and counterintuitive—that directly arise from the complex interaction among the relevant agents, each of which is assumed to behave according to certain rules. Agent-based modelling is a very powerful approach which, however, requires a detailed understanding of the behaviours of all relevant agents, be they institutions, firms, or consumers. Econometric methods, on the other hand, can be applied effectively even when such detailed understanding of the problem is lacking, however their use required extensive datasets, typically time-series, and panel data. Both optimization and forecasting models can be used to study a range of problems occurring over different timescales—typically spanning years to decades.

The purpose of forecasting or simulation models is clearly very different to that of optimization models, and yet the two approaches are complementary: they can be used to address different problems, but they can also be applied to the same problem to gain a better understanding of it. One notable example where an optimization and a simulation model have been used together is the high-profile IEA study “Net-Zero by 2050” (IEA, 2021) where global pathways to net-zero have been identified and assessed from the point of view of social optimum (optimization) as well as based on the expected real-world responses to the relevant policies (simulation). For practical purposes, however, generally only one kind of model is used to address a particular policy problem, the choice being based on both the nature of the problem and the availability of tried and tested tools that fits it. Such considerations have informed our choice of the TIMES modelling platform, as is further explained in Sect. 8.4.

Lastly, it is worth mentioning that in principle more comprehensive tools could be developed that combine both optimization and simulation approaches, as well as economic, engineering, and natural environment components, all in one. However, modelling practice suggests that, as the complexity of a model increases, its transparency and ease of interpretation decreases, and so does its practical value. Therefore, when tackling a complex policy problem, it is often preferable to use a set of self-standing tools—including theoretical frameworks and computer-based models of different kinds—that can complement and corroborate one another, rather than attempting to develop a single tool that combines multiple methods and approaches.

Having provided a high-level categorization of computer-based models for policy analysis, here we will briefly discuss some types that are particularly relevant to sustainability problems such as those that characterize Qatar.

Let us begin from the problem of mitigating environmental damage while sustaining economic prosperity and social development. As discussed earlier, in Qatar and other GCC countries, this problem is inextricably linked with the imperative of diversifying the economy away from fossil fuel export and energy-intensive industries, and towards knowledge-based, high value-added new sectors that can generate the necessary economic value and social development (General Secretariat for Development Planning, 2008). Policymakers in Qatar and other GCC countries have been grappling with this problem for long, and achieved some degree of success, however dependence on the hydrocarbons industry in general remains high. Achieving the desired degree of economic diversification is difficult due to the presence of systemic barriers to change, overcoming which requires a set of distinct yet interlinked policy decisions. Computer models that allow to study the likely response of the country’s economy to combinations of different policies are therefore suitable tools to aid decision-making.

A range of economic models exist, both simulation and optimization-based, that can be applied to sustainability problems. Among them, particularly worth mentioning are Computable General Equilibrium (CGE) models, which capture the structure of the current economic system and the behaviour of its main actors (firms, governments, and consumers), and simulate the impacts that policy changes can bring to it, including on employment, expenditure, and income. These models are capable of representing the economic system under study in detail and can reveal complex dynamics leading to indirect or unintended effects of given policies. CGE models have emerged from Input–Output analysis and in their more recent declination—known as Dynamic Stochastic General Equilibrium (DSGE) models—also offer the ability to study not just long-term effects of policy measures but also the adjustment path that the economic system goes through as it evolves from one equilibrium point to another, thus offering further valuable insight to policymakers. A CGE model of the Qatari economy is available, currently owned by the Planning and Statistics Authority (PSA). CGE models have already been applied to sustainability problems in other GCC countries, such as the macroeconomic impacts of renewable energy policies in Saudi Arabia (Blazquez et al., 2017), and can be a critical tool to study sustainability policies in Qatar as well.

Closely linked with the problem of diversifying the economy away from fossil fuels, the other increasingly pressing issue for Qatar and other GCC countries is reducing carbon emissions domestically and the carbon content of the fuels and other products they export. This requires, inter alia, replacing the existing civil and industrial infrastructure—developed over decades around the rentier economic model previously discussed—with one that is more energy efficient, has low emissions, and is compatible with the new economic model the country is aiming for. Such a transformation of all sectors of the energy system of Qatar requires substantial investments and decades to be completed, due to the large scale and long lifetime of the infrastructure. It is also a complex problem of systemic nature, as moving towards a low carbon, efficient energy system means that the different sectors within it (buildings, transport, power and water, and industry) will become increasingly interlinked and that decisions made today will have major consequences on future systems cost and environmental performance. The models that are typically used to study energy transition pathways are called energy systems models.

Different types of energy systems models exist, based on both optimization and simulation approaches. In industrialized countries such as the UK, these models have now been used for around two decades, and are now being increasingly used by developing countries too. In the GCC these tools have so far not been used by policymakers, however the picture is changing rapidly as the oil and gas exporting countries of the region are finally embracing the need for aggressive climate action. As GCC countries set themselves increasingly stringent carbon emissions reduction targets, the complex policy decisions that they are faced with will make energy systems models a critical tool for policy analysis for years to come. Recognizing the importance that such tools will have for Qatar, at the Qatar Environment and Energy Research Institute (QEERI) we are currently developing an energy systems model of Qatar; this is discussed in the following section.

Lastly, we recognize that several research teams in Qatar have developed and used different models of natural systems to conduct research around the environmental issues faced by the country. Due to space constraints, we will not discuss them here. However, we want to emphasize the potential for these models to be further leveraged for sustainability research purposes.

8.4 Developing an Energy Systems Model of Qatar

QEERI’s mission is to conduct market-driven research to address the energy, water, and environmental challenges of Qatar and other countries characterized by arid climates. Research teams at the Institute are developing a range of cutting-edge technology solutions that can be deployed in Qatar and exploited commercially in other markets, thus supporting two national imperatives: protect Qatar’s environment and promote the development of a knowledge-based economy. At QEERI we are acutely aware of the systemic and multi-dimensional nature of the challenges we are facing and this is why, alongside research and development activities, we also focus on the economics and policy research.

Motivated by the need to better inform both QEERI’s R&D agenda and government policy in a number of areas, back in 2019 at QEERI we realized the importance of equipping Qatar with an energy systems model of the same standard as those used by leading governments worldwide. Thanks to funding from the Qatar National Research Fund (QNRF) through the grant NPRP13S-0204-200,250, in partnership with Imperial College London, and with the support of Kahramaa (Qatar’s national electricity and water utility company) and the Abdullah Bin Hamad Al-Attiyah International Foundation for Energy & Sustainable Development, we are currently developing an energy systems model of Qatar that we expect to be ready for initial use by early 2023.

Since we first conceived the idea, the policy relevance of the model has further increased. In particular, having set its first carbon emission reduction target in 2021—a reduction of 25% of carbon emissions by 2030 relative to a business-as-usual scenario based on policies implemented up to 2019—Qatar will need to progressively tighten it in future, which will require continuous analysis aided by the necessary tools. At the same time, the Qatari government is introducing policies in a number of other areas (water, food, transport, buildings, etc.), all of which bear consequences in terms of climate change policy and that therefore need to be addressed in a systemic manner.

Based on the nature of the problem at hand—i.e. exploring least-cost technology and policy pathways to decarbonization and environmental protection in Qatar—and taking into consideration the need for a tool that is tried and tested and on which policymakers can rely, our choice has fallen on a particular kind of techno-economic optimization model called TIMES. A brief discussion of the nature of the model, its use to support policy analysis so far, and the particular value we believe add to Qatar follows below.

8.4.1 What Is a TIMES Model and How It Works

The name TIMES is an acronym that stands for “The Integrated MARKAL-EFOM System”. The TIMES modelling framework has evolved from the MARKAL (“MARKet Allocation”) framework originally developed in 1978 by the Energy Technology Systems Analysis Programme (ETSAP) of the International Energy Agency. The development of the MARKAL model was initially motivated by the need to explore alternatives to oil at a global level, due to supply security considerations. However, as the climate change issue became pressing on the policy agenda, MARKAL, and its successor, TIMES, provided policymakers with a very valuable tool to inform the development of energy-environmental policy strategies at national, regional, and global levels. We will further discuss the policy relevance of TIMES in Sect. 4.2, however first let’s briefly discuss its structure and functioning.

The TIMES modelling framework combines the engineering approach—it is a technology-rich, bottom-up model of the energy system—with the economic approach—it balances demand and supply within the energy system through partial equilibria at sector level. It is an optimization modelling framework that allows building least-cost energy systems transition pathways consistent with pre-defined policy targets by making decisions on equipment investment and operation, and on import and export of energy commodities. In doing so, the model also takes into account all technology and resource availability constraints set by the user. The TIMES modelling framework revolves around a specific objective function—an algorithm based on which the optimum solutions to the problem are found—and it can be used as a basis to develop TIMES models for any market or geographic area of choice (Loulou et al., 2005). No two TIMES models are the same; however, they operate according to the same principles.

The TIMES modelling framework is graphically illustrated in Fig. 8.3.

Fig. 8.3

Overview of TIMES modelling framework (Remme, 2007)

As the figure shows, TIMES models account for all steps of energy conversion, from fuel extraction and refining or renewable power generation—including energy imports and exports—through to transmission, distribution, and end-use in all sectors of the energy economy (buildings, transport, power generation, and industry). In the model, all relevant energy conversion and end-use technologies—both present and future—are included, and their adoption and use strategies are determined by the decisions of the relevant agents in the system—such as power companies, passenger car owners—who are characterized as rational and having perfect foresight. Constraints to agents’ behaviour or technology deployment can be introduced in the model to simulate the likely real-life effect of different policies. Model scenarios are driven by energy service demand projections—e.g. demand for cooling in buildings, transport of passengers and goods, etc.—which constitute an input to the model. Given the policy targets, service demand projections, and other constraints set by the user, the model computes transition scenarios that fulfil all requirements at the least cost to society. Policy analysis with TIMES is conducted by generating a number of scenarios that test different assumptions and policy approaches, and by comparing and contrasting them so as to derive the desired insights.

8.4.2 Use of TIMES in Policy Analysis Internationally

The TIMES model has been extensively used by governments worldwide to conduct energy-environmental policy analysis in support of major pieces of legislation. At the forefront is the UK, that has been using MARKAL and TIMES models to inform its climate change policy for almost two decades. Table 8.1 below provides a non-exhaustive list of instances of relevant use of TIMES by national governments.

Table 8.1 List of main countries where TIMES has been used for national energy-environmental policymaking (Gargiulo, 2021)

Apart from national governments, the TIMES model is also used by non-governmental research organizations to explore global energy transition and decarbonization scenarios, as well as major corporations in the oil and gas and other sectors, who use TIMES for planning purposes.

8.4.3 Policy Relevance of TIMES in Qatar

The Qatar TIMES model can generate evidence to support policymaking in a number of areas of interest to major national stakeholders in Qatar.

Firstly, the TIMES model is a major tool used worldwide to inform climate change policy, as illustrated in the previous section. This makes it relevant to the Ministry of Environment and Climate Change and complements the methods used so far to inform Qatar’s national climate change strategy and related targets. Clearly another key stakeholder in this area is QatarEnergy, because reducing carbon emissions from industry is going to be a critical part of any climate change plan. TIMES can help both entities assess which sectors and sub-sectors should be prioritized, and which should be tackled at a later time, so as to achieve the country’s overall carbon emission reduction targets in a cost-effective manner.

Linked to Qatar’s climate change policy are policies on energy efficiency (the Tarsheed programme), electric mobility, and solar energy, to name the main ones. These are overseen by Kahramaa who, as previously mentioned, is supporting the development of the Qatar TIMES model. As also illustrated in the previous section, TIMES has been used in several other countries to assess and design energy efficiency, sector-specific and technology-specific policies from a systems perspective. Kahramaa can, therefore, use the model to further inform and refine its policy programmes.

Lastly, TIMES can also be used to assess R&D priorities and innovation gaps at national level, which makes it relevant to the Qatar Research, Development, and Innovation Council (QRDI), the entity overseeing national policy in this area in fulfilment of the QNV 2030. The use of TIMES can, therefore, complement the analysis already undertaken by QRDI.

8.5 Recommendations for Future Work to Support Sustainability Policy in Qatar

In this chapter, we have illustrated the systemic nature of the sustainability policy challenges faced by Qatar, as environmental pressures—both global and local—force the country to rapidly transition away from a rentier economic model, diversify its economy, and create a knowledge-based society to preserve or increase its total economic, social and environmental capital. The complex decisions faced by policymakers today and in future, therefore, demand a systems approach and can be effectively supported through the deployment of a range of systems analysis tools, some of which we have briefly discussed.

Before these tools can be put to use in Qatar, however, we need to start from raising awareness among policymakers in government and industry on the need for a systems approach and the availability of tools to support it. The challenge is to gradually move away from a paradigm where individual entities make policy decisions in their respective domains without taking into full consideration the interlinkages among them, and where such decisions are mainly informed by one-off studies by international consultancy firms that may not be able to deploy the necessary tools, let alone tailor them to the needs of Qatar. A system approach inevitably requires a higher degree of coordination and the development and deployment of specific tools. Developing tools that are tailored to the national circumstances requires technical competencies and timeframes that are not compatible with those of typical consultancy projects. In other words, a systems approach to sustainability policymaking ideally requires government, industry, local experts, and international consultants to all work together in a continuous manner. Raising awareness and building capacity within government and industry is, therefore, going to be of critical importance. Thankfully, several entities exist in Qatar that are well placed to achieving this, especially if they work closely together.

The following step is to map the main systemic challenges that Qatar is faced with on the way to realizing its QNV 2030 and the relevant stakeholders. We have briefly discussed them earlier in the chapter: economic diversification away from the oil and gas sector, reduction of national carbon emissions and of the carbon content of fuel and commodity exports, the development of a national innovation system focusing on high-added value products and services, and the development of a knowledge-based society. These challenges are all interlinked, and a clear understanding of how they connect with one another is essential to addressing them.

Once the picture is clear, Qatar needs to equip itself with a toolkit to support sustainability policymaking. The tools chosen need to be robust and well-accepted internationally, to give policymakers confidence, and selected so as to complement one another and allow for better validation of the insights they generate. Adapting the tools to the specific circumstances of Qatar is a process that requires time and resources, and needs to be seen as an investment for the country, not an ad-hoc, policy-specific source of insight. Once the tools are available, they can be applied to national policymaking for years to come. For the tools to remain relevant over time, obviously they will have to be continuously updated and refined, which also requires resources. However, if correctly managed, the development and maintenance of the tools will not cost more than typical consultancy projects but will deliver substantial value to the country.

Such toolkit can take different forms; however, it will inevitably need to include a model of the country’s economy and an energy systems model. It will also need to include tools to conduct innovation systems analysis. Developing such tools for Qatar requires specific economic and technology policy expertise, as well as sector-specific and technology-specific knowledge. Much of the necessary expertise and knowledge is already available in the country, and we call for the contributors to this book to come together and work jointly to help address the sustainability challenges of Qatar from a systems perspective.