6. Integrated Policies for Climate, Air, Ecosystems, Energy and Transport

Simon Buckle
Mariana Mirabile
Aimee Aguilar Jaber
Elisa Lanzi
Rob Dellink
Will Symes
Assia Elgouacem
Ben Henderson
Bas van Ruijven
Ulf Dieckmann
Petr Havlik
Taher Kahil
Keywan Riahi
Yoshihide Wada
Fabian Wagner
Paul Kishimoto

Human well-being depends on human and natural systems, with ever-increasing fractions of the earth actively managed for human benefit (see for example, Haberl et al., 2007, and Vitousek et al., 1986). The focus of this chapter is on the interplay between these systems and human well-being viewed through the lens of the climate and ecosystems, focusing on the critically important mitigation challenges in the energy and transport systems. The chapter provides three perspectives on the complex of problems around climate and energy use, and their relationship both to healthy ecosystems and human well-being in terms of air pollution. Understanding the interactions between the natural and human systems on the global, national, and local scales is essential to formulating effective sustainable policies, and strengthened IIASA-OECD collaboration can make a valuable contribution on each level. The next section takes a macro or global level perspective on the trade-offs implicit in climate mitigation and ecosystems. Section 3 zooms in to the level of an individual jurisdiction or country to understand the balance between climate policies and development; while section 4 takes a sectoral perspective and examines interlinkages between human well-being, transport, and air quality.

The conceptual framework is inspired by a paper by Waage et al. (2015), but significantly modified to illustrate these key interlinkages (Figure 6.1). The “well-being” SDGs, such as SDG 1 on ending poverty and SDG 3 on good health and well-being, are at the (orange) centre of the figure. These well-being SDGs depend on achieving other SDGs, such as food security (SDG 2), access to reliable, affordable, sustainable and modern energy for all (SDG 7), and clean water and sanitation (SDG 6). Of course, achieving these SDGs depends critically on the availability and effectiveness of different types of infrastructures and systems, which are represented by the middle (grey) ring.

The analysis needs to go beyond human systems however, since these are critically reliant on ecosystems and the environment – the outer ring of the diagram, shaded both green and blue to reflect the importance of both terrestrial and marine ecosystems, as well as the climate system. This dependence is both direct (Arrow 1), for example in terms of provisioning services (fuel or water abstraction), and indirect (Arrow 2) since ecosystems also provide services that we might think of as infrastructure services, such as water purification or flood protection (Millennium Ecosystem Assessment (MEA), 2005). Of course, human activities also affect these ecosystems in many ways, reducing the scale and range of ecosystem services they can provide in different and often radically changed contexts (IPBES, 2019; MEA, 2005).1 Some of these impacts – like the waste of water – may be ameliorated by the infrastructures we construct (Arrow 3), such as water treatment plants.

Similarly, the operation of the infrastructures, systems, and associated technologies that provide us with so many benefits may also cause environmental damages (Arrow 4), for instance, the emissions from a petrol or diesel car. Some of these damages are local, confined to a district or a city, but many have far-ranging or even global consequences such as the emission of carbon dioxide and other greenhouse gases (GHGs), which are still rising rapidly despite international efforts to reduce them. An additional level of complexity is the different time-scales on which different impacts may occur and their degree of temporal persistence.

Of course, there are relationships and feedbacks (Arrow 5) within the environment – or the “earth systems” – such as the atmosphere, oceans, ice sheets, soils. For example, climate change is fundamentally modifying the global water cycle, changing the distribution and intensity of rainfall, which affects the services that ecosystems can provide to us. In the other direction, ongoing, large-scale deforestation and forest degradation results in the emission of large amounts of CO2 and reduces the potential for these forests to safely store carbon dioxide emitted in the future.2 Not to mention that tropical forests are also biodiversity hotspots and so deforestation directly increases the risks of a sixth mass extinction event.

These human impacts on ecosystems and the environment are not cost-free, even if there are some - possibly transient - benefits for some regions. Arrows 6a and 6b in Figure 6.1 illustrate the fact that changes to the climate and ecosystems will in turn impact on human well-being, either directly (6a), or mediated through their effect on infrastructures (6b, e.g. damages from extreme weather).

The dependence of human well-being on the closely linked human and natural systems is increasing, both in intensity and in pervasiveness. At different temporal and spatial scales, these interdependencies may have very different characteristics and are likely to require different approaches, in terms of how we model and understand them as well as the economic and policy approaches used to manage these complex interactions and dependencies (Nicholson et al, 2009).

Regarding the climate, human activity is driving the planet into completely uncharted territory, out of the comfortable climatic regime in which humans and their societies evolved over the last 10,000 years (IPCC, 2014). The risks of severe, pervasive, and irreversible damage will increase unless we invest in sustainable infrastructures (IPCC, 2014). In the absence of further policy action, climate change has strong impacts on the environment, but also on the economy.3

Very real benefits are expected if we can limit the global temperature increase from climate change to 1.5 degrees rather than 2 degrees Celsius or higher, as is made clear from the recent IPCC Special Report on 1.5 degrees (IPCC 2018), in terms of reduced heatwaves and flooding, greater food security, and lower levels of water stress. There would also be benefits in other environmental domains, including water quality, ecosystem services, and air quality.

However, the way in which we try to achieve such stringent mitigation goals will determine the macro-level risks and trade-offs between the climate system, ecosystems, and human well-being. The following characteristics of global emissions reduction pathways will be critical:

  • The stringency of global mitigation will determine the scale and extent of climate impacts on both human and natural systems. A recent IIASA study (Byers et al., 2018) found that global exposure to multi-sector risks (in water, energy, and land) approximately doubles between 1.5C and 2C global mean temperature change.

  • The rate at which the climate changes will also have implications for how quickly natural and human systems can adapt to the changes, which in turn has policy implications in terms of how mitigation policy is implemented. For example, there is strong evidence that a focus on mitigating the effects of some short-lived climate pollutants in a targeted way could both reduce the pace of climate change over this century and provide significant benefits by avoiding damages from air pollution to both human health and food production (Shindell et al., 2012). Interactions between climate change and air pollution are significant (Lanzi and Dellink, 2019; McCollum et al., 2013) and reduced damages from both would have beneficial economic outcomes (OECD, 2015 and 2016). Indeed, the health co-benefits of climate policy from improved air quality have been found to outweigh or at least counterbalance the costs of meeting climate policy goals (Markandya et al., 2018; Vandyck et al., 2018).

  • The extent to which pathways depend on bio-energy and biomass, either as a primary fuel or as a component of carbon dioxide removal technologies such as Biomass-enhanced Carbon Capture and Sequestration (BECCS). The greater the extent of dependence, the greater the implications for patterns of land-use, including for food production, and the higher the risks to ecosystems, the services they provide, and the underlying biodiversity on which they depend. Hasegawa et al. (2018) show that if the climate stabilisation policies broadly in line with the Paris Agreement (RCP 2.6) were implemented through a uniform carbon tax across sectors and regions, the number of undernourished people could be higher than in a scenario with greater levels of climate change (RCP 6.0). At the same time, Frank et al. (2017) show that through remunerating carbon sinks in addition to taxing the emissions, a large part of the negative impacts on food security could be avoided. Havlik et al. (2014) demonstrate that because of the widely differing GHG efficiencies across regions, international trade can be an effective mitigation measure. This can lead to increases in agricultural production in GHG efficient regions to compensate for reduced production in GHG intensive regions.

Evidently, outcomes will not solely be determined by climate policy action. There is significant uncertainty over what sort of world humans will be living in in 2050, and this is even truer of 2100. Scenario analysis is one of the key tools for trying to understand what the range of possible future worlds might mean for efforts to manage the simultaneous challenges of ensuring human well-being in the face of rapid economic and population growth and urbanisation while simultaneously trying to limit the extent of the climate risks we face.

The latest set of state of the art scenarios, the Shared Socioeconomic Pathways (SSPs), were the outcome of a collaboration between several different research teams, including OECD and IIASA. They aim to capture the severity of the challenges to both mitigation and adaptation action in five different storylines for how the world might develop, and can be combined with pathways for the future development of GHG concentrations and other climate forcing agents to create a matrix of scenarios out to 2100.

The SSPs economic pathways that are at the foundation of this scenario work were developed based on OECD economic projections (Dellink et al., 2017). IIASA provided demographic pathways, which were used by the OECD to produce the economic pathways. These were then used as a reference for scenario comparisons and studies encompassing such issues as energy, water, and land-use futures under different levels of climate action. These economic projections also informed the OECD’s recent work on climate change and economic growth (OECD, 2017a), which underlined the value of well-aligned policy packages in mobilising investment and social support for the low-emissions transition and sustaining economic growth.

While climate considerations alone would argue for the maximum level of stringency in mitigation action to reduce both the extent and pace of climate change, this has major implications for the transformation of social and economic systems as well as the extent of climate impacts. The rapid transformations required to meet stringent goals are likely to incur greater adjustment costs, offset by reduced climate impacts and other benefits, including savings, facilitated by more rapid technological advances. This could in turn influence development opportunities and paths that reduce the welfare, adaptive capacity, and flexibility of societies to deal with the impacts of climate change. These effects, and the balance between development and mitigation, will be context specific, and while they are often addressed at a country level, the issues are likely to be most acute and intensely felt at smaller regional, city, or even local scales.

The ambition of mitigation action at a global level will determine the intensity of potential trade-offs between mitigation measures and their potential (in)direct impacts on ecosystems and human well-being at smaller scales. A particularly acute challenge will be the interdependencies between water, energy, and land (WEL). Over the past years, the nexus approach of integrally analysing these three domains has gained traction. A nexus approach gives equal weight to each sector (including the environmental needs) and tries to identify the interactions among sectors to better understand the synergies and trade-offs involved in meeting future resource demands in a sustainable way. The ultimate objective is to identify solutions that capitalise on potential synergies and co-benefits, minimising counterproductive policies. However, these approaches greatly increase analytical complexity.

IIASA has developed open-access scientific computing frameworks designed to aid decision-makers with complex choices regarding the development of water, energy, land resources, and infrastructure in a given river basin or administrative region (Wada et al., 2019; Kahil et al., 2018; Vinca et al., 2019). These tools link engineering-economic models representing investment and allocation decisions across water, energy, and land-use to water resource models, representing the detailed biophysical processes at high spatial and temporal resolutions. The tools can be applied in interactive stakeholder meetings, gaining comprehensive insights into the synergies and trade-offs of policies, technological solutions, and investments across water, energy, and land decisions4.

For its part, the OECD has analysed the economic aspects of the land, water, and energy nexus, focusing on the economic consequences of possible restrictions to the availability of land, water, or energy (OECD, 2017b). Separately, in a policy dialogue with the government of the republic of Korea (OECD, 2018a), the OECD identified a number of areas where progress could be made in managing the water-energy-land-food (WELF) nexus in Korea. The tools and approaches of the two organisations are complementary. OECD economic and policy analysis and approaches can provide insights that build on the detailed biophysical and technology modelling IIASA can provide.

Turning to the risks associated with climate change, future populations will be exposed to a range of climate change hazards of varying intensities that will alter from place to place, with some ‘hotspots’ exposed to more risks than others, compounding the challenges (Diffenbaugh and Giorgi, 2012; Diffenbaugh et al., 2007; Piontek et al., 2014; OECD, 2017b). Risks depend both on the severity of climate change and subsequent hazards as well as, critically, on the population’s spatial distribution (exposure) along with their vulnerability and capacity to prepare for and manage changing risks (IPCC, 2012). Stakeholders increasingly demand better tools and information to assist long-term decision-making and policy development. However, the capacity of regional, national, and local planners to develop and analyse socioeconomic projections and climate change impacts information varies widely. Recent efforts at IIASA seek to quantify the impacts of a variety of future climates (Byers et al., 2018) by holistically compiling and analysing spatially explicit hydrologic, climate, and socioeconomic data based on the SSPs.

This state-of-the-art analysis provides a basis for performing novel vulnerability assessments at fine spatial scales and at the country level. The approach brings new levels of consistency across socioeconomic and climate scenarios – as well as through the range of spatial scales. This allows both adaptation and mitigation responses to be informed by more immediate, tailored descriptions of risks and impacts. There is a clear opportunity to complement these modelling insights with the economic and policy analysis capabilities of the OECD to improve our understanding of how to manage complex and adaptive coupled human and natural systems under conditions of uncertainty.

Efforts to mitigate climate change are likely to be more successful and less costly when there is a two-way alignment between climate actions, broader goals of human well-being, and sustainable development (OECD, 2019). Transport systems can bring access to employment and income (SDGs 1, 8, 10), education (SDG 4), and health care (SDG 3). Yet, some systems - for instance, those dominated by private, fossil-fuelled light duty vehicles - provide mobility in ways that undermine progress on these and other sustainable goals. These negative impacts occur:

  • Within the system, for instance, by limiting accessibility for women or other disadvantaged groups (SDG 5, 10); or by exposing people to road injury (SDG 3).

  • Through infrastructures, for instance by misallocating land to parking and roads instead of other uses (SDG 11).

  • Via natural systems, including by worsening climate change (SDG 13); through use of carbon-intensive energy (SDG 7); through damage to ecosystems (SDG 6, 14, 15); and through local air pollution (SDG 3).

Analysis of key issues such as the environmental impacts of transport illustrates the need for multi-scale and linked-systems analysis. Emissions from fossil fuel burning in vehicles affect human health locally, but electrified alternatives still cause non-exhaust emissions and may cause distant emissions with different health impacts if the electricity comes from fossil sources. Therefore, policies to reduce these impacts need to go beyond inducing manufacturers to produce cleaner vehicles and electric vehicles, to, for instance:

  • Reducing individual drivers’ use of existing vehicles at the local level, including by providing public transit and active transport alternatives.

  • Supplying cleaner electricity (at the local, regional, or national level) or alternative (e.g. bio-) fuels based on internationally-sourced feedstock.

Each instrument to enact these different policies has economic impacts that reverberate across scales and the linked systems; and each has different effects on the emissions of the GHGs that drive climate change. This argues for a systems approach to integrally analyse the policy measures, co-benefits and trade-offs and costs.

Overall, shifting the policy focus to enhancing accessibility can better align decisions in the transport sector with well-being and sustainable development goals. First, because it focuses attention on improved access to opportunities and activities, rather than on higher physical movement. Second, focusing on improving accessibility (through enhancing physical access to opportunities, ensuring affordable services, and improving road safety) recognises the potentially important role of sustainable transport modes and of approaches that create proximity of housing to these economic and social opportunities. Such an approach could also support government climate change mitigation policies, as well as reducing air pollution and associated health impacts. Ensuring accessibility through alternative modes is key to achieving the shift away from individual vehicles, which transport demand management policies (e.g. road, parking and fuel prices) aim to achieve. On the other, it is also central to avoiding transport-related social exclusion or disproportionate economic transport costs for the population. This approach can also help ensure that new technologies (e.g. “on-demand” shared mobility services) are introduced in a way that they can contribute to climate and wider well-being and sustainability goals.

Changes in transport mode will require infrastructure but also behavioural changes, which can be stimulated by policies. A recent study at the OECD focuses on the effect of congestion pricing on the demand for clean transport modes, drawing on an empirical analysis of the effect of Milan’s congestion charge on the use of bike sharing. It finds that congestion pricing significantly increases bike sharing in the time windows when it is applied. On the other hand, recent work from IIASA (McCollum et al., 2017) shows that the emission reduction potential from the transport sector could be lower once consumer behaviour is taken into account.

The multiplicity of combinations for possible responses requires integrative and multi-scale analysis to highlight which development pathways bring greatest progress towards the air quality/human health, climate, and other goals at lowest cost. However, the relevance of information from these streams of work would benefit from greater IIASA-OECD collaboration. In particular, as urban-scale interventions spread in countries with a mix of rural, suburban, and differently-scaled urban areas, their benefits and trade-offs will vary. Both the OECD and IIASA have a range of tools to look at impacts and policies. By carefully linking insights from fine-grained urban models and analysis of good practice in policy design and implementation to aggregate impacts and economic feedbacks, broad and local progress towards human development goals can be studied at the same time, helping policymakers spot and avoid trade-offs.

Several future directions should be pursued to develop the understanding of these integrated systems. First, the nexus modelling of complex, adaptive inter-linked systems under conditions of change and uncertainty, with a range of specific spatial, climatic and socio-economic contexts and policy approaches should be expanded. It is also important to connect stakeholders systematically during the model development process, to ensure that interventions are accepted by stakeholders when implemented. Furthermore, there should be a concerted effort to combine modelling tools and data at different spatial levels to develop insights that are reliable, including at smaller spatial scales. The development of these models may then be used to inform and assess strategies and policies using models and developing indicators that put well-being and sustainability at the centre of decision-making.


Byers et al (2018), “Global exposure and vulnerability to multi-sector development and climate change hotspots”, Environmental Research Letters, Vol. 13/5i: https://doi.org/10.1088/1748-9326/aabf45

Daly, H.E., (2005). “Economics in a full world”, Scientific American, Vol. 293/3, pp.100-107: https://doi.org/10.1038/scientificamerican0905-100

Daly, H.E. (2015), "Economics for a Full World," Great Transition Initiative, https://www.greattransition.org/publication/economics-for-a-full-world

Dellink, R., J. Chateau, E. Lanzi, B. Magné (2017), “Long-term economic growth projections in the Shared Socioeconomic Pathways”, Global Environ. Change, Vol. 42, pp. 200-214

Diffenbaugh et al. (2007), “Heat stress intensification in the Mediterranean climate change hotspot”, Geophysical Research Letters, Vol. 34/11, https://doi.org/10.1029/2007GL030000

Frank et al. (2017), “Reducing greenhouse gas emissions in agriculture without compromising food security?”, Environmental Research Letters, Vol. 12/10, https://doi.org/10.1088/1748-9326/aa8c83

Haberl, H., et al., (2007). “Quantifying and mapping the human appropriation of net primary production in earth's terrestrial ecosystems”, Proceedings of the National Academy of Sciences, Vol. 104/31, pp.12942-12947. https://doi.org/10.1073/pnas.0704243104

Harris, N., (2016). “Global Forest Watch Climate: Summary of Methods and Data”, World Resources Institute, Washington D.C., USA

Havlík et al, (2014), “Climate change mitigation through livestock system transitions”, Proceedings of the National Academy of Sciences, Vol. 111/10, pp.3709-3714, https://doi.org/10.1073/pnas.1308044111

International Energy Agency (IEA) (2018), World Energy Outlook, IEA, Paris

IPBES (2019): Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. S. Díaz, J. Settele, E. S. Brondízio E.S., H. T. Ngo, M. Guèze, J. Agard, A. Arneth, P. Balvanera, K. A. Brauman, S. H. M. Butchart, K. M. A. Chan, L. A. Garibaldi, K. Ichii, J. Liu, S. M. Subramanian, G. F. Midgley, P. Miloslavich, Z. Molnár, D. Obura, A. Pfaff, S. Polasky, A. Purvis, J. Razzaque, B. Reyers, R. Roy Chowdhury, Y. J. Shin, I. J. Visseren-Hamakers, K. J. Willis, and C. N. Zayas (eds.). IPBES secretariat, Bonn, Germany. 56 pages. https://doi.org/10.5281/zenodo.3553579

Kahil et al. (2018). A Continental-Scale Hydroeconomic Model for Integrating Water-Energy-Land Nexus Solutions. Water Resources Research, 54, 7511–7533

Laurance, W.F. and Arrea, I.B. (2017), “Roads to riches or ruin?”, Science, Vol. 358/6362, pp. 442-444, https://doi.org/10.1126/science.aao0312

Markandya, A. et al. (2018), “Health co-benefits from air pollution and mitigation costs of”, Lancet Planet Health, Vol. 2, pp. 126-33

McCollum, D.L., Krey, V., Riahi, K., Kolp, P., Grubler, A., Makowski, M., Nakicenovic, N., 2013. Climate policies can help resolve energy security and air pollution challenges. Climatic Change 119, 479–494. https://doi.org/10.1007/s10584-013-0710-y

McCollum et al. (2017), “Improving the behavioural realism of global integrated assessment models: An application to consumers’ vehicle choices”, Transportation research Part D: Transport and Environment, Vol. 55, pp. 322-342, https://doi.org/10.1016/j.trd.2016.04.003

Millennium Ecosystem Assessment, (2005). “Ecosystems and Human Well-being: Synthesis”, Island Press, Washington, DC

Nicholson, E., et al. (2009). “Priority research areas for ecosystem services in a changing world”, Journal of Applied Ecology, Vol. 46/6, pp.1139-1144, https://doi.org/10.1111/j.1365-2664.2009.01716.x

N. S. Diffenbaugh, F Giorgi, (2012), “Climate change hotspots in the CMIP5 global climate model ensemble”, Climatic Change, Vol. 114/3-4, pp. 813-822, https://doi.org/10.1007/s10584-012-0570-x

OECD (2015), “The Economic Consequences of Climate Change”, OECD Publishing, Paris

OECD, IEA, NEA, & ITF (2015), “Aligning Policies for a Low-carbon Economy”, OECD Publishing, Paris, https://doi.org/10.1787/9789264233294-en

OECD (2017a), “Investing in Climate, Investing in Growth”, OECD Publishing, Paris, https://doi.org/10.1787/9789264273528-en

OECD (2017b), “The Land-Water-Energy Nexus: Biophysical and Economic Consequences”, OECD Publishing, Paris, https://doi.org/10.1787/9789264279360-en

OECD (2018a), “Managing the Water-Energy-Land-Food Nexus in Korea: Policies and Governance Options”, OECD Studies on Water, OECD Publishing, Paris, https://doi.org/10.1787/9789264306523-en

OECD (2018b) “Rethinking Urban Sprawl - Moving Towards Sustainable Cities”, OECD Publishing, Paris, https://doi.org/10.1787/9789264189881-en

OECD (2019) “Accelerating Climate Action: Refocusing Policies through a Well-being Lens”, OECD Publishing, Paris, https://doi.org/10.1787/2f4c8c9a-en

Piontek et al (2014) , “Multisectoral climate impact hotspots in a warming world”, Proceedings of the National Academy of Sciences , Vol. 111/9, pp. 3233-3238, https://doi.org/10.1073/pnas.1222471110

Shindell et al. (2012), “Simultaneously mitigating near-term climate change and improving human health and food security”. Science, Vol. 335, pp. 183-189, https://doi.org/10.1126/science.1210026

Vandyck, T. et al. (2018), “Air quality co-benefits for human health and agriculture counterbalance costs to meet Paris Agreement pledges”, Nature Communications, Vol. 9, https://doi.org/10.1038/s41467-018-06885-9

Vinca et al. (2019). The Nexus Solutions Tool (NEST): An open platform for optimizing multi-scale energy-water-land system transformations. Geoscientific Model Development Discussion, https://doi.org/10.5194/gmd-2019-134

Vitousek, P.M. et al. (1986). “Human appropriation of the products of photosynthesis”, BioScience, Vol. 36/6, pp. 368-373, https://doi.org/10.2307/1310258

Waage, J. et al. (2015). “Governing the UN Sustainable Development Goals: interactions, infrastructures, and institutions”, The Lancet Global Health, Vol. 3/5, pp. 251-252, https://doi.org/10.1016/S2214-109X(15)70112-9

Wada et al. (2019). Co-designing Indus Water-Energy-Land Futures. One Earth 1


← 1. The Millennium Ecosystems Assessment (2005) defined four categories: provisioning; regulating; supporting; and cultural.

← 2. In recent years estimated around 4.8 GtCO2-eq per year, comparable to the GHG emissions from Europe (Harris 2016)

← 3. Climate change impacts could lead to economic costs that can rise up to 3% of global GDP by 2060 and up to around 6% of GDP in most damaged regions, such as South and South East Asia and Sub-Saharan Africa (OECD, 2015). However, as the report notes, there is a still a lot that cannot be quantified, so this could be a serious under-estimate should, for example, we push the climate beyond critical tipping points/

← 4. See: https://www.iiasa.ac.at/web/home/research/iswel/ISWEL.html

Metadata, Legal and Rights

This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. Extracts from publications may be subject to additional disclaimers, which are set out in the complete version of the publication, available at the link provided.


The use of this work, whether digital or print, is governed by the Terms and Conditions to be found at http://www.oecd.org/termsandconditions.