Globally, the population living in cities is increasing with 66% of people expected to live in urban areas by 2050 [1
]. Today, cities are responsible for over 78% of the global energy consumption and over 60% of greenhouse gas (GHG) emissions [2
], but less is known about how they drive resource use and sustainability impacts. They are centres of socio-economic strength and are responsible for 85% of gross domestic product (GDP) [3
]. They are therefore central in both driving consumption of resources and the associated sustainability implications, and as such are also of critical importance in implementing solutions for sustainability [4
There has been noticeable progress in reducing GHG emissions with initiatives such as the Covenant of Mayors that has over 7000 signatories from EU cities [5
]. Furthermore, C40 cities is a group of 96 global cities that focus on reducing GHG emissions in urban areas and who together represent a quarter of the global economy [4
]. Measurement of GHG emissions can be performed using either production-based accounting (PBA) that focuses on the emissions produced by activities within city borders and jurisdiction, or consumption-based accounting (CBA). The latter includes upstream emissions from the production of all products and services consumed by citizens regardless of where production occurs but excludes emissions from exported goods and services [6
]. Recent studies that have compared the two accounting methods have found that consumption-based emissions (CBE) can be significantly higher than production-based emissions (PBE) [7
]. A study of China, the UK and the US found that CBE was higher than PBE for most cities [8
], whilst Harris et al. [9
] found that on average CBE were twice as large as PBE for ten European cities. In a study of four Chinese megacities it was found that 48–70% of the CBE occurred upstream and outside the city [10
]. Similarly, Chen et al. [11
] calculated 50% for Sydney and Melbourne, whilst C40 cities [4
] obtained an average of 60% for 79 global cities.
However, current reporting of city GHG emissions almost exclusively focusses on PBE, disregarding CBE [12
]. This leads to responses in city strategies limited to actions such as improving public transport and energy efficiency of building stock [7
]. Meanwhile, consumption-based emissions that relate to the supply chain and life cycle of resources and products, have barely been addressed in city strategies [13
This extends to other areas of sustainability. For instance, whilst recycling initiatives have increased [14
], measures fostering more encompassing circular economy actions such as reuse, refurbishment and remanufacturing, appear to be in their infancy. Whilst the merits of densification of cities has received attention in literature, many cities continue to grow spatially, impacting on eco-system services, biodiversity and recreation areas [15
]. This also has negative ramifications for the health and well-being of citizens, as green and blue space is lost [16
There are an increasing number of studies that recognise the effects of air pollution on health and the resultant costs (from hospital admissions, deaths, illness and medical needs) [19
]. Nonetheless, the literature on costs and benefits of comprehensive sustainable actions is still developing and is performed at a macro level with few studies examining scenarios for individual cities [23
]. Recently, however, Gouldson et al. [25
] explored the economic case for low GHG responses in five diverse global cities (Leeds, UK; Kolkata, India; Lima, Peru; Johor Bahru, Malaysia and Palembang in Indonesia). They reported that the required investments for reductions of 15–24% in GHG emissions (relative to BAU) would equate to 0.4–0.9% of GDP but result in savings in the form of reduced energy between 1.7% and 9.5%.
There are a growing range of methods available to assess the current status of sustainability of cities from indexes such as the Siemens Green Index [26
], material flow analysis methods [27
], urban metabolism [29
] coupled with life cycle analysis [30
], through to assessing single indicators such as the ecological footprint, carbon footprint and water footprint. Lavers Westin et al. [31
] combined comprehensive material flow analysis with life cycle assessment datasets to understand the consumption hotspots for three Swedish cities.
Few studies examine the effects of future city strategies on sustainability impacts. However, forecasting, modelling and scenario analysis are needed to help understand the future implications of potential city planning and development strategies [32
]. The complexities of the interactions of different indicators, such as land use, consumption, socio-economic effects and health and well-being, and their interlinkages is an enormous challenge for progress in sustainability [34
Scenario analysis is one method to help understand the implications of future pathways and aid strategic decision making [35
]. Three different approaches are used within environmental sciences in scenario storyline development: exploratory, normative and business-as-usual [37
]. Qualitative and quantitative scenario methods can be combined into the Story and Simulation (SAS) approach, used for example in the Millennium Ecosystem Assessment and the GEO-4 Scenarios [38
The aim of this paper is to investigate how city sustainability strategies for 10 European cities can affect the sustainability performance in the future. To do this we compare the current status with a business-as-usual (BAU) scenario for 2050 and a post-carbon sustainability scenario (PC2050). The latter scenario is based on a vision and set of actions, developed by the city stakeholders of each city. A mixed methodological approach is applied to address a wide range of sustainability implications. We combine a semi-quantitative indicator analysis, GHG accounting, spatial modelling of land-use change and a cost–benefit analysis of improved health from reduced air pollution. The paper seeks to answer the following questions:
What is the sustainability performance of the cities of the two scenarios compared to the year 2007?
How do the GHG emissions compare using PBA and CBA for each of the cities?
What are the potential land-use changes under both scenarios and what are the implications?
What are the cost implications for health from investing in renewable energy and energy efficiency?
The paper presents the findings from the sustainability assessment work package of the EU FP7 POCACITO project (Post Carbon Cities of Tomorrow). The accounting procedure and results for the GHG emissions have already been extensively covered in a previous publication [9
]. The novelty of this paper is that it presents the full assessment combining the findings from four different but complementary methodologies, to assess the sustainability implications of future city scenarios. In order to do so, we repeat the most relevant results of the previous paper in the results section.
In the next section we introduce the background to the research, the modelling approach and the four analytical methods used in our study. We then present the results in Section 3
, followed by a discussion of the results for each method in Section 4
and provide a brief concluding summary in Section 5
The analysis has provided some valuable insights about the potential future pathways of low carbon strategies compared to BAU. The mixed methodological approach highlights how the PC2050 strategies are advantageous from one perspective but that challenges remain for others. The following sections discuss the results for each of the methods.
4.1. Semi-Quantitative Analysis of KPIs
The assessment of sustainability indicators showed that cities are moving in a positive direction for most indicators under BAU but the performance of PC2050 is superior. However, this improvement primarily relates to the environmental indicators, with less difference noticeable for the economic or social indicators. This reflects the focus of the city stakeholder actions and targets in creating the scenarios. A noted issue for several cities is “poverty level” which is indicative of the increasing disparity between rich and poor in many European and global cities (Tammaru et al., 2016), and is also linked to segregation of housing (a particular issue for Malmö).
4.2. GHG Accounting
In the baseline year 2007, upstream emissions were on average 48% of the total CBE demonstrating the importance of considering supply chain emissions in addition to PBE. This is comparable to Mi et al. (2019) who found that CBE accounted for over 50% for four Chinese cities (with a similar range of 4–25 tCO2e). For the future scenarios, the share and importance of CBE increases.
Under both BAU and PC2050 there are significant reductions in PBE compared to 2007, decreasing by 31% and 68% respectively. This is due to existing plans for most cities under BAU to reduce PBE, which are improved under the PC2050 city strategies. However, only Copenhagen comes close under BAU to achieving zero PBE with 0.7 tCO2e per capita. Most cities remain in the range of 2–4 tCO2e per capita, with Istanbul being the highest with 5 tCO2e per capita. However, CBE increases for eight cities, for both BAU and PC2050 rising by an average of 33% and 35%, respectively. This increase is primarily linked to rising GDP and the associated increase in spending and final demand, which overrides gains in local and global (production) efficiency improvements.
The results show that the visions and actions of stakeholders for PC2050 made a significant reduction in PBE. Nonetheless, consumption-based impacts were not considered, and the focus was on traditional production-based responses, whilst the CBE still increased. This is consistent with global approaches of cities [23
]. Therefore, using PBA would suggest a decoupling of GHG emissions and economic output, which is often touted by governments [71
] but using CBA shows the opposite trend [9
Cities are in a unique position to mobilise and influence local actors [8
] and therefore have an opportunity to address CBE more fully. Two overall approaches are fostering action in the supply chain by imposing standards and capturing the full value of imported components and materials through the circular economy [8
]. The latter can be achieved through facilities such as repair cafes, exchange locations for used goods [72
], by supporting local companies that refurbish, remanufacture and recycle, as well as sharing schemes. Alternatives such as reducing food waste may be as effective but less expensive than the option of retrofitting buildings or upgrading transport systems [45
One limitation of our analysis is the age of the EXIOBASE database whose underlying data is from 2007. However, our main aim was to understand the implications of PC2050 strategies compared to BAU and not make forecasts. Our methodologies for both scenarios were consistent in the use of EXIOBASE. In addition, we used the most robust projection available (e.g., IEA, 2015) to adjust the underlying data tables within that represent the global production systems.
4.3. Ecosystem Services—Land-Use Changes
The results show that the encroachment of urban land on non-urban land is a risk under BAU for virtually all of the cities, with Malmö being the highest with a 43.3% increase in urban land derived from non-urban land.
This is of concern for two primary reasons. Firstly, the importance of green recreational areas and non-urban land is increasingly recognised by research in terms of benefits for health, well-being and quality of life [16
]. Secondly, research also shows that sprawling cities require more infrastructure and are therefore more resource intensive and less energy efficient [74
]. Therefore, they have a higher carbon footprint than dense city areas.
Densification and urban sprawl were generally not well covered in the city visions and actions of POCACITO case study cities. Therefore, there is a need to ensure policies and strategies are developed to incorporate dense development.
4.4. Socio-Economic Analysis
The simplified cost–benefit analysis of improved health from a reduction in fossil fuel use showed positive results for seven cities under BAU and nine cities for PC2050. The only exception is Istanbul which incurs increased health costs due to rising pollution from transport and energy production under BAU and to a lesser extent PC2050. The results mirror other studies which are beginning to recognise the costs and implications of air pollution [20
]. For instance, the costs in 2009 of damage caused by emissions just from industries of the European Pollutant Release and Transfer Register (E-PRTR) were estimated at EUR 102–169 billion. Meanwhile, Cui et al. [19
] showed that reductions in air pollution in Jinan led to US$
318 million between 2013 and 2017, but further reductions could have translated to $
US 1.3 billion in economic benefits.
The average benefit–cost ratio is 1.0 for BAU and 2.5 for PC2050 which aligns with Urge-Vorsatz et al. [70
] who modelled a deep efficiency scenario for building renovations in the EU27 with cumulative costs of $
US 5.1 trillion to 2050 and cumulative costs of $
US 9.8 trillion.
Our study showed that the estimated costs of renewable energy transitions and house renovations are only 0.31% to 1.5% of GDP between 2018 and 2050. The study used a discount rate of 3% for costs but 1% for benefits to provide maximum value to potential future benefits [76
]. This provides a slight bias towards the benefits over costs, although we argue that it is justified. Firstly, the underlying figures for economic costs we utilized are based on a percentage of premature deaths of the country GDP, thereby averaged across the country. However, cities are more affected by air pollution and hence the benefits are likely to be higher. In addition, there are many other benefits to reduced air pollution (e.g., increased recreational facility) other than reduced deaths which were not included. A major limitation of our study is that it omits costs for the transport infrastructure. This would have been impossible to do or estimate within the project due to the complexity of cities and the need to design the systems. In addition, one could argue that the overall cost of development to 2050 of sustainable transport would be no greater than developing an unsustainable network. For instance, remodelled costs for the UK to reach net zero GHG emissions by 2050 show that it can be achieved without financial penalty [77
]. However, some of the costs, e.g., for household renovation, would need to be carried out by private owners, and so subsidies might be needed to incentivise.
Energy demand of PC2050 compared to BAU was projected to be 9% to 43% (an average of 23%) lower than BAU, which are associated with similar reductions in energy costs.
In addition, a significant number of jobs would result from implementation of the modelled level of renewable energy. These numbers are highly uncertain and indicative only. It is also not certain whether these are direct or indirect jobs, what sectors would benefit, if the jobs are in the EU or outsourced, and what the net effect on the labour market is. However, it does suggest that a significant quantity of jobs would be created for building renovation and for SMEs within the EU, consistent with other studies [69
Overall, the assessment suggests that the benefits of the PC2050 strategies and the implementation of renewable energy and building renovation are far greater than BAU and more than compensate for any costs incurred.
This paper has used a combination of qualitative and quantitative methods to provide a comprehensive sustainability assessment of the BAU and PC2050 scenarios. It has shown the value of using a mixed-method approach so that the qualitative analysis can support and increase the robustness of quantitative modelling.
The analysis shows clear benefits of the PC2050 sustainability strategies compared to BAU, although critical challenges remain for most of the cities. Chief among these is that despite significant decreases in PBE emissions, primarily from actions on transport, buildings and energy, the CBE for almost all cities was projected to grow in PC2050, compared to 2007. This is mainly due to increasing affluence, linked to increasing consumption. Notably, the results also imply that none of the cities are currently on course to achieve the objectives of the 2016 Paris Agreement on GHG mitigation. Cities must therefore begin to address this, first by recognition and accounting of CBE. Secondly, through implementation of measures to support more sustainable production and consumption strategies such as the circular economy.
The KPI analysis highlighted the wide environmental benefits and to a lesser extent social and economic benefits of PC2050. However, there were some notable concerns in the areas of inequality and poverty, which is an increasing global challenge. The land-use change study demonstrated the continuing trend of urban sprawl and the potential for this trend to be sustained. Since green and blue areas are linked to health and amenities, there is a clear risk to health and costs if densification does not occur. Finally, the cost–benefit study indicated that the PC2050 strategies can be cost positive in the long term, provide significant jobs and improve the health of the city’s citizens by reducing air pollution.