The Effect of Geographic Agglomeration on the Efficacy and Welfare Consequences of Climate Action

doi:10.21203/rs.3.rs-1652900/v1

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The Effect of Geographic Agglomeration on the Efficacy and Welfare Consequences of Climate Action

https://doi.org/10.21203/rs.3.rs-1652900/v1

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If national climate plans match the priorities of the average community, to what extent does it matter that many communities are very different from the average? Using a dataset of c.33,000 community GHG footprints from Lower Level Super Output Areas in England made-up of 12 emissions sources, this analysis assesses the consequences of priority areas for climate action being set at different geographic levels. Results show that setting priorities at a local level could modestly increase the share of all emissions covered by a climate action plan. This suggests that the efficacy of a climate action plan may also be modestly improved by local prioritisation of climate actions. More significantly, the share of emissions covered by climate action is found to be dramatically less variable between communities when local priorities for action are used in place of national priorities. This suggests that the welfare consequences of action may also be shared more equally when local priorities guide action. These results show that the geographic lens applied to understanding the climate challenge – independent of governance approaches or policies for action – is a meaningful consideration for the efficacy and the welfare consequences of climate action. More generally, engaging with the effect of geographic agglomeration can help to inform the roles of national and local actors around prioritising and leading climate action. Further analysis is needed to understand how wider factors important to climate action, including capacity, are affected by agglomeration, whether these results hold in other nations, and how a dynamic assessment of climate action prioritisation over time might affect these results.

Climate Analysis and Modeling

climate action planning

climate change mitigation

polycentric governance

Paris Agreement

Following the Paris Agreement, global climate governance has been characterised by a growing number and diversity of actors. Climate action strategies and commitments have become increasingly common from urban governments (Grafakos et al., 2019), businesses (Kuramochi et al., 2020), central banks (Campiglio et al., 2018), faith groups and individuals (Bomberg and Hague, 2018).

This shift towards polycentric modes of climate action is seen to have a number of potential benefits for climate action. A greater diversity of actors can lead to more dynamic and innovative approaches to governance (Jordan et al., 2015). Devolution and depoliticization of responsibility can lead to more effective decision-making (Romero-Lankao et al., 2018). Democratic legitimacy can be increased where polycentric approaches bring stakeholders and citizens closer to decision making processes (Cattino and Reckien, 2021). And higher levels of engagement facilitated by polycentric governance approaches can help to build a social mandate for action (Howarth et al., 2021).

Non-state and sub-national actors face a number of challenges, however, realising the potential thought to exist from their leadership. Key technical and financial capacities are concentrated at the national level, and existing institutional infrastructures and agreements around climate change are primarily between national governments (Held and Roger, 2018). In addition, some sources of emissions typically fall outside of the jurisdiction of non-state actors. For example, the Committee on Climate Change in the UK estimates that local governments only have influence over approximately one-third of GHG emissions released in their geographies (*CCC, 2020).

Consequently, key aspects of climate governance, including the setting of priority areas for action, are usually established by national governments and reflect a national perspective on the challenge of decarbonisation. In the UK, for example, the government’s Net-Zero strategy is seen to guide the nation’s decarbonisation and establishes a sector-based framework for action.

To date the UK has achieved more than half the required reductions in emissions to meet its 2050 target, however more than 90% of reductions have come from just three sources: The electricity grid, industrial processes, and the fossil fuel industry (*). Looking forward the UK government released its Net-Zero Strategy (UK Government 2021*) in October 2021. The independent Committee on Climate Change has described these plans as a “step forward”, but has also raised concerns about a lack of detail in plans around, aviation, hydrogen, biomass, food, heat and buildings (*). The UK government’s strategic approach to climate action is therefore currently characterised by an evolving prioritisation of sectors.

In the following we explore the extent that the use of different geographies leads to different outcomes in the coverage of climate action plans across between LSOAs. We start by outlining our approach. Following this we explain the mechanism that could lead to different prioritisations of climate actions, assess how prioritisation is affected using the 12 sectors that makeup each LSOAs emissions footprint, estimate the scale of impact resulting from different prioritisations of climate actions, and finally show the extent that different indicators can predict the degree to which an LSOA may be affected by a local versus national prioritisation of climate actions.

We explore the consequences of different geographic scales being used in the setting of priority areas by assessing a dataset of c.33,000 emissions footprints from Lower Layer Super-Outputs Areas (LSOAs) covering 12 sources of emissions from the Centre for Research into Energy Demand Solutions (CRED) place-based carbon calculator (*). LSOAs, a geographic designation that includes an average population of 1500 people, are used to represent a ‘community level’ geography. It should be noted, however, no formal layer of government exists at the LSOA level.

Priority areas for climate action are identified in this analysis based solely on the relative scale of sectors: A climate plan with three sectors will include the three largest sectors. This sets aside a large set of factors, including ones that are socio-technical, political, and economic (Balouktsi, 2019; Dale et al., 2019; Howarth et al., 2021) involved in the determination of priority areas for action, under the assumption is made that more or better opportunities for action are found in sectors with more emissions.

The efficacy of a climate action plan in this paper is interpreted narrowly as the share of emissions it covers. This is based on the previously noted assumption that a larger volume of emissions may reveal more and/or better opportunities for intervention.

The welfare consequences of action are explored by comparing the share of emissions covered between LSOAs. The extent and nature of impacts on public welfare from climate action are uncertain (Ekins and Zenghelis, 2021), highly specific to governance approaches (Gouldson et al., 2016), measures implemented (Millward-Hopkins et al., 2017), sector considered (Mayrhofer and Gupta, 2016), and the socio-economic context (Colenbrander et al., 2017), among an array of wider factors. Setting aside these considerations, we assume that if the share of emissions covered by a climate action plan between communities is more similar, the welfare consequences of action will be more similar.

Prioritisation of climate action: A comparison of top-down and bottom-up approaches

Figure 1 presents the density of total emissions in England using different scales of analysis. As the scale moves from the smallest geography, Local Super Output Area (n = 32,844), to ward (n = 6786), local authority district (n = 309), county (n = 91) and region (n = 9) variation between datapoints is reduced as relatively higher and lower emission geographies are combined. At the LSOA level one standard deviation extends 3.4 tonnes of emissions from the mean while at the region level one standard deviation extends only .9 tonnes from the mean. Across each geography the total volume of emissions is the same and the number of people is the same, therefore the mean level of emissions is the same.

Figure 1 presents the mechanism for, but not evidence of, the priorities for climate action being affected by the scale of analysis: If for each observation the ranking of emissions by sector was the same and only the absolute size of emissions was different, the ranking of emissions by sector would be the same at all geographies. If the ranking of emissions by sector is not the same, however, the aggregation of emissions by higher level geographies would lead to different rankings of sectors at different geographies.

In Fig. 2 we compare the ranking of emissions by sector at the national scale and at the LSOA scale with each cell identifying the share of observations where the ranking is the same. For example, 1x1 shows that 53% of the time the sector with the largest volume of emissions is the same sector at the national scale as it is at the LSOA level. This figure demonstrates that the ranking of emissions by sector is meaningfully affected by the geography used for analysis: The largest source of emissions at the national scale is only among the largest three sources of emissions from an LSOA 63.1% of the time (52.8% + 7.6% + 2.7%). Similarly, the top 3 sources of emissions from the nation will only include the top 3 from an LSOA just over one-third of the time (.337%).

To the extent climate action prioritisation is based on a ranking of the emissions from different sectors, Fig. 2 show that a national ranking and prioritisation will be significantly different from a local prioritisation. The degree to which this affects climate action, however, depends on the size of different sectors, the specifics of the rankings, and the number of sectors prioritised by a climate action plan. If three sectors are always the largest at the LSOA level (and therefore also at the national level), differences in rankings would not affect the coverage of a climate action plan that addresses at least three sectors.

Figure 3 compares the share of emissions covered by climate action plans derived from national (teal) or local (red) prioritisation. It also shows how the inclusion of different numbers of sectors in a climate action plan affects its coverage of total emissions. At x = 1, for example, the red boxplot shows the share of emissions from the largest sector at the national level across 32,844 LSOAs in England, while the teal boxplot shows the share of emissions from the largest sector specific to each LSOA. At x = 2 the sum of the two largest national or local sectors is presented.

Two conclusions can be drawn from Fig. 3. The first is that while the coverage of climate action plans developed from the bottom-up (i.e. using the specific sectors largest in each LSOA) leads to a larger proportion of emissions being covered, the difference is small. If one sector is considered for climate action national action would cover 16% of UK emissions while action based on the largest local sectors would cover 20% of emissions. A shift to local priorities would therefore increase the emissions covered by climate action by 27%. However, as the number of sectors considered in a plan increases the difference in coverage diminishes rapidly. If three sectors are considered, focusing on local priorities would increase coverage 15% and at five priorities the amount of emissions covered increases by only 4%.

Second, the variability in the coverage of climate action plans between LSOAs is dramatically larger when national prioritisation is used in the place of local prioritisation. If three sectors are the focus on a climate action plan the average LSOA covers a similar volume of emissions whether priorities are set at a national or local level: If priority sectors are determined at the national level 44% of emissions would be covered and if local priorities are used the share increases to 51%. For a subset of LSOAs, however, the difference in coverage is quite stark. The LSOA in the 10th percentile for coverage of its emissions would be addressing only 30% of its emissions if it were to focus on the three largest national sector while this would increase to 47% of emissions if it were to focus its largest sectors.

Place-based prioritisation therefore substantially improves the coverage of climate action for a subset of LSOAs. Identifying these communities is important to improve the efficacy of climate action, but may be even more important from an equity standpoint: If climate actions are costly, these places may be addressing less than their fair share of emissions. If climate action carries benefits, on the other hand, either indirectly via cleaner air or job opportunities, or directly via investment and government subsidies, these places may be receiving less than their fair share. Given the far reaching

To identify places where the coverage of a climate action plan is significantly different when different geographies are used to determine priority sectors for action, we can assess two key factors. The variation in a sector’s emissions between LSOAs fundamentally drives different rankings of sectors at different geographies. Second, the volume of emissions from a sector determines the degree that a different ranking of a sector leads to consequences for the amount of emissions covered by a climate action plan.

From Fig. 4 we can see that the sectors that have the highest emissions also have the most variation between LSOAs. For the largest sector, air travel, for example, the LSOA in the 80th percentile for emissions is responsible for more than 4 times the average per capita emissions of the LSOA in the 20th percentile. By contrast for emissions from electricity the LSOA in the 80th percentile is responsible for only 40% more emissions than the average per capita emissions of LSOA in the 20th percentile.

Figure 4 also suggests that socio-economic characteristics of LSOAs may be correlated with the degree of similarity between national and local prioritisations of sectors. This can be seen from sectors where emissions that have been found to rise with income, including ‘air travel’ and ‘recreation’ showing more variation between LSOAs and higher emissions than sectors such as ‘electricity’ which have been found to have a weaker relationship with income (Ivanova et al., 2018).

Table 1 shows the correlation between a set of socio-economic indicators and the difference between the coverage of local and national climate action plans. Results suggest that socio-economic status may be a strong predictor of the extent the national prioritisation of actions aligns with a local prioritisation. With each indicator a higher value indicates a less desirable socio-economic status, suggesting that employment, income, and measures of deprivation are each higher where the match between national and local priority sectors is poorer. All results are significant at the 1% level, a result which is driven by the size of the dataset.

Table 1: Pearson’s Correlation Coefficient for the difference between the coverage of local and national climate action plans and LSOA level social indicators.

Socio-economic indicator	Correlation with the difference between local and national prioritisation
Income Domain Score	0.55
Income Deprivation Affecting Children Index (IDACI)	0.51
Income Deprivation Affecting Older People Index (IDAOPI)	0.43
Employment Domain Score	0.57

Prioritising climate action: One size (nearly) fits all?

Analysis suggests that the volume of emissions covered by a climate action plan may only be minorly effected by the geography used to determine priority areas for action. If the volume of emissions covered by two climate action plans is substantially different it could reasonably be assumed that the opportunities for intervention are different, with more emissions leading to more and/or better opportunities for action. As the volume of carbon between the two plans becomes increasingly similar, however, this assumption becomes more tenuous. In the most extreme case, the share of total UK emissions covered by a climate action plan is increased by approximately 5 percentage points if local priorities for action are used instead of national priorities.

One might therefore be tempted to conclude from this that geography has a limited influence on the overall effectiveness of climate action. There may be room, however, for further analysis to test this result for four reasons.

Firstly, the scale of emissions by sector is not the only factor whose heterogeneity is diminished by aggregation. Capacities, including knowledge, technical expertise, and financial resources, will also be unevenly distributed across geographies and by the same mechanism come to appear more evenly distributed when viewed from successively higher geographies. To the extent capacity for climate action is greater in wealthier places, the places where national prioritisation most poorly matches with local priorities may also be the places where capacity deficits are highest, based on the findings in Table 1. More simply, the consequences for effective climate action could be magnified by looking at wider factors that enable climate action.

A second consideration concerns the geography used for this analysis. As a consequence of being relatively small, and therefore having minimal climatic differences across its area, and having a single energy grid, emissions are relatively homogenous in England relative to other parts of the world (Millward-Hopkins et al., 2017; Minx et al., 2013; Sudmant et al., 2018). The degree to which top-down prioritisation of climate actions effects the efficacy of climate action may therefore be more limited in the UK than in other places.

Third, the static presentation of climate action in this analysis may obscure the longer-term consequences of variation in the level of climate action between places. This is raised, for example, by Gouldson et al (2015) who make the case that the early stages of climate action enable the development of the modes and structures of governance that enable deeper mitigation in the future.

Finally, analysis here uses LSOAs as the smallest geographic unit, but LSOAs are a relatively clumsy representation of communities or ‘places’ since they are not built around local characteristics. Moving from statistical geographies, such as LSOAs, to meaningful representations of local areas has been explored for industries and employment in England (Beatty et al., 2007; Beatty and Fothergill, 1996) and recent work explores place-based climate action in the UK (Howarth and Parsons, 2021). Definitions and datasets to represent local-level climate action, however, are not yet developed.

The burdens and benefits of climate action: One size, uncertain consequences?

Economic analysis has historically considered the costs and benefits of climate mitigation separately. Exemplifying this, mitigation costs and benefits were different working groups in the IPCC assessment process (Köberle et al., 2021).

Recent analyses, however, portray the transition to net zero emissions as a net economic opportunity (Hepburn et al., 2020; Zenghelis, 2021). Green investment can support economic recovery from COVID-19 (Zenghelis, 2021), help to correct market failures such as those associated with fossil subsidies (Monasterolo and Raberto, 2019), and support innovation and long term economic growth (Stern, 2015). Case studies and literature reviews find that both private financial returns (Colenbrander et al., 2017; Gouldson et al., 2016; Sudmant et al., 2016) and wider public benefits via cleaner air, reduced congestion and new employment *(Gouldson et al., n.d.; Haines, 2017), can substantially outweigh the financial costs of mitigation. Overwhelming these benefits, of course, are the value of impacts avoided from biodiversity loss (Pires et al., 2018), heat stress (Santamouris, 2020; Vicedo-Cabrera et al., 2021), reduced agriculture productivity (Ortiz-Bobea et al., 2021), desertification (Huang et al., 2020), and other impacts of climate change.

Accompanying potential benefits climate action, however, are the need for reskilling millions of workers *(Bowen and Kuralbayeva, n.d.; Robins et al., 2019), the burden on the financial system of stranded assets (Mercure et al., 2018), the need to mobilise trillions in investment capital (Giglio et al., 2021), and the challenge of unlocking social and economic systems tied to fossil fuels (Ivanova et al., 2018). In many cases these costs may be concentrated in particular geographies, or for particular subsets of the population (Green and Gambhir, 2019). Challenging further the question of whether mitigation leads to net costs or benefits, different policy approaches will have different welfare consequences with even small changes to policies sometimes leading to substantial changes in their socio-economic impacts (Klenert et al., 2018).

Given uncertainty around the scale and nature of both the impacts of climate change and the actions we take to address climate change, climate equity and climate justice loom large for policymakers. Analysis here shows a mechanism for the lens of climate policymaking to lead to variation in levels of climate action between communities, potentially magnifying variation in the welfare consequences of action.

If climate action priorities were set nationally, actions in aggregate led to net welfare benefits, and those benefits were at least partially excludable or rival, results here suggest that those benefits of climate action could accrue disproportionately to relatively wealthier populations. Alternatively, if climate action imposes welfare costs, then in the same scenario climate action could play a redistributive role.

Results also provide an indication of the scale of these impacts. If the three sectors that are largest on a national scale were the focus of climate action the LSOAs addressing the largest share of their emissions via these actions (90th percentile) would be addressing 85% more emissions than the LSOAs with the lowest coverage (the 10th percentile). When local priorities drive action, by contrast, LSOAs with the highest coverage (the 90th percentile), would address only 19% more emissions than those LSOAs with the lowest coverage (the 10th percentile). To the extent the welfare consequences of climate action are a function of the share of emissions a community is required to address, the differences between places would therefore be dramatically larger if priorities for action were made from a national perspective.

Since low carbon investments can generate path dependencies, especially where they are expressly designed to remake the economy (Hepburn et al., 2020; Zenghelis, 2021), these effects could compound over time. And as we are forced to confront more intractable sources of emissions and to more deeply embed climate policy in social and economic policymaking, it would be reasonable to assume the scale of welfare impacts from climate action will increase. The role of geography in shaping the way different actions are prioritised will therefore likely become more important over time, and should be considered more explicitly in academic and policy analysis.

Implications for climate policy: How place-based should climate action be?

Compared with the national government, a diverse set of regional and local actors have taken a divergent approach to climate governance in England. The national approach to climate action, characterised by a focus on specific sectors, an expanding scope of action and rising targets, is an incremental approach to climate action. The climate targets set by 168 local authorities (Howarth et al 2022*), of which nearly half are for 2030, by contrast, demand dramatic near-term society-wide reductions in emissions – a transformative approach to climate action. The national approach has been driven by market-based measures and regulatory interventions while local action has to date been driven by public-private partnerships and actions to address own-source emissions (Howarth et al 2021*).

Even the arguments for action at each level, if not in opposition, present climate action from differing perspectives. Climate action at the local and community level, often developed through place-based roadmaps (Grafakos et al., 2019; Williamson et al., 2021), supported by programs of community engagement (Howarth et al 2021), and developed with narratives that position climate change around communities, cities, homes and the countryside (Howarth and Parsons, 2021), frequently make emotional appeals foundational to their case (Aristotle’s pathos). By contrast, the national approach to climate action, with its basis in legal text and techno-economic modelling, makes logical appeals more central (Aristotle’s logos).

Analysis here provides a means of rationalising some of this divide, and for understanding its implications for climate governance. Preventing more than 1.5 degrees of warming over the coming century will require all sources GHG emissions to reach net zero, implying all sectors are prioritised and all actors take action. But between levels of emissions today and decades into the future lie a myriad of paths characterised by the different ways sectors and actions can be prioritised.

Place-based prioritisation of climate actions reduces the costs of geographic agglomeration. Taken to its limit, household or individual-level prioritisation of actions could eliminate these costs entirely. To atomise action in this way, however, would create challenges relating to coordination of, and capacity and responsibility for, climate action that are the very reason governance approaches emerge in the first place. More generally, even as polycentric modes of climate governance and action are seen to hold promise, a move away from centralised governance may have consequences for the boldness (Ciplet and Harrison, 2020; D’Alisa and Kallis, 2016; Hsu et al., 2020), pace (Ciplet and Harrison, 2020; Tabory and Ramaswami, 2020) and democratic legitimacy (Creasy et al., 2021) of climate action.

The question is therefore not whether local and distributed forms of governance should necessarily replace existing forms of governance, but how each can complement and strengthen the other. Amongst a wider set of factors to be considered, the way geographic agglomeration affects the prioritisation of actions can help to inform this discussion.

Where prioritisation is less likely to be affected, as with emissions from electricity and transport, common programs to action will be less likely to generate the forms of efficacy and equity consequences that can be associated with differences between national and local prioritisation. These sectors, not coincidentally, are also ones where there is a strategic rationale for certain actions to be nationally led: Focusing on the electricity grid, for example, enables deeper decarbonisation of transport and buildings. Wider reasons for programs of action to be developed around the characteristics of places are, of course, still critical.

Where emissions are more variable between communities and larger in scale, as with emissions from flying, nutrition, and the consumption of goods and services, greater differences between LSOAs imply a greater risk of geographic agglomeration leading to efficacy and equity consequences. Consequently, policy approaches in these areas, whether developed at the national level or by lower levels of government, may benefit from being tailored to the characteristics of places. Locally led action, in addition to offering opportunity to design actions to local contexts, may also be more effective for overcoming political and social barriers to action in these sectors (Howarth et al., 2020).

Missing in the landscape of English governance is an institution akin to a province or state that can facilitate coordination between national and local level actors. Newly developed institutions of regional governance from other parts of the UK may offer an example of how this gap can be filled. The Yorkshire and Humber Climate Commission (YHCC), established in 2021, offers support for local authorities looking to turn climate targets into strategies and action, provides a venue for local authorities to develop coordinated approaches to action, and a provide a voice for the region as it moves to accelerate climate action.

Forms of climate governance and the climate actions they lead to have well-explored consequences for the effectiveness of climate action, and public welfare. Overlooked has been the role of geography in shaping our perspective on the climate challenge we face, and in so doing generating a unique set of implications for the efficacy of action and public welfare. In this analysis we demonstrate the scale of these effects in the UK.

Results show that in aggregate the volume of emissions covered by a climate action plan will be similar whether it is developed from the top-down via a national perspective of the largest sectors, or from the bottom-up via the largest sectors in each of 33,000 Local Level Super Output Areas in England. This similarity suggests that place-based prioritisation of climate actions may, in aggregate, have a limited impact on the effectiveness of the climate action approaches developed.

A relatively small impact in aggregate, however, hides a substantial impact on the share of emissions covered in some communities. Since climate actions lead to a range of costs and benefits born both by the places that generate emissions and the economy in general, a greater variance in the share of emissions covered signals potential for the welfare effects of action to also be more variable.

These findings can inform can help to inform climate governance by adding to our understanding of the extent to which emissions from different sectors and sources may benefit from programs of action that are tailored to local places. More generally, more explicit consideration of the way different geographic scales reveal and obscure variation between places can help to develop our understanding of the roles of national and local actors in climate governance. Further research is critically needed, however, to understand how other factors, such as capacity for action, are affected by geographic agglomeration, whether these results hold for other geographies, how these results are effected by a dynamic analysis, and whether a unit of analysis that can replace the use of LSOAs provides a different results. Understanding the effect of geographic aggregation on these factors will be critical for understanding how transformation to a zero-carbon economy and society can be realised.

Competing interests: The authors declare no competing interests.

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The Effect of Geographic Agglomeration on the Efficacy and Welfare Consequences of Climate Action

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