A case study of avoiding the heat-related mortality impacts of climate change under mitigation scenarios

We compare heat-related mortality impacts for three European cities, London, Lisbon and Budapest, under five climate change policies representing different dates at which carbon dioxide (CO2) emissions peak, rates at which emissions decline, and emissions floors, and compare them with a non-mitigation business-as-usual emissions scenario, for three time periods, the 2030s, 2050s and 2080s. Under an SRES A1B business-as-usual emissions scenario and using climate projections from 21 GCMs, heat-related mortality rates (per 100,000 of the population) attributable to climate change in the 2080s are simulated to be in the range 2-6 for London, 4-50 for Lisbon and 10-24 for Budapest. Whilst the policy scenarios serve to reduce the number of heat-related deaths attributable to climate change, by up to 70% of the A1B impacts under an aggressive mitigation scenario that gives a 50% chance of avoiding a 2°C global-mean temperature rise from pre-industrial times, they do not eradicate the effects of climate change on heat-related mortality. The magnitude of avoided impacts is minor in the early 21st century but increases towards the end of the century. Importantly, the magnitude of avoided impacts is more sensitive to the year at which emissions are reduced than to the rate at which emissions are reduced. © 2011 Published by Elsevier Ltd

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2°C, followed by stabilisation to 4°C

Effects of climate change on combined labour productivity and supply: an empirical, multi-model study

Although effects on labour is one of the most tangible and attributable climate impact, our quantification of these effects is insufficient and based on weak methodologies. Partly, this gap is due to the inability to resolve different impact channels, such as changes in time allocation (labour supply) and slowdown of work (labour productivity). Explicitly resolving those in a multi-model inter-comparison framework can help to improve estimates of the effects of climate change on labour effectiveness. In this empirical, multi-model study, we used a large collection of micro-survey data aggregated to subnational regions across the world to estimate new, robust global and regional temperature and wet-bulb globe temperature exposure-response functions (ERFs) for labour supply. We then assessed the uncertainty in existing labour productivity response functions and derived an augmented mean function. Finally, we combined these two dimensions of labour into a single compound metric (effective labour effects). This combined measure allowed us to estimate the effect of future climate change on both the number of hours worked and on the productivity of workers during their working hours under 1·5°C, 2·0°C, and 3·0°C of global warming. We separately analysed low-exposure (indoors or outdoors in the shade) and high-exposure (outdoor in the sun) sectors. We found differentiated empirical regional and sectoral ERF's for labour supply. Current climate conditions already negatively affect labour effectiveness, particularly in tropical countries. Future climate change will reduce global total labour in the low-exposure sectors by 18 percentage points (range −48·8 to 5·3) under a scenario of 3·0°C warming (24·8 percentage points in the high-exposure sectors). The reductions will be 25·9 percentage points (–48·8 to 2·7) in Africa, 18·6 percentage points (–33·6 to 5·3) in Asia, and 10·4 percentage points (–35·0 to 2·6) in the Americas in the low-exposure sectors. These regional effects are projected to be substantially higher for labour outdoors in full sunlight compared with indoors (or outdoors in the shade) with the average reductions in total labour projected to be 32·8 percentage points (–66·3 to 1·6) in Africa, 25·0 percentage points (–66·3 to 7·0) in Asia, and 16·7 percentage points (–45·5 to 4·4) in the Americas. Both labour supply and productivity are projected to decrease under future climate change in most parts of the world, and particularly in tropical regions. Parts of sub-Saharan Africa, south Asia, and southeast Asia are at highest risk under future warming scenarios. The heterogeneous regional response functions suggest that it is necessary to move away from one-size-fits-all response functions to investigate the climate effect on labour. Our findings imply income and distributional consequences in terms of increased inequality and poverty, especially in low-income countries, where the labour effects are projected to be high

Exposure to waste sites and their impact on health: a panel and geospatial analysis of nationally representative data from South Africa, 2008–2015

Background Rapid population growth, urbanisation, and economic development have led to an unprecedented number of waste sites in developing countries. This challenge has become a contentious international relations issue, with an unsustainable amount of waste and its health consequences often being borne by developing countries. However, little national-level evidence is available in sub-Saharan Africa to quantify the association between exposure to waste sites and health. Methods We used panel data from the South African National Income Dynamics Study (SA-NIDS) to investigate the association between exposure to waste sites and asthma, tuberculosis, diabetes, and depression. The SA-NIDS is a panel survey of a nationally representative sample in South Africa, which includes data reporting the health status of 32 255 individuals between 2008 and 2015. The study exposure was distance of households, in km, to the nearest waste site, derived from waste site geospatial locations from the South Africa Waste Information System. Findings We observed a substantial increase in exposure of households to waste sites between 2008 and 2015. The median distance between study households and waste sites decreased from 68·3 km (IQR 31·1–111·7) to 8·5 km (3·0–23·7). Residing within 5 km of a waste site was significantly associated with asthma (adjusted relative risk 1·41; 95% CI 1·20–1·64), tuberculosis (1·18; 1·02–1·36), diabetes (1·25; 1·05–1·49), and depression (1·08; 1·03–1·14). The association persisted even after controlling for multiple socioeconomic factors. Interpretation We identified multiple adverse health outcomes in individuals living close to waste sites at a national level in South Africa, suggesting the need to reduce the number and size of waste sites to diminish harmful effects on health and wellbeing for communities living in close proximity to such sites. Funding South African Medical Research Council, South African National Treasury, and Wellcome Trust

Use of satellite remote sensing to validate reservoir operations in global hydrological models: a case study from the CONUS

Although river discharge simulations from global hydrological models have undergone extensive validation, there has been less validation of reservoir operations, primarily because of limited observational data. However, recent advancements in satellite remote sensing technology have facilitated the collection of valuable data regarding water surface area and elevation, thereby providing the ability to validate reservoir storage. In this study, we sought to establish a methodology for validation and intercomparison of reservoir storage within global hydrological model simulations using satellite-derived data. Accordingly, we chose two satellite-derived reservoir operation products, DAHITI and GRSAD, to create monthly time series storage data for seven reservoirs in the contiguous United States (CONUS) , with access to long-term ground truth data (the total catchment area accounts for about 9 % of CONUS). We assessed two global hydrological models that participated in the Inter Sectoral Model Intercomparison Project (ISIMIP) Phase 3 project, H08 and WaterGAP2, with three distinct forcing datasets: GSWP3-W5E5 (GW), CR20v3-W5E5 (CW), and CR20v3-ERA5 (CE). The results indicated that WaterGAP2 generally outperforms H08; the CW forcing dataset demonstrated superior results compared with GW and CE; the DAHITI showed better consistency with ground observations than GRSAD if temporal coverage is sufficient. Overall, our study emphasizes the potential uses of satellite remote sensing data in reservoir operations validation and underscores the importance of normalization and decomposition techniques for improved validation efficacy. The results highlight the relative performances of different hydrological models and forcing datasets, yielding insights concerning future advancements in reservoir simulation and operational studies

UK National Ecosystem Assessment Follow-on. Work package 7: Operationalising scenarios in the UK National Ecosystem Assessment Follow-on

Summary Study aims and approach An aim of the UK NEA Follow-on (UK NEAFO) is to develop and communicate the evidence base of the UK NEA and make it relevant to decision and policy making. It also provides an important opportunity for those working on scenario methods and concepts to scrutinise the role of futures thinking in the management of ecosystem services and so develop their effectiveness as decision support tools. In this study we have therefore asked: how can the UK NEA scenarios help us to understand, manage and communicate the consequences of changes in ecosystem services across all scales? There are many different understandings about what scenarios are, and what they should be used for. To clarify the issues surrounding the role of scenarios, we have approached this work from two angles. We have firstly looked at the way the storylines can support decision making processes. Secondly, we have looked at the content of the scenarios themselves and explored how through the use of models the UK NEA scenarios as products might be refined to enhance their value as analytical tools. Scenarios in Action We used the opportunity of a series of meetings with stakeholders to develop the UK NEA scenarios from a process perspective. These meetings took various forms, but throughout the main aim was to find out whether people found the scenarios sufficiently believable, challenging and relevant. In workshops organised by the scenario team in Leeds, Edinburgh and Belfast, we worked with participants on a series of tasks designed to help them immerse themselves in the scenarios and reflect on them critically. While those we worked with had many comments about the scenarios in detail, the evidence we collected from these meetings suggests that the majority of people found the scenarios to be plausible and the projections consistent. The majority also agreed with the proposition that the suite of scenarios as a whole addressed a relevant ranges of issues. We explored with the workshop participants several ways in which the storylines could be enriched, by: developing the narrative about the way people might live in the different scenario worlds; developing time-lines for the scenarios; thinking more deeply about regional and local differences; and, exploring how the scenarios would frustrate or facilitate the embedding of the ecosystem approach in decision making. We found that while all of these elements had value in terms of stimulating discussion and understanding of the scenarios, they were not needed in order to address deficiencies in the original storylines in terms of plausibility or credibility. The evidence we collected therefore suggests that the existing narratives are probably sufficient as an entry point for discussions about the future of ecosystem services in the UK. What was apparent from the observations that we made in the workshops was that it would probably be a mistake to ‘over-engineer’ or ‘over-specify’ the narratives because there needs to be room for discussion and probing. We were struck how people took the existing scenarios and found new features and ideas in them than had not been identified by in the original work. For example, in one session National Security, with its emphasis on resource efficiency, was found to be ‘greener’ than it initially looks. In another Local Stewardship was discovered to need some degree of central control and regulation to work efficiently. These kinds of discussion are evidence of the reflection, deliberation and social learning that can be promoted by using the UK NEA scenarios. UK NEAFO Work Package 7: Operationalising scenarios 7 In the workshop we organised in Belfast we found that the presentation of the scenarios could be tailored to a specific region (i.e. Northern Ireland) and, through area-specific breakout groups during the workshop, to specific localities within it. However, our experiences here emphasised the need for considerable preparation, consultation with the stakeholder community, and changing of the workshop format to make the scenarios intelligible and engaging to local stakeholders. Work on the use of the scenarios in a more explicit decision support role will be reported via the work on response options (WP8), which considered how they could be used to ‘stress-test’ policy response options. The experience gained from the work undertaken in the early stages of UK NEAFO was that the scenarios appeared to provide a suitable platform for the work, but that the stresstesting methodology needed to be refined. During the follow-on we have also interviewed policy leads in Defra, for example, to gain a better picture of policy needs, and the way scenarios might usefully serve them. Apart from the challenge of ‘relevance’ it is clear that the time needed for people to work with scenarios probably means that they are less useful to policy customers in the context of their everyday work but can be useful at a very broad and strategic level. However, there is clearly an opportunity for scenarios to be used more extensively through commissioned work. The importance of commissioned work has been emphasised during the follow-on phase by invitations to observe the work of the CAMERAS1 work in Scotland, and the Noise Study being undertaken for Defra. Both are actively using the UK NEA scenarios. The outcomes of these on-going studies will be reported elsewhere by others. Nevertheless, even though these projects are at a preliminary stage they help us better understand how scenarios can be used to communicate the consequences of changes in ecosystem services to different groups and individuals. Scenarios as products: developing the model base The UK NEA scenarios were initially used to make both qualitative and quantitative projections. The quantitative work mainly involved modelling how land cover would change under the different scenarios (Haines-Young et al. 2011). Although these data were used to make an analysis of the changes in marginal economic values for some ecosystem services during the initial phase of the UK NEA, they have not been fully exploited. At the time it was recognised that there were many gaps in our understanding of the links between land cover and ecosystem services; UK NEAFO has provided the opportunity to address some of these deficiencies. Thus in the follow-on work we have sought to extend the range of models that can be used to explore the UK NEA scenarios. The modelling work has not sought to change the scenarios fundamentally, but to enrich the insights that can be derived from exploring the differences between them in a systematic, and quantitative way. The goal, has been to extend the analysis that can be built up around the narratives and hence enrich the scenarios as ‘products’. Four topic areas were selected as the focus for this work: flood and drought risk (based on an analysis of changes in river flows), biodiversity (farmland birds), marine and cultural ecosystem services. Catchment modelling We looked at the effects of land-use change on river flows under each of the UK NEA scenarios. We modelled hydrological discharge within 34 UK catchments and calculated four hydrological indicators for each catchment: average annual discharge, flood hazard, and Q5 and Q95 (measures of the magnitude of unusually high (Q5) and unusually low (Q95) flows). For our flood hazard indicator we calculated the interval between floods of a size currently occurring every 30 years. Although we kept climate constant in the models, as we wanted to isolate the effects of land cover change, we ran them for both the high and low climate change land cover variants for each scenario. 1 A Coordinated Agenda for Marine, Environment and Rural Affairs Science, 2011-2016. http://www.scotland.gov.uk/Topics/Research/About/EBAR/CAMERASsite In general, the ‘green’ scenarios, Nature@Work and Green and Pleasant Land, as well as National Security, were associated with lower flows than currently occur (when measured using any of the four indicators). However, for a given scenario there was a great deal of variability between catchments in terms of the size and statistical significance of the differences. The magnitude of change across all scenarios and catchments ranged from -13% to 6% for average annual discharge, -14 to 7% for Q5, -24 to 27 % for Q95 and -16 to 36 years for flood hazard. Differences were particularly evident between Nature@Work and World Markets, with the latter associated with higher flows than occur currently, and the majority of the statistically significant increased flows. Some catchments showed significant changes that were different in sign between these two scenarios. Taken together, our results indicate that that in managing change a balance needs to be struck between alleviating the likelihoods of increased drought and increased flooding, depending on the likely effects of these phenomena in the catchment. Farmland birds We looked at the relationship between land use data produced during the first phase of the UK NEA and models of farmland bird populations, in 1kmx1km squares covered by the Breeding Bird Survey (BBS) and Winter Farmland Bird Survey (WFBS). We used Functional Space Models to estimate the annual population growth rate under each scenario of each of the 19 farmland bird species used to calculate the farmland bird index (Gregory et al. 2004). We used this to look at the relationship between land use under the scenarios and: i) the average population growth rate for all 19 species, and ii) a subset of 11 species showing declining population trends under current land use. Overall we found that land use change across the scenarios had relatively little impact. However, the only statistically significant change was for declining species under Green and Pleasant Land, where population growth rates became significantly more negative. We used Mechanistic Models to estimate the number of over-winter ‘bird-days’ for two types of seed-eating farmland birds, a yellowhammer-type and linnet-type These species were chosen because they differ in their food preferences with respect to cereal, oil and weed seeds, but between them are representative of the diversity of seed-eating farmland birds as a whole. We found a significant decline in the ecological value of lowland agricultural areas for these species across all UK NEA scenarios, but the greatest impact was for scenarios with the highest monetised values for ecosystem services, as measured by the first phase of the UK NEA (Nature@Work, Green and Pleasant Land). This appears to be due to the fact that, compared with the baseline, the area of arable crops declines most sharply under these scenarios, due partly to changes in land use but also because of conversion of arable land to other habitats important for ecosystem services (e.g. woodland). Taken together these results imply a trade-off between overall value for ecosystem services and conservation of farmland birds, and highlight the need to consider the specific impacts of land use change on biodiversity, alongside other ecosystem services. Marine ecosystem services Only a limited attempt was made to model marine ecosystem services during the first phase of the UK NEA. In the follow-on we have conducted preliminary work to produce spatially explicit models for three important marine ecosystem services: fisheries landings, aquaculture production and carbon sequestration. We made comparisons between baseline data and time slices for 2015, 2030 UK NEAFO Work Package 7: Operationalising scenarios 9 and 2060 under four of the UK NEA scenarios that were considered most relevant for the sector, and mapped these across UK territorial waters. There is a high degree of uncertainty associated with the models, mainly due to a lack of suitable data and poor knowledge of the drivers of change. In many cases, in the absence of robust quantitative models, we needed to take the qualitative descriptions of the UK NEA scenarios and combine these with expert knowledge to estimate changes in the three types of ecosystem service. We estimated that in three of the four scenarios: Nature@Work, Local Stewardship and National Security, fisheries landings would be, by 2060 only slightly lower or at higher levels than they are today. Under World Markets, however, projected landings would decline significantly by 2060, due to a lack of regulation combined with high levels of investment from private capital. In the light of this, it was interesting that aquaculture was at higher levels under World Markets than under any of the other scenarios, although all of them showed higher levels than the baseline. This was because under this scenario more investment capital would be available to invest in fish farms. We believe that carbon sequestration would be most likely to be impacted by the World Markets and Natural Security, due to higher CO2 emissions causing an increase in ocean acidification. Our results, although tentative, mark a significant first step in attempts to map and project the impact of possible future change on marine ecosystem services. Cultural Ecosystem Services In the first phase of the UK NEA, the relationship between the drivers of change and cultural ecosystem services (CES) was mainly explored through the impact they had on land cover. For UK NEAFO, we additionally used the Monitor of Engagement for the Natural Environment (MENE) dataset. We examined how the UK NEA scenarios can be used as a framework to explore the relationship between the supply of cultural spaces in the landscape and peoples preferences for different types of natural spaces and practices in them. We have developed a Bayesian Belief Network (BBN) that allows users to explore these relationships interactively and look at the potential impacts of changes socio-demographic structure of the kind described by the UK NEA scenarios. Our spatial analysis of the MENE data showed that people tend to select locations with higher woodland cover than the average for the surroundings, when they travel intermediate distances from their home, but that this tendency declines when they travel longer distances. Woodland cover is projected to double under both Nature@Work and Green and Pleasant Land, and both provide more opportunities to visit woodland close to home than under scenarios such as World Markets. However, our analysis shows that on the basis of the current geography of people and woodlands, the way planting is targeting under Green and Pleasant Land has the potential to deliver greater joint benefits from biodiversity change and cultural ecosystem services than Nature@Work. The BBN we have developed using the HUGIN Expert software allows the relationships within the MENE data to be explored interactively; it is hosted on a prototype website that is open to the wider community. By examining the relationships between socio-demographic characteristics of the MENE respondents, the types of natural spaces they visit and the activities they do in them, this BBN tool allows users to explore the impacts of possible future change on the supply and demand of CES. Conclusion How can plausible future scenarios help understand, manage and communicate the consequences of changes in ecosystem services across all scales? In this work we have shown that they can be used to promote understanding by the deliberative processes that they engender. The UK NEA scenarios appear to be sufficiently rich and comprehensive to support debate across a wide range of topic areas relevant to current policy concerns. The scenarios can also help understanding by providing a framework in which current models can be applied and the outcome used both to test the plausibility of the scenarios themselves and to deepen the insights that can be derived from them. These analytical ‘scenario products’ can be equally important both in terms of deepening our understanding of the assumptions on which the scenarios are built and in stimulating debate about their implications. We have shown that the distinction between the ‘process’ and ‘product’ dimensions of scenario thinking is a useful one, given the many ways scenarios can be used. The distinction clarifies some of the different purposes and problems that scenarios work seeks to address. However, our work also demonstrates that both components have their strengths, and neither can be taken isolation. If we are to use scenarios to understand, manage and communicate the consequences of changes in ecosystem services across different scales and in different contexts, then targeted analytical studies developed within the qualitative framework of the UK NEA scenarios, can enrich our understanding of today’s issues and how we might respond to them

Adaptation to climate change: a comparative analysis of modelling methods for heat-related mortality

Background: Multiple methods are employed for modelling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known on the relative sensitivity of impacts to “adaptation uncertainty” (i.e. the inclusion/exclusion of adaptation modelling), relative to using multiple climate models and emissions scenarios. Objectives: (1) Compare the range in projected impacts that arises from using different adaptation modelling methods; (2) compare the range in impacts that arises from adaptation uncertainty to ranges from using multiple climate models and emissions scenarios; (3) recommend modelling method(s) to use in future impact assessments. Methods: We estimated impacts for 2070-2099, for 14 European cities, applying six different methods for modelling adaptation; also with climate projections from five climate models, run under two emissions scenarios to explore the relative effects of climate modelling and emissions uncertainty. Results: The range of the difference (%) in impacts between including and excluding adaptation, irrespective of climate modelling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modelling and emissions uncertainty. Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modelling. We recommend absolute threshold shifts and reductions in slope

International perceptions of urban blue-green infrastructure: A comparison across four cities

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Blue-Green infrastructure (BGI) is recognised internationally as an approach for managing urban water challenges while enhancing society and the environment through the provision of multiple co-benefits. This research employed an online survey to investigate the perceptions of BGI held by professional stakeholders in four cities with established BGI programs: Newcastle (UK), Ningbo (China), Portland (Oregon USA), and Rotterdam (The Netherlands) (64 respondents). The results show that challenges associated with having too much water (e.g., pluvial and fluvial flood risk, water quality deterioration) are driving urban water management agendas. Perceptions of governance drivers for BGI implementation, BGI leaders, and strategies for improving BGI uptake, are markedly different in the four cities reflecting the varied local, regional and national responsibilities for BGI implementation. In addition to managing urban water, BGI is universally valued for its positive impact on residents’ quality of life; however, a transformative change in policy and practice towards truly multifunctional infrastructure is needed to optimise the delivery of multiple BGI benefits to address each city’s priorities and strategic objectives. Changes needed to improve BGI uptake, e.g., increasing the awareness of policy-makers to multifunctional BGI, has international relevance for other cities on their journeys to sustainable blue-green futures