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Flood insurance coverage can enhance financial resilience of households to changing flood risk caused by climate change. However, income inequalities imply that not all households can afford flood insurance. The uptake of flood insurance in voluntary markets may decline when flood risk increases as a result of climate change. This increase in flood risk may cause substantially higher risk-based insurance premiums, reduce the willingness to purchase flood insurance, and worsen problems with the unaffordability of coverage for low-income households. A socio-economic tipping-point can occur when the functioning of a formal flood insurance system is hampered by diminishing demand for coverage. In this study, we examine whether such a tipping-point can occur in Europe for current flood insurance systems under different trends in future flood risk caused by climate and socio-economic change. This analysis gives insights into regional inequalities concerning the ability to continue to use flood insurance as an instrument to adapt to changing flood risk. For this study, we adapt the "Dynamic Integrated Flood and Insurance" (DIFI) model by integrating new flood risk simulations in the model that enable examining impacts from various scenarios of climate and socio-economic change on flood insurance premiums and consumer demand. Our results show rising unaffordability and declining demand for flood insurance across scenarios towards 2080. Under a high climate change scenario, simulations show the occurrence of a socio-economic tipping-point in several regions, where insurance uptake almost disappears. A tipping-point and related inequalities in the ability to use flood insurance as an adaptation instrument can be mitigated by introducing reforms of flood insurance arrangements.
Quantitative detection and attribution of groundwater level variations in the Amu Darya Delta
(2020)
In the past few decades, the shrinkage of the Aral Sea is one of the biggest ecological catastrophes caused by human activity. To quantify the joint impact of both human activities and climate change on groundwater, the spatiotemporal groundwater dynamic characteristics in the Amu Darya Delta of the Aral Sea from 1999 to 2017 were analyzed, using the groundwater level, climate conditions, remote sensing data, and irrigation information. Statistics analysis was adopted to analyze the trend of groundwater variation, including intensity, periodicity, spatial structure, while the Pearson correlation analysis and principal component analysis (PCA) were used to quantify the impact of climate change and human activities on the variabilities of the groundwater level. Results reveal that the local groundwater dynamic has varied considerably. From 1999 to 2002, the groundwater level dropped from -189 cm to -350 cm. Until 2017, the groundwater level rose back to -211 cm with fluctuation. Seasonally, the fluctuation period of groundwater level and irrigation water was similar, both were about 18 months. Spatially, the groundwater level kept stable within the irrigation area and bare land but fluctuated drastically around the irrigation area. The Pearson correlation analysis reveals that the dynamic of the groundwater level is closely related to irrigation activity within the irrigation area (Nukus: -0.583), while for the place adjacent to the Aral Sea, the groundwater level is closely related to the Large Aral Sea water level (Muynak: 0.355). The results of PCA showed that the cumulative contribution rate of the first three components exceeds 85%. The study reveals that human activities have a great impact on groundwater, effective management, and the development of water resources in arid areas is an essential prerequisite for ecological protection.
In recent years, nature-based solutions are receiving increasing attention in the field of disaster risk reduction and climate change adaptation as inclusive, no regret approaches. Ecosystem-based adaptation (EbA) can mitigate the impacts of climate change, build resilience and tackle environmental degradation thereby supporting the targets set by the 2030 Agenda, the Paris Agreement and the Sendai Framework. Despite these benefits, EbA is still rarely implemented in practice. To better understand the barriers to implementation, this research examines policy-makers' perceptions of EbA, using an extended version of Protection Motivation Theory as an analytical framework. Through semi-structured interviews with policy-makers at regional and provincial level in Central Vietnam, it was found that EbA is generally considered a promising response option, mainly due to its multiple ecosystem-service benefits. The demand for EbA measures was largely driven by the perceived consequences of natural hazards and climate change. Insufficient perceived response efficacy and time-lags in effectiveness for disaster risk reduction were identified as key impediments for implementation. Pilot projects and capacity building on EbA are important means to overcome these perceptual barriers. This paper contributes to bridging the knowledge-gap on political decision-making regarding EbA and can, thereby, promote its mainstreaming into policy plans.
In a changing world, phytoplankton communities face a large variety of challenges including altered light regimes. These alterations are caused by more pronounced stratification due to rising temperatures, enhanced eutrophication, and browning of lakes. Community responses toward these effects can emerge as alterations in physiology, biomass, biochemical composition, or diversity. In this study, we addressed the combined effects of changes in light and nutrient conditions on community responses. In particular, we investigated how light intensity and variability under two nutrient conditions influence (1) fast responses such as adjustments in photosynthesis, (2) intermediate responses such as pigment adaptation and (3) slow responses such as changes in community biomass and species composition. Therefore, we exposed communities consisting of five phytoplankton species belonging to different taxonomic groups to two constant and two variable light intensity treatments combined with two levels of phosphorus supply. The tested phytoplankton communities exhibited increased fast reactions of photosynthetic processes to light variability and light intensity. The adjustment of their light harvesting mechanisms via community pigment composition was not affected by light intensity, variability, or nutrient supply. However, pigment specific effects of light intensity, light variability, and nutrient supply on the proportion of the respective pigments were detected. Biomass was positively affected by higher light intensity and nutrient concentrations while the direction of the effect of variability was modulated by light intensity. Light variability had a negative impact on biomass at low, but a positive impact at high light intensity. The effects on community composition were species specific. Generally, the proportion of green algae was higher under high light intensity, whereas the cyanobacterium performed better under low light conditions. In addition to that, the diatom and the cryptophyte performed better with high nutrient supply while the green algae as well as the cyanobacterium performed better at low nutrient conditions. This shows that light intensity, light variability, and nutrient supply interactively affect communities. Furthermore, the responses are highly species and pigment specific, thus to clarify the effects of climate change a deeper understanding of the effects of light variability and species interactions within communities is important.
In a changing world, phytoplankton communities face a large variety of challenges including altered light regimes. These alterations are caused by more pronounced stratification due to rising temperatures, enhanced eutrophication, and browning of lakes. Community responses toward these effects can emerge as alterations in physiology, biomass, biochemical composition, or diversity. In this study, we addressed the combined effects of changes in light and nutrient conditions on community responses. In particular, we investigated how light intensity and variability under two nutrient conditions influence (1) fast responses such as adjustments in photosynthesis, (2) intermediate responses such as pigment adaptation and (3) slow responses such as changes in community biomass and species composition. Therefore, we exposed communities consisting of five phytoplankton species belonging to different taxonomic groups to two constant and two variable light intensity treatments combined with two levels of phosphorus supply. The tested phytoplankton communities exhibited increased fast reactions of photosynthetic processes to light variability and light intensity. The adjustment of their light harvesting mechanisms via community pigment composition was not affected by light intensity, variability, or nutrient supply. However, pigment specific effects of light intensity, light variability, and nutrient supply on the proportion of the respective pigments were detected. Biomass was positively affected by higher light intensity and nutrient concentrations while the direction of the effect of variability was modulated by light intensity. Light variability had a negative impact on biomass at low, but a positive impact at high light intensity. The effects on community composition were species specific. Generally, the proportion of green algae was higher under high light intensity, whereas the cyanobacterium performed better under low light conditions. In addition to that, the diatom and the cryptophyte performed better with high nutrient supply while the green algae as well as the cyanobacterium performed better at low nutrient conditions. This shows that light intensity, light variability, and nutrient supply interactively affect communities. Furthermore, the responses are highly species and pigment specific, thus to clarify the effects of climate change a deeper understanding of the effects of light variability and species interactions within communities is important.
The Arctic ecosystem, a reservoir of genetic microbial diversity, represents a virtually unlimited source of microorganisms that could interact with human beings. Despite continuous exploration of Arctic habitats and description of their microbial communities, bacterial phenotypes commonly associated with pathogenicity, such as hemolytic activity, have rarely been reported. In this study, samples of snow, fresh and marine water, soil, and sediment from several habitats in the Arctic archipelago of Svalbard were collected during Summer, 2017. Bacterial isolates were obtained after incubation on oligotrophic media at different temperatures and their hemolytic potential was assessed on sheep blood agar plates. Partial (alpha) or true (beta) hemolysis was observed in 32 out of 78 bacterial species. Genes expressing cytolytic compounds, such as hemolysins, likely increase the general fitness of the producing microorganisms and confer a competitive advantage over the availability of nutrients in natural habitats. In environmental species, the nutrient-acquisition function of these compounds presumably precedes their function as toxins for mammalian erythrocytes. However, in the light of global warming, the presence of hemolytic bacteria in Arctic environments highlights the possible risks associated with these microorganisms in the event of habitat melting/destruction, ecosystem transition, and re-colonization.
Using a novel agent-based model, we study how US withdrawal might influence the political process established by the Paris Agreement, and hence the prospects for reaching the collective goal to limit warming below 2 degrees C. Our model enables us to analyze to what extent reaching this goal despite US withdrawal would place more stringent requirements on other core elements of the Paris cooperation process. We find, first, that the effect of a US withdrawal depends critically on the extent to which member countries reciprocate others' promises and contributions. Second, while the 2 degrees C goal will likely be reached only under a very small set of conditions in any event, even temporary US withdrawal will further narrow this set significantly. Reaching this goal will then require other countries to step up their ambition at the first opportunity and to comply nearly 100% with their pledges, while maintaining high confidence in the Paris Agreements institutions. Third, although a US withdrawal will first primarily affect the United States' own emissions, it will eventually prove even more detrimental to other countries' emissions.
Multi-year index-based insurance for adapting Water Utility Companies to hydrological drought
(2020)
The sustainability of water utility companies is threatened by non-stationary drivers, such as climate and anthropogenic changes. To cope with potential economic losses, instruments such as insurance are useful for planning scenarios and mitigating impacts, but data limitations and risk uncertainties affect premium estimation and, consequently, business sustainability. This research estimated the possible economic impacts of business interruption to the Sao Paulo Water Utility Company derived from hydrological drought and how this could be mitigated with an insurance scheme. Multi-year insurance (MYI) was proposed through a set of "change" drivers: the climate driver, through forcing the water evaluation and planning system (WEAP) hydrological tool; the anthropogenic driver, through water demand projections; and the economic driver, associated with recent water price policies adopted by the utility company during water scarcity periods. In our study case, the evaluated indices showed that MYI contracts that cover only longer droughts, regardless of the magnitude, offer better financial performance than contracts that cover all events (in terms of drought duration). Moreover, through MYI contracts, we demonstrate solvency for the insurance fund in the long term and an annual average actuarially fair premium close to the total expected revenue reduction.
High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987–2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987–1997, to much more positive trends across large regions of HMA during the periods 1997–2007 and 2007–2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.
We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7–14% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73–142$/tCO2 in 2020, rising to 92–181$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise.