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Seed dispersal plays an important role in population dynamics in agricultural ecosystems, but the effects of surrounding vegetation height on seed dispersal and population connectivity on the landscape scale have rarely been studied. Understanding the effects of surrounding vegetation height on seed dispersal will provide important information for land-use management in agricultural landscapes to prevent the spread of undesired weeds or enhance functional connectivity. We used two model species, Phragmites australis and Typha latifolia, growing in small natural ponds known as kettle holes, in an agricultural landscape to evaluate the effects of surrounding vegetation height on wind dispersal and population connectivity between kettle holes. Seed dispersal distance and the probability of long-distance dispersal (LDD) were simulated with the mechanistic WALD model under three scenarios of "low", "dynamic" and "high" surrounding vegetation height. Connectivity between the origin and target kettle holes was quantified with a connectivity index adapted from Hanski and Thomas (1994). Our results show that mean seed dispersal distance decreases with the height of surrounding matrix vegetation, but the probability of long-distance dispersal (LDD) increases with vegetation height. This indicates an important vegetation-based trade-off between mean dispersal distance and LDD, which has an impact on connectivity. Matrix vegetation height has a negative effect on mean seed dispersal distance but a positive effect on the probability of LDD. This positive effect and its impact on connectivity provide novel insights into landscape level (meta-)population and community dynamics - a change in matrix vegetation height by land-use or climatic changes could strongly affect the spread and connectivity of wind-dispersed plants. The opposite effect of vegetation height on mean seed dispersal distance and the probability of LDD should therefore be considered in management and analyses of future land-use and climate change effects.
Scaling agriculture to the globally rising population demands new approaches for future crop production such as multilayer and multitrophic indoor farming. Moreover, there is a current trend towards sustainable local solutions for aquaculture and saline agriculture. In this context, halophytes are becoming increasingly important for research and the food industry. As Salicornia europaea is a highly salt-tolerant obligate halophyte that can be used as a food crop, indoor cultivation with saline water is of particular interest. Therefore, finding a sustainable alternative to the use of seawater in non-coastal regions is crucial. Our goal was to determine whether natural brines, which are widely distributed and often available in inland areas, provide an alternative water source for the cultivation of saline organisms. This case study investigated the potential use of natural brines for the production of S. europaea. In the control group, which reflects the optimal growth conditions, fresh weight was increased, but there was no significant difference between the treatment groups comparing natural brines with artificial sea water. A similar pattern was observed for carotenoids and chlorophylls. Individual components showed significant differences. However, within treatments, there were mostly no changes. In summary, we showed that the influence of the different chloride concentrations was higher than the salt composition. Moreover, nutrient-enriched natural brine was demonstrated to be a suitable alternative for cultivation of S. europaea in terms of yield and nutritional quality. Thus, the present study provides the first evidence for the future potential of natural brine waters for the further development of aquaculture systems and saline agriculture in inland regions.
Stochastic modeling of precipitation for estimation of hydrological extremes is an important element of flood risk assessment and management. The spatially consistent estimation of rainfall fields and their temporal variability remains challenging and is addressed by various stochastic weather generators.
In this study, two types of weather generators are evaluated against observed data and benchmarked regarding their ability to simulate spatio-temporal precipitation fields in the Rhine catchment. A multi-site station-based weather generator uses an auto-regressive model and estimates the spatial correlation structure between stations. Another weather generator is raster-based and uses the nearest-neighbor resampling technique for reshuffling daily patterns while preserving the correlation structure between the observations.
Both weather generators perform well and are comparable at the point (station) scale with regards to daily mean and 99.9th percentile precipitation as well as concerning wet/dry frequencies and transition probabilities. The areal extreme precipitation at the sub-basin scale is however overestimated in the station-based weather generator due to an overestimation of the correlation structure between individual stations. The auto-regressive model tends to generate larger rainfall fields in space for extreme precipitation than observed, particularly in summer. The weather generator based on nearest-neighbor resampling reproduces the observed daily and multiday (5, 10 and 20) extreme events in a similar magnitude. Improvements in performance regarding wet frequencies and transition probabilities are recommended for both models.
Mehrphasige DNAPL-Pools zählen zu den häufigsten Ursachen für Grundwasserkontaminationen und sind bekannt für ihre Langlebigkeit. Obwohl Untersuchungen bereits gezeigt haben, dass die Phasen sich in ihrer Wasserlöslichkeit gegenseitig beeinflussen, werden diese Interaktionen von bisherigen Modellen vernachlässigt. Aus diesem Grund wurde ein semi-analytisches Berechnungsmodell entwickelt, welches die Poolzusammensetzung als zeitlich variabel behandelt. Basierend auf dem Raoult’schen Gesetz werden für jede Komponente Molanteil, effektive Wasserlöslichkeit und schließlich der Schadstoffaustrag infolge Advektion, Dispersion und Diffusion bestimmt. Die Ergebnisse unterscheiden sich deutlich von Studien an einphasigen Pools. So wird gezeigt, dass Schadstofffrachten über die Zeit sowohl zu- als auch abnehmen können und dass ohne Berücksichtigung des Raoult’schen Gesetzes sowohl die Langlebigkeit von DNAPL-Pools als auch die Dauer bis zur Unterschreitung von Grenzwerten teils deutlich unterschätzt wird. Eine Sensitivitätsanalyse zeigt zudem, dass schwer lösliche Nebenbestandteile nicht vernachlässigt werden dürfen, leicht lösliche hingegen schon.
Less is more!
(2021)
Enhancing consumer satisfaction and well-being is an important objective of companies, retailers and public policy makers. In the current debate on climate change, a consistent theme is that consumers in developed countries must learn to consume less. The present study (based on representative data sets from the US, N = 1,017, and Germany, N = 1030) addresses these issues by using a scenario-based experiment to analyze how satisfied voluntary simplifiers (people who voluntarily abstain from consumption) are with their purchase decisions in the case of a muesli brand. The research question is whether people who follow a sustainable, simple lifestyle are more satisfied with their daily consumption choices than people who have a more consumerist lifestyle. If so, it would be easier for many people to change their lifestyles and consume less. In addition, this scenario experiment manipulates consumer empowerment and decision complexity since both factors are supposed to influence purchase satisfaction. The results are consistent across both countries and indicate that voluntary simplifiers experience a higher level of purchasing satisfaction than non-simplifiers, whereby empowerment and decision complexity play different roles.
Climate science provides strong evidence of the necessity of limiting global warming to 1.5 °C, in line with the Paris Climate Agreement. The IPCC 1.5 °C special report (SR1.5) presents 414 emissions scenarios modelled for the report, of which around 50 are classified as '1.5 °C scenarios', with no or low temperature overshoot. These emission scenarios differ in their reliance on individual mitigation levers, including reduction of global energy demand, decarbonisation of energy production, development of land-management systems, and the pace and scale of deploying carbon dioxide removal (CDR) technologies. The reliance of 1.5 °C scenarios on these levers needs to be critically assessed in light of the potentials of the relevant technologies and roll-out plans. We use a set of five parameters to bundle and characterise the mitigation levers employed in the SR1.5 1.5 °C scenarios. For each of these levers, we draw on the literature to define 'medium' and 'high' upper bounds that delineate between their 'reasonable', 'challenging' and 'speculative' use by mid century. We do not find any 1.5 °C scenarios that stay within all medium upper bounds on the five mitigation levers. Scenarios most frequently 'over use' CDR with geological storage as a mitigation lever, whilst reductions of energy demand and carbon intensity of energy production are 'over used' less frequently. If we allow mitigation levers to be employed up to our high upper bounds, we are left with 22 of the SR1.5 1.5 °C scenarios with no or low overshoot. The scenarios that fulfil these criteria are characterised by greater coverage of the available mitigation levers than those scenarios that exceed at least one of the high upper bounds. When excluding the two scenarios that exceed the SR1.5 carbon budget for limiting global warming to 1.5 °C, this subset of 1.5 °C scenarios shows a range of 15–22 Gt CO2 (16–22 Gt CO2 interquartile range) for emissions in 2030. For the year of reaching net zero CO2 emissions the range is 2039–2061 (2049–2057 interquartile range).
Leaching zones within potash seams generally represent a significant risk to subsurface mining operations and the construction of technical caverns in salt rocks, but their temporal and spatial formation has been investigated only rudimentarily to date. To the knowledge of the authors, current reactive transport simulation implementations are not capable to address hydraulic-chemical interactions within potash salt. For this reason, a reactive transport model has been developed and complemented by an innovative approach to calculate the interchange of minerals and solution at the water-rock interface. Using this model, a scenario analysis was carried out based on a carnallite-bearing potash seam. The results show that the evolution of leaching zones depends on the mineral composition and dissolution rate of the original salt rock, and that the formation can be classified by the dimensionless parameters of Peclet (Pe) and Damkohler (Da). For Pe > 2 and Da > 1, a funnel-shaped leaching zone is formed, otherwise the dissolution front is planar. Additionally, Da > 1 results in the formation of a sylvinitic zone and a flow barrier. Most scenarios represent hybrid forms of these cases. The simulated shapes and mineralogies are confirmed by literature data and can be used to assess the hazard potential.
Tropical cyclones range among the costliest disasters on Earth. Their economic repercussions along the supply and trade network also affect remote economies that are not directly affected. We here simulate possible global repercussions on consumption for the example case of Hurricane Sandy in the US (2012) using the shock-propagation model Acclimate. The modeled shock yields a global three-phase ripple: an initial production demand reduction and associated consumption price decrease, followed by a supply shortage with increasing prices, and finally a recovery phase. Regions with strong trade relations to the US experience strong magnitudes of the ripple. A dominating demand reduction or supply shortage leads to overall consumption gains or losses of a region, respectively. While finding these repercussions in historic data is challenging due to strong volatility of economic interactions, numerical models like ours can help to identify them by approaching the problem from an exploratory angle, isolating the effect of interest. For this, our model simulates the economic interactions of over 7000 regional economic sectors, interlinked through about 1.8 million trade relations. Under global warming, the wave-like structures of the economic response to major hurricanes like the one simulated here are likely to intensify and potentially overlap with other weather extremes.
Energy system developments and investments in the decisive decade for the Paris Agreement goals
(2021)
The Paris Agreement does not only stipulate to limit the global average temperature increase to well below 2 °C, it also calls for 'making finance flows consistent with a pathway towards low greenhouse gas emissions'. Consequently, there is an urgent need to understand the implications of climate targets for energy systems and quantify the associated investment requirements in the coming decade. A meaningful analysis must however consider the near-term mitigation requirements to avoid the overshoot of a temperature goal. It must also include the recently observed fast technological progress in key mitigation options. Here, we use a new and unique scenario ensemble that limit peak warming by construction and that stems from seven up-to-date integrated assessment models. This allows us to study the near-term implications of different limits to peak temperature increase under a consistent and up-to-date set of assumptions. We find that ambitious immediate action allows for limiting median warming outcomes to well below 2 °C in all models. By contrast, current nationally determined contributions for 2030 would add around 0.2 °C of peak warming, leading to an unavoidable transgression of 1.5 °C in all models, and 2 °C in some. In contrast to the incremental changes as foreseen by current plans, ambitious peak warming targets require decisive emission cuts until 2030, with the most substantial contribution to decarbonization coming from the power sector. Therefore, investments into low-carbon power generation need to increase beyond current levels to meet the Paris goals, especially for solar and wind technologies and related system enhancements for electricity transmission, distribution and storage. Estimates on absolute investment levels, up-scaling of other low-carbon power generation technologies and investment shares in less ambitious scenarios vary considerably across models. In scenarios limiting peak warming to below 2 °C, while coal is phased out quickly, oil and gas are still being used significantly until 2030, albeit at lower than current levels. This requires continued investments into existing oil and gas infrastructure, but investments into new fields in such scenarios might not be needed. The results show that credible and effective policy action is essential for ensuring efficient allocation of investments aligned with medium-term climate targets.