Beschreibung: Cyanobacteria are major contributors to algal blooms in inland waters, threatening ecosystem function and water uses, especially when toxin-producing strains dominate. Here, we examine 140 hyperspectral (HS) images of five representatives of the widespread, potentially toxin-producing and bloom-forming genera Microcystis, Planktothrix, Aphanizomenon, Chrysosporum and Dolichospermum, to determine the potential of utilizing visible and near-infrared (VIS/NIR) reflectance for their discrimination. Cultures were grown under various light and nutrient conditions to induce a wide range of pigment and spectral variability, mimicking variations potentially found in natural environments. Importantly, we assumed a simplified scenario where all spectral variability was derived from cyanobacteria. Throughout the cyanobacterial life cycle, multiple HS images were acquired along with extractions of chlorophyll a and phycocyanin. Images were calibrated and average spectra from the region of interest were extracted using k-means algorithm. The spectral data were pre-processed with seven methods for subsequent integration into Random Forest models, whose performances were evaluated with different metrics on the training, validation and testing sets. Successful classification rates close to 90 % were achieved using either the first or second derivative along with spectral smoothing, identifying important wavelengths in both the VIS and NIR. Microcystis and Chrysosporum were the genera achieving the highest accuracy (〉95 %), followed by Planktothrix (79 %), and finally Dolichospermum and Aphanizomenon (〉50 %). The potential of HS imagery to discriminate among toxic cyanobacteria is discussed in the context of advanced monitoring, aiming to enhance remote sensing capabilities and risk predictions for water bodies affected by cyanobacterial harmful algal blooms.

Beschreibung: Buildings constitute one of the main GHG emitting sectors, and energy efficiency is a key lever to reduce emissions in the sector. Global climate policy has so far mostly focused on economy-wide emissions. However, emission reduction actions are ultimately sectoral, and opportunities and barriers to achieving emission reductions vary strongly among sectors. This article therefore seeks to analyse to what extent more targeted global governance may help to leverage mitigation enablers and overcome barriers to energy efficiency in buildings. To this end, the article first synthesises existing literature on mitigation enablers and barriers as well as existing literature on how global governance may help address these barriers ("governance potential"). On this basis, the article analyses to what extent this governance potential has already been activated by existing activities of international institutions. Finally, the article discusses how identified governance gaps could be closed. The analysis finds that despite the local characteristics of the sector, global governance has a number of levers at its disposal that could be used to promote emission reductions via energy efficiency. In practice, however, lacking attention to energy efficiency in buildings at national level is mirrored at the international level. Recently, though, a number of coalitions demanding stronger action have emerged. Such frontrunners could work through like-minded coalitions and at the same time try to improve conditions for cooperation in the climate regime and other existing institutions.

Beschreibung: Earth system science is an interdisciplinary effort to understand the fundamentals and interactions of environmental processes. Interdisciplinary research is challenging since it demands the integration of scientific schemes and practices from different research fields into a collaborative work environment. This paper introduces the framework F4ESS that supports this integration. F4ESS provides methods and technologies that facilitate the development of integrative work environments for Earth system science. F4ESS enables scientists a) to outline structured and summarized descriptions of scientific procedures to facilitate communication and synthesis, b) to combine a large variety of distributed data analysis software into seamless data analysis chains and workflows, c) to visually combine and interactively explore the manifold spatiotemporal data and results to support understanding and knowledge creation. The F4ESS methods and technologies are generic and can be applied in various scientific fields. We discuss F4ESS in the context of the interdisciplinary investigation of flood events.

Beschreibung: The project "Plastic Credits - Financing the Transition to the Global Circular Economy" supports the implementation of a waste management structure in India's rural regions. By that it aims to improve the current waste collection and treatment structures in the pilot regions Goa, Maharashtra, and Kerala. Herein, the project focuses on low value plastics (LVP), and especially multi-layer plastics (MLP), that have no market value. In order to analyze the environmental impacts of the project, an Environmental Impact Assessment (EIA) was conducted. The considered environmental components comprise: greenhouse gas emissions, usage of primary resources, impacts on marine and terrestrial wildlife, standard of living, and economic costs.

Beschreibung: The Combination Service for Time-variable Gravity fields (COST-G) operationally provides combinations of monthly Earth gravity field models derived from observations of the microwave ranging instrument of the GRACE Follow-on (GRACE-FO) satellite mission, applying the quality control and combination methodology originally developed by the Horizon 2020 project European Gravity Service for Improved Emergency Management for the data of the GRACE satellites. In the frame of the follow-up Horizon 2020 project Global Gravity-based Groundwater Product (G3P), the GRACE-FO combination is used to derive global grids of groundwater storage anomalies. To meet the user requirements and achieve optimal signal-to-noise ratio, the combination has been further developed and extended to incorporate: • new time-series based on the alternative accelerometer transplant product generated in the frame of the project by the Institute of Geodesy at the Graz University of Technology, which specifically improves the estimation of the C30 coefficient and also reduces the noise at medium to short wavelengths, and • the new time-series AIUB–GRACE-FO–RL02 of monthly GRACE-FO gravity fields, which is derived at the Astronomical Institute of the University of Bern by applying empirical noise modelling techniques. The COST-G quality control confirms the consistency of the contributing GRACE-FO time-series concerning the signal amplitude of seasonal hydrology in large river basins and the secular mass change in polar regions, but it also indicates rather diverse noise characteristics. The difference in the noise levels is taken into account in the combination process by relative weights derived by variance component estimation on the solution level. The weights are expected to be inverse proportional to the noise levels of the individual gravity field solutions. However, this expectation is violated when applying the weighting scheme as developed for the GRACE combination. The reason is found in the high-order coefficients of the gravity field, which are poorly determined from the low–low range-rate observations due to the observation geometry and suffer from aliasing due to the malfunctioning accelerometer onboard one of the GRACE-FO satellites. Hence, for the final G3P-combination a revised weighting scheme is applied where the gravity field coefficients beyond order 60 are excluded from the determination of the weights. The quality of the combined gravity fields is assessed by comparison of the noise content and the signal-to-noise ratio with the individual time-series. Independent validation is provided by the COST-G validation centre at the GFZ German Research Centre for Geosciences, where orbit fits of the low-flying Gravity and steady-state Ocean Circulation Explorer satellite are performed that confirm the high quality of the combined GRACE-FO gravity fields. By the end of the G3P project, the new combination scheme is implemented by COST-G as the new COST-G–GRACE-FO–RL02 and continued to be used for the operational GRACE-FO combination.

Beschreibung: This report documents the drilling operations of the Early Jurassic Earth System and Timescale scientific drilling project (JET, ICDP Project: 5065). The wells 5065_1_A, 5065_1_B, 5065_1_A were drilled in 2019-2021 with the support of the International Continental Scientific Drilling Program (ICDP) and the UK Natural Environment Research Council (NERC). Alternatively, the site is known as Prees 2 (Holes A – C). Prees 1 was a nearby hydrocarbon exploration well drilled by Trend Petroleum in 1972–1973. The project aims to construct a fully integrated and astronomically calibrated timescale for the Early Jurassic, a time in Earth history during which important physical, chemical, and biological elements of the modern Earth system were initiated. The JET drilling campaign supplements the earlier Llanbedr (Mochras Farm) borehole (1967 – 1969) in NW Wales – usually known as Mo-chras – which recovered a 1.3 km thick succession comprising the Rhaetian (Upper Triassic), Hettangian, Sinemurian, Pliensbachian and Toarcian (Lower Jurassic) stages (Woodland, 1971; Hesselbo et al., 2013). Using the combined framework of Prees and Mochras, internal and ex-ternal forcing factors on the Earth system will be documented and quantified for major palaeo-environmental events, such as the Late Triassic mass extinction and the Early Toarcian Oceanic Anoxic Event, and for the more stable ‘background’ state.

Beschreibung: Energy performance contracting (EPC) as a market instrument has been effective in promoting energy efficiency worldwide, but it has encountered many insurmountable obstacles in rural energy management. In this study, based on the characteristics of energy management in rural areas, three EPC modes are designed and tested in 24,000 rural households. The test results show that two adapted EPC modes of local government involvement and energy payment directly from the national grid can effectively overcome the barriers encountered in the traditional EPC modes and work well under the economic and social environmental conditions in rural areas. The key to the adaptation of the traditional EPC modes is the introduction of the local government as the third party. Participation of the third party can effectively reduce and remove the barriers and risks and increase the mutual trust between the clients (households) and the energy service companies (ESCOs). Based on the testing results, this study suggests that governmental departments should formulate relevant EPC policies and technical guidelines within the rural context. This research recommends that farmers should not manage their energy services by themselves and it is suggested to out-contracting ESCOs by applying the modes developed and tested by this paper.

Beschreibung: BACKGROUND AND OBJECTIVES: Soil or rock types in a region are often interpreted qualitatively by visually comparing various geophysical properties such as seismic wave velocity and vulnerability, as well as gravity data. Better insight and less human-dependent interpretation of soil types can be obtained from a joint analysis of separated and independent geophysical parameters. This paper discusses the application of a neural network approach to derive rock properties and seismic vulnerability from horizontal-to-vertical seismic ratio and seismic wave velocity data recorded in Majalengka-West Java, Indonesia.METHODS: Seismic microtremors were recorded at 54 locations and additionally multichannel analyses of surface wave experiments were performed at 18 locations because the multichannel analyses of surface wave experiment needs more effort and space. From the two methods, the values of the average shear wave velocity for the upper 30 meters, peak amplitudes and the dominant frequency between the measurement points were obtained from the interpolation of those geophysical data. Neural network was then applied to adaptively cluster and map the geophysical parameters. Four learning model clusters were developed from the three input seismic parameters: shear wave velocity, peak amplitude, and dominant frequency. FINDINGS: Generally, the values of the horizontal to vertical spectral ratios in the west of the study area were low (less than 5) compared with those in the southeastern part. The dominant frequency values in the west were mostly low at around 0.1–3 Hertz, associated with thick sedimentary layer. The pattern of the shear wave velocity map correlates with that of the horizontal to vertical spectral ratio map as the amplification is related to the soil or rock rigidity represented by the shear wave velocity. The combination of the geophysical data showed new features which is not found on the geological map such as in the eastern part of the study area. CONCLUSION: The application of the neural network based clustering analysis to the geophysical data revealed four rock types which are difficult to observe visually. The four clusters classified based on the variation of the geophysical parameters show a good correlation to rock types obtained from previous geological surveys. The clustering classified safe and vulnerable regions although detailed investigation is still required for confirmation before further development. This study demonstrates that low-cost geophysical experiments combined with neural network-based clustering can provide additional information which is important for seismic hazard mitigation in densely populated areas.

Beschreibung: Given the many threats to freshwater biodiversity, we need to be able to resolve which of the multiple stressors present in rivers are most important in driving change. Phytoplankton are a key component of the aquatic ecosystem, their abundance, species richness and functional richness are important indicators of ecosystem health. In this study, spatial variables, physiochemical conditions, water flow alterations and land use patterns were considered as the joint stressors from a lowland rural catchment. A modeling approach combining an ecohydrological model with machine learning was applied. The results implied that land use and flow regime, rather than nutrients, were most important in explaining differences in the phytoplankton community. In particular, the percentage of water body area and medium level residential urban area were key to driving the rising phytoplankton abundance in this rural catchment. The proportion of forest and pasture area were the leading factors controlling the variations of species richness. In this case deciduous forest cover affected the species richness in a positive way, while, pasture share had a negative effect. Indicators of hydrological alteration were found to be the best predictors for the differences in functional richness. This integrated model framework was found to be suitable for analysis of complex environmental conditions in river basin management. A key message would be the significance of forest area preservation and ecohydrological restoration in maintaining both phytoplankton richness and their functional role in river ecosystems.

Beschreibung: Accurate age estimates are crucial for assessing the life-histories of fish and providing management advice, but validation studies are rare for many species. We corroborated age estimates with annual cycles of oxygen isotopes (δ18O) in otoliths of 86 northern pike (Esox lucius) from the southern Baltic Sea, compared results with visual age estimates from scales and otoliths, and assessed bias introduced by different age-estimation structures on von Bertalanffy growth models and age-structured population models. Age estimates from otoliths were accurate, while age estimates from scales significantly underestimated the age of pike older than 6 years compared to the corroborated reference age. Asymptotic length () was larger, and the growth coefficient was lower for scale ages than for corroborated age and otolith age estimates. Consequentially, scale-informed population models overestimated maximum sustainable yield (), biomass at (), relative frequency of trophy fish (), and optimal minimum length limit but underestimated fishing mortality at (). Using scale-based ages to inform management regulations for pike may therefore result in conservative management and lost yield. The overestimated asymptotic length may instill unrealistic expectations of trophy potential in recreational anglers targeting large pike, while the overestimation in MSY would cause unrealistic expectations of yield potential in commercial fishers.