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Wastewater generation model to predict impacts of urine separation on wastewater treatment plants
(2024)
Wastewater treatment plants (WWTPs) are under increasing pressure to enhance resource efficiency and reduce emissions into water bodies. The separation of urine within the catchment area may be an alternative to mitigate the need for costly expansions of central WWTPs. While previous investigations assumed a spatially uniform implementation of urine separation across the catchment area, the present study focuses on an adapted stochastic wastewater generation model, which allows the simulation of various wastewater streams (e.g., urine) on a household level. This enables the non-uniform separation of urine across a catchment area. The model is part of a holistic modelling framework to determine the influence of targeted urine separation in catchments on the operation and emissions of central WWTPs, which will be briefly introduced. The wastewater generation model is validated through an extensive sampling and measurement series.
Results based on observed and simulated wastewater quantity and quality for a catchment area of 366 residents for two dry weather days indicate the suitability of the model for wastewater generation and transport modelling. Based on this, four scenarios for urine separation were defined. The results indicate a potential influence of spatial distribution on the peaks of total nitrogen and total phosphorus.
Potential and risks of water reuse in Brandenburg (Germany) – an interdisciplinary case study
(2024)
For Brandenburg, a region in Germany with increasing water shortage and drought events, water reuse can counteract competition scenarios between drinking water supply, agricultural irrigation, and industrial use. Centralized and decentralized sources for reclaimed water are found to potentially substitute 245 or 28% of irrigation water, respectively, in agriculture production in Brandenburg. For such a reuse scenario, the
fate of organic micropollutants is examined for diatrizoate (DZA) and carbamazepine (CBZ). Retention in local sandy soil and transfer into roots and leaves of arugula are analyzed in lysimeter studies and greenhouse pot experiments. Vertical transport was found for DZA and accumulation in or on arugula roots with a root concentration factor of 1,925+34% but a low bioconcentration factor due to intrinsic molecule properties. CBZ was not found to be mobile in the sandy soil but accumulates in arugula roots and leaves by factors of 70+7% and 155+12%, respectively. Further research on potential plant uptake and groundwater enrichment for more substances is highly recommended as well as tertiary wastewater treatment prior to water reuse.
Das vorliegende Kompetenzmodell zur Berufsbildung für nachhaltige Entwicklung (BBNE) in Lebensmittelhandwerk und Lebensmittelindustrie enthält eine Kompetenzmatrix, deren Felder der Strukturierung dienen, welche nicht isoliert, sondern in ihrem Gesamtzusammenhang zu betrachten sind.
Ergänzt wird diese Matrix durch nachhaltigkeitsrelevante Kernkompetenzen sowie dazugehörige Kompetenzziele.
When simulating and optimizing urban energy systems, the focus is usually on minimizing financial costs or greenhouse gas (GHG) emissions. As energy systems transition towards a growing share of renewable energy sources and technological complexity, environmental impacts that affect more than just GHG emissions, such as resource extractions, water and land use impacts or impacts on human health, are becoming increasingly relevant.
To address this gap, this thesis introduces an automated coupling procedure for energy system modeling (ESM) and life cycle assessment (LCA). The implementation includes general recommendations and a practical coupling of the Open Energy Modelling Framework (oemof) based Spreadsheet Energy System Model Generator (SESMG) with a suitable LCA software.
The LCA procedure involves goal and scope definition, inventory analysis, impact assessment, and interpretation. To adapt these steps to different energy system models, the LCA should be attributional, process-based and territorial. Further, the openLCA software by Green-Delta serves as a suitable soft-linking tool. The main challenge of the coupling procedure is the inventory analysis. Data collection faces limitations, reasoned by the commercialization and high maintenance efforts in open-source databases. After evaluating free databases, the Prozessorientierte Basisdaten für Umweltmanagement-Instrumente (ProBas) database of the Umweltbundesamt emerged as the most suitable choice for the coupling. However, also this database lacks traceability of datasets or compatibility with a comprehensive impact assessment.
A generalized framework for the LCA application of energy systems was developed. The framework is based on an ex-post LCA assessment that considers the combination of the two approaches within every step of the procedure. Main considerations of this framework include automatic calculations of the inventory analysis and the impact assessment for different energy technologies, as well as calculations summed up for all technologies of energy system scenarios. Further, technology mapping and data harmonization are essential considerations for the automatic coupling and double counting of impacts needs to be avoided.
Subsequently, the framework is realized with the adaption of the SESMG. Its database-independent realization allows compatibility with different databases in openLCA. For the selected ProBas database, the tool can be used with different available energy technologies. The use of unit processes is encouraged for data harmonization. Result interpretation of the LCA (in general or with the SESMG) should not solely focus on the absolute values of the impact categories, but rather on the comparative strengths among scenarios and technologies.
The successful application to a reference single-family building using the ProBas database revealed varied environmental impacts, in relation with a higher reduction in GHG emissions, with an increase of 11 % in terrestrial acidification impacts in the emission-optimized scenario. These findings emphasize a more comprehensive perspective on environmental impacts and provide a valuable validation of the developed methodology.
Future research should include the improvement of data harmonization, the inclusion of more datasets for a more customized analysis of energy systems and more applications. The coupled approach offers a promising avenue for gaining deeper insights into optimizing urban energy systems.
This study investigates the role of individual differences in channel choice and switching behavior in a multichannel environment using latent class analysis on data from 1512 customers. Psychographic variables from five domains (risk attitudes, cognitive ability, motivation, personality, and decision-making style) serve as covariates for multichannel customer behavior. We identify six segments that differ significantly on six psychographic variables (readiness to take risks, need for cognition, autotelic and instrumental need for touch, and rational and intuitive decision-making styles). The results advance the theory-building of multichannel customer behavior and present insights for proactively managing customer journeys of distinct segments.