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Digitalization or the wide implementation of digital technologies in our energy systems are believed to make our systems smarter, more efficient and reliable. Furthermore, a much higher integration of renewable energy sources into the systems is expected, as well as new business possibilities are generated by the use of innovative digital technologies and processes. In this context, the IEA DHC Annex TS4 project is aiming at promoting the opportunities of the integration of digital processes into DHC schemes. This implies the clarification of the role of digitalization for different parts within the operation and maintenance of the district heating and cooling system. Furthermore, the implementation of these technologies is going to be demonstrated in a close cooperation with a number of industry partners. Moreover, the challenges such as data security and privacy as well as questions about data ownership are also addressed. Traditionally, district heating and cooling (DHC) networks are operated with a limited number of controls (as the control of the supply temperatures or the network pressure) to secure the required supply task and to optimize economics and ecologic performance. Detailed information of the supply and utilization structures (e.g. heat plant characteristics, power demand or time profiles) is not provided in classical network operation. An optimized heat generation and overall network operation is possible with more information on the demand and flexibility options (storages) resulting in e.g. peak shaving and the reduction of expensive peak boiler use. In these systems a wider integration of fluctuating heat sources, such as solar thermal energy and power-to-heat applications operating on the electricity markets, can be shown in already realized projects. Wider implementation of information and communication technologies, as in many other industries, unlocks potentials for better network management based on real-time measurement data and the integration of new business models. A growing number of companies are offering products and services, as e.g. digital analyses platforms or smart meters, in this frame. The current changes and developments in the operating environment are presenting both opportunities and threats for district heating providers. The main impact of the integration of digital technologies and methods for district heating providers is expected to be in the changing business environment. Via these new technologies the ways of working and using already established business models will change, new services and products will enter the market. On the other hand, existing business models are affected by the increased energy efficiency of the building stock caused by reduced heat sales and by the customer's demand for alternative heating solutions. Here digitalization will bring new methods to meet changing customer needs and to communicate with the different groups of customers. The special importance of digitalization in district heating systems is that digitalization is a prerequisite in innovative low temperature, so-called 4th generation, heat networks to integrate renewable and fluctuating heat sources. So, digitalization has the potential to make heat networks more sustainable, more reliable, has the potential to integrate more renewable energy, more excess heat, better suitable for the integration of lower temperature levels e.g. via an optimal usage of heat pumps or CHP units, more profitable e.g. via the reduction of expensive fossil fuel consumption or via the reduction of transmission losses. The presentation, the abstract presents and discusses the first results from the research work within the IEA DHC Annex TS4 on "Digitalisation of District Heating Systems-Optimised Operation and Maintenance of District Heating and Cooling Systems via Digital Process Management".

The advent of DNA sequencing revolutionized the field of microbiome research. Many organisms, by virtue of their codependence and/or growth rate, are either impossible or extremely challenging to get into pure culture. Sequencing allows important taxonomic and phylogenetic information to be obtained independent of culturing. Development of the sequencing technology itself has allowed for high throughput workflow that has allowed low cost and extensive sampling of microbiomes across environments. The co-development of reference datasets for taxonomy and functional assignments, along with open-source bioinformatics pipelines has further empowered scientists to explore microbiomes in many environments. However, there are limitations to sequence data that have constrained the ecological inferences in microbiome research. One such limitation, the compositional nature of sequence data, has impeded our ability to make accurate inferences about the environmental drivers of taxon abundance and covariance across conditions. In this dissertation I explore the use of quantitative PCR in combination with sequencing techniques to generate “Quantitative Sequencing” data (QSeq) that mitigates the limitations of compositionality on inferences relating to taxon abundance and covariance across environmental gradients. In chapter 1, I reviewed key characteristics of the soil environment and sequencing as a mechanism for sampling. In chapter 2, I leveraged modeling, synthesis, and literature review methods to establish the questions and data characteristics that demand QSeq methodology. I show that even small amounts of variation in total abundance make determining the effects of environment (biotic and abiotic factors) on any given taxon unreliable without QSeq. In Chapter 3, I extend the logic of quantitative sequencing to improve metagenome prediction from PICRUSt2. Using data synthesis methods, accounting for 16S gene abundance consistently improved the accuracy of predicted functional genes. This was confirmed by high correlations between predicted and measured gene abundance (QPCR). There was however a large variation in prediction accuracy, likely due in part to database biases and in part to decoupling of bacterial function from taxonomy. In Chapter 4, I applied QSeq in the context of an experimental, long-term farming system that has large gradients in total abundance with depth, and I used QSeq to identify taxa that changed in abundance due to different farming system management and soil depth. Finally in Chapter 5, I used QSeq to identify putative N-fixing taxa that responded to glyphosate in four experimental farming systems. I show that the abundance of these taxa were decoupled from other effects of glyphosate on N-fixation in soybean across farming systems.

Low temperature district heating is a heat supply technology for efficient, environmental friendly and cost effective community supply. Moreover, it is recognized as a key technology for transforming and decarbonating heat energy systems by efficient integration of renewable energy sources as solar thermal, geothermal and other waste heat sources. The results from the international cooperation activity IEA DHC Annex TS2 on "Implementation of Low-Temperature District Heating Systems" provide advice and recipes for obtaining lower network temperatures as well as information on other features to include in existing and new district heating systems (Averfalk et al. 2021). Accomplished by summarizing the economic benefits of low-temperature district heating and gained experiences from early adopters in various urban areas throughout Europe. Lessons learned can be applied in new and expanding district heating systems and are presented in this paper. We discuss economic benefits, temperature levels in buildings, temperature levels in district heating systems, an applied case, competitiveness of low temperature district heating and transition strategies for cities with existing district heating systems.