Alina Ursula Rosa Walch

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Shallow ground-source heat pumps (GSHPs) are a promising technology for contributing to the decarbonisation of the energy sector. In heating-dominated climates, the combined use of GSHPs for both heating and cooling increases their technical potential, def ...

To achieve the goals of the Paris Agreement on climate change, governments around the world must shift to renewable energy (RE) to drastically reduce their CO2 emissions within the next 10-30 years. The development of effective strategies for RE integratio ...

With wind power providing an increasing amount of electricity worldwide, the quantification of its spatio-temporal variations and the related uncertainty is crucial for energy planners and policy-makers. Here, we propose a methodological framework which (1 ...

The increasing use of ground-source heat pumps (GSHPs) for heating and cooling of buildings raises questions regarding the technical potential of GSHPs and their impact on the temperature in the shallow subsurface. In this paper, we develop a method using ...

Regional-scale urban residential densification provides an opportunity to tackle multiple challenges of sustain-ability in cities. But framework for detailed large-scale analysis of densification potentials and their integration with natural capital to ass ...

District heating and cooling networks connect and distribute thermal energy resources within a network of sources and demands. While individual networks have been extensively studied, the scaling up of this technology requires the interconnection of larger ...

In 2020, Covid-19-related mobility restrictions resulted in the most extensive human made air -quality changes ever recorded. The changes in mobility are quantified in terms of outdoor air pollution (concentrations of PM2.5 and NO2) and the associated heal ...

Solar photovoltaics (PV) will play an important role in decarbonising the energy system. To date, most assessments of PV transition pathways focus on least-cost aspects, without neither considering the time needed to achieve a substantial PV deployment, no ...

The large-scale deployment of photovoltaics (PV) on building rooftops can play a significant role in the transition to a low-carbon energy system. To date, the lack of high-resolution building and environmental data and the large uncertainties related to e ...

Using Machine Learning (ML) algorithms for classification of the existing residential neighbourhoods and their spatial characteristics (e.g. density) so as to provide plausible scenarios for designing future sustainable housing is a novel application. Here ...

The spatio-temporal patterns of the existing rooftop photovoltaic (PV) production can provide valuable insights for the design of effective strategies for PV integration at large scale. In this work, we quantify the hourly production of existing rooftop PV ...

The extraction of shallow geothermal energy using borehole heat exchangers (BHEs) is a promising approach for decarbonisation of the heating sector. However, a dense deployment of BHEs may lead to thermal interference between neighboring boreholes and ther ...

To understand the opportunities and challenges of large shares of solar photovoltaics (PV) in our electricity mix, various large-scale studies of PV potential on building roofs have been conducted in recent years. The use of different datasets, methods and ...

Alina Ursula Rosa Walch

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Shallow geothermal energy potential for heating and cooling of buildings with regeneration under climate change scenarios

Spatio-Temporal Estimation of Renewable Energy Potential in Built Environments using Big Data

Spatio-temporal estimation of wind speed and wind power using extreme learning machines: predictions, uncertainty and technical potential

Using Machine Learning to estimate the technical potential of shallow ground-source heat pumps with thermal interference

A machine learning methodology to quantify the potential of urban densification in the Oxford-Cambridge Arc, United Kingdom

Optimal spatial resource allocation in networks: Application to district heating and cooling

Covid-19 mobility restrictions: impacts on urban air quality and health

Strategic PV expansion and its impact on regional electricity self-sufficiency: Case study of Switzerland

Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty

Residential density classification for sustainable housing development using a machine learning approach

Quantification of existing rooftop PV hourly generation capacity and validation against measurement data

Quantifying the technical geothermal potential from shallow borehole heat exchangers at regional scale

A critical comparison of methods to estimate solar rooftop photovoltaic potential in Switzerland