Mara Hauck
Biographic Data
| ID | 8000676 |
|---|---|
| NAME | Mara Hauck |
| GIVEN NAMES | Mara |
| FAMILY NAME | Hauck |
| SIGNATURE | HAUCK M |
| AFFILIATIONS | Radboud University Nijmegen |
| ORCID | 0000-0002-1992-3329 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Deriving experience curves
Experience curves are widely used for cost estimates in energy-economy models and are proposed as a forecasting tool for projecting the future environmental impact of emerging technologies. However, further application is limited by data availability and methodological challenges related to modelling the dynamic relationship between cost, different kinds of learning, and scale effects . This paper systematically compares existing experience curve…
A systematic approach to assess the environmental impact of emerging technologies
Estimating the environmental impact of emerging technologies at different stages of development is uncertain but necessary to guide investment, research, and development. Here, we propose a systematic procedure to assess the future impacts of emerging technologies. In the technology development stage (technology readiness level
Estimating the Greenhouse Gas Balance of Individual Gas‐Fired and Oil‐Fired Electricity Plants on a Global Scale
Life cycle greenhouse gas (LC‐GHG) emissions from electricity generated by a specific resource, such as gas and oil, are commonly reported on a country‐by‐country basis. Estimation of variability in LC‐GHG emissions of individual power plants can, however, be particularly useful to evaluate or identify appropriate environmental policy measures. Here, we developed a regression model to predict LC‐GHG emissions per kilowatt‐hour (kWh) of electricit…
How to quantify uncertainty and variability in life cycle assessment
n Contains fulltext :\n 133118.pdf (Publisher’s version ) (Open Access)\n \n Contains fulltext :\n 133118.pdf (Author’s version preprint ) (Open Access)\n \n Contains fulltext :\n 133118(supplement).pdf (Author’s version preprint ) (Open Access)\n
No prominent works on this page.
How to quantify uncertainty and variability in life cycle assessment
n Contains fulltext :\n 133118.pdf (Publisher’s version ) (Open Access)\n \n Contains fulltext :\n 133118.pdf (Author’s version preprint ) (Open Access)\n \n Contains fulltext :\n 133118(supplement).pdf (Author’s version preprint ) (Open Access)\n
Estimating the Greenhouse Gas Balance of Individual Gas‐Fired and Oil‐Fired Electricity Plants on a Global Scale
Life cycle greenhouse gas (LC‐GHG) emissions from electricity generated by a specific resource, such as gas and oil, are commonly reported on a country‐by‐country basis. Estimation of variability in LC‐GHG emissions of individual power plants can, however, be particularly useful to evaluate or identify appropriate environmental policy measures. Here, we developed a regression model to predict LC‐GHG emissions per kilowatt‐hour (kWh) of electricit…
A systematic approach to assess the environmental impact of emerging technologies
Estimating the environmental impact of emerging technologies at different stages of development is uncertain but necessary to guide investment, research, and development. Here, we propose a systematic procedure to assess the future impacts of emerging technologies. In the technology development stage (technology readiness level
Deriving experience curves
Experience curves are widely used for cost estimates in energy-economy models and are proposed as a forecasting tool for projecting the future environmental impact of emerging technologies. However, further application is limited by data availability and methodological challenges related to modelling the dynamic relationship between cost, different kinds of learning, and scale effects . This paper systematically compares existing experience curve…
Economics (4 works) · Electricity (3 works) · Engineering (3 works) · Environmental Impact and Sustainability (3 works) · Environmental Science (3 works) · Greenhouse gas (3 works) · Atmospheric and Environmental Gas Dynamics (2 works) · Combined cycle (2 works) · Computer Science (2 works) · Ecology (2 works)