Lynn H Kaack

Biographic Data

ID6822854
NAMELynn H Kaack
GIVEN NAMESLynn H
FAMILY NAMEKaack
SIGNATUREKAACK L H
AFFILIATIONSHertie School
ORCID0000-0003-3630-3102
VERIFIEDYes
TOTAL WORKS6
TOTAL CITATIONS0
AUTHOR COUNT6
EDITOR COUNT0
FIRST PUBLICATION YEAR2018
LATEST PUBLICATION YEAR2026
H-INDEX0

  • Framing artificial intelligence as a policy instrument in urban climate action

    Open AccessMarie Josefine Hintz, Lynn H Kaack et al.ARTICLECities2026

    Urban practitioners increasingly integrate artificial intelligence (AI) into tasks related to the implementation of climate action. With the impact of AI transcending specific tasks but changing responsibilities and routines, it must be considered as a policy instrument. While research identified potential AI applications and traced implementation processes, it remains understudied how practitioners introduce AI and how AI systems change workflow…

  • Practical implementation of artificial intelligence for climate change mitigation in cities – priorities, collaborations and challenges

    Open AccessMarie Josefine Hintz, Milena Gro et al.ARTICLEEnergy Research & Social Science2025References: 23

    European cities are increasingly exploring artificial intelligence (AI) applications to achieve their climate goals. Yet, how European city administrations implement AI-for-climate projects remains unclear. To address this gap, we interviewed city staff and urban innovation experts (n=15 interviewees) from Amsterdam, Berlin, Copenhagen, Greater Paris, Helsinki, and Vienna about their motivations, challenges, solutions, and partnerships when deplo…

  • Data gaps in transport behavior are bottleneck for tracking progress towards healthy sustainable transport in European cities

    Open AccessGuillaume Chevance, Mark Nieuwenhuijsen et al.ARTICLEEnvironmental Research Letters2024

    Data gaps in transport behavior are bottleneck for tracking progress towards healthy sustainable transport in European cities, Chevance, Guillaume, Nieuwenhuijsen, Mark, Braga, Kaue, Clifton, Kelly, Hoadley, Suzanne, Kaack, Lynn H, Kaiser, Silke K, Lampkowski, Marcelo, Lupu, Iuliana, Radics, Miklós, Velázquez-Cortés, Daniel, Williams, Sarah, Woodcock, James, Tonne, Cathryn

  • Tackling Climate Change with Machine Learning

    Open AccessDavid Rolnick, Priya L Donti et al.ARTICLEACM Computing Surveys2023

    Climate change is one of the greatest challenges facing humanity, and we, as machine learning (ML) experts, may wonder how we can help. Here we describe how ML can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by ML, in collaboration with other fields. Our recommendations encompass …

  • Digitizing a sustainable future

    Open AccessLucia A Reisch, Lucas Joppa et al.ARTICLEOne Earth2021

  • Decarbonizing intraregional freight systems with a focus on modal shift

    Open AccessLynn H Kaack, Parth Vaishnav et al.ARTICLEEnvironmental Research Letters2018

    Road freight transportation accounts for around 7% of total world energy-related carbon dioxide emissions. With the appropriate incentives, energy savings and emissions reductions can be achieved by shifting freight to rail or water modes, both of which are far more efficient than road. We briefly introduce five general strategies for decarbonizing freight transportation, and then focus on the literature and data relevant to estimating the global…