Abstract A growing number of researchers and stakeholders have started to address climate change from the bottom up: by devising scientific models, climate plans, low-carbon strategies and development policies with climate co-benefits. Little is known about the comparative characteristics of these interventions, including their relative efficacy, potentials and emissions reductions. A more systematic understanding is required to delineate the urban mitigation space and inform decision-making. Here, we utilize bibliometric methods and machine learning to meta-analyze 5635 urban case studies of climate change mitigation. We identify 867 studies that explicitly consider technological or policy instruments, and categorize these studies according to policy type, sector, abatement potential, and socio-technological composition to obtain a first heuristic of what is their pattern. Overall, we find 41 different urban solutions with an average GHG abatement potential ranging from 5.2% to 105%, most of them clustering in the building and transport sectors. More than three-fourth of the solutions are on demand side. Less than 10% of all studies were ex-post policy evaluations. Our results demonstrate that technology-oriented interventions in urban waste, transport and energy sectors have the highest marginal abatement potential, while system-wide interventions, e.g. urban form related measures have lower marginal abatement potential but wider scope. We also demonstrate that integrating measures across urban sectors realizes synergies in GHG emission reductions. Our results reveal a rich evidence of techno-policy choices that together enlarge the urban solutions space and augment actions currently considered in global assessments of climate mitigation.