Skip to main content

MIMOSA: Integrated Assessment Model for Cost-Benefit Analysis

Project description

MIMOSA: Integrated Assessment Model for Cost-Benefit Analysis

MIMOSA is an Integrated Assessment Model (IAM) part of the IMAGE family, with 26 regions covering the whole world. It is a relatively simple Cost-Benefit IAM that still covers the relevant technological and socio-economic dynamics. The climate impacts are calculated using state-of-the-art COACCH damage functions, and the mitigation costs have been directly calibrated to the IPCC AR6 WGIII database.

MIMOSA is being developed at the Copernicus Institute of Sustainable Development at Utrecht University, and is part of the IMAGE modelling framework.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mimosa-1.2.0.tar.gz (659.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mimosa-1.2.0-py3-none-any.whl (876.5 kB view details)

Uploaded Python 3

File details

Details for the file mimosa-1.2.0.tar.gz.

File metadata

  • Download URL: mimosa-1.2.0.tar.gz
  • Upload date:
  • Size: 659.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.7

File hashes

Hashes for mimosa-1.2.0.tar.gz
Algorithm Hash digest
SHA256 f6a12552ca309d9ac3eb8316fd6884ed98184ebcfddc1c1a2aaafb310a080cc3
MD5 1b5997475bcf195585abe28cc9ff143d
BLAKE2b-256 c242014a69143659efca1a4602b2ee48587b584249900b1dd63c7deb7889842f

See more details on using hashes here.

File details

Details for the file mimosa-1.2.0-py3-none-any.whl.

File metadata

  • Download URL: mimosa-1.2.0-py3-none-any.whl
  • Upload date:
  • Size: 876.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.7

File hashes

Hashes for mimosa-1.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 819bb1cdf745aa48f67e1ef2617dc35dfc1c5793bafab4ed5fbc674abb615596
MD5 dd3da20ff18d48f2e5b5ba0834d91ca8
BLAKE2b-256 c6c2fbdcec8bb6aeb883d30081f500e9271f02567aec4c89e2dc78c1ae3d9eb6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page