No mention of Hachaichi's work

• Mohammed Hachaichi References https://jonudell.info/h/facet/?max=100&expanded=true&user=stopresetgo&exactTagSearch=true&any=hachaichi

• Key Finding
  • This paper uses machine learning to overcome unavailable carbon footprints inventories of the Global South
  • which are usually hampered by:
    • lack of local urban emissions data,
    • reduced climate footprint, and
    • shortages in climate finance.

• using these algorithms, the author estimates 24,110 cities' carbon footprints of the Global South

  • to provide a comprehensive analysis on a planetary scale,
  • while allocating responsibilities according to the cities' regions and sizes.

• author

  • Mohammed Hachaichi

• Highlights
  • Downscaling seven of nine = planetary boundaries indicators
    • to the city scale-level
    • for 62 major cities in the = Middle East North Africa (MENA) region
  • Extended-Environmental Input-Output analysis is used to estimate cities’ footprints.
  • The Planetary Boundaries framework is a controlling tool for cities footprints.
  • City-level carbon footprint is higher than the national-level by 17%.

• Title
  • Downscaling the planetary boundaries (Pbs) framework to city scale-level: De-risking MENA region’s environment future
• Author
  • Mohamed Hachaichi

• Title = Water-Food-Energy Nexus i
• n Global Cities:

• Addressing Complex Urban Interdependencies

• Abstract

  • Understanding how water, food, and energy interact in the form of the water-food-energy (WFE) nexus is essential for sustainable development which advocates enhancing human well-being and poverty reduction.

  • The application of the WFE nexus has seen diverse approaches to its implementation in cities across the globe.

  • There is a need to share knowledge in order to improve urban information exchange which focuses on the WFE nexus’ application and impacts on the United Nations (UN) Sustainable Development Goals.
  • In this study,
    • Natural Language Processing (NLP) and
    • Affinity Propagation Algorithm (APA)
  • are employed to explore and assess the application of the WFE nexus:
    • first on a regional basis
    • second on the city level
  • The results show that after the exhaustive search of a database containing:
    • 32,736 case studies focusing on
    • 2,233 cities,
  • African and Latin American cities:
  • have the most potential to encounter resource shortages (i.e., WFE limitation)
    • are systematically underrepresented in literature
    • Southern hemisphere cities can benefit from knowledge transfer because of their limited urban intelligence programmes.
  • Hence, with regional and topic bias,
  • there is a potential for more mutual learning links
  • between cities that can increase WFE nexus policy exchange
  • between the Northern and Southern hemispheres
  • through the bottom-up case-study knowledge.