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Project

Hyper-LOCAL Solutions to GLOBAL Challenges

Optimizing environmental, social, and economic performance of cities


Cities play a central role in the climate crisis. According to the latest Intergovernmental Panel on Climate Change (IPCC) report, cities contribute 67-72% of global carbon emissions. The IPCC also highlights that ‘How new cities and towns are designed, constructed, managed, and powered will lock-in behavior, lifestyles, and future GHG emissions’. Given that cities represent such a large portion of carbon emissions and are continuing to expand, there is an opportunity to address climate change by making interventions that foster a more sustainable urban life.

When addressing the climate crisis, most of our attention and resources are going to national and intergovernmental institutions. However, relying solely on these large institutions comes at the risk of changes not being implemented at the pace necessary to contend with the climate crisis. Rather than waiting for national action, there are interventions that local communities can take today. We believe local, community-scale initiatives will be critical to trigger the transformation needed to meet climate mitigation targets.

MIT City Science group approach

At the MIT City Science group, we believe that, for future cities to thrive, they should be composed of a network of dense and diverse human-scale high-performing districts. These districts would give citizens access to everything necessary for daily life within a walkable distance. 


This model of the city has several socio-economic benefits, but it also has the potential to help to alleviate the environmental burden of urban life. For instance, if people can find jobs and the amenities needed to carry out their daily lives within short distances, commuting emissions would significantly decrease. Shorter trips would reduce car dependency favoring more sustainable modes of transportation such as walking or biking. Similarly, having people live in more densely populated areas rather than in suburbs means changing the housing type from single-family detached houses to more efficient and compact apartments. As environmental, social, and economic factors are closely intertwined, these ideas do not only contribute to lowering CO2 emissions but also to improving the social and economic performance of cities. 

Case study: transformation of MIT-Kendall Square

In this project, we evaluate the environmental impacts of the components of the City Science’s future  city proposal. We use Kendall Sq. in Cambridge, USA, as a case study. We have built a model that estimates the average metric tons of CO2- equivalent per person and year regarding the mobility of people, building-related energy consumption, and food. These emissions are based on an attributional life-cycle assessment analysis that considers the impacts of each product or service from the extraction of the raw materials through their manufacturing, use, and final disposal.


This model evaluates the environmental impact of the following interventions:

  • Electric Vehicles, Grid decarbonization: Electric vehicles gradually substitute current combustion-engine vehicles. On-site interventions will be complemented by off-site decarbonized grids. This mixture will allow communities to decarbonize energy consumption at faster rates than would be possible with regular decarbonization of the grid.
  • High performance architecture and Hybrid work: Deep building retrofit to extend the lifespan of buildings, and to increase the efficiency of existing buildings. People will work from home sometimes to reduce commute.
  • Proximity to housing, jobs and amenities: Fostering that all the people living and working in Kendall could live within a walkable distance between home and jobs. Create an appropriate mix and density of jobs, homes, and amenities so that people can live, work, and find the necessary amenities for daily life within a walking distance.
  • Hyper-efficient places of living: Use of architectural robotics in existing and new buildings to allocate the new population and create more compact, multipurpose, transformable rooms. Transformable, compact, and efficient apartments will also help to create more diverse neighborhoods. 
  • Lightweight community scale mobility: Autonomous shared micro-mobility can then help to further reduce the emissions of the remaining short-distance trips.
  • Low carbon diet: Transition from the standard United States diet, which is heavily meat-based, to a more locally produced plant-based diet. The transition in the diet is modeled in varying degrees ranging from eating vegan food one to seven days per week. 
  • High-density power: Transition from the current electricity mix to a more sustainable and on-site energy supply one which includes nuclear batteries.
  • Air travel, Durable goods, Internet, and Services:  Reduce emissions by reducing air travel, using fewer materials, and reusing goods.

Limitations

  • While this study provides estimates that can give helpful information on the orders of magnitude of different interventions, the specific numbers are subject to various sources of uncertainty, such as the lack of data and modeling simplifications. 
  • In the cases in which there was a lack of granular local data, we have used national averages instead. 
  • The way that the interventions have been modeled contains several assumptions. Even if these assumptions are largely based on literature, the outputs of the model would be different if other hypotheses had been considered. In the future, we plan to include sensitivity analyses to estimate the impact of such assumptions.
  • There is uncertainty related to the environmental impacts of emerging technologies that have not been deployed to scale, or do not have life-cycle assessments yet, such as robotic architecture, autonomous micro-mobility, or nuclear batteries.
  • In terms of diet, we have not included the cost of ending the life of products or services before their estimated end of life.

Credits

  • Land-use modeling: Pablo Barrenechea, Luis Alonso, Ronan Doorley, Diego Antonelli, Markus Elkatsha
  • Energy modeling: Andrés Rico, Leticia Izquierdo, Maitane Iruretagoyena
  • Mobility modeling: Ainhoa Genua, Naroa Coretti
  • Diet modeling: Alex Berke, Juan Múgica
  • Interface: Leticia Izquierdo, Chance (Jiajie) Li, Diego Antonelli, Gabriela Bila, Justin Blinder
  • Graphic design: Gabriela Bila, Leticia Izquierdo
  • Direction: Kent Larson