Live-work symmetry

Team members: Xuan Liu, Carolina Fonseca, Chunfeng Yang, Walter Zesk

Research suggests that high-density neighborhoods in which the residents live and work, dramatically reduces the carbon footprint of the city by eliminating commuting related emissions [UK Department for Business, 2019]. In addition to the environmental benefits, the commingled density offers provides social benefits by increasing the intensity and variety of human interaction.

Achieving this dense, “live-work balance” in Kendall Square represents a transformation from the current state -- a migration embodied in a multitude of individual choices. This investigation seeks to enhance our understanding of the relationships between:

● The ideal migration in terms of impact on carbon footprint
● The underlying choices constituting this migration
● Changes required in the city to influence those chosed and accomodate the result
● The future form of the live-work balanced city

Local Amenities

Team members:  Pablo Barrenechea, Ainhoa Genua, ‘Chance’ Jiajie Li, Juan Múgica, Luke Reeve, and Jade Wu.

Consumers purchase groceries and other commodities through various options: local stores, supermarket chains, farmer’s markets, online platforms, mobile vans, etc. This paper identifies them into the following categories: retail stores, local marketplaces, delivery, and mobile amenities. The entire lifecycles of these shopping options emit different levels of CO2. They can also positively impact community well-being by facilitating human encounters and communication among people with diverse backgrounds.

The COVID-19 pandemic has affected numerical aspects of consumers’ behaviors, including transforming their shopping trend towards a scheme where more people rely on deliveries and intentionally avoid interactions.

This paper aims to assess the various shopping options for daily living close to where people live,
quantify their impact on community well-being through model simulation, and propose solutions to
re-orient these options, if necessary. We used Kendall Square as a case study.

Growtein

Team members: Rebecca Brand, Jon Chinen, Selin Sahin, Connie Wang

Animal-based food production accounts for 57% of greenhouse gas emissions. This number takes into account the emissions generated by raising, feeding, processing, and transporting livestock. The United States alone imports approximately 15% of their foods. The globalization of food has resulted in 14% of GHG emissions to come from food transportation. Shifting to a plant based or alternative protein diet is critical to reduce carbon emissions. Current alternative proteins exist on a spectrum: from the commonly available soy, whey, or pea proteins; to the newer to market, engineered, plant-based products such as Impossible Foods and Beyond Meat. Although a staple protein source in other cultures in Africa, Asia, and Latin America, an emerging market for alternative proteins in the global. West includes insects, such as crickets, with 25% of the world consuming insects on a regular basis. For the comparable amount of protein produced, plant-based proteins and cultivated proteins emit 86-99% less carbon emissions compared to legacy sources of meat-based proteins. We looked to Kendall Square as a case study to develop an interactive tool that city leaders, developers, and urban farming stakeholders can utilize to better inform the decision-making process around what types of alternative proteins to produce, in which areas of the city, and with what types of urban farming technologies are most needed to improve the emotional wellbeing, physical health, and environmental health while also minimizing carbon emissions, cost, and space required to meet the protein needs of
peoples in Kendall Square. Growtein shall empower diverse stakeholders to have more informed discourse around development of locally-sourced farming and regenerative agriculture solutions in an urban context.

Multi-Purpose Autonomous Vehicles

Team members: Jin Gao, Chance Li, Hiromu Ryan Rose, Ziyi Tang, Trent Tepool

According to a study by Morgan Stanley, the transport sector is heavily reliant on fossil fuels, accounting for 45% of global oil demand. However, autonomous vehicles (AVs) offer significant environmental benefits in fuel usage, as noted by the Southwest Research Institute study2 claiming that AVs can lead to as much as a 20% improvement in fuel consumption. Hence, the goal of this simulation project is to design a low-carbon, efficient transportation system to shift the usage and reliance on high fossil fuel consuming vehicles to multi-purpose vehicles, helping to imagine what an optimal transportation system in the future may look like. To accomplish this, we introduce a Multi-Purpose Autonomous Vehicle (MPAV). Based on a modular design strategy, the MPAV is able to perform various tasks such as street-cleaning and delivering commercial goods. For this simulation, we simplify it to carrying people and goods (parcels and food) and test two models with different capacities. We choose Kendall Square as a representative site for the future low-carbon, entrepreneurial city, as it houses a large number of high-tech enterprises and households that generate huge demand for parcel and food delivery from companies and commuters. Through simulation, we hope to find a balance between existing transportation options, MPAVs, and potentially other future modes of transportation to meet the transportation demands of the people of Kendall Square. The findings of our study provide a methodology to investigate different urban mobility scenarios and to assist public and private stakeholders in forecasting the size of deployment of new shared mobility services for passengers and packages. Additionally, the simulation tool also allows for testing different strategies for rebalancing fleets or distributing charging stations, or may even be used to model the effects of various transportation policy implementations that may encourage mode shifts among users to more sustainable modes of transportation, such as congestion pricing.