GSSS 2019-Project Presentations

GSSS 2019 Home Logistics Faculty Faculty Publications Lecture Abstracts & Slides Participants Schedule Background Readings Projects & Working Groups Project Presentations Examples of past projects After Hours Restaurant Guide Resource Guide Photos

Presentation Schedule

2019 Global Sustainability Summer School Presentations Friday, July 26

Time | Group | Title

9:00 AM – Group 1 – City Scaling of Bike Data

9:15 AM – Group 2 – Modeling complexity and scale

9:30 AM – Group 3 – SDGs - Data-derived arguments for a more granular approach to the SDGs

9:45 AM - Group 4 – Urban Shrinkage and the Sustainability Gap

   10:05 AM – Break (25 min)

10:30 AM – Group 5 – Commutety - social connectivity for improved shared/public transit

10:50 AM – Group 6 – Cycling in São Paulo - using impact data to create a vision for cycling

11:20 AM – Group 7 – Dragging Change - mobilizing informal economies for greener cities in the global south

   12:00 PM – Lunch Break (1 hour)

1:00 PM – Group 8 – Analysis of EV Charging Stations

1:20 PM – Group 9 - Lighttime - night lights and energy scaling in cities

1:50 PM – Group 10 – SDGs and City Level Interventions

   2:30 PM – Break (30 min)

3:00 PM – Group 11 – Taking the “Pulse” of the City

3:20 PM – Farewell

Groups & Titles & Abstracts

Group 1
City Scaling of Bike Data

Cycling for everyday purposes offers many co-benefits. Its ability to advance social good and sustainability (broadly defined) crosses many urban systems, including energy, climate change, local/personal economies, education/youth development, public health and social connectivity. Efforts to promote this advantageous mode of travel, as well as to understand the determinants of bicycling mode choice, have been advanced over several decades. Yet, progress has been slow. Less than 1% of Americans currently ride bicycles to work, for example. In recent years, cities have been the site of increased interest, however, with cycling rates growing in cities much faster than the national average. This growth has been uneven between cities, raising an important question. Why are some cities so far ahead of others in bicycle transportation? As the act of choosing to bike for purposeful transportation is a sociotechnical system, with dependence upon both socioeconomic and infrastructure dimensions, the scaling theory of cities may offer interesting insights into this question. It is with this motivation that this project was undertaken.

Scaling of cities theory mathematically explains empirical data that suggests that urban properties scale according to power relations. Social quantities are theoretically expected to scale according to a factor of 1.15, while infrastructure is expected to scale by a factor of only 0.85. The theory proposes that social network effects explain the observed superlinear behavior of social quantities with city size and that economies of scale in the denser environments that accompany population growth explain the sublinear growth of urban infrastructure.

Biking data is becoming increasingly ubiquitous, though not always in machine-readable form. This project examined two parameters expected to scale superlinearly with city population in accordance with expected social outputs of cities (number of bike commuters and number of daily trips by bike). The impact of time on the scaling factor was also explored for the former variable. Infrastructure-related variables were also examined (number of bike share bikes and two composite measures of ‘bike friendliness’, BNA or bicycle network analysis, and PeopleforBikes City Rating). BNA captures bicycle network comfort and accessibility to places, while City Ratings additionally include factors that address ridership, equity and speed of network transformation.

As predicted by theory, both socioeconomic variables were found to scale superlinearly with city size and number of bike share bikes was found to scale sublinearly. The two indicators of “bike friendliness” did not correlate with population. These parameters may correlate with urban density, a factor that can be impacted by collective decision making. The pattern of individual cities in the regressions were explained in many instances, but anomalies were identified that warrant further investigation.

Despite evidence suggesting strong interest in biking, it has not been normalized in American society and may be in early stages of adoption, which could explain differences between expected scaling factors and empirical ones. This preliminary research suggests that bike behavior and infrastructure may indeed be characterized by city scaling laws and warrants deeper exploration as a means of understanding the emergence of bike cultures.

Participants: Susan Grasso

Group 2
Returns to Civilizational Scale

Abstract (I am still rethinking how I want to structure the project and am continually revising this): It is well-established that, among cities, several important socioeconomic quantities scale to city population in non-linear manners. Our goal in this project is to investigate whether similar scaling patterns can be derived on the level of a full civilization. We will attempt to describe how scale-dependence may govern the deployment of technology, and in particular the technologies for the low-carbon energy transition that is known to be necessary to achieve the climate change targets set forth in the Paris Agreement. Our methods are primarily literature review, and a key object is to established hypotheses for future research.

Participants: Michael Goff

Group 3
Scaling Laws and the SDGs – Leveraging Complex Systems Science to optimize SDG data collection, analysis and impact.

The UN Sustainable Development Goals embody humanity’s ambition for a sustainable, equitable future. Considerable effort is being made to monitor progress towards the SDGs and to use these data to improve policymaking, particularly in developing countries. Given the challenges in collecting, analyzing and disseminating these data, particularly in countries and regions in which data infrastructure is weak, the international community should optimize all aspects of collection, analysis and dissemination. The recent progress in applying the tools of complex systems science, such as scaling theory and network theory, to humans systems like cities, suggests that the methods of Complex Systems Science (CSS) could be deployed to improve the analysis of existing SDG data and/or motivate more impactful data collection and use.

To explore the relevance of CSS to the SDGs, data from SDG7 – Affordable and Clean Energy was analyzed for scaling relationships. Data for the SDG7 sub-goal “Share of Population with Access to Electricity” is collected at the national level and disaggregated into rural and urban categories. Using the data from 42 countries in sub-Saharan Africa (SSA) log-log plots of “Population with Electricity Access” vs “Total Population” were prepared for the rural and urban cases. The Urban Electricity Access data scaled linearly (ß ≈ 1.0), while the Rural Electricity Access data scaled sub-linearly ß ≈ 0.84).

The scaling of the urban data implies that energy access in African cities is being handled at the individual level and that the synergies available in urban systems are not being achieved. The scaling of the rural data is consistent with the scaling of infrastructure in the U.S. and implies that the drivers of rural electrification are optimizing efficient distribution. The intense need for energy access in SSA implies that efforts should be made to tip the development of both the urban and rural SSA power sectors into a mode that features faster connection creation, i.e. ß ≈ 1.16 until the goal of universal energy access is achieved.

Given that these data appear to fall into these scaling regimes, it seems warranted to explore the theory behind the development of the African power sector using the tools of Complex Systems Science. Armed with the insights from such a theory, the work of international statistics and developments agencies could likely be made more impactful.

Participants: Gerard Ostheimer

Group 4
Urban Shrinkage: dynamics of change and the sustainability gap

A number of cities across the OECD are declining, particularly small and mid-sized cities. In the absence of growth these cities face serious challenges in both maintaining the quality of life for residents that remain and in meeting necessary sustainability goals for the future. In this presentation we offer an over of differing types of shrinkage, the levers of shrinkage and then focus on the case of Detroit. This case illustrates the particular challenges arising from decline. We conclude with some questions about possible alternatives or “soft landings” for other cities experiencing urban shrinkage.

Participants: Joshua Akers, Nick Allen, Carly Anderson

Group 5
Commutety - social connectivity for improved shared/public transit

Public transit has been shown to be an efficient means of moving large numbers of people in urban areas with comparatively low environmental impact. This becomes crucial to improving sustainability and easing congestion in these metropolitan areas. However, in the US, public transit ridership has been historically low and has fallen over time in many metro areas. There primary reason for this is because of lack of infrastructure, but social reasons also reinforce low ridership, including social isolation and perceptions of safety. In the Commutety project, we investigate the vicious cycle of low transit ridership and propose a solution that leverages the power of weak ties in social networks to build “moving communities” of transit riders, who can then advocate for improvement. We also propose a framework that has riders/public, urban planners, and local businesses as stakeholders to enable positive feedback loops that could sustain and nurture public transit.

Participants: Ashley Zappe, Navaneethan Santhanam, Kyong Whan Choe

Group 6
Cycling in São Paulo - using impact data to create a vision for cycling

São Paulo saw a sudden and marked expansion in the total length of cycling lanes across the city in the period 2014-2016.

This project i. contextualizes the São Paulo city cycling policy implementation process in terms of the city’s transportation challenges and political situation, ii. builds a version of the WHO HEAT model (localized to post-policy-implementation São Paulo conditions) to estimate health and economic benefits of cycling in the city, and iii. contrasts these results to a summary of the impact research that was generated as follow-up to the policy. This information is then used as the basis for a reflection on how one could build a vision of a sustainable São Paulo that could be of use both to policy makers interested in expanding or maintaining the biking policy and to civil society as a whole.

This is meant serve as a starting point for further discussions, including considerations on the usefulness of data precision for public policy and vision-building and possible policy proposals that bring together diverse sectors of society (bikers, activists, businesses and government) with reference to a rich/complex vision of the city.

Participants: Andre Gimenez, Eduardo Ferraciolli, Nina Rismal, Carrie Snyder

Group 7
Dragging Change

The objective of the dragging change research project is to identify a best-practice model for including informal / slum neighborhood communities in the global climate change response. Formal governance generally has limited reach in less developed countries. Where it does reach, it is limited to top-down, regulatory control of a relatively small formal sector. To the extent that the informal / slum community is engaged, the relationship is often confrontational where the desired outcome is the removal of the community. Compounding these difficulties is the reality that climate change is generally not among the primary or immediate concerns of the informal / slum neighborhood communities. Drawing upon generally accepted network theory, while proposing a more sophisticated understanding of the weak – strong relationship distinction, the proposed research project provides a framework for behavioural change at the slum / informal neighbourhood community level, while maintaining reference to formal governance concerns.

Participants: Claudia Brochert, Sarah Brown, Jennifer Giroux, Matthew King, Isabella Perez, Andrew Gardiner

Group 8
Analysis of EV Charging Stations

abstract

Participants: Ray Herberer, James Williams, Edgar Valdes

Group 9
Lighttime - night lights and energy scaling in cities

The principal objective of Lighttime project is to identify regularities in city scaling with respect to two variables: metropolitan-area-level nighttime luminosity data and energy consumption. The methodology is based on Origins of Scaling in Cities(Bettancourt, 2013) that uses a simple linear regression.

The first step in our work is to establish the relationship between metropolitan-level night time luminosity data and the population size of US Metropolitan Statistical Areas. The interesting question here is whether nightlights represent infrastructural, housing, or socioeconomic phenomena in cities. We used 4 measures of nighttime luminosity - NTL, RAD, VANUI, and VIIRS. We identified that each of these measures scales sublinearly with city population, suggesting that nightlights was more associated with infrastructure rather than population. However, the scaling parameter 𝛃 varied from 0.71 to 0.89, indicating a deviation from the classic 5/6 th -power scaling law observed in other situations.

In the second part of our project, we attempted to establish scaling relationships between metropolitan-level energy consumption and the population of US metro areas at the residential, commercial, and industrial sectors. We also had data on the number of dwellings, commercial units, and industrial units.

The final section attempts to link sectoral energy consumption and nightlights. We were interested in decomposing the nightlight signal by sector into its constituent parts to examine whether they had different scaling relationships with population, which may explain our earlier findings.

Participants: Navaneethan Santhanam, Ana Rios, Eduardo Ferraciolli, Andre Gimenez, Wenhao Chen

Group 10
The SDGs applied to the city level

The Sustainable Development Goals are traditionally applied to the actions and efforts of nation-states around the world. However, there is an increasing level of interest from city administrations and city-focused researchers in applying the SDGs to the efforts and policies enacted at the metropolitan level. This presentation focuses on a subset of the full interplay between the different SDGs, their goals, their indicators, and different interventions, exploring the complexity of their impacts, the importance of policy/intervention context, and how the different levels of analysis of the SDG framework can help reveal different interconnections. The forms of intervention we focus on include mobility, building benchmarking, clean energy and gasification.

Participants: Tom Watson, Ville Taajamaa, Josh Loughman, Isabella Perez, Mike Specian, Sharanya Sarathy, Sarah Brown, Jesse Lopez

Group 11
Taking the "Pulse" of the City

During this course, we have reviewed a number of ways of measuring important city metrics. Following up from Charlie Catlett’s description of the Array of Things as a “fitness tracker” for the city, our group explored strategies for establishing diagnostic benchmarking for city health. We discuss opportunities to reframe the city as an organism (rather than as a human-made mechanism). Building from there, we pose a number of questions about ways in which our current metrics fail to capture “city health.” Where are there gaps in our traditional metrics for the city? How can we roughly estimate the “pulse” of a city with data available right now (e.g. mobility and social activity). In what ways will we be able to improve our ability to “check a city’s pulse” with sensor technologies (like IoT devices or AoT sensors) in the future?

Participants: Charlotte McKernan, Giorgia Cecchinato, David Torres