? Grid intensity view:


Letter from the Editors
Michelle Thorne, Babitha George and Shannon Dosemagen

Conversation With Branch’s Cover Artists
Aravani Art Project

Open Climate Then and Now
Shannon Dosemagen, Emilio Velis, Luis Felipe R. Murillo, Evelin Heidel, Michelle Thorne, Alex Stinson

Solarpunk and Repair

Taeyoon Choi

Geography of Robots

After-Times® M22 HD
Deepa Bhasthi

The Repair Shop 2049: Mending Things and Mobilising the Solarpunk Aesthetic
Paul Coulton, Tom Macpherson-Pope, Michael Stead

Solar-Centered Designing: An Eccentric Proposal
Andres Colmenares

Climate Justice Now

Climate Justice: The Debt Is Not On Us
Brisetha Hendricks, Kristophina Shilongo

A Call to Action for Environmental Justice in Tech
Sanjana Paul

New Research on Climate Justice and Digital Rights
Fieke Jansen

The Different Intersections of Digital rights and Climate
Shannon Dosemagen, Evelin Heidel, Emelia Williams, Katie Hoeberling

The Power of Open

Map of the Future
Shayna Robinson

Wikipedians Reimagine Open Climate in the African Context
Maxwell Beganim, Otuo-Acheampong Boakye, Euphemia Uwandu

Critical Openness and Digital Sustainability
Emilio Velis

African Traditional Knowledge and Open Science for Climate Mitigation
Thomas Mboa, Ahou Rachel Koumi

Anna Berti Suman

Slow Tech, Hi Craft

Slowing Down AI with Speculative Friction
Bogdana Rakova

River Walks, Mutual Aid and Open Futures
Siddharth Agarwal

Michelle Cheripka

Alternative Computing Environments

Computing from the South / Computação do Sul
TC Silva, LF Murillo, Vince Tozzi, Francisco Caminati, Alice Bonafé, Junior Paixão, Mariana Rocha Arduini , Djakson Filho, Layla Xavier

Learning from COWs: Community Owned Wifi-Mesh
TB Dinesh, Shafali Jain, Sanketh Kumar, Micah Alex

Smarter, Greener Cities through Community, Open Data and Systems Thinking
Sruti Modekurty

Tech’s Environmental Impact

Apple just launched its first self-repair program. Other tech companies are about to follow.
Maddie Stone, Grist

Environmental Impact Assessment of Open Technology
Allie Novak, Shannon Dosemagen

Boavizta Project: Assessing the Environmental Impact of Digital Technology with Open Tools
Eric Fourboul, David Ekchajzer

The Fermi Problem of Climate Change
Anna Knörr

Fossil-Free Internet

The People’s Cloud: Manifesting Community and Eco-led Digital Spaces
Sarah Kearns

CO2.js: An Open Library for Digital Carbon Reporting
Fershad Irani

Library Love

Social Infrastructure Is What Love Looks Like in Public
Mai Ishikawa Sutton

Leading with Slow Craft
Nate Hill

Changing Soft Adaptation Limits, Seed By Seed
Daniela Soleri, Rebecca Newburn, Nate Kleinman, Mary K Johnson, Hayden Kesterson, Nick P Wrenn

About Branch

Unknown grid intensity

Smarter, Greener Cities through Community, Open Data and Systems Thinking

What comes to mind when you think of a “smart city”? Do you think of a sci-fi city with flying cars or a city like Singapore with high-tech supertrees? Perhaps it conjures dystopian images of cameras and sensors on every corner, tracking your every move? The general idea of smart cities is to use technology and data to make cities more efficient and better places to live. This has come with mixed success.

But what if “smart” cities were less about high-tech solutions and more about making better use of resources, like making information more accessible and better incorporating community knowledge? What if it meant doing more with less?

In addition to the myriad of challenges urban areas face—homelessness, traffic congestion, economic deprivation—climate change is creating new problems and exacerbating existing ones. Vulnerable populations, especially those in the Global South, will suffer the greatest consequences. Cities need to urgently implement mitigation and adaptation solutions, by making smarter and faster decisions. 

An important characteristic of a smart city is the flow of information on air pollution, traffic, trees, hospitalizations, procurement projects, and more. We live in the age of Big Data, with petabytes of data generated every day. There is enormous potential to use all of that data to help us implement better climate change solutions and make decisions faster. It can help us pinpoint problems, implement the most effective solutions and track progress. However, data inequities and lack of accessibility get in the way. 

To start, there is a huge discrepancy in the generation and availability of data between the Global North and the Global South. For instance, air pollution is a common problem for many cities—over 90% of the world’s population is breathing unclean air—yet half of national governments do not produce air quality data. Within the Global North, data inequities persist between wealthier areas and those occupied by marginalized groups.

Even where data exists, it is often siloed, difficult to access, or uses inconsistent formats. Many governments in both the Global North and Global South lack the needed technical resources. The time investment and skills required to use the data also make it difficult for affected communities to understand and take action. Not to mention a variety of other factors affecting data use, including political willingness and cultural attitudes. 

All together, this means very little data is actually put to use. For smart cities to be “smarter” and realize their potential, it will take a paradigm shift, using systems thinking, centering on community, and requiring openness. 

Systems thinking involves viewing the city as a whole, instead of focusing on individual problems and sectors, such as air pollution or the energy sector. It’s a system of many interlinked components, with feedback loops constantly shifting the dynamics. This new viewpoint allows you to dig deeper into the root causes of problems and find more effective solutions, even multi-win solutions. These can be policies or interventions that cut across various parts of the system such as housing, transportation, and the environment, resulting in better outcomes for all.

For example, air pollution in a particular area could be attributed to high levels of car traffic. One solution might be to reroute traffic to another, less populated part of the city. But that would just shift the problem. Zooming out, you realize air pollution is just a symptom of a larger transportation problem. The prolific use of cars in cities results in less public space, less investment in public transport infrastructure, lower health outcomes in often poor neighborhoods. Intervening at a higher level by changing people’s mobility patterns, would have a much bigger impact. Expanding public transportation could encourage people to drive less, reducing greenhouse gas emissions and pollution, promoting more active mobility, and better connecting parts of the city. 

Systems thinking is important for more deeply understanding problems and finding more effective solutions. Data and technology can be powerful tools for decision-making if leveraged using the following principles.

1. Center on Community

Residents are the most important part of a smart city. As both users and experts, they intimately understand problems and even potential solutions. Communities should be co-creators in every step of the process – data generation, data interpretation, solution ideation and implementation. This is especially important for frontline communities at greatest risk from climate change. It builds trust and incorporates important context, overall improving outcomes. Ugandan company Airqo for example is using local knowledge to build sensors specifically for the African context and empowering local groups and governments to reduce air pollution. 

2. Open and Accessible

Open data has many benefits: from increasing transparency and accountability to enabling innovation. Making data open is also essential for breaking down silos on a local scale between city entities, making it easier to view the city as a system, and on a global scale, aiding international collaboration. Climate change doesn’t stop at borders—our data and solutions need to break down barriers as well. The data also needs to be accessible—meaning stakeholders understand how to retrieve and interpret data, while preserving privacy. Community data hubs with distributed ownership and federated information exchange show promise as a potential implementation model. 

3. Tied to Goals or Policies

It is not enough to collect and analyze data. In many cases, we know the problems, we need to start implementing solutions. Every piece of data collected should be tied to a goal or policy, ensuring the data is actually helpful and is used to advance solutions. Goals and policies will also be more explicitly tracked for progress and effectiveness. In many cases, just enough, or good enough data, is all that is needed for decision-making. Greater data generation comes with monetary and environmental costs of storage and processing, without leading to much better insight. A tweeting air quality monitor in Beijing is an incredible example of how just one monitor spurred enormous investment and policy changes, and ultimately cleaner air.

Climate change is here and we are running out of time. We need intelligent, community-powered solutions for mitigation and adaptation now. An action-oriented city led by openness and systems thinking, closely aligned with resident needs, will not only be a smarter city, it will be a greener and healthier city for all.

About the Author

Sruti Modekurty is currently a student in the Erasmus Joint Masters in Urban Climate and Sustainability program. Her previous work spans nonprofit, government and industry, mainly focused on open data, civic tech, and cities.