Leveraging data science to reach zero carbon cities – potential & opportunity

Achievement of global climate stabilization goals requires reduction of carbon emissions in the industrial world to a degree which effectively requires all developed world cities to become zero carbon between 2030 and 2050 (Kennedy & Sgouridis 2011). Such cities will source all energy from renewable energy sources. The operational landscape of electricity, heating and cooling, water and transport systems is increasingly integrating data collection, storage, sharing and analysis to optimize operation and align multiple stakeholders in each infrastructural value chain towards common goals of efficiency and cost-effectiveness (Fleming 2017).

Today’s cities are the engines of the new data economy. The rise of energy trading systems, distributed energy sources, electric vehicles, on-demand transport, intelligent water management and responsive lighting are rapidly replacing the legacy infrastructure and service delivery models that served the cities of the twentieth century (Barns 2018). As a consequence, the millions of interactions and transactions that take place in cities on any given day — from volumes of energy used, movements of people, traffic, water and waste, social media interactions, emails, financial and retail transactions — are now generating huge volumes of data of increasing value to governments and businesses as they seek to apply data-driven methodologies to improve the quality and efficiency of city services (Ahmadi Zeleti et al. 2016).

Both academia and industry are focusing on energy management in cities, with many practical solutions developed at the level of buildings or individual city systems (Ejaz et al. 2017). Integrating these systems requires upgrading the institutional knowledge infrastructure associated with participation in decision making, public and social services, transparent governance, and political strategies and perspectives (Bibri 2018). Data science can empower a city with new insights and intelligence to support the identification of patterns and human relationships, enabling citizens, planners and city managers with smart instruments that support appropriate decision-making, discovery, exploration, and explanation on complex city dynamics (Kourtit et al. 2017).

Data science initiatives such as big data, internet of things, blockchain and business intelligence have the potential to improve implementation, foster greater understanding of social challenges, facilitate collaboration between governments, citizens and businesses, and usher in a new era of digital government services, but more research is needed to explore how best to consider data science in that context (Bertot & Choi 2013). In the energy sector, production and consumption data and energy systems are increasingly supported by emerging information technologies, changing the landscape of traditional energy industry where data science can lead to significantly improved efficiency and new business opportunities. Based on the big data analytics and services, energy is now being saved in ways that were not possible in the past (Zhou et al. 2016).

While governments have the unique legitimacy to collect and process large amounts of data generated within their borders and manage basic infrastructure to the benefit of all its citizens, private sector innovations based on technologies like big data, internet of things or blockchain cannot be replicated in the public sector with the same speed as they have in the private since their social impact is much greater (Kim et al. 2014). This may be due to difference in goals. The main goal of the private sector is to earn profits by providing goods and services, developing/sustaining a competitive edge, and satisfying customers and other stakeholders by providing value. In government, the main goal is to maintain domestic tranquillity, achieve sustainable development, secure citizens’ basic rights, and promote the general welfare and economic growth (Deloitte 2016). Most businesses aim to make short-term decisions with a limited number of actors in a competitive market environment. Decision making in government usually takes much longer and is conducted through consultation and mutual consent of a large number of diverse actors, including officials, interest groups, and ordinary citizens (Kim et al. 2014).

As an example of applied data science, big data could potentially transform city governments being more efficient, effective and evidence-based but critics point towards the limited capacity of government to overcome the siloed structure of data storage and manage the diverse stakeholders involved in setting up a data ecosystem (Giest 2017). In the past, city leadership had relatively limited engagement with users of city infrastructure, having to arrange specific public meetings or surveys to get feedback on system effectiveness and gather proposals for improvements and/or policy measures (Fleming 2017). Today and increasingly in the future, cities are able use the data from sensor networks embedded in city infrastructure and, through social media, people’s opinion to more rapidly identify opportunities to optimize all aspects of the city (Philip Chen & Zhang 2014).

In their effort to utilize big data, city governments largely focus on one of two data use models: a centralized structure where a city data centre is established or a decentralized model in which data scientists are integrated into different city departments who then compile data from various sources (Giest 2017). There is a concern that under time pressure, these structures are short term and end up enforcing the existing silos of people, IT and data. They further lead to an overemphasis on technological aspects of big data integration rather than more profound local government reform addressing the collection and use of big data.  The focus on technology also pulls resources from a potential information management system that specifically addresses the ways in which the data are integrated into decision-making (Barns 2018). Adjusting government structure for energy strategy and policy implementation to accommodate data science elements increasingly challenges the existing capacities within the government and processes of evidence-based decision making.

As an example, using data that currently exists in most large cities, it is possible to estimate the annual carbon emissions at a city level, but not yet in real time or in terms of understanding the detail of citizens’ behaviours. There is a lack of both quality and quantity of data to provide a true city-wide picture in real time. Data are also not uniformly available, as data is rather concentrated in clusters (Kourtit et al. 2017). The challenge is acquiring these existing data, extracting useful information and transforming it into actionable knowledge to facilitate implementation of set policies and strategies. How to deal with the variations in availability and quality of data is a key issue for cities not just to address the digital divide but also for the research community to develop new algorithms to help close the gaps in data and knowledge (Creutzig et al. n.d.).

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Image from: Frost & Sullivan

7 thoughts on “Leveraging data science to reach zero carbon cities – potential & opportunity

  1. Luka,

    My last role being in Fintech business development where blockchain technology was at the time an emerging technology which my division was considering to offer to our clients, I read your post with great interest.

    Assessing which data should be integrated into decision-making should indeed prevail but as you clearly state, all too often, more time is spent by government employees on defining which technology they should opt for. By the time they have decided on a specific technology, it is nearly obsolete. Technological solutions are important but the data used by these technological solutions and more specifically its granularity is key.

    Having said that, Blockchain technology is in my view a great technology cities should definitely look into right now. Indeed, it should enable them to store much greater amounts of data and the high level of granularity if provides to organisations would allow them to define much more efficient and targeted energy efficient policies.

    It is no longer about old fashioned datamarts storing large amounts data nobody can use easily but about technology like blockchain which enable organisations to store even greater amounts of data and use it in a much smarter way thanks to its ability to retrieve data much more easily.

    I do hope that governments embrace this new technology as soon as possible to contribute to a substantial reduction of carbon emissions.

    Liked by 2 people

    1. Luka,

      Reading your post enticed me to look into blockchain and the sustainable cities development.

      The World Bank mentions blockchain as one of the Top 7 disruptive technologies for cities https://blogs.worldbank.org/sustainablecities/top-7-disruptive-technologies-cities.

      They explain how technology is triggering fundamental disruptions and transforming the delivery of services by cities to their citizens.

      Other technological disruptions are:

      – 5G mobile networks
      – Artificial intelligence / machine learning / Big Data
      – Autonomous vehicles
      – Low-cost space exploration, micro-satellites
      – Biometrics, digital ID and digital payments
      – Drones

      The one which caught my attention is drones since I came across those a few years ago when discussing their use for catastrophe risk management with my husband.

      So, after carrying out a quick internet search, I came across fascinating material on this topic and thought that you may find this video interesting.
      https://www.bing.com/videos/search?q=how+to+use+drones+for+cities+development&docid=608010764046372692&mid=3BBD427F4B3FE01252743BBD427F4B3FE0125274&view=detail&FORM=VIREHT

      I had heard of cargo drones but not thought of drones as a tool to help decongest cities!

      Like

  2. I always enjoy reading your posts – so insightful and clear to understand. Okay so the question I have is how does a city like Dubai aim for zero carbon when it has one of the major airline hubs in the world in its neighbourhood ? Who does the data analysis – Dubai or where the airline is based ? How can Dubai leverage the major airlines to improve in their carbon efforts therefore creating a positive outcome for Dubai ? I look forward to your next posting 🙂

    Liked by 1 person

    1. Thanks for the kind words 🙂 That’s a great point you made and it’s addressed in the Carbon Abatement Strategy 2021… however we do focus on road transport first as it represents about 60% of all sources of pollutants. Analysis is done by a specialist organization on the topic called Dubai Carbon. As for carbon deduction, we’re right now moving from 99% gas to 25% solar by 2030 and 75% clean by 2050, as energy generation is largest in GHG emissions. It’s an exciting time here and things that took/take decades elsewhere move here at breakneck speed sometimes 🙂

      Like

      1. That’s great to hear – it’s never going to be just Dubai solving the issues that arrive on their door step. I wouldn’t have thought on road transport first in comparison to air traffic but the issue of pollutants needs to be addressed. If Dubai can make the change then there is no reason why the rest of the world can’t follow – OPEC may not be so supportive though…….the challenge of getting all the levers of change to work in unionism.

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  4. Very interesting post! Indeed, I believe one of the problem is that most cities (maybe not Dubai) but let’s say European ones, are organised in an old fashion way. Let’s take Paris for example, we have a subway system which has been built in 1900. Today, it transports 6 millions passengers a day.
    The 600 km of waste water sewerage system dates back from 1878 and so does the housing system.

    How can a city like Paris, who suffers from overpopulation, become a zero carbon city?

    I wonder if acquiring existing data, extracting useful information and transforming it into actionable knowledge to facilitate implementation of set policies and strategies will be enough.
    But one thing is sure: it will be useful and might lead to a better understanding of the difficulties the city is facing.

    It’s only by understanding our problems that we can address them!

    It may be easier for younger cities to use blockchain. Indeed, in november, the government of Australia announced an AU$8 million fund to begin a blockchain project in the city of Fremantle..
    “The project, which involves academic, infrastructure and technology partners, will assess how cities can use blockchain technology and data analytics to integrate distributed energy and water systems. The federal funding comes as part of the government’s inaugural Smart Cities and Suburbs Program which aims to solve practical problems.”
    It will involve a large solar and water treatment setup that will demonstrate how blockchain technology could be used to coordinate smart grids in cities.

    However, one last thought is that some blockchains consume a lot of energy and have an important carbon footprint. The energy footprint of bitcoin, for example, which each unit weighs an average of 3 tonnes C02, is roughly similar to Ireland’s carbon footprint.

    City governments should therefore learn to efficiently use some well-chosen applied data science in order to become more efficient, effective and evidence-based.

    Liked by 1 person

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