Automating the War on Noise Pollution


Article by Linda Poon: “Any city dweller is no stranger to the frequent revving of motorbikes and car engines, made all the more intolerable after the months of silence during pandemic lockdowns. Some cities have decided to take action. 

Paris police set up an anti-noise patrol in 2020 to ticket motorists whose vehicles exceed a certain decibel level, and soon, the city will start piloting the use of noise sensors in two neighborhoods. Called Medusa, each device uses four microphones to detect and measure noise levels, and two cameras to help authorities track down the culprit. No decibel threshold or fines will be set during the three-month trial period, according to French newspaper Liberation, but it’ll test the potentials and limits of automating the war on sound pollution.

Cities like Toronto and Philadelphia are also considering deploying similar tools. By now, research has been mounting about the health effects of continuous noise exposure, including links to high blood pressure and heart disease, and to poor mental health. And for years, many cities have been tackling noise through ordinances and urban design, including various bans on leaf blowers, on construction at certain hours and on cars. Some have even hired “night mayors” to, among other things, address complaints about after-hours noise.

But enforcement, even with the help of simple camera-and-noise radars, has been a challenge. Since 2018,  the Canadian city of Edmonton has been piloting the use of four radars attached to light poles at busy intersections in the downtown area. A 2021 report on the second phase of the project completed in 2020, found that officials had to manually sift through the data to take out noise made by, say, sirens. And the recordings didn’t always provide strong enough evidence against the offender in court. It was also costly: The pilot cost taxpayers $192,000, while fines generated a little more than half that amount, according to CTV News Edmonton.

Those obstacles have made noise pollution an increasingly popular target for smart city innovation, with companies and researchers looking to make environmental monitoring systems do more than just measure decibel levels…(More)”.

A tale of two labs: Rethinking urban living labs for advancing citizen engagement in food system transformations


Paper by Anke Brons et al: “Citizen engagement is heralded as essential for food democracy and equality, yet the implementation of inclusive citizen engagement mechanisms in urban food systems governance has lagged behind. This paper aims to further the agenda of citizen engagement in the transformation towards healthy and sustainable urban food systems by offering a conceptual reflection on urban living labs (ULLs) as a methodological platform. Over the past decades, ULLs have become increasingly popular to actively engage citizens in methodological testbeds for innovations within real-world settings. The paper proposes that ULLs as a tool for inclusive citizen engagement can be utilized in two ways: (i) the ULL as the daily life of which citizens are the experts, aimed at uncovering the unreflexive agency of a highly diverse population in co-shaping the food system and (ii) the ULL as a break with daily life aimed at facilitating reflexive agency in (re)shaping food futures. We argue that both ULL approaches have the potential to facilitate inclusive citizen engagement in different ways by strengthening the breadth and the depth of citizen engagement respectively. The paper concludes by proposing a sequential implementation of the two types of ULL, paying attention to spatial configurations and the short-termed nature of ULLs….(More)”.

Cities and the Climate-Data Gap


Article by Robert Muggah and Carlo Ratti: “With cities facing disastrous climate stresses and shocks in the coming years, one would think they would be rushing to implement mitigation and adaptation strategies. Yet most urban residents are only dimly aware of the risks, because their cities’ mayors, managers, and councils are not collecting or analyzing the right kinds of information.

With more governments adopting strategies to reduce greenhouse-gas (GHG) emissions, cities everywhere need to get better at collecting and interpreting climate data. More than 11,000 cities have already signed up to a global covenant to tackle climate change and manage the transition to clean energy, and many aim to achieve net-zero emissions before their national counterparts do. Yet virtually all of them still lack the basic tools for measuring progress.

Closing this gap has become urgent, because climate change is already disrupting cities around the world. Cities on almost every continent are being ravaged by heat waves, fires, typhoons, and hurricanes. Coastal cities are being battered by severe flooding connected to sea-level rise. And some megacities and their sprawling peripheries are being reconsidered altogether, as in the case of Indonesia’s $34 billion plan to move its capital from Jakarta to Borneo by 2024.

Worse, while many subnational governments are setting ambitious new green targets, over 40% of cities (home to some 400 million people) still have no meaningful climate-preparedness strategy. And this share is even lower in Africa and Asia – where an estimated 90% of all future urbanization in the next three decades is expected to occur.

We know that climate-preparedness plans are closely correlated with investment in climate action including nature-based solutions and systematic resilience. But strategies alone are not enough. We also need to scale up data-driven monitoring platforms. Powered by satellites and sensors, these systems can track temperatures inside and outside buildings, alert city dwellers to air-quality issues, and provide high-resolution information on concentrations of specific GHGs (carbon dioxide and nitrogen dioxide) and particulate matter…(More)”.

The AI Carbon Footprint and Responsibilities of AI Scientists


Paper by Guglielmo Tamburrini: “This article examines ethical implications of the growing AI carbon footprint, focusing on the fair distribution of prospective responsibilities among groups of involved actors. First, major groups of involved actors are identified, including AI scientists, AI industry, and AI infrastructure providers, from datacenters to electrical energy suppliers. Second, responsibilities of AI scientists concerning climate warming mitigation actions are disentangled from responsibilities of other involved actors. Third, to implement these responsibilities nudging interventions are suggested, leveraging on AI competitive games which would prize research combining better system accuracy with greater computational and energy efficiency. Finally, in addition to the AI carbon footprint, it is argued that another ethical issue with a genuinely global dimension is now emerging in the AI ethics agenda. This issue concerns the threats that AI-powered cyberweapons pose to the digital command, control, and communication infrastructure of nuclear weapons systems…(More)”.

Climate Change and AI: Recommendations for Government


Press Release: “A new report, developed by the Centre for AI & Climate and Climate Change AI for the Global Partnership on AI (GPAI), calls for governments to recognise the potential for artificial intelligence (AI) to accelerate the transition to net zero, and to put in place the support needed to advance AI-for-climate solutions. The report is being presented at COP26 today.

The report, Climate Change and AI: Recommendations for Government, highlights 48 specific recommendations for how governments can both support the application of AI to climate challenges and address the climate-related risks that AI poses.

The report was commissioned by the Global Partnership on AI (GPAI), a partnership between 18 countries and the EU that brings together experts from across countries and sectors to help shape the development of AI.

AI is already being used to support climate action in a wide range of use cases, several of which the report highlights. These include:

  • National Grid ESO, which has used AI to double the accuracy of its forecasts of UK electricity demand. Radically improving forecasts of electricity demand and renewable energy generation will be critical in enabling greater proportions of renewable energy on electricity grids.
  • The UN Satellite Centre (UNOSAT), which has developed the FloodAI system that delivers high-frequency flood reports. FloodAI’s reports, which use a combination of satellite data and machine learning, have improved the response to climate-related disasters in Asia and Africa.
  • Climate TRACE, a global coalition of organizations, which has radically improved the transparency and accuracy of emissions monitoring by leveraging AI algorithms and data from more than 300 satellites and 11,000 sensors.

The authors also detail critical bottlenecks that are impeding faster adoption. To address these, the report calls for governments to:

  • Improve data ecosystems in sectors critical to climate transition, including the development of digital twins in e.g. the energy sector.
  • Increase support for research, innovation, and deployment through targeted funding, infrastructure, and improved market designs.
  • Make climate change a central consideration in AI strategies to shape the responsible development of AI as a whole.
  • Support greater international collaboration and capacity building to facilitate the development and governance of AI-for-climate solutions….(More)”.

Countries’ climate pledges built on flawed data


Article by Chris Mooney, Juliet Eilperin, Desmond Butler, John Muyskens, Anu Narayanswamy, and Naema Ahmed: “Across the world, many countries underreporttheir greenhouse gas emissions in their reports to the United Nations, a Washington Post investigation has found. An examination of 196 country reports reveals a giant gap between what nations declare their emissions to be versus the greenhouse gases they are sending into the atmosphere. The gap ranges from at least 8.5 billion to as high as 13.3 billion tons a year of underreported emissions — big enough to move the needle on how much the Earth will warm.

The plan to save the world from the worst of climate change is built on data. But the data the world is relying on is inaccurate.

“If we don’t know the state of emissions today, we don’t know whether we’re cutting emissions meaningfully and substantially,” said Rob Jackson, a professor at Stanford University and chair of the Global Carbon Project, a collaboration of hundreds of researchers. “The atmosphere ultimately is the truth. The atmosphere is what we care about. The concentration of methane and other greenhouse gases in the atmosphere is what’s affecting climate.”

At the low end, the gap is larger than the yearly emissions of the United States. At the high end, it approaches the emissions of China and comprises 23 percent of humanity’s total contribution to the planet’s warming, The Post found…

A new generation of sophisticated satellites that can measure greenhouse gases are now orbiting Earth, and they can detect massive methane leaks. Data from the International Energy Agency (IEA) lists Russia as the world’s top oil and gas methane emitter, but that’s not what Russia reports to the United Nations. Its official numbers fall millions of tons shy of what independent scientific analyses show, a Post investigation found. Many oil and gas producers in the Persian Gulf region, such as the United Arab Emirates and Qatar, also report very small levels of oil and gas methane emission that don’t line up with other scientific data sets.

“It’s hard to imagine how policymakers are going to pursue ambitious climate actions if they’re not getting the right data from national governments on how big the problem is,” said Glenn Hurowitz, chief executive of Mighty Earth, an environmental advocacy group….(More)”.

A Climate Equity Agenda Informed by Community Brilliance


Essay by Jalonne L. White-Newsome: “Even with decades of data, state-of-the-art tools and prediction technologies, and clear signals that the impacts of climate change pose a threat to public health, there is still a major disconnect that is allowing extreme weather events to disrupt the health and well-being of low-income communities and people of color across the United States. Centering the health and well-being of these communities within cross-sector partnerships between residents, scientists, government, industry, and philanthropy can drive climate adaptation and resilience…(More)”

Launch of UN Biodiversity Lab 2.0: Spatial data and the future of our planet


Press Release: “…The UNBL 2.0 is a free, open-source platform that enables governments and others to access state-of-the-art maps and data on nature, climate change, and human development in new ways to generate insight for nature and sustainable development. It is freely available online to governments and other stakeholders as a digital public good…

The UNBL 2.0 release responds to a known global gap in the types of spatial data and tools, providing an invaluable resource to nations around the world to take transformative action. Users can now access over 400 of the world’s best available global spatial data layers; create secure workspaces to incorporate national data alongside global data; use curated data collections to generate insight for action; and more. Without specialized tools or training, decision-makers can leverage the power of spatial data to support priority-setting and the implementation of nature-based solutions. Dynamic metrics and indicators on the state of our planet are also available….(More)”.

The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations


Paper by Josh Cowls, Andreas Tsamados, Mariarosaria Taddeo & Luciano Floridi: “In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment….(More)”.

Solutions to Plastic Pollution: A Conceptual Framework to Tackle a Wicked Problem


Chapter by Martin Wagner: “There is a broad willingness to act on global plastic pollution as well as a plethora of available technological, governance, and societal solutions. However, this solution space has not been organized in a larger conceptual framework yet. In this essay, I propose such a framework, place the available solutions in it, and use it to explore the value-laden issues that motivate the diverse problem formulations and the preferences for certain solutions by certain actors. To set the scene, I argue that plastic pollution shares the key features of wicked problems, namely, scientific, political, and societal complexity and uncertainty as well as a diversity in the views of actors. To explore the latter, plastic pollution can be framed as a waste, resource, economic, societal, or systemic problem.

Doing so results in different and sometimes conflicting sets of preferred solutions, including improving waste management; recycling and reuse; implementing levies, taxes, and bans as well as ethical consumerism; raising awareness; and a transition to a circular economy. Deciding which of these solutions is desirable is, again, not a purely rational choice. Accordingly, the social deliberations on these solution sets can be organized across four scales of change. At the geographic and time scales, we need to clarify where and when we want to solve the plastic problem. On the scale of responsibility, we need to clarify who is accountable, has the means to make change, and carries the costs. At the magnitude scale, we need to discuss which level of change we desire on a spectrum of status quo to revolution. All these issues are inherently linked to value judgments and worldviews that must, therefore, be part of an open and inclusive debate to facilitate solving the wicked problem of plastic pollution…(More)”.