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Tracking Emissions with Remote Sensing, with Gavin McCormick

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Conteúdo fornecido por Project Climate, Center for Law, Energy & the Environment, Berkeley Law and Berkeley Law. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Project Climate, Center for Law, Energy & the Environment, Berkeley Law and Berkeley Law ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

The Need to Accurately Quantify Emissions

As we begin to come to terms with the reality of the fossil fuel industry’s role in climate change, many policymakers are looking towards market-based mechanisms to curb the level of emissions released by harmful polluters. Market-based mechanisms include taxing pollution directly (through a carbon tax) or implementing a cap and trade system. Under the Clean Air Act and other laws, power plants must report air emissions from their operations. Unfortunately, not all emissions are reported or fully monitored, including emissions of greenhouse gases, leaving regulators with incomplete information. Without accurate reports on emissions, policymakers cannot create effective policy. Some companies may use offsets to mitigate greenhouse gas emissions from their operations. However, many offsets have proven to be ineffective, resulting in market inefficiencies and hindering our ability to effectively enact climate policy. To gain a more accurate picture of climate emissions, climate scientists and others are beginning to create innovative strategies to determine factories' GHG emissions without relying on the polluter themselves through the use of satellite data.

A Bird’s Eye View Solution

Satellite imagery provides a potentially publicly accessible way to view emissions data, increase emissions transparency, and put pressure on polluters to change their behavior. Organizations like WattTime, a non-profit artificial intelligence firm, have begun to train AI to use satellite imagery data and emissions numbers from historical data in order to track global air pollution across different sources. After images have been taken, WattTime applies various algorithms to detect the levels of emissions based on visible smoke, heat, and NO2. WattTime started out of Automated Emissions Reduction (AER) software, which uses machine learning to figure out the least-carbon intensive time to use electricity and automatically switches appliances to use electricity during those times of day. This new method of obtaining emissions data has many potential applications towards fighting climate change.

Why It’s Worth Considering

Tracking real-time emissions based on satellite imagery has a variety of benefits in achieving tangible pollution reduction. Climate policy and action are dependent upon accurate reports of emissions levels. Data from satellite imagery provides independent data making it more difficult to underreport emissions. More accurate and independent emissions data will incentivize greater focus and action on mitigation and will make enforcement of emissions limits easier.

Beyond the potential advantages for climate policy, public access to data is essential in informing consumers on the impacts of their individual choices. Providing people with a better sense of the environmental impacts of the goods they consume can change consumer choices. Greater transparency around emissions can thus help make climate policy more effective.

Satellite imagery data can also be used to identify areas that may be well located to support renewable energy development and to monitor the impacts of those developments. Additionally, data taken from satellite imagery can help identify sources of raw materials that have lower and higher environmental impact, potentially assisting in achieving supply chain decarbonization.

The Reality

Although remote sensing has great advantages, there are still important challenges to note. In terms of the mechanics of satellite imagery, accuracy can be hindered due to limited temporal and spatial resolution, high levels of cloudiness, and increased vegetation that may block images. The number and configuration of satellites also impacts the data. Further, it remains to be seen whether governments will try and block the use of satellite data in their jurisdictions.

About Our Guest

Gavin McCormick is the co-founder of WattTime and executive director of Climate TRACE. As both an entrepreneur and academic, he is currently working towards developing efficient, low-cost ways to assist in the transition to renewable energy. McCormick is hopeful that the use of satellite imagery data can mark a positive turning point in the fight against the climate crisis.

Further Reading

For a transcript of this episode, please visit https://climatebreak.org/tracking-emissions-with-remote-sensing-with-gavin-mccormick/

  continue reading

173 episódios

Artwork
iconCompartilhar
 
Manage episode 407884475 series 3382676
Conteúdo fornecido por Project Climate, Center for Law, Energy & the Environment, Berkeley Law and Berkeley Law. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Project Climate, Center for Law, Energy & the Environment, Berkeley Law and Berkeley Law ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

The Need to Accurately Quantify Emissions

As we begin to come to terms with the reality of the fossil fuel industry’s role in climate change, many policymakers are looking towards market-based mechanisms to curb the level of emissions released by harmful polluters. Market-based mechanisms include taxing pollution directly (through a carbon tax) or implementing a cap and trade system. Under the Clean Air Act and other laws, power plants must report air emissions from their operations. Unfortunately, not all emissions are reported or fully monitored, including emissions of greenhouse gases, leaving regulators with incomplete information. Without accurate reports on emissions, policymakers cannot create effective policy. Some companies may use offsets to mitigate greenhouse gas emissions from their operations. However, many offsets have proven to be ineffective, resulting in market inefficiencies and hindering our ability to effectively enact climate policy. To gain a more accurate picture of climate emissions, climate scientists and others are beginning to create innovative strategies to determine factories' GHG emissions without relying on the polluter themselves through the use of satellite data.

A Bird’s Eye View Solution

Satellite imagery provides a potentially publicly accessible way to view emissions data, increase emissions transparency, and put pressure on polluters to change their behavior. Organizations like WattTime, a non-profit artificial intelligence firm, have begun to train AI to use satellite imagery data and emissions numbers from historical data in order to track global air pollution across different sources. After images have been taken, WattTime applies various algorithms to detect the levels of emissions based on visible smoke, heat, and NO2. WattTime started out of Automated Emissions Reduction (AER) software, which uses machine learning to figure out the least-carbon intensive time to use electricity and automatically switches appliances to use electricity during those times of day. This new method of obtaining emissions data has many potential applications towards fighting climate change.

Why It’s Worth Considering

Tracking real-time emissions based on satellite imagery has a variety of benefits in achieving tangible pollution reduction. Climate policy and action are dependent upon accurate reports of emissions levels. Data from satellite imagery provides independent data making it more difficult to underreport emissions. More accurate and independent emissions data will incentivize greater focus and action on mitigation and will make enforcement of emissions limits easier.

Beyond the potential advantages for climate policy, public access to data is essential in informing consumers on the impacts of their individual choices. Providing people with a better sense of the environmental impacts of the goods they consume can change consumer choices. Greater transparency around emissions can thus help make climate policy more effective.

Satellite imagery data can also be used to identify areas that may be well located to support renewable energy development and to monitor the impacts of those developments. Additionally, data taken from satellite imagery can help identify sources of raw materials that have lower and higher environmental impact, potentially assisting in achieving supply chain decarbonization.

The Reality

Although remote sensing has great advantages, there are still important challenges to note. In terms of the mechanics of satellite imagery, accuracy can be hindered due to limited temporal and spatial resolution, high levels of cloudiness, and increased vegetation that may block images. The number and configuration of satellites also impacts the data. Further, it remains to be seen whether governments will try and block the use of satellite data in their jurisdictions.

About Our Guest

Gavin McCormick is the co-founder of WattTime and executive director of Climate TRACE. As both an entrepreneur and academic, he is currently working towards developing efficient, low-cost ways to assist in the transition to renewable energy. McCormick is hopeful that the use of satellite imagery data can mark a positive turning point in the fight against the climate crisis.

Further Reading

For a transcript of this episode, please visit https://climatebreak.org/tracking-emissions-with-remote-sensing-with-gavin-mccormick/

  continue reading

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