Tackling climate change with machine learning

 Rolnick D, Donti PL, Kaack LH, Kochanski K, Lacoste A, Sankaran K, Ross AS, Milojevic-Dupont N, Jaques N, Waldman-Brown A, et al. (2022) Tackling climate change with machine learning. ACM Computing Surveys (CSUR) 55(2):1–96.

How to Avoid a Climate Disaster (如何避免氣候災難)

Bill Gates, How to Avoid a Climate Disaster: The Solutions We Have and the Breakthroughs We Need, Random House, February 23, 2021.

Machine-Guided Discovery of a Real-World Rogue Wave (瘋狗浪) Model

台北天文館，AI 找到如何預測巨浪的公式，2023 年 12 月 02 日 

Dion Häfner, Johannes Gemmrich, Markus Jochum, Machine-Guided Discovery of a Real-World Rogue Wave Model,  Proceedings of the National Academy of Sciences (2023), 120(48). (arXiv, data, code)

Artificial Intelligence and the Future of Universities

Dimitris Bertsimas, Artificial Intelligence and the Future of Universities, Texas A&M Institute of Data Science, 2023.

Optimization of carbon emission reduction paths in the low-carbon power dispatching process

J. Jin, Q. Wen, S. Cheng, Y. Qiu, X. Zhang, and X. Guo, Optimization of carbon emission reduction paths in the low-carbon power dispatching process, Renewable Energy, Volume 188, April 2022, Pages 425-436.

With the development of low-carbon electricity, the scale of wind power is expanding continuously and carbon trading for thermal power is popularized gradually. In this context, the optimal combination of thermal power and wind power needs to be further promoted to build up the synergy of carbon reduction. To solve such low-carbon power dispatching problem in the wind power integrated system imported with carbon trading, this paper firstly presents a distributed robust optimization model. Next, the scenario-based characterization of wind power and allocation methods of initial carbon emission rights are discussed for model solution. Finally, empirical analysis shows that: (1) the proposed model proves to be rational and feasible, which can accomplish a good compromise between economy, environment and robustness of power system, (2) wind power integration dose help carbon reduction ratio to achieve up to 50% with lower operating costs and carbon emissions, while carbon trading is really an effective approach for tapping greater carbon reduction potential of thermal power, and (3) more reasonable proportions of wind power in coping with its inherent uncertainties, and more appropriate cooperation modes of thermal power for dealing with carbon trading unpredictability are determined under the different requirement of carbon reduction.

National energy system optimization modelling for decarbonization pathways analysis

F.A. Plazas-Niño, N.R. Ortiz-Pimiento, E.G. Montes-Páez, National energy system optimization modelling for decarbonization pathways analysis: A systematic literature review, Renewable and Sustainable Energy Reviews, Volume 162, July 2022, 112406.

Energy planning is fundamental to ensure a sustainable, affordable, and reliable energy mix for the future. Energy system optimization models (ESOMs) are the accurate tools to guide decision-making in national energy planning. This article presents a systematic literature review covering the main ESOMs, the input and output data involved, the trends in scenario analysis for decarbonization pathways in national economies, and the challenges associated with energy system optimization modelling. The first part introduces the characterization of ESOMs, showing a trend in modelling focused on long-term, multisector, multiperiod, bottom-up, linear programming, and perfect foresight. Secondly, the analysis shows the intensive data requirements, including future demand profiles, fuel price projections, energy potentials, and techno-economic characteristics of technologies. This review also reveals that decarbonization pathways are the principal objective in energy system optimization modelling, including key drivers such as high-share renewable energy integration, energy efficiency increase, sector coupling, and sustainable transport. The last section presents ten challenges and their corresponding opportunities in research, highlighting the improvement of spatiotemporal resolution, transparency, the inclusion of social aspects, the representation of developing country features, and quality and availability data.

Carbon dioxide capture, transport and storage supply chains

Viola Becattini, Paolo Gabrielli, Cristina Antonini, Jordi Campos, Alberto Acquilino, Giovanni Sansavini, Marco Mazzotti, Carbon dioxide capture, transport and storage supply chains: Optimal economic and environmental performance of infrastructure rollout, International Journal of Greenhouse Gas Control, Volume 117, June 2022, 103635.

This work presents a novel optimization framework for the optimal design of carbon capture, transport, and storage supply chains in terms of installation, sizing and operation of carbon dioxide (CO2) capture and transport technologies. The optimal design problem is formulated as a mixed-integer linear program that minimizes the total costs of the supply chains while complying with different emissions reduction pathways over a deployment time horizon of 25 years. All design decisions are time-dependent and are taken with a yearly resolution. Whereas the model is general, here its features are illustrated by designing optimal supply chains to decarbonize the Swiss waste-to-energy sector, for various emission reduction pathways, when up to two storage sites are considered, namely one in the North Sea assumed to be already available and a hypothetical one in Switzerland assumed to be possibly available in the future. Findings show that, unless a domestic storage site becomes available soon, the transport cost is the greatest contribution to the overall costs, followed by the capture cost, while the storage cost plays only a minor role. Pipelines are the most cost-effective mode of transport for large volumes of transported CO2, especially when considering multi-year time horizons for the planning of the supply chains. Ship and barge connections are competitive with pipeline connections, whereas rail and truck connections are cost-optimal only when considering shortsighted time horizons or small volumes of CO2 transported.

Multimodal artificial intelligence

Jessica Leung, Omega Rho Keynote: Artificial Intelligence and the Future of Universities, ORMS Today, 2022.

Léonard Boussioux, Cynthia Zeng, Théo Guénais, and Dimitris Bertsimas, Hurricane Forecasting: A Novel Multimodal Machine Learning Framework, Weather and Forecasting, March 2022, 37(6), pp. 817–831.

Soenksen, L.R., Ma, Y., Zeng, C. et al. Integrated multimodal artificial intelligence framework for healthcare applications. Nature Machine Intelligence 5, 149 (2022). https://doi.org/10.1038/s41746-022-00689-4. (Data and Code)

10 Breakthrough Technologies 2023

 David Rotman, 10 Breakthrough Technologies 2023, MIT Technology Review, January 9, 2023.

Our annual look at 10 Breakthrough Technologies—including CRISPR for high cholesterol, battery recycling, AI that makes images, and the James Webb Space Telescope—that will have a profound effect on our lives. Plus care robots, 3-D printing pioneers, and chasing bugs on the blockchain.

2021 Tesla Impact Report

2021 Tesla Impact Report

Autopilot Safety

In 2021, we recorded 0.22 crashes for every million miles driven in which drivers were using Autopilot technology (Autosteer and active safety features). For drivers who were not using Autopilot technology (no Autosteer and active safety features), we recorded 0.77 crashes for every million miles driven. By comparison, NHTSA’s most recent data shows that in the United States there are 1.81 automobile crashes for every million miles driven.

Tackling Climate Change with Machine Learning

David Rolnic et al., Tackling Climate Change with Machine Learning, ACM Computing Surveys, Volume 55, Issue 2, March 2023, Article No.: 42, pp 1–96, https://doi.org/10.1145/3485128

Climate change is one of the greatest challenges facing humanity, and we, as machine learning (ML) experts, may wonder how we can help. Here we describe how ML can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by ML, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the ML community to join the global effort against climate change.

洗髮精董座投身環保面膜

楊絲貽，「生命有限可留下什麼？」洗髮精董座投身環保面膜，商業周刊第1765期，2021.09.08

「全球品牌都會變綠，遲早而已，」歐萊德董事長葛望平說。

歐萊德是台灣企業中，很早就喊出在一定時間內，承諾達成百分之百再生能源的企業；過去幾年，他們不僅研發出百分之百再生塑膠材料（PCR，Post-Consumer Recycled）製成的洗髮精瓶身、全球第一支再生壓頭，2020年全品項也達成碳中和成果。...

The Future of Supply Chains

Paul Marks, The Future of Supply Chains, Communications of the ACM, July 2021, Vol. 64, No. 7, Pages 19-21.

Today's supply chains are labor-intensive and expensive to run. A number of autonomous systems that reduce the human factor are about to change all that.

What do the sidewalks around us, the airspace above us, interstate freeways, and deep ocean shipping lanes have in common? The answer is that they are all places where developers of autonomous technology are trying to revolutionize the economics of supply chains. The plan is to use robotic technology to deliver anything from packages to take-out food, groceries, or bulk freight in ways that can reduce the logistics industry's dependence on that most expensive of supply chain costs: human labor. if the use of electric drivetrains can cut carbon emissions too, so much the better.

Bearing Brings AI-Powered Operational Efficiencies to the Maritime Shipping Industry

Bearing.ai, Bearing Brings AI-Powered Operational Efficiencies to the Maritime Shipping Industry, February 16, 2021.

Bearing exits stealth mode and launches its AI-driven operations optimization platform, which provides a wide range of actionable insights to shipping companies, leading to improved efficiency, safety and reduced gas greenhouse emissions. Bearing’s platform is powered by highly accurate ship performance models built on real-world data, allowing it to predict fuel consumption, speed, and other performance factors much more accurately than existing solutions on the market. (e.g., Bearing’s typical prediction accuracy for fuel consumption is over 98% per voyage, compared to a typical existing accuracy of 80%).

Greta Thunberg - Inspiring Others to Take a Stand Against Climate Change

 Greta Thunberg - Inspiring Others to Take a Stand Against Climate Change | The Daily Show

2020 year in review by McKinsey

McKinsey, 2020 year in review, 2020/12/28.

川湖回收水、防空污連閃兩危機

侯良儒，中小企業也能部署！川湖回收水、防空污連閃兩危機，商業周刊第1709期，2020-08-13

不接受砍價決心轉型

從代工轉做品牌，先投入無毒電鍍

 

處理廢水選最難的路 

花二千萬建回收廠， 遇旱保住訂單

當時 ，川湖只要停工一天 ，就是一千二百萬元的損失 ；同時，假如無法出貨 ，客戶便會轉向中國的工廠下單。

成本和風險的抉擇，還發生在五年前

 

警覺空汙法規將趨嚴 

精算長期成本後，換成天然氣鍋爐

Decisive actions to emerge stronger in the next normal

Kevin Sneader, Shubham Singhal, and Bob Sternfels, What now? Decisive actions to emerge stronger in the next normal, McKinsey & Company, September 2020 (pdf)

1. Think of the return as a muscle
2. Focus on high-impact actions
3. Rebuild for speed
4. Reimagine the workforce from the top down
5. Make bold portfolio moves
6. Reset technology plans
7. Rethink the global footprint
8. Take the lead on climate and sustainability
9. Think about the role of regulation and government
10. Make purpose part of everything

ESG now a third of MioTech’s A.I. business

MioTech, ESG 101

digfin group, ESG now a third of MioTech’s A.I. business,  September 9, 2019.

MioTech builds A.I.-based solutions to help buy sides get insight from data analytics, and to help sell-side research departments and private banks’ relationship managers tell data-driven stories. It bases its service on building a library of cross-references (a “knowledge graph”) around a multitude of data points on Asian companies. The idea is to use big-data correlations to spot patterns....

Recyclers turn to AI robots after waste import bans

Adam Green, Recyclers turn to AI robots after waste import bans, Financial Times, 2020/7/1.

To recycle in a cost-effective, comprehensive and safe way, goods must be broken down into their constituent commodities to be sold on, in a process that has been likened to “unscrambling an egg”....

Automation often stokes anxiety about mass unemployment, but the recycling sector has been struggling to find enough workers. The US waste and recycling industry has suffered labour shortages in recent years. By limiting the influx of foreign workers to do jobs locals are not keen on, the UK’s departure from the EU is expected to hit the UK’s waste management sector hard. 

“This technology is creating a sustainable workforce for jobs that aren’t being filled,” says Mr Wirth. “These are the dull, dirty, dangerous kind of jobs which robotics and AI is perfect for.”