Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning 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 machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.

Tackling Climate Change with Machine Learning

Simulations of stellar convection with CO5BOLD

Global greenhouse gas emissions can be traced to five economic sectors: energy, industry, buildings, transport and AFOLU (agriculture, forestry and other land uses). In this topical review we synthesize the literature to explain recent trends in global and regional emissions in each of these sectors. To contextualise our review, we present estimates of greenhouse gas emissions trends by sector from 1990 to 2018, describing the major sources of emissions growth, stability and decline across ten global regions. Both the literature and data emphasize limited progress towards reducing greenhouse gas emissions. The prominent global pattern is a continuation of underlying drivers with few signs of emerging limits to demand, nor of a deep shift towards the delivery of low and zero carbon services across sectors. We observe a moderate decarbonisation of energy systems in Europe and North America, driven by fuel switching and the increasing penetration of renewables. By contrast, in rapidly industrialising regions, fossil-based energy systems have continuously expanded, only very recently slowing down in their growth. Strong demand for materials, floor area, energy services and travel have driven emissions growth in the industry, buildings and transport sectors, particularly in Eastern Asia, Southern Asia and South-East Asia. An expansion of agriculture into carbon-dense tropical forest areas has driven recent increases in AFOLU emissions in Latin America, South-East Asia and Africa. Identifying, understanding, and tackling the most persistent and climate-damaging trends across sectors is a fundamental concern for research and policy as humanity treads deeper into the Anthropocene.

https://iopscience.iop.org/article/10.1088/1748-9326/abee4e/pdf

A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018

Transportation in a 100% renewable energy system

Precipitation of energetic particles into the atmosphere greatly disturbs the chemical composition from the upper stratosphere to the lower thermosphere. Most important are changes to the budget of atmospheric nitric oxides (NOx = N, NO, NO2) and to atmospheric reactive hydrogen oxides (HOx = H, OH, HO2), which both contribute to ozone loss in the stratosphere and mesosphere. The impact of energetic particle precipitation on the chemical composition of the atmosphere has been studied since the 1960s, and there are a number of observations as well as model studies concerning especially the auroral impact and large solar particle events. Changes to the NOx budget due to energetic particle precipitation can be quite long-lived during polar winter and can then be transported down into the lower mesosphere and stratosphere, where NOx is one of the main participants in catalytic ozone destruction. Energetic particle precipitation can also affect temperatures and dynamics of the atmosphere from the source region down to the stratosphere and possibly even down to the surface, due to a coupling of chemical composition changes affecting atmospheric heating and cooling rates, the mean circulation, and wave propagation and breaking. Thus, energetic particle precipitation impacts have been implemented in chemistry-climate models reaching from the surface up to the mesosphere or lower thermosphere. However, there are still a number of open questions in the theoretical description of the energetic particle precipitation impact; the most important are uncertainties in the formation rate of different NOx species due to energetic particle precipitation, and the complex coupling between chemical changes, atmospheric heating and cooling rates, and atmospheric dynamics.

/pdf/energetic-particle-precipitation-and-the-chemistry-of-the-fitpttl7l5.pdf

Energetic Particle Precipitation and the Chemistry of the Mesosphere/Lower Thermosphere

Global transportation energy use is steeply rising, mainly as a result of increasing population and economic activity. Petroleum fuels remain the dominant energy source, reflecting advantages such as high energy density, low cost, and market availability. The movement of people and freight makes a major contribution to economic development and social well-being, but it also negatively impacts climate change, air quality, health, social cohesion, and safety. Following a review published 20 years ago in the Annual Review of Environment and Resources (then named the Annual Review of Energy and the Environment) by Lee Schipper, we examine current trends and potential futures, revising several major global transport/energy reports. There are significant opportunities to slow travel growth and improve efficiency. Alternatives to petroleum exist but have different characteristics in terms of availability, cost, distribution, infrastructure, storage, and public acceptability. The transition to low-carbon equitabl...

https://www.annualreviews.org/doi/pdf/10.1146/annurev-environ-031913-100450

Geetam Tiwari

Papers

Energy for Transport