Greenhouse gas emissionsGreenhouse gas emissions (abbreviated as GHG emissions) from human activities strengthen the greenhouse effect, contributing to climate change. Carbon dioxide (), from burning fossil fuels such as coal, oil, and natural gas, is one of the most important factors in causing climate change. The largest emitters are China followed by the US, although the United States has higher emissions per capita. The main producers fueling the emissions globally are large oil and gas companies.
Emissions tradingEmissions trading is a market-based approach to controlling pollution by providing economic incentives for reducing the emissions of pollutants. The concept is also known as cap and trade (CAT) or emissions trading scheme (ETS). Carbon emission trading for and other greenhouse gases has been introduced in China, the European Union and other countries as a key tool for climate change mitigation. Other schemes include sulfur dioxide and other pollutants.
Vehicle emission standardEmission standards are the legal requirements governing air pollutants released into the atmosphere. Emission standards set quantitative limits on the permissible amount of specific air pollutants that may be released from specific sources over specific timeframes. They are generally designed to achieve air quality standards and to protect human life. Different regions and countries have different standards for vehicle emissions. Many emissions standards focus on regulating pollutants released by automobiles (motor cars) and other powered vehicles.
Carbon emission tradingEmission trading (ETS) for carbon dioxide (CO2) and other greenhouse gases (GHG) is a form of carbon pricing; also known as cap and trade (CAT) or carbon pricing. It is an approach to limit climate change by creating a market with limited allowances for emissions. This can lower competitiveness of fossil fuels and accelerate investments into low carbon sources of energy such as wind power and photovoltaics. Fossil fuels are the main driver for climate change. They account for 89% of all CO2 emissions and 68% of all GHG emissions.
Emission intensityLife-cycle greenhouse gas emissions of energy sources An emission intensity (also carbon intensity or C.I.) is the emission rate of a given pollutant relative to the intensity of a specific activity, or an industrial production process; for example grams of carbon dioxide released per megajoule of energy produced, or the ratio of greenhouse gas emissions produced to gross domestic product (GDP).
Methane emissionsIncreasing methane emissions are a major contributor to the rising concentration of greenhouse gases in Earth's atmosphere, and are responsible for up to one-third of near-term global heating. During 2019, about 60% (360 million tons) of methane released globally was from human activities, while natural sources contributed about 40% (230 million tons). Reducing methane emissions by capturing and utilizing the gas can produce simultaneous environmental and economic benefits.
Embedded emissionsOne way of attributing greenhouse gas (GHG) emissions is to measure the embedded emissions of goods that are being consumed (also referred to as "embodied emissions", "embodied carbon emissions", or "embodied carbon"). This is different from the question of to what extent the policies of one country to reduce emissions affect emissions in other countries (the "spillover effect" and "carbon leakage" of an emissions reduction policy). The UNFCCC measures emissions according to production, rather than consumption.
Nationally determined contributionA nationally determined contribution (NDC) or intended nationally determined contribution (INDC) is a non-binding national plan highlighting climate change mitigation, including climate-related targets for greenhouse gas emission reductions. These plans also include policies and measures governments aim to implement in response to climate change and as a contribution to achieve the global targets set out in the Paris Agreement. NDCs are the first greenhouse gas targets under the UNFCCC that apply equally to both developed and developing countries.
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
ResearchResearch is "creative and systematic work undertaken to increase the stock of knowledge". It involves the collection, organization and analysis of evidence to increase understanding of a topic, characterized by a particular attentiveness to controlling sources of bias and error. These activities are characterized by accounting and controlling for biases. A research project may be an expansion on past work in the field. To test the validity of instruments, procedures, or experiments, research may replicate elements of prior projects or the project as a whole.
Environmental justiceEnvironmental justice or eco-justice, is a social movement to address environmental injustice, which occurs when poor and marginalized communities are harmed by hazardous waste, resource extraction, and other land uses from which they do not benefit. The movement has generated hundreds of studies showing that exposure to environmental harm is inequitably distributed. The movement began in the United States in the 1980s. It was heavily influenced by the American civil rights movement and focused on environmental racism within rich countries.
Vehicle emissions controlVehicle emissions control is the study of reducing the emissions produced by motor vehicles, especially internal combustion engines. Emissions of many air pollutants have been shown to have variety of negative effects on public health and the natural environment. Emissions that are principal pollutants of concern include: Hydrocarbons (HC) – A class of burned or partially burned fuel, hydrocarbons are toxins. Hydrocarbons are a major contributor to smog, which can be a major problem in urban areas.
Economic growthEconomic growth can be defined as the increase or improvement in the inflation-adjusted market value of the goods and services produced by an economy in a financial year. Statisticians conventionally measure such growth as the percent rate of increase in the real and nominal gross domestic product (GDP). Growth is usually calculated in real terms – i.e., inflation-adjusted terms – to eliminate the distorting effect of inflation on the prices of goods produced. Measurement of economic growth uses national income accounting.
Nature-based solutionsNature-based solutions (NBS) is the sustainable management and use of natural features and processes to tackle socio-environmental issues. These issues include climate change (mitigation and adaptation), water security, water pollution, food security, human health, biodiversity loss, and disaster risk management. The European Commission's definition of NBS states that these solutions are "inspired and supported by nature, which are cost-effective, simultaneously provide environmental, social and economic benefits and help build resilience.
Climate change mitigationClimate change mitigation is action to limit climate change by reducing emissions of greenhouse gases or removing those gases from the atmosphere. The recent rise in global average temperature is mostly due to emissions from burning fossil fuels such as coal, oil, and natural gas. Mitigation can reduce emissions by transitioning to sustainable energy sources, conserving energy, and increasing efficiency. It is possible to remove carbon dioxide () from the atmosphere by enlarging forests, restoring wetlands and using other natural and technical processes.
EnvironmentalismEnvironmentalism or environmental rights is a broad philosophy, ideology, and social movement about supporting life, habitats, and surroundings. While environmentalism focuses more on the environmental and nature-related aspects of green ideology and politics, ecologism combines the ideology of social ecology and environmentalism. Ecologism is more commonly used in continental European languages, while environmentalism is more commonly used in English but the words have slightly different connotations.
Unsupervised learningUnsupervised learning, is paradigm in machine learning where, in contrast to supervised learning and semi-supervised learning, algorithms learn patterns exclusively from unlabeled data. Neural network tasks are often categorized as discriminative (recognition) or generative (imagination). Often but not always, discriminative tasks use supervised methods and generative tasks use unsupervised (see Venn diagram); however, the separation is very hazy. For example, object recognition favors supervised learning but unsupervised learning can also cluster objects into groups.
European emission standardsThe European emission standards are vehicle emission standards for pollution from the use of new land surface vehicles sold in the European Union and European Economic Area member states and the United Kingdom, and ships in EU waters. The standards are defined in a series of European Union directives staging the progressive introduction of increasingly stringent standards. the standards do not include non-exhaust emissions such as particulates from tyres and brakes.
Intergovernmental Panel on Climate ChangeThe Intergovernmental Panel on Climate Change (IPCC) is an intergovernmental body of the United Nations. Its job is to advance scientific knowledge about climate change caused by human activities. The World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP) established the IPCC in 1988. The United Nations endorsed the creation of the IPCC later that year. It has a secretariat in Geneva, Switzerland, hosted by the WMO. It has 195 member states who govern the IPCC.
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
