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Palabras clave – provistas por la editorial

shale gas; n/a; Tapio’s model; 1)); tea; VARIMAX-ECM model; wave energy converter; error correction mechanism model; low-carbon agriculture; hybrid ship power systems; greenhouse gas emissions; STIRPAT model; textile industry; carbon tax; refined oil distribution; pushback control; takeoff rate; economic growth; generalized regression neural network (GRNN); Industry 4.0; HOMER software; population growth; Markov forecasting model; household consumption; life cycle assessment; green quality management; agricultural-related sectors; non-energy uses of fossil fuels; investment under uncertainty; CO2 emissions forecasting; decoupling analysis; CO2 emissions; quotas allocation; carbon price fluctuation; final energy consumption; ethylene supply; household CO2 emissions (HCEs); green transportation; Li-ion battery; Activity-Based Costing (ABC); decoupling elasticity; causal factors; renewable energy; per capita household CO2 emissions (PHCEs); shipping; input–output model; carbon intensity target; climate change; Monte Carlo method; CLA Model; energy intensity; total carbon emissions; mathematical programming; sustainable development; Generalized Divisia Index; carbon trading; influence factor; tire industry; socio-economic scenarios; hybrid genetic algorithm; economic growth and the environment; non-linear programming; environmental impact; capacity expansion; product-mix decision model; influencing factors; scenario forecast; energy structure; China; carbon emissions; inventory routing problem; green manufacturing; fairness; power industry; activity-based costing (ABC); aircraft; electric power industry; taxi time; real options analysis; carbon footprint; LT-ARIMAXS model; carbon intensity; gray model (GM (1; reducing carbon emissions; sustainable agriculture; long-term