A survey on the energy consumption and environmental impact of video streaming is presented, highlighting the significant role of video streaming in global greenhouse gas (GHG) emissions. Video streaming, which accounts for over 65% of internet traffic, has increased dramatically due to remote work, multimedia communication, and high-resolution content. The survey explores the energy consumption and environmental impact of video streaming, focusing on content provisioning and consumption, and identifies key factors affecting energy use, such as encoding schemes, resource requirements, storage, content retrieval, decoding, and display. The survey also identifies weaknesses in current video streaming technologies that require further research for improved energy efficiency, including fixed bitrate ladders in HTTP live streaming, inefficient hardware utilization, and a lack of comprehensive open energy measurement datasets. The survey discusses the challenges in measuring and reducing the energy consumption and carbon footprint of video streaming, including variability in carbon footprint measurements, uncertainty in carbon emission estimates, and the decoupling of data growth from energy consumption. It also considers the factors affecting carbon emission calculations, such as electricity generation sources, imported electricity, and the timing of electricity use. The survey provides an overview of video encoding formats, including AVC, HEVC, VVC, VP9, and AV1, and analyzes their energy consumption and efficiency. It also discusses resource requirements for content provisioning, including the use of cloud and edge computing, and the optimization of energy consumption through heuristic methods, linear programming, parallelization, system dynamics, and game theory. The survey also examines the storage of encoded video content on CDNs, discussing energy-efficient caching algorithms and the impact of deploying applications on the cloud and edge. It identifies research gaps, including optimized video encoding parameters, energy-efficient transcoding, on-demand HLS segment encoding and storage, optimized HLS video bitrate ladders, optimized ABR multi-codec bitrate ladders, cloud resources profiling, energy-based pricing for cloud services, and optimized virtualized cloud technology. The survey concludes that reducing the environmental impact of video streaming requires a comprehensive understanding of the energy consumption and carbon emissions associated with video streaming, as well as the development of sustainable and efficient video streaming technologies.A survey on the energy consumption and environmental impact of video streaming is presented, highlighting the significant role of video streaming in global greenhouse gas (GHG) emissions. Video streaming, which accounts for over 65% of internet traffic, has increased dramatically due to remote work, multimedia communication, and high-resolution content. The survey explores the energy consumption and environmental impact of video streaming, focusing on content provisioning and consumption, and identifies key factors affecting energy use, such as encoding schemes, resource requirements, storage, content retrieval, decoding, and display. The survey also identifies weaknesses in current video streaming technologies that require further research for improved energy efficiency, including fixed bitrate ladders in HTTP live streaming, inefficient hardware utilization, and a lack of comprehensive open energy measurement datasets. The survey discusses the challenges in measuring and reducing the energy consumption and carbon footprint of video streaming, including variability in carbon footprint measurements, uncertainty in carbon emission estimates, and the decoupling of data growth from energy consumption. It also considers the factors affecting carbon emission calculations, such as electricity generation sources, imported electricity, and the timing of electricity use. The survey provides an overview of video encoding formats, including AVC, HEVC, VVC, VP9, and AV1, and analyzes their energy consumption and efficiency. It also discusses resource requirements for content provisioning, including the use of cloud and edge computing, and the optimization of energy consumption through heuristic methods, linear programming, parallelization, system dynamics, and game theory. The survey also examines the storage of encoded video content on CDNs, discussing energy-efficient caching algorithms and the impact of deploying applications on the cloud and edge. It identifies research gaps, including optimized video encoding parameters, energy-efficient transcoding, on-demand HLS segment encoding and storage, optimized HLS video bitrate ladders, optimized ABR multi-codec bitrate ladders, cloud resources profiling, energy-based pricing for cloud services, and optimized virtualized cloud technology. The survey concludes that reducing the environmental impact of video streaming requires a comprehensive understanding of the energy consumption and carbon emissions associated with video streaming, as well as the development of sustainable and efficient video streaming technologies.