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Titlebook: Waste-to-Energy; Recent Developments Abd El-Fatah Abomohra,Qingyuan Wang,Jin Huang Book 2022 The Editor(s) (if applicable) and The Author(

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發(fā)表于 2025-3-28 17:25:22 | 只看該作者
Waste to Energy Plant in Spain: A Case Study Using Technoeconomic Analysis, (MSW) with a total capacity of more than 350,000?tons of waste treated per year, which means the generation of more than 180,000?MWh of electricity and 110,000?tons of steam per year. The positive and negative impacts generated by this facility are identified, discussed, and monetarily valued to ca
42#
發(fā)表于 2025-3-28 21:40:39 | 只看該作者
Phycoremediation: Role of Microalgae in Waste Management and Energy Production,omically and environmentally favorable option for removing waste from effluents. In this sense, the objective of this chapter is to present the role of microalgae in waste management and energy production as phycoremediation agents. The main highlights of the chapter include an overview of microalga
43#
發(fā)表于 2025-3-29 00:10:53 | 只看該作者
Case Study in Arid and Semi-arid Regions,roving soil fertility, besides highlighting the potential of the by-product water in stretching the limited water resources to support the growth of plants and animal life in arid and semi-arid regions. The chapter concludes by stating the main challenges and recommendations for sustainable bioenerg
44#
發(fā)表于 2025-3-29 03:21:28 | 只看該作者
45#
發(fā)表于 2025-3-29 09:26:34 | 只看該作者
46#
發(fā)表于 2025-3-29 13:04:07 | 只看該作者
Book 2022or alternative biofuels and other integrated approaches such as wastewater treatment, plastic degradation, and CO2 sequestration in a cost-effective and eco-friendly way. In addition, different routes of waste recycling for enhanced biofuel production and case studies are presented with environmenta
47#
發(fā)表于 2025-3-29 17:23:04 | 只看該作者
48#
發(fā)表于 2025-3-29 22:13:01 | 只看該作者
49#
發(fā)表于 2025-3-30 00:48:00 | 只看該作者
50#
發(fā)表于 2025-3-30 04:17:11 | 只看該作者
Jiafu Lin,YanZhao Zhang,Tao Song,Haifeng Sues the depth map guided by the extracted features in different regions. Qualitative and quantitative experiments were conducted on the DTU and BlendedMVS datasets. The results show the effectiveness of the proposed modules of ALFE, GFE and RA-DRM, and the comparisons indicate that our learning-based MVS method is superior to related methods.
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