Solid waste management (SWM) is a vital issue for environmental and human health, as increasing waste generation poses serious challenges to conventional methods of waste disposal. These methods are often associated with high costs, low efficiency, and negative impacts, such as greenhouse gas emissions, leachate, and odors. To address these challenges, emerging green technologies have been developed to manage waste in a more effective and sustainable way, while reducing the environmental and social burdens of SWM. This paper provides a meta-analysis of the emerging green technologies for SWM, based on a systematic review of the literature from 2019 to 2023. The paper covers four main aspects: (1) the current status and challenges of SWM, such as the lack of regulations, infrastructure, and awareness; (2) the techno-economic, environmental, and social impacts of SWM technologies, such as the costs, benefits, risks, and opportunities; (3) the optimization strategies for minimizing waste and maximizing resource recovery, such as the waste hierarchy, life cycle assessment, and circular economy principles; and (4) the applications of artificial intelligence in SWM. The paper reveals that green technologies such as waste-to-energy, recycling, composting, and bioreactor landfills can offer significant advantages for SWM, but they also encounter various barriers and limitations, such as technical, financial, institutional, and behavioral challenges. The paper recommends that policymakers and stakeholders should cooperate to create a conducive environment for the adoption and implementation of these technologies.
Author Contributions
Conceptualization, writing—original draft preparation, S.S. and K.N.; writing—draft preparation, review, and editing, S.S. and R.S.; writing—final draft review and editing, R.S. All authors. contributed equally to this work. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
No new data were created or analyzed in this study. Data sharing is not applicable to this article.
Conflicts of Interest
The authors declare no conflict of interest.
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