Membrane technologies for sustainable development goals: A critical review of bright horizons
Bibliographic record
Abstract
With the emergence of global challenges, sustainability has become a pivotal element in the world’s development agendas. To achieve global development, 17 sustainability development goals (SDGs) were developed by the United Nations in 2012. Recently, membrane technologies have been rising to the spotlight as a promising green alternative for the accomplishment of these SDGs. This is due to their numerous advantages including high selectivity, lower cost, relatively easy upscaling, mild processing conditions, compact system with minimized steel usage, and reduced energy consumption. Despite its growing importance in sustainable development, membrane technologies have not been reviewed and rigorously analyzed for all SDGs. This review critically analyzes membrane technologies' significant position in SDGs to fill this gap in the literature. More precisely, this review uniquely delves into the versatile role of membrane technologies in contributing to the SDGs with state-of-the-art examples, hence, aiding in solving pressing global challenges such as clean water, affordable and clean energy, climate action, poverty, life below water, etc. Furthermore, by evaluating the economic and social dimensions of membrane technologies in sustainable development, this review comprehensively highlights the holistic advantages offered by various membrane processes in the accomplishment of SDGs. This paper concludes by discussing future directions that could be implemented to harness the full potential of membrane technologies in SDGs accomplishment. • Membrane technologies gained tremendous interest as a sustainable and promising path to achieve the SDGs. • The economic and social aspects of membrane technologies are evaluated towards serving various SDGs. • Membrane technologies have the advantages of selective separation, while cost and energy effective. • Membrane technologies contribute directly to SDG 2 (Zero hunger), 3 (Good health and well-being), 6 (Clean water and sanitation), 7 (Affordable and clean energy), 11 (Sustainable cities and communities), 12 (Responsible consumption and production), 13 (Climate action), and 14 (Life below water). • Membrane technology contributes indirectly to SDG 1 (No poverty), 8 (Decent work and economic growth), 9 (Industry, innovation and infrastructure), and 15 (Life on land). • Coupling membrane technologies with renewable energy sources and developing advanced greener materials and fabrication techniques appear to be viable solutions towards SDGs. • Establishing global partnerships is required to facilitate the adoption of successful membrane technologies in accomplishing SDGs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".