Natural cloud brightening enhanced by marine primary organic aerosols

Clicks: 3
ID: 328683
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #340 of 342 articles by views in national science review

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 342 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Abstract Marine primary organic aerosols (mPOA) play a key role in ocean-atmosphere-climate interactions. Yet their effects on cloud formation remain uncertain because mPOA number size distribution measurements are lacking, obscuring its parameterizations for climate models. The mPOA number size distribution is resolved by combining long-term hygroscopicity, size, number and composition measurements in pristine marine air. The resulting bimodal distribution shows strong Aitken (∼60 nm) and accumulation (∼150 nm) modes, unlike the parameterization in widely used models. Total mPOA number is probably underestimated by a factor of three (observed/parameterized ≈ 3.1), doubling mPOA-originated cloud condensation nuclei (CCN) across realistic marine supersaturations. An observation-guided sensitivity analysis indicates a potential first aerosol indirect effect of –0.03 to –0.04 W/m2 over the global ocean, reaching –0.1 to –0.2 W/m2 over biologically active waters when mPOA surface tension reduction is considered, underscoring the need for trustworthy mPOA representation to reduce the uncertainties in aerosol-cloud interactions.
Reference Key
openalex_W7213466956 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Wei Xu, Baihua Chen, Lin Wang, Keran Zhang, Lei Lu, Kirsten Nicole Fossum, Emmanuel Chevassus, Liyuan Zhou, Haobin Zhong, Chunshui Lin, Yanan Zhan, Jingye Ren, Dan Dan Huang, Ruqian Miao, Darius Ceburnis, Ru-Jin Huang, Colin O'Dowd, Jurgita Ovadnevaite
Journal national science review
Year 2026
DOI
10.1093/nsr/nwag604
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.