Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Runsheng Song"'
Autor:
Runsheng Song, Mengya Tao, Dingsheng Li, Yuwei Qin, Arturo A. Keller, Alexander Chang, Sangwon Suh
Publikováno v:
Ambio
Ambio, vol 51, iss 3
Ambio, vol 51, iss 3
Species Sensitivity Distribution (SSD) is a key metric for understanding the potential ecotoxicological impacts of chemicals. However, SSDs have been developed to estimate for only handful of chemicals due to the scarcity of experimental toxicity dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a98e3ac0f1b7d596d9b452320833da2
https://doi.org/10.1007/s13280-021-01598-8
https://doi.org/10.1007/s13280-021-01598-8
Autor:
José I. Zenteno, Sarah E. Anderson, Elizabeth H. T. Hiroyasu, Ying Wang, Runsheng Song, Timbo Stillinger, Owen R. Liu, Joseph Palazzo, Christina L. Tague
Publikováno v:
Water Resources Research. 53:4459-4475
With climate change, the extent, severity, and frequency of droughts around the world are expected to increase. This study analyzed the ability of water districts to meet mandatory urban water conservation targets, which are a common policy response
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::653b7fa76f6784b70e27205d97560094
https://doi.org/10.1002/2016wr020136
https://doi.org/10.1002/2016wr020136
Publikováno v:
Environmental science & technology, vol 51, iss 21
Song, R; Qin, Y; Suh, S; & Keller, AA. (2017). Dynamic Model for the Stocks and Release Flows of Engineered Nanomaterials. Environmental Science and Technology, 51(21), 12424-12433. doi: 10.1021/acs.est.7b01907. UC Santa Barbara: Retrieved from: http://www.escholarship.org/uc/item/5m40d0kz
Song, R; Qin, Y; Suh, S; & Keller, AA. (2017). Dynamic Model for the Stocks and Release Flows of Engineered Nanomaterials. Environmental Science and Technology, 51(21), 12424-12433. doi: 10.1021/acs.est.7b01907. UC Santa Barbara: Retrieved from: http://www.escholarship.org/uc/item/5m40d0kz
© 2017 American Chemical Society. Most existing life-cycle release models for engineered nanomaterials (ENM) are static, ignoring the dynamics of stock and flows of ENMs. Our model, nanoRelease, estimates the annual releases of ENMs from manufacturi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b78423116c414308fb07aa70b9dd0cc
https://pubmed.ncbi.nlm.nih.gov/29022708
https://pubmed.ncbi.nlm.nih.gov/29022708
Publikováno v:
Song, R; Keller, AA; & Suh, S. (2017). Rapid Life-Cycle Impact Screening Using Artificial Neural Networks. Environmental Science and Technology, 51(18), 10777-10785. doi: 10.1021/acs.est.7b02862. UC Santa Barbara: Retrieved from: http://www.escholarship.org/uc/item/7tr8n61t
Environmental science & technology, vol 51, iss 18
Environmental science & technology, vol 51, iss 18
© 2017 American Chemical Society. The number of chemicals in the market is rapidly increasing, while our understanding of the life-cycle impacts of these chemicals lags considerably. To address this, we developed deep artificial neural network (ANN)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec2ad2ff758867e11597ee4c96b9ea79
http://www.escholarship.org/uc/item/7tr8n61t
http://www.escholarship.org/uc/item/7tr8n61t
