中文版 | English

在结果中检索

GSTDTAP

浏览/检索结果: 共5条，第1-5条 帮助

已选(0)清除 条数/页：   排序方式：
Machine learning uncovers aerosol size information from chemistry and meteorology to quantify potential cloud-forming particles 期刊论文
Geophysical Research Letters, 2021
作者:  Arshad Arjunan Nair;  Fangqun Yu;  Pedro Campuzano-Jost;  Paul J. DeMott;  Ezra J. T. Levin;  Jose L. Jimenez;  Jeff Peischl;  Ilana B. Pollack;  Carley D. Fredrickson;  Andreas J. Beyersdorf;  Benjamin A. Nault;  Minsu Park;  Seong Soo Yum;  Brett B. Palm;  Lu Xu;  Ilann Bourgeois;  Bruce E. Anderson;  Athanasios Nenes;  Luke D. Ziemba;  Richard H. Moore;  Taehyoung Lee;  Taehyun Park;  Chelsea R. Thompson;  Frank Flocke;  Lewis Gregory Huey;  Michelle J. Kim;  Qiaoyun Peng
收藏  |  浏览/下载：14/0  |  提交时间：2021/10/22
Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements 期刊论文
Atmospheric Chemistry and Physics, 2020
作者:  Arshad Arjunan Nair and Fangqun Yu
收藏  |  浏览/下载：6/0  |  提交时间：2020/06/16
Wintertime new particle formation and its contribution to cloud condensation nuclei in the Northeastern United States 期刊论文
ATMOSPHERIC CHEMISTRY AND PHYSICS, 2020, 20 (4) : 2591-2601
作者:  Yu, Fangqun;  Luo, Gan;  Nair, Arshad Arjunan;  Schwab, James J.;  Sherman, James P.;  Zhang, Yanda
收藏  |  浏览/下载：8/0  |  提交时间：2020/07/02
Spatioseasonal Variations of Atmospheric Ammonia Concentrations Over the United States: Comprehensive Model-Observation Comparison 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2019, 124 (12) : 6571-6582
作者:  Nair, Arshad Arjunan;  Yu, Fangqun;  Luo, Gan
收藏  |  浏览/下载：7/0  |  提交时间：2019/11/26
atmospheric ammonia  spatiotemporal variation  model-observation comparison  new particle formation  emission reduction  ecosystem  
Long-Term Trend of Gaseous Ammonia Over the United States: Modeling and Comparison With Observations 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2018, 123 (15) : 8315-8325
作者:  Yu, Fangqun;  Nair, Arshad Arjunan;  Luo, Gan
收藏  |  浏览/下载：6/0  |  提交时间：2019/04/09
gaseous ammonia  long-term trend  emission reduction  particle formation  ecosystem  Ammonia Monitoring Network