Zobrazeno 1 - 10
of 35
pro vyhledávání: '"K. Emma Knowland"'
Autor:
Viral Shah, Christoph A. Keller, K. Emma Knowland, Amy Christiansen, Lu Hu, Haolin Wang, Xiao Lu, Becky Alexander, Daniel J. Jacob
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 5, Pp n/a-n/a (2024)
Abstract Tropospheric ozone is an air pollutant and a greenhouse gas whose anthropogenic production is limited principally by the supply of nitrogen oxides (NOx) from combustion. Tropospheric ozone in the northern hemisphere has been rising despite t
Externí odkaz:
https://doaj.org/article/03a8a98fb19148c29a905f1d55605b22
Autor:
Laura A. Gladson, Kevin R. Cromar, Marya Ghazipura, K. Emma Knowland, Christoph A. Keller, Bryan Duncan
Publikováno v:
Environment International, Vol 159, Iss , Pp 107023- (2022)
Air pollution poses a serious threat to children’s respiratory health around the world. Satellite remote-sensing technology and air quality models can provide pollution data on a global scale, necessary for risk communication efforts in regions wit
Externí odkaz:
https://doaj.org/article/f2d10d5d8a444cdc90ff73377630c4cb
Autor:
Bryan N. Duncan, Carl A. Malings, K. Emma Knowland, Daniel C. Anderson, Ana I. Prados, Christoph A. Keller, Kevin R. Cromar, Steven Pawson, Holli Ensz
Publikováno v:
GeoHealth, Vol 5, Iss 9, Pp n/a-n/a (2021)
Abstract The combination of air quality (AQ) data from satellites and low‐cost sensor systems, along with output from AQ models, have the potential to augment high‐quality, regulatory‐grade data in countries with in situ monitoring networks and
Externí odkaz:
https://doaj.org/article/a2bec55d6bd14dc1a4717c92efc777c0
Autor:
Christoph A. Keller, K. Emma Knowland, Bryan N. Duncan, Junhua Liu, Daniel C. Anderson, Sampa Das, Robert A. Lucchesi, Elizabeth W. Lundgren, Julie M. Nicely, Eric Nielsen, Lesley E. Ott, Emily Saunders, Sarah A. Strode, Pamela A. Wales, Daniel J. Jacob, Steven Pawson
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 13, Iss 4, Pp n/a-n/a (2021)
Abstract The Goddard Earth Observing System composition forecast (GEOS‐CF) system is a high‐resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office (GMAO). GEOS‐CF offers a new tool for atmos
Externí odkaz:
https://doaj.org/article/43c13655448f4051835f21053c3dd765
Publikováno v:
Atmosphere, Vol 13, Iss 6, p 876 (2022)
A cold air outbreak (CAO) is an extreme weather phenomenon that has significant social and economic impacts over a large region of the midlatitudes. However, the dynamical mechanism of the occurrence and evolution of CAO events, particularly the role
Externí odkaz:
https://doaj.org/article/c0640ed9f882424db4331406de2e8357
Autor:
John T. Sullivan, Arnoud Apituley, Nora Mettig, Karin Kreher, K. Emma Knowland, Marc Allaart, Ankie Piters, Michel Van Roozendael, Pepijn Veefkind, Jerry R. Ziemke, Natalya Kramarova, Mark Weber, Alexei Rozanov, Laurence Twigg, Grant Sumnicht, Thomas J. McGee
Publikováno v:
Atmospheric Chemistry and Physics. 22:11137-11153
A TROPOspheric Monitoring Instrument (TROPOMI) validation campaign was held in the Netherlands based at the CESAR (Cabauw Experimental Site for Atmospheric Research) observatory during September 2019. The TROpomi vaLIdation eXperiment (TROLIX-19) con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e48374488746831cd32044632bd03951
https://doi.org/10.5194/acp-22-11137-2022
https://doi.org/10.5194/acp-22-11137-2022
Autor:
Fei Liu, Steffen Beirle, Joanna Joiner, Sungyeon Choi, Zhining Tao, K. Emma Knowland, Steven Smith, Daniel Q. Tong, Thomas Wagner
We map high-resolution nitrogen oxides (NOx) emissions in US cities from the retrieved TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO2) columns. A new database of gridded emissions at a horizontal spatial resolution of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f1a0e915efa4ba182346bf14b9e51e1
https://doi.org/10.5194/egusphere-egu23-1606
https://doi.org/10.5194/egusphere-egu23-1606
Combining Machine Learning and Numerical Simulation for High-Resolution PM2.5 Concentration Forecast
Publikováno v:
Environmental Science & Technology. 56:1544-1556
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bc1ac4a9f86caf747daabfa3429356a
https://doi.org/10.1021/acs.est.1c05578
https://doi.org/10.1021/acs.est.1c05578
Autor:
Pamela A Wales, Christoph A. Keller, K. Emma Knowland, Steven Pawson, Sungyeon Choi, Francois. Hendrick, Michel Van Roozendael, Ross J. Salawitch, Raid Suleiman, William Swanson
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6fe7b2d1c91f955f4c1b54fce3c73c7c
https://doi.org/10.1002/essoar.10512665.1
https://doi.org/10.1002/essoar.10512665.1