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Supplemental Aeration System Design For The Houston Ship Channel

CITE Title : Supplemental Aeration System Design For The Houston Ship Channel Personal Author(s) : Hoskings, Thomas Wayne, 1948-;Reynolds, Tom D.;Hann, R. W. (Roy William), 1934-; Corporate Authors(s) : Texas A & M University, Sea Grant College Program,;National Sea Grant Program (U.S.); Published Date : 1977 Series : TAMU-SG ; 78-201 URL : /view/noaa/12062 Hoskings, Thomas Wayne, 1948- et al. (1977). Supplemental Aeration System Design For The Houston Ship Channel. Hoskings, Thomas Wayne, 1948- and Reynolds, Tom D. and Hann, R. W. (Roy William), 1934- "Supplemental Aeration System Design For The Houston Ship Channel" (1977) Hoskings, Thomas Wayne, 1948- et al. "Supplemental Aeration System Design For The Houston Ship Channel" , 1977 Export RIS Citation Information.

:

Hoskings, Thomas Wayne, 1948- ;

Reynolds, Tom D.

1977 | TAMU-SG ; 78-201

No Description
Houston Ship Channel/Galveston Bay current prediction quality assurance miniproject

CITE Title : Houston Ship Channel/Galveston Bay current prediction quality assurance miniproject Personal Author(s) : Williams, Robert G.;Frey, Henry R.;Bethem, Thomas; Corporate Authors(s) : United States. National Ocean Service. Office of Oceanography and Marine Assessment Published Date : 1990 Series : NOAA technical memorandum NOS/OMA ; 53 URL : /view/noaa/30395 Williams, Robert G. et al. (1990). Houston Ship Channel/Galveston Bay current prediction quality assurance miniproject. Williams, Robert G. and Frey, Henry R. and Bethem, Thomas "Houston Ship Channel/Galveston Bay current prediction quality assurance miniproject" (1990) Williams, Robert G. et al. "Houston Ship Channel/Galveston Bay current prediction quality assurance miniproject" , 1990 Export RIS Citation Information.

:

Williams, Robert G. ;

Frey, Henry R.

1990 | NOAA technical memorandum NOS/OMA ; 53

No Description
A comprehensive approach combining positive matrix factorization modeling, meteorology, and machine learning for source apportionment of surface ozone precursors: Underlying factors contributing to ozone formation in Houston, Texas

CITE Title : A comprehensive approach combining positive matrix factorization modeling, meteorology, and machine learning for source apportionment of surface ozone precursors: Underlying factors contributing to ozone formation in Houston, Texas Personal Author(s) : Nelson, D.;Choi, Y.;Sadeghi, B.;Yeganeh, A.K.;Ghahremanloo, M.;Park, J.; Published Date : 2023 Source : Environmental Pollution 334 (2023) 122223 DOI : https://doi.org/10.1016/j.envpol.2023.122223 Journal Title : Environmental Pollution Nelson, D. et al. (2023). A comprehensive approach combining positive matrix factorization modeling, meteorology, and machine learning for source apportionment of surface ozone precursors: Underlying factors contributing to ozone formation in Houston, Texas. 334https://doi.org/10.1016/j.envpol.2023.122223 Nelson, D. et al. "A comprehensive approach combining positive matrix factorization modeling, meteorology, and machine learning for source apportionment of surface ozone precursors: Underlying factors contributing to ozone formation in Houston, Texas" 334 (2023), https://doi.org/10.1016/j.envpol.2023.122223 Nelson, D. et al. "A comprehensive approach combining positive matrix factorization modeling, meteorology, and machine learning for source apportionment of surface ozone precursors: Underlying factors contributing to ozone formation in Houston, Texas" vol. 334, 2023, https://doi.org/10.1016/j.envpol.2023.122223 Export RIS Citation Information.

:

Nelson, D.

;

Choi, Y.

2023 | Environmental Pollution 334 (2023) 122223

:

Ozone concentrations in Houston, Texas, are among the highest in the United States, posing significant risks to human health. This study aimed to eval...