Marc L. Serre
Affiliations: | Environmental Sciences & Engineering | University of North Carolina, Chapel Hill, Chapel Hill, NC |
Area:
Environmental Sciences, Environmental Engineering, HydrologyWebsite:
https://sph.unc.edu/adv_profile/marc-serre-phd/Google:
"Marc Laurent Serre" OR "Marc L. Serre"Bio:
https://www.proquest.com/openview/b44f7ea7f888c61873e82e9eb0b329b6/1
Cross-listing: Envirotree
Parents
Sign in to add mentor| George Christakos | grad student | 1999 | UNC Chapel Hill (MathTree) | |
| (Environmental spatiotemporal mapping and groundwater flow modelling using the BME and ST methods) | ||||
Children
Sign in to add trainee| Sitthichok Puangthongthub | grad student | 2006 | UNC Chapel Hill |
| Eric S. Money | grad student | 2009 | UNC Chapel Hill |
| Yasuyuki Akita | grad student | 2010 | UNC Chapel Hill |
| William B. Allshouse | grad student | 2014 | UNC Chapel Hill |
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Publications
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| Valencia A, Serre M, Arunachalam S. (2023) A hyperlocal hybrid data fusion near-road PM2.5 and NO2 annual risk and environmental justice assessment across the United States. Plos One. 18: e0286406 |
| Fox LC, Miller WC, Gesink D, et al. (2023) Progression of a large syphilis outbreak in rural North Carolina through space and time: Application of a Bayesian Maximum Entropy graphical user interface. Plos Global Public Health. 3: e0001714 |
| DeLang MN, Becker JS, Chang KL, et al. (2021) Mapping Yearly Fine Resolution Global Surface Ozone through the Bayesian Maximum Entropy Data Fusion of Observations and Model Output for 1990-2017. Environmental Science & Technology |
| Cleland SE, West JJ, Jia Y, et al. (2020) Estimating Wildfire Smoke Concentrations during the October 2017 California Fires through BME Space/Time Data Fusion of Observed, Modeled, and Satellite-Derived PM. Environmental Science & Technology |
| Younan D, Petkus AJ, Widaman KF, et al. (2019) Particulate matter and episodic memory decline mediated by early neuroanatomic biomarkers of Alzheimer's disease. Brain : a Journal of Neurology |
| Isakov V, Arunachalam S, Baldauf R, et al. (2019) Combining Dispersion Modeling and Monitoring Data for Community-Scale Air Quality Characterization. Atmosphere. 10: 1-610 |
| Chang K, Cooper OR, West JJ, et al. (2019) A new method (M<sup>3</sup>Fusion v1) for combining observations and multiple model output for an improved estimate of the global surface ozone distribution Geoscientific Model Development. 12: 955-978 |
| Ayub R, Messier KP, Serre ML, et al. (2019) Non-point source evaluation of groundwater nitrate contamination from agriculture under geologic uncertainty Stochastic Environmental Research and Risk Assessment. 33: 939-956 |
| Holcomb DA, Messier KP, Serre ML, et al. (2018) Geostatistical prediction of microbial water quality throughout a stream network using meteorology, land cover, and spatiotemporal autocorrelation. Environmental Science & Technology |
| Reyes JM, Hubbard HF, Stiegel MA, et al. (2018) Predicting polycyclic aromatic hydrocarbons using a mass fraction approach in a geostatistical framework across North Carolina. Journal of Exposure Science & Environmental Epidemiology |