Standard
An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution. / Di, Qian; Amini, Heresh; Shi, Liuhua; Kloog, Itai; Silvern, Rachel; Kelly, James; Sabath, M. Benjamin; Choirat, Christine; Koutrakis, Petros; Lyapustin, Alexei; Wang, Yujie; Mickley, Loretta J.; Schwartz, Joel.
In:
Environment International, Vol. 130, 104909, 2019.
Research output: Contribution to journal › Journal article › peer-review
Harvard
Di, Q, Amini, H, Shi, L, Kloog, I, Silvern, R, Kelly, J, Sabath, MB, Choirat, C, Koutrakis, P, Lyapustin, A, Wang, Y, Mickley, LJ & Schwartz, J 2019, '
An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution',
Environment International, vol. 130, 104909.
https://doi.org/10.1016/j.envint.2019.104909
APA
Di, Q., Amini, H., Shi, L., Kloog, I., Silvern, R., Kelly, J., Sabath, M. B., Choirat, C., Koutrakis, P., Lyapustin, A., Wang, Y., Mickley, L. J., & Schwartz, J. (2019).
An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution.
Environment International,
130, [104909].
https://doi.org/10.1016/j.envint.2019.104909
Vancouver
Di Q, Amini H, Shi L, Kloog I, Silvern R, Kelly J et al.
An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution.
Environment International. 2019;130. 104909.
https://doi.org/10.1016/j.envint.2019.104909
Author
Di, Qian ; Amini, Heresh ; Shi, Liuhua ; Kloog, Itai ; Silvern, Rachel ; Kelly, James ; Sabath, M. Benjamin ; Choirat, Christine ; Koutrakis, Petros ; Lyapustin, Alexei ; Wang, Yujie ; Mickley, Loretta J. ; Schwartz, Joel. / An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution. In: Environment International. 2019 ; Vol. 130.
Bibtex
@article{66c032b5783f421f9fce6fd467324dfe,
title = "An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution",
keywords = "Fine particulate matter (PM2.5), Ensemble model, Neural network, Gradient boosting, Random forest",
author = "Qian Di and Heresh Amini and Liuhua Shi and Itai Kloog and Rachel Silvern and James Kelly and Sabath, {M. Benjamin} and Christine Choirat and Petros Koutrakis and Alexei Lyapustin and Yujie Wang and Mickley, {Loretta J.} and Joel Schwartz",
year = "2019",
doi = "10.1016/j.envint.2019.104909",
language = "English",
volume = "130",
journal = "Environment international",
issn = "0160-4120",
publisher = "Pergamon Press",
}
RIS
TY - JOUR
T1 - An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution
AU - Di, Qian
AU - Amini, Heresh
AU - Shi, Liuhua
AU - Kloog, Itai
AU - Silvern, Rachel
AU - Kelly, James
AU - Sabath, M. Benjamin
AU - Choirat, Christine
AU - Koutrakis, Petros
AU - Lyapustin, Alexei
AU - Wang, Yujie
AU - Mickley, Loretta J.
AU - Schwartz, Joel
PY - 2019
Y1 - 2019
KW - Fine particulate matter (PM2.5)
KW - Ensemble model
KW - Neural network
KW - Gradient boosting
KW - Random forest
U2 - 10.1016/j.envint.2019.104909
DO - 10.1016/j.envint.2019.104909
M3 - Journal article
C2 - 31272018
VL - 130
JO - Environment international
JF - Environment international
SN - 0160-4120
M1 - 104909
ER -