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2020-12-15
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1. Kousehlar, M., & Widom, E. (2019). Sources of metals in atmospheric particulate matter in Tehran, Iran: Tree bark biomonitoring. Applied Geochemistry104, 71-82.

https://doi.org/10.1016/j.apgeochem.2019.03.018

2. Suleiman, A., Tight, M. R., & Quinn, A. D. (2019). Applying machine learning methods in managing urban concentrations of traffic-related particulate matter (PM10 and PM2. 5). Atmospheric Pollution Research10(1), 134-144.

https://doi.org/10.1016/j.apr.2018.07.001

3. Just, A. C., Arfer, K. B., Rush, J., Dorman, M., Shtein, A., Lyapustin, A., & Kloog, I. (2020). Advancing methodologies for applying machine learning and evaluating spatiotemporal models of fine particulate matter (PM2. 5) using satellite data over large regions. Atmospheric Environment239, 117649.

https://doi.org/10.1016/j.atmosenv.2020.117649
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Effect of tree-ring detrending method on apparent growth trends of black and white spruce in interior Alaska Patrick F Sullivan1,Robert R Pattison2,Annalis H Brownlee1,Sean M P Cahoon1andTeresa N Hollingsworth3 Published 31 October 2016•© 2016 IOP Publishing Ltd Environmental Resear..
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20201215_Narayan Bhusal
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Seasonal variation in the canopy color of temperate evergreen conifer forests New Phytologist (2020) doi: 10.1111/nph.17046