scholarly journals Development of a Computational Software to Forecast Ozone Levels

Author(s):  
Elena Agirre ◽  
Albaro Anta ◽  
Luis Javier R. Barro
Keyword(s):  
Ecotoxicology ◽  
2021 ◽  
Author(s):  
Ambra Dell’Orso ◽  
Elena Kuzminsky ◽  
Victoria Bermejo-Bermejo ◽  
Raquel Ruiz-Checa ◽  
Rocío Alonso-Del Amo ◽  
...  

2021 ◽  
Vol 11 (5) ◽  
pp. 2388
Author(s):  
Yongku Kim ◽  
Jeongjin Lee

In environmental studies, it is important to assess how regulatory standards for air pollutants affect public health. High ozone levels contribute to harmful air pollutants. The EPA regulates ozone levels by setting ozone standards to protect public health. It is thus crucial to assess how various regulatory ozone standards affect non-accidental mortality related to respiratory deaths during the ozone season. The original rollback approach provides an adjusted ozone process under a new regulation scenario in a deterministic fashion. Herein, we consider a statistical rollback approach to allow for uncertainty in the rollback procedure by adopting the quantile matching method so that it provides flexible rollback sets. Hierarchical Bayesian models are used to predict the potential effects of different ozone standards on human health. We apply the method to epidemiologic data.


2016 ◽  
Vol 129 (3) ◽  
pp. 297-308
Author(s):  
Sandra Rayne ◽  
Alan Gertler ◽  
Barbara Zielinska ◽  
Andrzej Bytnerowicz ◽  
Joel Burley ◽  
...  

2013 ◽  
Vol 28 (3) ◽  
pp. 455-465 ◽  
Author(s):  
Francisco J. Moral ◽  
Francisco J. Rebollo ◽  
Francisco Méndez
Keyword(s):  

1978 ◽  
Vol 12 (11) ◽  
pp. 2173-2177 ◽  
Author(s):  
R.G. Derwent ◽  
A.E.J. Eggleton ◽  
M.L. Williams ◽  
C.A. Bell

2015 ◽  
Vol 8 (10) ◽  
pp. 4487-4505 ◽  
Author(s):  
K.-L. Chang ◽  
S. Guillas ◽  
V. E. Fioletov

Abstract. Total column ozone variations estimated using ground-based stations provide important independent source of information in addition to satellite-based estimates. This estimation has been vigorously challenged by data inhomogeneity in time and by the irregularity of the spatial distribution of stations, as well as by interruptions in observation records. Furthermore, some stations have calibration issues and thus observations may drift. In this paper we compare the spatial interpolation of ozone levels using the novel stochastic partial differential equation (SPDE) approach with the covariance-based kriging. We show how these new spatial predictions are more accurate, less uncertain and more robust. We construct long-term zonal means to investigate the robustness against the absence of measurements at some stations as well as instruments drifts. We conclude that time series analyzes can benefit from the SPDE approach compared to the covariance-based kriging when stations are missing, but the positive impact of the technique is less pronounced in the case of drifts.


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