Monitoring Environmental Risk by a Methodology Based on Control Charts

Saulo, Helton; Leiva, Víctor; Ruggeri, Fabrizio

doi:10.1007/978-3-319-18029-8_14

Cited by 7 publications

(4 citation statements)

References 31 publications

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“…Control charting is well established in manufacturing [2] and has been adopted in many disciplines, including environmental monitoring, e.g., [97][98][99]. Control charts have been used in many environmental studies, including studies of water quality, air quality, sediment quality, and many others [21,30,37,41,72,[100][101][102][103][104][105][106][107][108][109][110][111].…”

Section: Discussionmentioning

confidence: 99%

A Review of Control Charts and Exploring Their Utility for Regional Environmental Monitoring Programs

Arciszewski

2023

Environments

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Industrial control charts are used in manufacturing to quickly and robustly indicate the status of production and to prompt any necessary corrective actions. The library of tools available for these tasks has grown over time and many have been used in other disciplines with similar objectives, including environmental monitoring. While the utility of control charts in environmental monitoring has been recognized, and the tools have already been used in many individual studies, they may be underutilized in some types of programs. For example, control charts may be especially useful for reporting and evaluating data from regional surveillance monitoring programs, but they are not yet routinely used. The purpose of this study was to promote the use of control charts in regional environmental monitoring by surveying the literature for control charting techniques suitable for the various types of data available from large programs measuring multiple indicators at multiple locations across various physical environments. Example datasets were obtained for Canada’s Oil Sands Region, including water quality, air quality, facility production and performance, and bird communities, and were analyzed using univariate (e.g., x-bar) and multivariate (e.g., Hotelling’s T2) control charts. The control charts indicated multiple instances of unexpected observations and highlighted subtle patterns in all of the example data. While control charts are not uniquely able to identify potentially relevant patterns in data and can be challenging to apply in some monitoring analyses, this work emphasizes the broad utility of the tools for straightforwardly presenting the results from standardized and routine surveillance monitoring.

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Section: Discussionmentioning

confidence: 99%

A Review of Control Charts and Exploring Their Utility for Regional Environmental Monitoring Programs

Arciszewski

2023

Environments

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“…Efficient R packages have been developed by Leiva et al and Barros et al Interested readers are referred to the following articles for further reading. For different applications of the univariate BS, multivariate BS, and related distributions, one may look at the works of Ahmed et al, Aslam et al, Aslam and Kantam, Baklizi and El Masri, Balakrishnan et al, Balamurali et al, Castillo et al, Desousa et al, Garcia‐Papani et al, Gomes et al, Ismail, Kotz et al, Leiva and Marchant, Leiva and Saulo, Leiva et al, Lio and Park, Lio et al, Marchant et al, Paula et al, Podlaski, Rojas et al, Saulo et al, Upadhyay et al, Vilca et al, Villegas et al, Wanke et al, Wanke and Leiva, Wu and Tsai, Zhang et al, and the references cited therein. In a recent paper, Mohammadi et al have discussed the modeling of wind speed and wind power distributions by a BS distribution.…”

Section: Concluding Remarks and Further Readingmentioning

confidence: 99%

Birnbaum‐Saunders distribution: A review of models, analysis, and applications

Balakrishnan

Kundu

2018

Appl Stoch Models Bus & Ind

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Birnbaum and Saunders introduced a two-parameter lifetime distribution to model the fatigue life of a metal, subject to cyclic stress. Since then, extensive work has been done on this model providing different interpretations, constructions, generalizations, inferential methods, and extensions to bivariate, multivariate, and matrix-variate cases. More than 200 papers and one research monograph have already appeared describing all these aspects and developments. In this paper, we provide a detailed review of all these developments and, at the same time, indicate several open problems that could be considered for further research. KEYWORDSBayes estimators, EM algorithm, Fisher information matrix, hazard function, length-biased distribution, moments and inverse moments, probability density function, stochastic orderings, TP 2 property 4

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“…(), Marchant et al. (), and Saulo et al (). As in the LN model, and unlike the other mentioned probability models, the physical arguments of the BS model allows us to postulate it as a candidate to describe air contaminant concentrations; see details in Section 2.…”

Section: Introductionmentioning

confidence: 96%

“…The use of such charts has been expanded to other areas, including environmental and health risk assessment; see Lund and Seymour (), Manly and Mackenzie (), Grigg and Farewell (), Ferreira‐Baptista and De Miguel (), Woodall (), Morrison (), and Saulo et al. (). The power or effectiveness of a control chart is usually measured by the average run length (ARL), which is the average number of inspected samples required to advert an out‐of‐control condition after it has occurred.…”

Section: Introductionmentioning

confidence: 99%

A criterion for environmental assessment using Birnbaum–Saunders attribute control charts

et al. 2015

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e Assessing environmental risk is useful for preventing adverse effects on human health in highly polluted cities. We design a criterion for environmental monitoring based on an attribute control chart for the number of dangerous contaminant levels when the concentration to be monitored follows a Birnbaum-Saunders distribution. This distribution is being widely applied to environmental data. We provide a novel justification for its usage in environmental sciences. The control coefficient and the minimum inspection concentration for the designed criterion are determined to yield the specified in-control average run length, whereas the out-of-control case is obtained according to a shift in the target mean. A simulation study is conducted to evaluate the proposed criterion, which reports its performance to provide earlier alerts of out-of-control processes. An application with real-world environmental data is carried out to validate its coherence with what is reported by the health authority.

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Monitoring Environmental Risk by a Methodology Based on Control Charts

Cited by 7 publications

References 31 publications

A Review of Control Charts and Exploring Their Utility for Regional Environmental Monitoring Programs

A Review of Control Charts and Exploring Their Utility for Regional Environmental Monitoring Programs

Birnbaum‐Saunders distribution: A review of models, analysis, and applications

A criterion for environmental assessment using Birnbaum–Saunders attribute control charts

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