Monitoring and Comparing Air and Green House Gases Emissions of Various Countries
Ambreen Shafqat (),
Qurat ul An Sabir (),
Su-Fen Yang (),
Muhammad Aslam (),
Mohammed Albassam () and
Kashif Abbas ()
Additional contact information
Ambreen Shafqat: Department of Urology
Qurat ul An Sabir: University of Arizona
Su-Fen Yang: National Chengchi University
Muhammad Aslam: King Abdulaziz University
Mohammed Albassam: King Abdulaziz University
Kashif Abbas: Riphah International University
Journal of Agricultural, Biological and Environmental Statistics, 2024, vol. 29, issue 3, No 11, 644 pages
Abstract:
Abstract The quality assurance of the earth-atmosphere system, which runs primarily to temperature variations and other disturbances of the earth’s climate, compels the assessment of greenhouse gases (GHG) emissions due to various Organizations for Economic Co-operation and Development (OECD) countries’ human activities that disturb the radioactive energy balance. The purpose of this paper is to thus determine the usefulness and acceptability of statistical process control for assessing the level of GHG emissions from OECD countries. We apply the exponentially weighted moving average (EWMA) control charts with one-time, two-time, and three-time smoothing processes for monitoring the process variance under a repetitive sampling scheme, named S $$^{\textrm{2}}$$ 2 -EWMA $$_{\textrm{RS}}$$ RS , S $$^{\textrm{2}}$$ 2 -DEWMA $$_{\textrm{RS}}$$ RS and S $$^{\textrm{2}}$$ 2 -TEWMA $$_{\textrm{RS}}$$ RS charts, and also utilize a cumulative sum (CUSUM) control chart under a repetitive sampling scheme, named as S2-CUSUMRS chart, to assess these countries’ emission levels of GHG. The control charts are a graphical representation of the trend product of sequential procedures. All the OECD countries can thus independently measure their emission level of GHG as a self-assessment tool. Consequently, we recommend use of the advanced control charts as a tool for OECD assessment at an individual country level.
Keywords: Control chart; Green energy; Variance; Simulation; CUSUM (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13253-023-00560-3
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