
Some Approaches to Measuring Environmental Safety
DOI:
https://doi.org/10.30564/jees.v8i9.13763Abstract
The article is devoted to the measurement of environmental safety. The differentiation between the methodological concepts of safety and danger is carried out. The requirements for measures of environmental safety are substantiated. The correlation between safety and development, safety and danger is revealed. A quantitative approach to the environmental safety assessment is proposed. The objectives of environmental safety as a science and practical activity, along with the criteria for achieving these objectives, are substantiated. In the article, life expectancy is analyzed as an indicator of environmental safety as well as its dependence on other state development priorities, such as the costs of giving birth and raising children, supporting pregnant and lactating mothers, caring for pensioners, costs of ensuring industrial and transport safety, etc. It is substantiated that the mortality rate of the population at different ages, from different reasons, in different conditions, will represent the state of safety in a given place. The article considers the indicators that determine the quality (state) of the environment as the maximum permissible environmental load and the degree of proximity of the ecosystem state to the border of its sustainability. The possibilities and advantages of using the assessment of the photosynthetic organisms’ state as the indicator of environmental safety are substantiated.
Keywords:
Environmental Safety; Safety Level; Safety Criteria; Basic Values; Life Expectancy; Integral Indicators; Photosynthetic OrganismsReferences
[1] Aven T., Ben-Haim, Y., Andersen, H.B., et al, 2018. Society for Risk Analysis Glossary. Society for Risk Analysis: Herndon, VA, USA. Available from: https://www.sra.org/wp-content/uploads/2020/04/SRA-Glossary-FINAL.pdf
[2] Thompson, M.P., Zimmerman, T., Mindar, D., et al., 2016. General Technical Report RMRS-GTR-349: Risk Terminology Primer: Basic Principles and a Glossary for the Wildland Fire Management Community. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station: Fort Collins, CO, USA.
[3] Kucher, D.E., Kharchenko S.G., 2022. Some of environmental safety strategy approaches. Ecology and Industry of Russia. 26(10), 66–71. (in Russian)
[4] Presidential Executive Office, 2017. Decree of the President of the Russian Federation dated April 19, 2017 No. 176: About the Environmental Safety Strategy of the Russian Federation for the Period Until 2025. Presidential Executive Office: Moscow, Russia. Available from: http://www.kremlin.ru/acts/bank/41879 (in Russian)
[5] Einstein, A., 2007. The World As I See It. Book Tree: San Diego, CA, USA.
[6] Chrystal, K.A., 2003. Goodhart’s Law: Its Origins, Meaning and Implications for Monetary Policy. In: Mizen, P. (Ed.). Central Banking, Monetary Theory and Practice: Essays in Honour of Charles Goodhart, Volume One. Edward Elgar Publishing Limited: Cheltenham, UK. DOI: https://doi.org/10.4337/9781781950777.00022
[7] Pozdnyakov, A.I., 2002. On the conceptual apparatus of security theory (axiological approach). Information collection "Security". 7–8, 185–191. (in Russian)
[8] Netherlands Ministry of Housing, Physical Planning and the Environment (VROM), 1989. VROM90312/6–89: National Environmental Policy Plan "To Choose or To Lose". Netherlands Ministry of Housing, Spatial Planning and Environment: The Hague, The Netherlands.
[9] Odum, E.P., Barrett, G.W., 2005. Fundamentals of Ecology, 5th ed. Thomson Brooks/Cole: Belmont, CA, USA.
[10] Kucher, D.E., Kharchenko S.G., 2023. Why is methodology so important in risk assessment? Ecology and Industry of Russia. 27(3), 66–71. DOI: https://doi.org/10.18412/1816-0395-2023-3-66-71 (in Russian)
[11] Kucher, D.E., Kharchenko S.G., 2022. Environmental safety: The problem of concepts or sources of errors. Ecology and Industry of Russia. 26(4), 68–71. DOI: https://doi.org/10.18412/1816-0395-2022-4-68-71 (in Russian)
[12] Timiriazeff, K.A., 1948. Public Lectures, Speeches, and Scientific Research, Volume 1: The Sun, Life and Chlorophyll. Ogiz-Selkhozgiz: Moscow, Russia. (in Russian)
[13] Kirlian, S.D., Kirlian, V.K., 1961. Photography and visual observation using high-frequency currents. Journal of Scientific and Applied Photography and Cinematography. 6(6), 397–403. (in Russian).
[14] Kirlian, S.D. (inventor), 1949. Method for Receiving Photographic Pictures of Different Types of Objects. USSR Patent. N106401. 5 September 1949.
[15] Kirlian, S.D., Kirlian, V.K., 1963. AD 299 666: Photography and Visual Observation by Means of High-Frequency Currents. National Technical Information Service: Springfield, VA, USA.
[16] Ostrander, S., Schroeder, L., 1970. Psi Discoveries Behind the Iron Curtain. Prentice-Hall, Inc.: Englewood Cliffs, NJ, USA.
[17] Picler, W., Costa, E.T., 2024. Demystification of Colors in Kirlian Photography as a Clinical Diagnostic Method. In: Marques, J.L.B., Rodrigues, C.R., Suzuki, D.O.H., et al. (Eds.). IFMBE Proceedings, Vol. 98: IX Latin American Congress on Biomedical Engineering and XXVIII Brazilian Congress on Biomedical Engineering (CLAIB CBEB 2022). Springer: Cham, Switzerland. pp. 560–571. DOI: https://doi.org/10.1007/978-3-031-49401-7_58
[18] Miraglia, F.E., 2024. Unreliability of the Gas Discharge Visualization (GDV) Device and the Bio-Well for Biofield Science: Kirlian Photography Revisited and Investigated. Journal of Anomalistics. 24(1), 80–119. DOI: https://doi.org/10.23793/zfa.2024.080
[19] Chhabra, G., Onyema, E.M., Kumar, S., et al., 2022. Human Emotions Recognition, Analysis and Transformation by the Bioenergy Field in Smart Grid Using Image Processing. Electronics. 11(23), 4059. DOI: https://doi.org/10.3390/electronics11234059
[20] Patil, M.S., Arora, P.S., Shinde, J.N., 2023. Monitoring and Analysis of Stress Based on Human Aura. Interantional Journal of Scientific Research in Engineering and Management. 7(7). DOI: https://doi.org/10.55041/IJSREM24390
[21] Poojary, M., Srinivas, Y., 2022. A Novel Methodology for Disease Identification using Metaheuristic Algorithm and Aura Image. IJACSA: International Journal of Advanced Computer Science and Applications. 13(7), 590–594. DOI: https://doi.org/10.14569/ijacsa.2022.0130770
[22] Priyatkin, N.S., Arkhipov, M.V., Gusakova, L.P., et al., 2023. Application of gas discharge visualization technique for seeds hidden defects evaluation. Theoretical and Applied Ecology. 3, 37–48. DOI: https://doi.org/10.25750/1995-4301-2023-3-037-048 (in Russian)
[23] Gornale, S.S., Patil, S.S., Deo, A.W., et al., 2026. Transfer learning‑driven biofield image analysis for predictive modeling of diabetes. Journal of Medical Physics. 51(1), 136–144. DOI: https://doi.org/10.4103/jmp.jmp_245_25
[24] Wu, X., Liang, X., Wang, Y., et al., 2022. Non-Destructive Techniques for the Analysis and Evaluation of Meat Quality and Safety: A Review. Foods. 11(22): 3713. DOI: https://doi.org/10.3390/foods11223713
[25] Mandel, P., 1986. Energy Emission Analysis, New Application of Kirlian Photography for Holistic Health. Synthesis Publishing Co.: Essen, Germany.
[26] Sass, D.B., Meissner, D.C., 1985. Kirlian Photography Material Science, Testing and Ichnology. In: Snyder, R.L., Condrate, R.A., Johnson, P.F. (Eds.). Advances in Materials Characterization II. Materials Science Research, Vol. 19. Springer: Boston, MA, USA. DOI: https://doi.org/10.1007/978-1-4615-9439-0_31
[27] Solomon, G., Solomon, J., 2003. Harry Oldfield's Invisible Universe: The Story of One Man's Search for the Healing Methods That Will Help Us Survive the 21st Century. Campion Books: Artarmon, Australia.
[28] Kotrotkov, K., 2014. Energy Fields Electrophotonic Analysis in Humans and Nature. CreateSpace Independent Publishing Platform: North Charleston, SC, USA.
[29] Priyadarsini, K., Thangam, P., Gunasekaran, S., 2014. Kirlian Images in Medical Diagnosis: A Survey. International Journal of Computer Applications (IJCA). 5–7.
[30] Internationales Mandel Institut für Esogetische Medizin GmbH, n.d. Welcome at the International Mandel Institute. Available from: https://mandel-institut.com/en/ (cited 28 July 2026).
[31] Krippner, S., 1979. Biological applications of Kirlian photography. Journal of the American Society of Psychosomatic Dentistry and Medicine. 26(4), 122–128.
[32] Marino, A.A., Becker, R.O., Ullrich, B., et al., 1979. Kirlian Photography: Potential for use in diagnosis. Psvchoenergetic Systems. 3, 47–54. Available from: https://www.academia.edu/7975448/Kirlian_Photography_Potential_for_use_in_diagnosis
[33] Gornale, S.S., Patil, S.S., Deo, A.W., et al., 2024. Quantitative Analysis of Biofield Energy Imbalance through Color Segmentation and Classification Using Machine Learning Techniques. In Proceedings of the 2024 IEEE 9th International Conference for Convergence in Technology (I2CT), Pune, India, 5–7 April 2024; pp. 1–5. DOI: https://doi.org/10.1109/I2CT61223.2024.10543817
[34] Zhang, Y., Chen, N., Li, J., et al., 2026, Advanced optical probes assisted biomedical diagnostics. TrAC Trends in Analytical Chemistry. 197, 118729. DOI: https://doi.org/10.1016/j.trac.2026.118729
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Copyright © 2026 Sergey Grigoryevich Kharchenko, Dmitry Evgenievich Kucher

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Sergey Grigoryevich Kharchenko