Assessment of environmental risks in the regions of Kazakhstan using a composite index: method and application

The purpose of this study is to develop a methodology for assessing environmental risks and to test it using data on pollution across different regions of Kazakhstan.

Methodology. The study uses a literature review and deductive reasoning to find solutions to environmental pollution. Content analysis helps develop an integrated, weighted environmental risk through composite indexing. Economic and mathematical methods (including Moran’s I, spatial weights matrices), along with visualization techniques, are used to present the research results.

The uniqueness of this study lies in its focus on the influence of natural and climate features of a specific region, along with pollution from neighboring areas, rather than relying solely on national pollution indicators and their effects on the regional environment. Data collected and analyzed on emissions and waste in Kazakhstan's four largest regions allowed for the calculation and comparison of environmental risk levels. Regional environmental risk assessments were based on data of the end of 2024. The study revealed that Karaganda (1.26) and West Kazakhstan (1.78) regions experienced high environmental risk during this period, particularly due to the municipal waste index. Meanwhile, in East Kazakhstan, the index, at -0.0142, was considered quite low, and in Kyzylorda, it was closer to the boundary between moderate and high environmental risk (0.198).

The study highlights the importance of quick access to environmental data for guiding management decisions by regional governments. It also stresses the need to expand and sustain this research by developing a regional environmental database. Calculation of environmental risks helps to clarify measures for environmental management in regions adjusting decisions considering the weight of a particular index.

1. Wen L., Salmond J., Allen K. & Tadaki M. (2024). “Managing emerging environmental risks when we do not know enough about them: The case of respirable mineral dust”. Environmental Science and Policy, 155 (2024) 103715, DOI:10.1016/j.envsci.2024.103715

2. Feduzi A. & Runde J. (2014). “Uncovering unknown unknowns: towards a baconian approach to management decision-making”. Organizational Behavior and Human Decision Processes, 124 (2), 268–283 DOI:10.1016/j.obhdp.2014.04.001

3. Brocal F., Paltrinieri N., Gonz´ alez-Gaya C., Sebasti´ an M.A. & Reniers, G. (2021). “Approach to the selection of strategies for emerging risk management considering uncertainty as the main decision variable in occupational contexts”. Safety Science. 134, 105041, DOI:10.1016/j.ssci.2020.105041

4. Brocal F., Gonz´ alez C., Komljenovic D., Katina P.F. & Sebasti´ an, M.A. (2019). “Emerging risk management in industry 4.0: An approach to improve organizational and human performance in the complex systems”. Complexity, 2089763, 13 p, DOI:10.1155/2019/2089763

5. Brocal F., Sebasti´an, M.A. & Gonz´alez C. (2017). “Theoretical framework for the new and emerging occupational risk modeling and its monitoring through technology lifecycle of industrial processes”. Safety Science.. 99, 178–186. DOI:10.1016/j.ssci.2016.10.016

6. Lazar E., Pan J. & Wang Sh. (2025). “Measuring climate-related and environmental risks for equities”. Journal of Environmental Management. 373,123393 DOI:10.1016/j.jenvman.2024.123393

7. Shokravi F., Sheikhzeinoddin A., Fathi F. & Ardali F. (2025). “Evaluating the environmental performance index and economic, financial, and political risks impacts in top oil-exporting and importing countries”. Environmental and Sustainability Indicators. 26,100690, DOI: 10.1016/j.indic.2025.100690

8. Yamada H. Moran’s I for Multivariate Spatial Data. (2024). Mathematics. 12(17), 2746; https://doi.org/10.3390/math12172746

9. Chen Y. 2021An analytical process of spatial autocorrelation functions based on Moran’s index. Plos. April 14, https://doi.org/10.1371/journal.pone.0249589

10. López M. J. & Cuadrado J. J. (2009). “Aplicación del estándar UNE 150008 en la evaluación del riesgo ambiental: Un enfoque práctico”. Revista de Medio Ambiente, 84(3), 45–53. https://repositorio.unbosque.edu.co/

11. UN. About the United Nations Environment Programme. UNEP’s contribution to the Sustainable Development Goals (SDGs) https://www.unep.org/who-we-are/about-us

12. UNEP. (2019). Global environment outlook – GEO-6: Healthy planet, healthy people. Cambridge University Press. https://doi.org/10.1017/9781108627146

13. OECD. (2015). Preventing environmental damage from products: Risk-based approaches. Organisation for Economic Co-operation and Development. https://www.oecd.org/environment/

14. ISO. (2018). ISO 31010:2019 Risk management – Risk assessment techniques. International Organization for Standardization.

15. Bureau of National Statistics of the Republic of Kazakhstan 2023 https://stat.gov.kz/ru/

16. G. Rebitzer, T. Bux, “Practical implementation of ISO 14001 in industry – Risk-based thinking and performance evaluation,” Journal of Cleaner Production, 2017.