Regional differentiation of environmental risks and environmental protection financing in Ukraine based on open data

Abstract

Purpose. To assess regional differentiation in environmental risks and environmental protection financing in Ukraine and to test a transparent risk-oriented screening approach for detecting oblasts where the relative level of environmental pressure is not matched by an adequate financial response.

Methods. The empirical analysis is based on open statistical and analytical data. Mathematical modeling is based on the differentiation of environmental risks and environmental financing, taking into account pollutant emissions from stationary sources, air pollution in cities, capital investments and current expenditures of enterprises on environmental protection. The risk index was formed by min-max normalisation of the emission and air-pollution variables.

Results. The problem is considered in the context of the spatial concentration of industrial emissions, the need for evidence-based allocation of environmental resources, and the growing importance of recovery planning under wartime constraints. A pilot sample of four oblasts was selected: Dnipropetrovsk, Donetsk, Zaporizhzhia and Kyiv. These regions were chosen because comparable environmental and financial indicators were simultaneously available for them. For each region, the regional share of national emissions, the maximum urban air pollution index, the cumulative financial response for 2014-2023, the share of this response, the environmental pressure-to-finance ratio and an integrated risk index were calculated. The selected regions together accounted for the largest number of pollutant emissions from stationary sources in 2021, confirming the pronounced spatial concentration of industrial atmospheric pressure. Dnipropetrovsk oblast ranked first by the integrated risk index, and also had the largest share of cumulative financial response. Donetsk oblast ranked second by risk,  but demonstrated the strongest imbalance between pressure and financing. Zaporizhzhia oblast also showed an imbalance, Kyiv oblast had a lower atmospheric risk profile but a relatively higher financial share.

Conclusions. Open data can be used for preliminary diagnostics of regional discrepancies between environmental pressures and environmental protection financing. The proposed approach does not replace a full environmental assessment, but it can serve as an initial analytical module for identifying territories that require more detailed verification, targeted monitoring and priority consideration in regional environmental programmes. Further research should extend the model to a full panel of oblasts and include wartime environmental damage, waste, water, budget expenditure, environmental tax and socio-economic control variables.