Impact of oily wastewater for public health in rural area: a case study of Kazakhstan

Oil refinery industry historically has been related with groundwater pollution. According to WHO, contaminants may reach groundwater most easily as a result of discharge to the ground surface and subsequent infiltration through the soils, or releases from the ponds. Environmental Performance Review for Kazakhstan from UNECE states that oil refinery factories in Kazakhstan are one of the biggest sources of groundwater contamination despite of existing governmental and industry environmental monitoring systems. Recent studies showed that more than 50% of the people in rural Kazakhstan use groundwater for domestic purposes, consequently, many people potentially drink unsafe water. Despite this, oil refineries in Kazakhstan continue to discharge wastewater with high concentrations of different pollutants and these contaminants reach the groundwater very easily. The aim of this paper is to analyse and interpret a dataset obtained during a 6-year (2014–2019) monitoring program of the control of groundwater quality surrounding recipient of poorly treated wastewater discharges in one of the Kazakhstani industrial clusters. Multivariate statistical techniques and Heckman selection model were used for assessment of loading of natural and anthropogenic contribution to contamination, including separated evaluation of the impact of toxic substances.

The results show that PCAs have high loading of anthropogenic contamination to groundwater from the oil refinery industry coupled with natural geochemical processes. High concentrations of several parameters, such as total petroleum hydrocarbons, phenols, sodium, chlorides, sulphates, total dissolved solids and total hardness were identified. Water containing such exceeding concentrations of substances affects human body significantly and normally is considered to be rejected by consumers. By means of cluster analysis, the examined wells were combined in three groups according to the concentrations of chemicals and their locations. The results enable a prediction of the groundwater flow in the region studied as well as an estimation of which sites would be most severely affected by contamination. According to obtained data from Heckman analysis, focus of further research should be paid to the distribution of toxic contaminants. The industry is continuing to pollute the environment, which means that assessment of existent and future hazards is needed through improved monitoring system. Thus, the next step of the research considers contamination transport modelling for definite identification of groundwater flow and potentially affected rural areas.