Assessing thermal power effluent-induced air quality and associated environmental stress on Blumea lacera and Phyla nodiflora using chemometric, remote sensing and machine learning approach - Mahabub Rabbani; Mehebub Sarwar Hossain; Sk Saruk Islam; Sujit Kumar Roy; Aznarul Islam; Ismail Mondal; Sk Md Abu Imam Saadi (Geology, Ecology, and Landscapes)
Human interventions leading to effluent generation, which are critical threats to the environment. The Kolaghat Thermal Power Plant emits daily 7,500–8,000 metric tonnes of fly ash. Our investigation revealed fly ash deposition in the surrounding soil, containing high levels of copper (5.75 mg/kg) and iron (53.05 mg/kg). To evaluate the tolerance efficiency of Blumea lacera and Phyla nodiflora, we analysed various anatomical and biochemical parameters in plants from both polluted and non-polluted sites. The study integrated Sentinel-2 and Sentinel-5P satellite data with field investigations to validate six environmental indices, including CO, LST, NDVI, NO2, O3, and SO2. Machine learning (ML)-based models were employed for predictive analysis. In-situ findings indicated that stem pith length, cortical cells, epidermis of B. lacera, and cortex, vascular bundles, vessels of P. nodiflora, were smaller in polluted sites. Chlorophyll content in B. lacera was significantly reduced in polluted areas. ML-based parameters obtained an outstanding average accuracy of R2 (0.7–0.75), as well as root mean square error and mean absolute error. In conclusion, stress-tolerant activity in these plants manifests as inhibited growth. Both species, particularly B. lacera, show potential for phytoremediation, offering a natural solution to reduce pollutants at polluted sites.