A biochemical and morphological study with multiple linear regression modeling–based impact prediction of ambient air pollutants on some native tree species of Haldwani City of Kumaun Himalaya, Uttarakhand, India

Abstract

The current study was conducted around the province of Haldwani City, Uttarakhand, India, to understand the seasonal variation of ambient air pollutants (PM 2.5, PM 10 , SO 2 , and NO 2 ) and their impact on four tree species, i.e., neem ( Azadirachta indica ), mountain cedar ( Toona ciliate ), bottlebrush ( Callistemon citrinus ), and guava ( Psidium guajava ) during 2020–2021. Multiple linear regression (MLR)-based prediction analysis showed that the selected air quality variables (PM 2.5 , PM 10 , SO 2 , and NO 2 ) had a significant impact on the biochemical responses of selected tree spp. including, pH, ascorbic acid (AA), total chlorophyll content (T. Chl.), relative water content (RWC), and dust deposition potential. In this, the coefficient of variance ( R 2 ) of the developed models was in the range of 0.70–0.98. The ambient air pollutants showed significant seasonal variations as depicted by using the air pollution tolerance index (APTI) and anticipated performance index (API). The tree species from polluted sites observed more pollution tolerance than the tree species from the control site. Regression analysis showed a significant positive association between the biochemical characteristics and APTI, with the highest influence by AA ( R 2 = 0.961) followed by T. Chl., RWC, and pH. The APTI and API score was observed as maximum for A. indica and minimum for C. citrinus . The impact of air pollutants on the morphology of foliar surface was investigated by the scanning electron microscopy (SEM) and recorded various dust deposition patterns, stomatal blockages, and damage of guard cells in the trees growing along the polluted site (S2). The present study can assist environmental managers to examine the pollution-induced variables and develop an effective green belt for combating air pollution in polluted areas. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-023-27563-4.