SELECTING ROADSIDE TREE SPECIES AND BIOCHEMICAL INDICATORS FOR AIR POLLUTION MONITORING

Abstract

Roadside vegetation is widely used to monitor urban air quality, but two practical questions remain unsettled: which species should be planted along traffic corridors, and how few biochemical parameters are needed to detect pollution stress reliably. We measured eleven leaf biochemical parameters in seven roadside tree species at nine sites across three cities of north-western India, giving a balanced set of 693 determinations. All eleven parameters changed monotonically with pollution level in every species and city. No parameter differed significantly between the three cities, indicating a common regional response. Principal component analysis resolved the eleven parameters onto two nearly independent axes explaining 92.1% of total variance: a pollution-response axis (66.3%) carrying the antioxidants, malondialdehyde and leaf extract pH, and a pigment axis (25.8%) carrying chlorophyll, carotenoids and flavonoids. Ward cluster analysis placed the species in three tolerance classes, and this classification agreed exactly with an independent ranking by membrane damage. Ascorbic acid, proline and the three antioxidant enzymes were intercorrelated at r = 0.985 to 0.997 and therefore carry largely redundant information, whereas leaf extract pH was the only parameter correlating significantly with all ten others. We recommend Ficus benghalensis and Syzygium cumini for heavily trafficked corridors, and a graded monitoring protocol of one, two or three parameters according to available laboratory capacity.