With increasing atmospheric pollution and health issues associated with size of the particulate matter, it has become important to look for techniques that may improve the monitoring resolution. Magnetic bio-monitoring of particulate matter has been used in recent years in some countries as an approach for better spatial resolution that provides proxy indicators for the measurements over large areas. Delhi, which is one of the most polluted cities of not just India, but the whole world, is still probing to understand the possible sources. The present magnetic biomonitoring study was therefore, carried across different land use areas in some air pollution hotspots of Delhi, using common roadside tree species Morus alba, Ficus religiosa, Ficus virens and Ficus benghalensis to understand the magnitude and nature of the particulate pollution, and possible sources by studying magnetic properties (Magnetic susceptibility, Frequency-dependent susceptibility, S-ratio, and SIRM) of the dust deposited on leaves. Mass specific magnetic susceptibility (10⁻⁸ m³ kg⁻¹) values were found to follow the order: Traffic intersection area (25.6–66.5) > Industrial area (25.4–41.3) > Residential area (13.2–30.1) > Institutional area serving as control (2.7–6.6). High magnetic susceptibility values indicated particulates with ferrimagnetic grains of anthropogenic or technogenic origin. Frequency-dependent Susceptibility indicated dominance of coarse multidomain (MD) and Pseudo Single Domain (PSD) +MD grains in industrial area and major traffic intersection. Average S ratio across all study sites ranged from 0.92 to 0.99 indicating presence of soft magnetic mineral with low coercivity. High SIRM values (10⁻⁵Am² kg⁻¹) from 58.1 to 862.3 suggested prevalence of magnetite dominating atmospheric particulates particularly in traffic intersection and industrial area, and to some extent in residential area. Morus alba and Ficus religiosa were found more suitable bio-monitors and the technique provided useful information on size, mineralogy and possible source of the particulates.

The present study aims to extract a natural reddish brown colorant from Peepal (Ficus religiosa) for silk dyeing using the microwave radiation process (MW). The colorant was isolated in aqueous and acidic media, and MW treatment for 1, 2, 3, 4, and 5 min has been given to both fabric and extract to observe changes in color intensity. The dye variables have been optimized, and for sustainable shade making process with good fastness, 1.0–5.0 g/100 mL of sustainable chemical and bio-mordants has been employed. It has been found that after microwave treatment for 3 min, under selected conditions, the irradiated aqueous extract has given high color intensity onto silk fabric. The utilization of 3% of Al, 4% of Fe, and 2% of tannic acid (T.A.) as pre chemical mordant whereas 4% of Al, 4% of Fe, and 3% of tannic acid as post chemical mordant have given good color characteristics. In comparison, 4% of acacia and 3% of turmeric and pomegranate while 3% of acacia and turmeric and 4% of pomegranate extracts as post-bio-mordant have given excellent color characteristics. It is concluded that MW treatment has an excellent sustainable efficacy to isolate colorant from Peepal bark for silk dyeing, whereas the inclusion of bio-mordants has not only made the process more sustainable and environmental friendly but also best K/S, and L*a*b* values have been acquired.

Particulate matter (PM) is one of the most dangerous pollutants in the air. Urban vegetation, especially trees and shrubs, accumulates PM and reduces its concentration in ambient air. The aim of this study was to examine 10 tree and shrub species common for the Indian city of Jodhpur (Rajasthan) located on the edge of the Thar Desert and determine (1) the accumulation of surface and in-wax PM (both in three different size fractions), (2) the amount of epicuticular waxes on foliage, (3) the concentrations of heavy metals (Cd and Cu) on/in the leaves of the examined species, and (4) the level of heme oxygenase enzyme in leaves that accumulate PM and heavy metals. Among the investigated species, Ficus religiosa L. and Cordia myxa L. accumulated the greatest amount of total PM. F. religiosa is a tall tree with a lush, large crown and leaves with wavy edge, convex veins, and long petioles, while C. myxa have hairy leaves with convex veins. The lowest PM accumulation was recorded for drought-resistant Salvadora persica L. and Azadirachta indica A. Juss., which is probably due to their adaptation to growing conditions. Heavy metals (Cu and Cd) were found in the leaves of almost every examined species. The accumulation of heavy metals (especially Cu) was positively correlated with the amount of PM deposited on the foliage. A new finding of this study indicated a potentially important role of HO in the plants’ response to PM-induced stress. The correlation between HO and PM was stronger than that between HO and HMs. The results obtained in this study emphasise the role of plants in cleaning polluted air in conditions where there are very high concentrations of PM.

Green vegetation enrichment is a cost-effective technique for reducing atmospheric pollution. Fifteen common tropical plant species were assessed for identifying their air pollution tolerance, anticipated performance, and metal accumulation capacity at Jharia Coalfield and Reference (JCF) site using Air Pollution Tolerance Index (APTI), Anticipated Performance Index (API), and Metal Accumulation Index (MAI). Metal accumulation efficiencies were observed to be highest for Ficus benghalensis L. (12.67mg/kg) and Ficus religiosa L. (10.71 mg/kg). The values of APTI were found to be highest at JCF for F. benghalensis (APTI: 25.21 ± 0.95), F. religiosa (APTI: 23.02 ± 0.21), Alstonia scholaris (L.) R. Br. (APTI: 18.50 ± 0.43), Mangifera indica L. (APTI: 16.88 ± 0.65), Azadirachta indica A. Juss. (APTI: 15.87 ± 0.21), and Moringa oleifera Lam. (APTI: 16.32 ± 0.66). F. benghalensis and F. religiosa were found to be excellent performers to mitigate air pollution at JCF as per their API score. Values of MAI, APTI, and API were observed to be lowest at reference sites for all the studied plant species due to absence of any air polluting sources. The findings revealed that air pollution played a significant impact in influencing the biochemical and physiological parameters of plants in a contaminated coal mining area. The species with the maximum MAI and APTI values might be employed in developing a green belt to minimize the levels of pollutants into the atmosphere.

Twenty-one plant leaf materials were screened for benzene adsorption efficiency in the static system, and the leaf material from Dieffenbachia picta, Acrostichum aureum, Ficus religiosa, Lagerstroemia macrocarpa, Alstonia scholaris, and Dracaena sanderiana were found to have high potential for benzene removal. The relation between quantity and composition of wax to benzene removal efficiency was studied. Although high quantities of wax occurred in some leaf materials, low benzene removal was clearly found if compared with other plant materials with the same wax quantity. Alpha-linoleic acid and dodecyl cyclohexane were found to be the main composition in plant leaf materials with high benzene adsorption, and it might be a key factor for benzene removal.

The present study was planned to explore the bioaccumulation potential of 23 plant species via bioaccumulation factor (BAf), metal accumulation index (MAI), translocation potential (Tf), and comprehensive bioconcentration index (CBCI) for seven heavy metals (cadmium, chromium, cobalt, copper, iron, manganese, and zinc). The studied plants, in the vicinity of ponds at Sahlon: site 1, Chahal Khurd: site 2, and Karnana: site 3 in Shaheed Bhagat Singh Nagar, Punjab (India), were Ageratum conyzoides (L.) L., Amaranthus spinosus L., Amaranthus viridis L., Brassica napus L., Cannabis sativa L., Dalbergia sissoo DC., Duranta repens L., Dysphania ambrosioides (L.) Mosyakin & Clemants, Ficus infectoria Roxb., Ficus palmata Forssk., Ficus religiosa L., Ipomoea carnea Jacq., Medicago polymorpha L., Melia azedarach L., Morus indica L., Malva rotundifolia L., Panicum virgatum L., Parthenium hysterophorus L., Dolichos lablab L., Ricinus communis L., Rumex dentatus L., Senna occidentalis (L.) Link, and Solanum nigrum L. BAf and Tf values showed high inter-site deviations for studied metals. MAI values were found to be more substantial in shoots as compared with that of roots of plants. Maximum CBCI values were observed for M. azedarach (0.626), M. indica (0.572), D. sissoo (0.497), and R. communis (0.474) for site 1; F. infectoria (0.629), R. communis (0.541), D. sissoo (0.483), F. palmata (0.457), and D. repens (0.448) for site 2; D. sissoo (0.681), F. religiosa (0.447), and R. communis (0.429) for site 3. Although, high bioaccumulation of individual metals was observed in herbs like C. sativa, M. polymorpha, and Amaranthus spp., cumulatively, trees were found to be the better bioaccumulators of heavy metals.

Atmospheric pollution by opencast mining activities affects tree species around the mining area. The present study evaluated the responses of five native tree species to air pollution in Jharia coalfield. Sites were selected as closest to farthest from the mining area. Foliar dust deposition and foliar sulphate content affected stomatal conductance, superoxide dismutase activity and ascorbic acid and, thus, increased the susceptibility of sensitive species. Ficus benghalensis and Butea monosperma showed maximum dust deposition, while Adina cordifolia showed minimum deposition. Maximum dust deposition in Ficus benghalensis lowered stomatal conductance and, thus, checked the flux of other acidic gaseous pollutants which led to minimum variation in leaf extract pH. Higher stomatal conductance in Adina cordifolia and Aegle marmelos, on the other hand, facilitated the entry of acidic pollutants and disrupted many biological functions by altering photosynthesis and inducing membrane damage. Low variations in Ficus religiosa, Ficus benghalensis and Butea monosperma with sites and seasons suggest better physiological and morphological adaptations towards pollution load near coal mining areas. Tree species with better adaptation resisted variation in leaf extract pH by effectively metabolising sulphate and, thus, had higher chlorophyll content and relative water content.