Evaluation of Anticipated Performance Index, biochemical, and physiological parameters of Cupressus arizonica Greene and Juniperus excelsa Bieb for greenbelt development and biomonitoring of air pollution

Evaluation of the effects of dust pollution on specific plant species near and around the marble mining site in Rajasthan, India

Airborne particles (dust pollution) pose a significant threat to both human and plant populations. Plant leaves act as crucial biofilters, capturing significant amounts of air pollution; this characteristic offers a valuable tool to measure local pollution levels and assess individual plant species' ability to intercept and mitigate harmful dust particles. The present study was carried out to asses the effect of responses of various plant species to dust pollution near and around the marble mining site comprising residential site, highway area, and Central University of Rajasthan as control. The anticipated pollution index, air pollution tolerance index (APTI), dust absorption capacity, metal accumulation index (MAI), and biochemical factors were used to evaluate plant responses. Azadirachta indica A. Juss. demonstrated the highest (29.0) and Vachellia nilotica L. showed lowest (5.6) APTI, respectively. A. indica showed maximum MAI values in comparison to other plant species situated at residential site. Additionally, monitoring of particulate matter (PM10) observed to highest at highway, followed by mining, residential, and control sites. Overall A. indica representing highest APTI and effective dust capturing capacity at all sites could serve as potential pollution sinks. V. nilotica, with its very low APTI, can be marked as biomonitoring tool for detecting dust pollution.

Evaluation of air pollution (dust) tolerance index of three desert species Seidlitzia rosmarinus, Haloxylon aphyllum, and Nitraria schoberi under salinity stress

Dust causes adverse effects on the physiological and biochemical properties of plants, and under soil salinity conditions, these effects seem to be intensified, which limits their use in the development of the green belt around or within cities. In the research, the effect of salt (0, 30, and 60 dS m^-1) on air pollution (dust, 0 and 1.5 g m^-2 30 days^-1) tolerance index (APTI), peroxidase activity, and protein content of three desert species Seidlitzia rosmarinus, Haloxylon aphyllum, and Nitraria schoberi was investigated. The results indicated that the use of dust alone did not change the concentration of total chlorophyll in H. aphyllum, while it decreased the concentration of total chlorophyll by 18% in N. schoberi and 21% in S. rosmarinus. Under salt stress conditions, before and after applying dust, the concentration of total chlorophyll decreased in S. rosmarinus and N. schoberi plants, but there was no change in H. aphyllum. The amount of ascorbic acid, peroxide activity, and pH increased significantly with increasing salinity level before and after applying dust. Applying dust alone increased pH value only in N. schoberi and the amount of ascorbic acid and peroxidase in all three plants. Applying dust alone reduced relative water content and APTI only in N. schoberi plant and the amount of protein in all three plants. At salinity level of 60 dS m^-1 and with application of dust treatment, APTI was decreased by 10, 15, and 9% compared to its control before application of dust, respectively, in H. aphyllum, N. schoberi, and S. rosmarinus plants. Therefore, it was found that N. schoberi, which may be used as a bioindicator of air quality, has a lower APTI than S. rosmarinus and H. aphyllum, which may be served as suitable sinks to survive the air pollution (the development of a design on green belt around or within the city), under conditions of simultaneous application of dust and salt.

Prediction models for evaluating the impacts of ambient air pollutants on the biochemical response of selected tree species of Haridwar, India

This study aimed to assess the spatio-temporal impact of selected ambient air pollutants (SO₂, NO₂, PM₁₀, and PM_2.5) on the biochemical response of four tree species including Neem (Azadirachta indica), Mountain cedar (Toona ciliate), Bottlebrush (Callistemon citrinus), and Guava (Psidium guajava) in the province of Haridwar City, Uttarakhand, India. The study was performed in 2020 and 2021 over three selected sites (S1: institutional; S2: industrial; and S3: urban). Purposely, seasonal data of ambient air pollutants and biochemical parameters (ascorbic acid, carotenoid, chlorophyll, pH, relative water content, and dust load) of selected tree species were collected and analyzed using multiple linear regression (MLR) tool to develop prediction models. The results indicated that biochemical parameters of all tree species were negatively impacted by the polluted ambient air quality in the industrial and urban (S2 and S3) sites as compared to the non-polluted institutional (S1) site. The models were characterized by high prediction performance as indicated by the coefficient of determination (R²) values greater than 0.80. Moreover, A. indica was found to be more 'tolerant' based on the air pollution tolerance index (APTI) followed by T. ciliate, P. guajava, and C. citrinus. Similarly, the anticipated performance index (API) was reported higher for A. indica (75 to 81.25%) followed by T. ciliate (68.75 to 75.00%), P. guajava (56.25%), and C. citrinus (37.50%), respectively. This study revealed that the selected tree species are being negatively impacted by the induced pollutant exposure in the urban and industrial region of Haridwar, India which needs sufficient mitigation measures to conserve their diversities.

Screening of Plant Species Response and Performance for Green Belt Development: Implications for Semi-Urban Ecosystem Restoration

Screened plant species with potential for green belt development can act as eco-sustainable tools for restoring the polluted ecosystem. Eight plant species from two study locations in Ado-Odo, Ota, Ogun State, Nigeria, were examined to identify their air pollution response and performance by deploying two air pollution indices, namely air pollution tolerance index (APTI) and anticipated performance index (API). APTI results identified all screened plants as sensitive species suitable as bio-indicators of air pollution, with Ficus auriculata (2.42) common to the non-industrial location being the most sensitive. API scores categorized Ficus auriculata (56.25%) as a moderate performer, while Syzygium malaccense (75%) and Mangifera indica (75%) were identified as very good performers, suitable for green belt development. The relationship between each biochemical parameter with APTI was investigated using regression analysis and two-way analysis of variance. The model result showed a significant relationship between each biochemical parameter with APTI, and relative water content had the highest influence on APTI (R2 = 0.99436). Both indices (APTI and API) are suitable for screening and recommending native plant species for cultivation in the polluted environment, thus promoting ecological restoration. Hence, Syzygium malaccense, Mangifera indica and Ficus auriculata, respectively, were recommended for green belts design. Further intensive screening to identify tolerant species and best to excellent performer’s trees suitable for restoring the ecosystem is advised.

Assessment of Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API) of Roadside Plants for the Development of Greenbelt in Urban Area of Bathinda City, Punjab, India

The aim of the present study is to biomonitor the tolerance level of roadside plant species towards mitigation of air pollution for the development of greenbelt. The leaves of four plant species (Azadirachta indica, Ficus benghalensis, Melia azedarach and Polyalthia longifolia) were collected from 41 sampling sites of Bathinda city during summer and winter seasons. Seasonal variation in APTI and API was determined in selected plants. Highest APTI (13.54) was reported in F. benghalensis during summer and lowest APTI (11.69) in A. indica during winter season. The APTI and API value revealed that F. benghalensis was the best performer, A. indica and M. azedarach were excellent performers and P. longifolia a good performer in greenbelt development to mitigate the air pollution. Pearson's correlation analysis illustrated significant correlation between APTI, ascorbic acid, total chlorophyll, relative water and pH, respectively.