Assessing the environmental impact of air pollution on crops by monitoring air pollution tolerance index (APTI) and anticipated performance index (API)

Greenery planning for urban air pollution control based on biomonitoring potential: Explicit emphasis on foliar accumulation of particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs)

In this study, efficiencies of eight indigenous plants of Baishnabghata Patuli Township (BPT), southeast Kolkata, India, were explored as green barrier species and potentials of plant leaves were exploited for biomonitoring of particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs). The present work focused on studying PM capturing abilities (539.32-2766.27 μg cm-2) of plants (T. divaricata, N. oleander and B. acuminata being the most efficient species in retaining PM) along with the estimation of foliar contents of PM adhered to leaf surfaces (total sPM (large + coarse): 526.59-2731.76 μg cm-2) and embedded within waxes (total wPM (large + coarse): 8.73-34.51 μg cm-2). SEM imaging used to analyse leaf surfaces affirmed the presence of innate corrugated microstructures as main drivers for particle capture. Accumulation capacities of PAHs of vehicular origin (total index, TI > 4) were compared among the species based on measured concentrations (159.92-393.01 μg g-1) which indicated T. divaricata, P. alba and N. cadamba as highest PAHs accumulators. Specific leaf area (SLA) of plants (71.01-376.79 cm2 g-1), a measure of canopy-atmosphere interface, had great relevance in PAHs diffusion. Relative contribution (>90%) of 4-6 ring PAHs to total carcinogenic equivalent and potential as well as 5-6 ring PAHs to total mutagenic equivalent and potential had also been viewed with respect to benzo[a]pyrene. In-depth analysis of foliar traits and adoption of plant-based ranking strategies (air pollution tolerance index (APTI) and anticipated performance index (API)) provided a rationale for green belting. Each of the naturally selected plant species showed evidences of adaptations during abiotic stress to maximize survival and filtering effects for reductive elimination of ambient PM and PAHs, allowing holistic management of green spaces.

Assessment of air pollution tolerance potential of selected dicot tree species for urban forestry

Air pollution is one of the killers of our age especially for the urban areas. Urban forestry which involves planting more trees has been considered as one of the prominent strategies to mitigate air pollution. Identification of trees tolerant to air pollution is important for plantation drives being organized across the country. The present study aimed to compare the air pollution tolerance potential of 46 tree species growing in Guru Nanak Dev University (GNDU) campus, Amritsar, using two indices, viz., Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API). APTI is based on four biochemical parameters, viz., relative water content, leaf extract pH, total chlorophyll, and ascorbic acid contents of leaf samples, whereas API takes into consideration morphological and socioeconomic values of plant species along with their APTI. Based on APTI values calculated for 46 tree species, only 2 tree species, viz., Psidium guajava (46.26) and Cassia fistula (41.83), were found to be tolerant to air pollution, while 25 species showed intermediate tolerance. API scores revealed one tree species, namely, P. guajava, as an excellent performer, 8 species as very good performers, and 28 species as moderate to good performers against air pollution. In conclusion, tree species like Alstonia scholaris, C. fistula, Ficus tsjakela, Grevillea robusta, Kigelia africana, Mangifera indica, Melia azedarach, P. guajava, Pongamia pinnata, Pterospermum acerifolium, Putranjiva roxburghii, Syzygium cumini, Terminalia arjuna, and Toona ciliata can be considered as most desirable for plantations in areas around GNDU campus.

Environmental pollution biomonitoring around a cement factory based on the Air Pollution Tolerance Index of some tree species

The present study examined the ability of Quercus castaneifolia C.A.M., Parrotia persica C.A.M., and Carpinus betulus L. for environmental pollution biomonitoring based on the Air Pollution Tolerance Index (APTI). Four leaf traits, total leaf chlorophyll content, leaf extract pH, ascorbic acid content, and relative water content of leaf, were used to compute the APTI values. The study was conducted at five sites in the Hyrcanian forests at different distances from a cement factory close to the Neka city, northern Iran. Based on the results, a 22.5, 30.1, and 25.8% decrease was thus recorded in total chlorophyll content for Q. castaneifolia, P. persica, and C. betulus, respectively, compared to the reference site. However, ascorbic acid content shows an increment of 179.8, 116.8, and 97.3% for P. persica, C. betulus, and Q. castaneifolia, respectively, in the polluted sites as compared to the reference site. The relative water content of P. persica was significantly higher than of Q. castaneifolia and C. betulus in all studied sites. APTI was significantly different among the species, and P. persica was highly tolerant to air pollution, with the highest values of APTI ranging from 11.8 to 16.9. The APTI values of Q. castaneifolia ranged from 9.5 to 11.3 and showed an intermediate tolerance to air pollution. Also, the most sensitive species to air pollution was C. betulus, with a range of 6.6-7.9 in APTI values. Based on APTI values, it can be suggested that P. persica can be used as a biomonitor, while C. betulus can be used as a bioindicator for atmospheric dust deposition and heavy metal pollution.

Environmental impacts of air pollution and its abatement by plant species: A comprehensive review

Air pollution is one of the major global environmental issues urgently needed attention for its control through sustainable approaches. The release of air pollutants from various anthropogenic and natural processes imposes serious threats to the environment and human health. The green belt development using air pollution-tolerant plant species has become popular approach for air pollution remediation. Plants' biochemical and physiological attributes, especially relative water content, pH, ascorbic acid, and total chlorophyll content, are taken into account for assessing air pollution tolerance index (APTI). In contrast, anticipated performance index (API) is assessed based on socio-economic characteristics including "canopy structure, type, habit, laminar structure, economic value and APTI score" of plant species. Based on previous work, plants with high dust-capturing capacity are identified in Ficus benghalensis L. (0.95 to 7.58 mg/cm2), and highest overall PM accumulation capacity was observed in Ulmus pumila L. (PM10 = 72 µg/cm2 and PM2.5 = 70 µg/cm2) in the study from different regions. According to APTI, the plant species such as M. indica (11 to 29), Alstonia scholaris (L.) R. Br. (6 to 24), and F. benghalensis (17 to 26) have been widely reported as high air pollution-tolerant species and good to best performer in terms of API at different study sites. Statistically, previous studies show that ascorbic acid (R2 = 0.90) has good correlation with APTI among all the parameters. The plant species with high pollution tolerance capacity can be recommended for future plantation and green belt development.

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

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, PM₁₀, SO₂, and NO₂) 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, PM₁₀, SO₂, and NO₂) 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 (R²) 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 (R² = 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.

Assessment of air pollution tolerance index (APTI) and anticipated performance index (API) of selected roadside plant species for the green belt development at Ratnagiri City in the Konkan region of Maharashtra, India

Small towns are becoming hotspots of pollution due to industrial, urbanisation, and domestic activities. Air pollution affects human health and it is also responsible for physiological changes in plants. Green belt development programmes are cost-effective for the minimisation of air pollution. In the present study, to calculate air pollution tolerance index (APTI) and anticipated performance index (API), samples of 25 plant species were collected from each area i.e. the industrial (I), urban (U), and rural (R) areas and analysed for different parameters. Amongst all three areas, APTI of Artocarpus heterophyllus (46.74), Calotropis gigantea (43.63), and Bauhinia racemose (42.11) have shown the highest values and these plants can act as an inhibitor of air pollution. Also, the APTI of Ocimum tenuiflorum has found to be the lowest (12.05, 11.32, 12.86) as compared to other plant species amongst the three areas. Statistical analysis reveals that values of R² are consistent in case of total chlorophyll (TC) and ascorbic acid (AA). API index showed the efficiency of Calotropis gigantea (excellent), Artocarpus heterophyllus (very good), and Mangifera indica (very good) for the green belt development around the selected areas. It is recommended to plant above-mentioned plant species along the roadside by considering their air pollution tolerance ability and medicinal as well as economic importance. Furthermore, it is suggested to plant species of Artocarpus heterophyllus (jackfruit) and Mangifera indica (Alphonso mango) which will generate income source for the local government bodies (Ratnagiri Municipal Council), as the fruits and wood of these plants can be exported and sold.

Air pollution and corporate innovation: incentive or resistance? Evidence from regression discontinuity

The potentially serious economic consequences of China's severe air pollution problem cannot be overlooked, especially the impact on corporate innovation, which is a core driver guiding firms towards efficient and high-quality development. However, the existing literature has more often investigated the effect of pollution on corporate innovation from the perspective of environmental regulation, while relatively little research is available directly from the perspective of air pollution. In this study, for better causal identification and endogeneity treatment, we consider the Qin ling Mountains-Huai River heating policy as a quasi-natural experiment and explore for the first time the causal effect of air pollution on Chinese industrial firms' innovation through a geographical regression discontinuity (RD) approach. The results find that air pollution has a significant inhibitory effect on the industrial firms' innovation, especially for green innovation, where the innovation of state-owned enterprises, high pollution, and low monopoly firms are more sensitive to pollution. Specifically, a 1% increase in PM_2.5 emissions leads to a 0.803% reduction in the corporate total innovation, a 0.924% reduction in invention patents, a 0.574% reduction in utility model patents, and a 1.087% reduction in design patents. We have verified the robustness of this core finding through a series of robustness checks including adjustment bandwidth, IV estimation, and placebo test. Further to this, we find that air pollution may negatively affect corporate innovation through three channels: crowding out R&D investment, reducing total factor productivity (TFP), and reducing labor supply and the proportion of highly skilled employees. This study sheds light on the severe losses caused by air pollution on corporate innovation capabilities at the micro-level, deepening the understanding of the economic harm caused by air pollution. This suggests that as firms strive to improve their innovative capacity and competitiveness, they should also be aware of environmental protection and green development; otherwise, unnecessary losses in innovation dynamics will be incurred.

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.