DO₃SE (Deposition of Ozone for Stomatal Exchange), is a dry deposition model, designed to assess tropospheric ozone risk to vegetation, and is based on two alternative algorithms to estimate stomatal conductance: multiplicative and photosynthetic. The multiplicative model has been argued to perform better for leaf-level and regional-level application. In this study, we demonstrate that the photosynthetic model is superior to the multiplicative model even for leaf-level studies using measurements performed on Mangifera indica. We find that the multiplicative model overestimates the daytime stomatal conductance, when compared with measured stomatal conductance and prescribes zero conductance at night while measurements show an average conductance of 100 mmol(H₂O)m⁻²s⁻¹ between 9 p.m. and 4 a.m. The daytime overestimation of the multiplicative model can be significantly reduced when the model is modified to include a response function for ozone-induced stomatal closure. However, nighttime pollutant uptake fluxes can only be accurately assessed with the photosynthetic model which includes the stomatal opening at night during respiration and is capable of reproducing the measured nighttime stomatal conductance. At our site, the nocturnal flux contributes 64%, 39%, 46%, and 88% of the total for NO₂ uptake in winter, summer, monsoon, and post-monsoon, respectively. For SO₂, nocturnal uptake amounts to 35%, 28%, 28%, and 44% in winter, summer, monsoon, and post-monsoon, respectively while for ozone the nighttime uptake contributes 30%, 17%, 18%, and 29% of the total stomatal uptake in winter, summer, monsoon, and post-monsoon respectively.

This study explored the interspecies and seasonal variation of polycyclic aromatic hydrocarbons (PAHs) in the extracted lipids of the leaves of seven local plants in an urban environment of Kolkata (22°33′N and 88°20′E), India. Based on the degree of toxicity and carcinogenicity (expressed in terms of their Benzo(a)pyrene equivalent (BaPeq) concentrations) the overall foliar-PAH accumulation during the study period (September 2018‒;August 2019) in the various plants showed the following order: Nerium oleander (80.96 ± 30.08 ng.gdw−1) > Mangifera indica (74.15 ± 20.34 ng.gdw−1) > Lantana aculeata (60.13 ± 21.71 ng.gdw−1) > Thevetia peruviana (40.97 ± 12.45 ng.gdw−1) > Ixora coccinea (38.11 ± 9.5 ng.gdw−1) > Murraya paniculata (37.1 ± 7.35 ng.gdw−1) > Polyalthia longifolia (25.72 ± 5.71 ng.gdw−1). The PAHs like phenanthrene, anthracene, fluoranthene, pyrene, benzo(a)anthracene, chrysene, benzo (b+k)fluoranthene, benzo(a)pyrene, benzo [ghi]perylene and indeno [1,2,3-cd]pyrene were predominant during the study period over the PAHs like naphthalene, acynaphthylene, acenaphthene, fluorine and dibenz [a,h]anthracene in the extracted lipids. The temperature-dependent partitioning of the PAHs onto leaf-surface and photo-degradation could have affected the availability of the PAHs. The foliar PAH accumulation varied seasonally as winter (December–February) > postmonsoon (September–November) > premonsoon (March–May) > monsoon (June–August). The leaf epicuticular wax determined the PAH uptake and storage, which in turn was affected by the temperature and solar radiation. In consistence with the idea of “nature-based solutions” for deteriorated air quality remediation in an urban environment, this study could be a promising initiative to build up cost-effective biological filters to combat the airborne pollutants and improve urban air quality.

This paper evaluates the biosorption of toxic metal ions onto the bioadsorbents derived from mango (Mangifera indica) and guava (Psidium guiag) barks and their metal fixation mechanisms. Maximum metal biosorption capacities of the mango bioadsorbent were found in the following increasing order (mg/g): Hg (16.24) < Cu (22.24) < Cd (25.86) < Pb (60.85). Maximum metal biosorption capacities of guava bioadsorbent follow similar order (mg/g): Hg (21.48) < Cu (30.36) < Cd (32.54) < Pb (70.25), but with slightly higher adsorption capacities. The removal mechanisms of heavy metals using bioadsorbents have been ascertained by studying their surface properties and functional groups using various spectrometric, spectroscopic, and microscopic methods. Whewellite (C₂CaO₄·H₂O) has been identified in bioadsorbents based on the characterization of their surface properties using X-ray techniques (XPS and XRD), facilitating the ion exchange of metal ions with Ca²⁺ bonded with carboxylate moieties. For both the bioadsorbents, the Pb²⁺, Cu²⁺, and Cd²⁺ are biosorbed completely by ion exchange with Ca²⁺ (89–94%) and Mg²⁺ (7–12%), whereas Hg²⁺ is biosorbed partially (57–66%) by ion exchange with Ca²⁺ (38–42%) and Mg²⁺ (19–24%) due to involvement of other cations in the ion exchange processes. Bioadsorbents contain lignin which act as electron donor and reduced Cr(VI) into Cr(III) (29.87 and 37.25 mg/g) in acidic medium. Anionic Cr(VI) was not adsorbed onto bioadsorbents at higher pH due to their electrostatic repulsion with negatively charged carboxylic functional groups.

Traditional agroforestry systems, one of the time tested and dominant land use from tropical to sub-tropical regions, were recognized for their contributions to food production, biodiversity conservation, and atmospheric carbon sequestration. Their management often varies from region to region. However, these systems frequently mimic economically managed land uses due to increased pressure on the monetary requirement of their managers. The present study aims to evaluate (i) tree density, (ii) tree diversity indices, and (iii) identify the biomass carbon important tree species managed by different communities of the Indian Eastern Himalayan region. We found that the Mizo community harbored the highest number of tree species (35) in the traditional agroforestry system with the highest tree diversity index (3.47). Total biomass carbon of tropical agroforestry systems managed by different communities ranged between 4.72 Mg ha⁻¹ (Meitei) and 29.26 Mg ha⁻¹ (Bengali). Similarly, in the sub-tropical traditional agroforestry system, the highest and the lowest biomass carbon was observed in Mizo- (10.93 Mg ha⁻¹) and Angami- (6.05 Mg ha⁻¹) managed systems. Of the 31 biomass carbon, important species found across the traditional agroforestry systems, Artocarpus heterophyllus, had the highest occurrence (50%), followed by Parkia timoriana (37.5) and Amoora rohituka, Delonix regia, Mangifera indica, and Toona ciliata (25% for each species). Farmers’ preference to cash return of a species, trees density, and basal area were the determinant factors in the carbon stock potential of these systems. The present study suggests that the farmers’ preferred and dominant species in their agroecosystems have a limited scope of enhanced biomass carbon storage. Therefore, improvement of traditional agroforestry systems through selective incorporation of biomass carbon important tree species is recommended to enhance the carbon sink capacity of these systems.

The present work focused on the utilization of three local wastes, i.e., rambutan (Nephelium lappaceum), langsat (Lansium parasiticum), and mango (Mangifera indica) wastes, as organic substrates in a benthic microbial fuel cell (BMFC) to reduce the cadmium and lead concentrations from synthetic water. Out of the three wastes, the mango waste promoted a maximum current density (87.71 mA/m²) along with 78% and 80% removal efficiencies for Cd²⁺ and Pb²⁺, respectively. The bacterial identification proved that Klebsiella pneumoniae, Enterobacter, and Citrobacter were responsible for metal removal and energy generation. In the present work, the BMFC mechanism, current challenges, and future recommendations are also enclosed.

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.

Air pollutant concentration of Trivandrum, the capital of Kerala, exceeded the limits of National Ambient Air Quality (NAAQ) standards, according to a study conducted in 2015 by NATPAC. These polluted corridors harbour vegetation on roadsides and traffic islands, planted solely for aesthetic appeal. Analysis of air pollution tolerance levels of existing plants can act as a scientific basis for efficient planning of the urban landscape. Sixty-seven species, including flowering, fruit-bearing, ornamental, shade-providing and timber-yielding species, were screened for their relative resistance to air pollution. Based on leaf pH, relative water content, chlorophyll and ascorbic acid levels, the Air Pollution Tolerance Indices (APTI) of each species were formulated and they were grouped into the following: tolerant, moderately tolerant, intermediate and sensitive groups. Agave americana (18.40), Cassia roxburghii (17.63), Anacardium occidentale (11.97), Cassia fistula (11.60), Mangifera indica (11.59) and Saraca asoca (10.88) may be considered for planting near green spaces like roundabouts and near pollution prone industrial areas, as they belong to tolerant category. Comparison of APTI during summer and monsoon also revealed the stability of Agave americana, Saraca asoca, Ficus benghalensis, Peltophorum pterocarpum, Ficus elastica, Ixora finlaysoniana, Mangifera indica, Canna indica and Delonix regia in maintaining pollution tolerance even during water disparity. Agave americana, Anacardium occidentale, Ficus elastica, Mangifera indica, Syzygium cumini, Ficus benghalensis, Nerium oleander and Ficus benjamina were found to be suited for mass planting, as was evident from their Anticipated Performance Indices (API).

The present study reports the potential of carbon (C) storage in traditional agroforestry systems (i.e., a set of age-old agroforestry systems) under waterlogged environmental conditions from north-eastern India. An experiment was conducted in a farmer’s field and further used CO₂FIX model, allometric equations, and destructive sampling methods to know the potential of C sequestration. In this study area, agroforestry system is dominated by woody perennials like Areca catechu, Cocos nucifera, Mangifera indica, Artocarpus heterophyllus, Melocanna baccifera, and Colocasia esculenta as annual crop component. Need-based management of the drainage system has been built-up by making broad/narrow bunds for maintaining water levels at different stages of plant growth. The total annual carbon storage potential of this traditional agroforestry system was estimated as 103.760±8.630 t ha⁻¹year⁻¹. The highest annual carbon storage potential (97.900±8.090 t ha⁻¹year⁻¹) was recorded in annual crop components (i.e., Colocasia) followed by trees and its underlaid soil (4.250±0.340 t ha⁻¹year⁻¹) and lowest for bamboos (1.610± 0. 200 t ha⁻¹ year⁻¹). However, the estimated carbon stored, annually, was 24.992±1.502 t ha⁻¹ year⁻¹ in which Colocasia share maximum contribution (19.600±1.080 t ha⁻¹ year⁻¹) followed by trees + soil (3.798±0.229 t ha⁻¹ year⁻¹) and the minimum contribution from bamboos (1.594±0.193 t ha⁻¹ year⁻¹). Moreover, total carbon loss from harvesting of this system was 78.768±7.128 t ha⁻¹ year⁻¹. The study, therefore, recommends this agroforestry system for other waterlogged ecosystems at regional and/or global scale under a warm per-humid climate for both livelihood opportunities and environmental sustainability.

High atmospheric pollution levels in urban areas have become a global problem that threatens both human health and urban ecosystems. Trees that grow near areas with vehicular and industrial emissions can be highly affected, since they constitute the main barrier for emitted pollutants, with trees being either tolerant or sensitive to them. Different methodologies worldwide have been implemented to evaluate the tolerance and sensitivity of tree species to atmospheric pollutants. In this research, the air pollution tolerance index (APTI) and the anticipated performance index (API) are evaluated in order to determine both the degree of tolerance or sensitivity of trees to pollutants in the air and their performance in urban areas. To this end, six tree species found in four biomonitoring zones in the city of Medellín, Colombia, were selected: Mangifera indica, Tabebuia chrysantha-rosea, Erythrina fusca, Jacaranda mimosifolia, Fraxinus uhdei, and Spathodea campanulata. A total of 54 individual trees were evaluated by means of the APTI and API, and it was determined that the species with the highest tolerance (APTI≥16) and the best performance (81<API<90) was Mangifera indica, which highlights the importance of this species in urban areas with air quality problems. On the other hand, it was determined that the most sensitive species (APTI≤11) are Tabebuia chrysantha-rosea, Erythrina fusca, and Spathodea campanulata, while the species with poor performance (41<API<50) are Tabebuia chrysantha-rosea, Erythrina fusca, and Jacaranda mimosifolia. These values, therefore, can be used to classify which species can be planted as pollutant sinks and which as air quality bioindicators and thus highlight the importance of urban forests and trees for environmental management and planning in big cities with air quality problems.