Estimation of Anticipated Performance Index and Air Pollution Tolerance Index and of vegetation around the marble industrial areas of Potwar region: bioindicators of plant pollution response

Evaluation of air pollution tolerance index and anticipated performance index of selected roadside tree species in Ludhiana, India

Air quality has deteriorated in most big cities and becoming the fifth major cause of mortality in India. Among others, vehicle gaseous emission is a major contributor. Plants have different tolerance levels, which can be identified based on Air Pollution Tolerance Index (APTI). The objectives were to study the morphological and biochemical parameters for Air Pollution Tolerance Index (APTI) of selected roadside tree species (Acacia auriculiformis, Alstonia scholaris, Chukrasia tabularis, Cassia fistula, Cassia siamea, Dalbergia sissoo, Heterophragma adenophyllum, and Putranjiva roxburghii) at control (PAU campus) and polluted sites (roadside) during summer and winter seasons. The total chlorophyll content, ascorbic acid, leaf extract pH, leaf relative water content, total soluble sugar, phenols, and carotenoids ranged from 0.59 to 4.16 mg g^-1, 1.03 to 3.75 mg g^-1, 3.16 to 7.04, 46.01 to 71.65%, 10.78 to 23.83 mg g^-1, 0.51 to 1.35 mg ^-1, and 0.19 to 1.96 mg g^-1, respectively. The Air Pollution Tolerance Index of the selected trees ranged between7.65 and 11.19 and followed an order of Cassia fistula > Acacia auriculiformis > Dalbergia sissoo > Alstonia scholaris > Putranjiva roxburghii > Heterophragma adenophyllum > Cassia siamea > Chukrasia tabularis. The evaluation of Anticipated Performance Index (API) categorized the trees into poor (Dalbergia sissoo and Cassia siamea), moderate (Cassia fistula), and good (Acacia auriculiformis, Alstonia scholaris, Chukrasia tabularis, Heterophragma adenophyllum, and Putranjiva roxburghii) categories.

Estimation of air pollution tolerance and anticipated performance index of roadside plants along the national highway in a tropical urban city

One of the most serious environmental issues is air pollution. Unlike other environmental concerns, this form of pollution is extremely challenging to regulate. The greenery of roadside trees plays a significant role in air purification and pollutant absorption, therefore helping to mitigate environmental pollution. Several plants can absorb and store toxins in their leaves from the atmosphere. Green plants have the potential to work as sinks and filters for air pollutants. Green belt development along national highways is a cost-effective and environmentally sustainable method of reducing air pollution. Sensitive and tolerant plants against air pollution can be identified by evaluating their air pollution tolerance index (APTI) and anticipated performance index (API) values. In this study, the susceptibility level of plant species to air pollution was assessed using APTI and API. The four parameters on which APTI depends are ascorbic acid content, total chlorophyll content, relative water content, and leaf extract pH. For the estimation of API, the plant's biological and socioeconomic factors like tree habit, canopy structure, type, size, texture, and hardness of the plant are also assessed. These parameters were determined and incorporated into a formula that represents the APTI and API of plants. Moreover, multilinear regression modeling was performed using a Statistical Package for the Social Sciences (SPSS, V25) and found that pH and ascorbic acid content in plant leaves have a significant role in the calculation of APTI and tolerance potential of plants. Therefore, APTI was assessed with seventeen plant species that are abundant in the area along the national highway in Kanpur, Uttar Pradesh, from Jan to Mar 2020. The APTI showed that Saraca asoca was the most resistant to air pollution, whereas Vachellia nilotica was the most sensitive. In addition, plants with higher APTI can also be used to reduce air pollution, while plants with lower APTI can be utilized to monitor air pollution. Based on the calculated API score, it is found that Ficus elastica (% score > 90) is the best option for green belt development. Urban local body (ULB) can also adopt Ficus religiosa, Saraca asoca, and Aucuba japonica (having % a grade score of 80-90) for mitigation of air pollution. The study indicates that plantations of tolerant species are useful for biomonitoring and developing green belts on and along national highways.

Politics of the natural vegetation to balance the hazardous level of elements in marble polluted ecosystem through phytoremediation and physiological responses

The current paper evaluates the phytoremediation ability and physiological responses of selected resistant plant species to the hazardous levels of elements in the marble waste polluted ecosystem. Preliminary results demonstrate that all the indicator/resistant plant species i.e., Ailanthus altissima, Arundo donax, Cynodon dactylon, Erigeron canadensis, Cannabis sativa, Ficus carica, Lathyrus aphaca, Morus alba, Populus alba, Robinia pseudoacacia and Vitex negundo were the best Phyto-extractors and Phyto-stabilizers for most of the heavy metals in general and Mg, Ca, Fe, Cu and Na in particular (at p < 0.05). Structural Equation Modeling confirmed that marble waste pollution has a direct and significant (R² =0.80) impact on proline synthesis and hence a role in combating the pollution. Chlorophyll content decreased by 4% in studied plant species when the concentration of pollutants increased. It is concluded that the studied bio-indicators - the abundant plant species of the Marble Waste Polluted Systems (MWPS) have a significant role in its remediation. Increasing proline accumulation and decreasing chlorophyll contents with an increase in pollution in the studied plants show resilience of the ecosystem in response to the external lithospheric toxicities. It is recommended that the recognized plant species could be planted abundantly to remediate the MWPS around the marble processing and other such industries and their catchments.

Variation of tree biochemical and physiological characters under different air pollution stresses

The present work was undertaken in order to detect some pollution responsive variables such as ascorbic acid, pH, total chlorophyll, relative water content, total soluble sugar, amino acid and protein of four selected plant species, namely Ficus religiosa, Anthocephalus cadamba, Lagerstroemia speciosa and Cassia siamea, at nine different sites of Durgapur, West Bengal, India. The spatial variability analyses of Air Pollution Tolerance Index (APTI) along with Anticipated Performance Index (API) were also examined on each plant species. In this study, the highest APTI was recorded in L. speciosa (183.54 mg/g) during 2015 at site S5 (CCR), whereas the lowest APTI was reported in C. siamea (11.25 mg/g) during 2014 at site S3 (DGC). The API gradation revealed that L. speciosa was categorised as a best performer followed by A. cadamba and F. religiosa; in contrast, C. siamea showed poor performance among all the sites. One-way ANOVA (at p < 0.05, with Dunnett's post hoc) was conducted for spatial variability analysis both on biochemical parameters and air pollutants (SO₂, NOx and SPM) with respect to control site, while two-way ANOVA also operated for the detection of spatio-temporal interaction on concerned biochemical parameters of each tree species. A significant positive correlation was observed both in ascorbic acid and APTI of A. cadamba and L. speciosa with the air pollutants. So it would be said that, for varied environmental situations, different biochemical responses have been reflected by vegetation of the same species. Thus, the present study has tremendous potentiality to screening out tree species on the basis of APTI with pooling their API assessment category and spatial variability detection of biochemical parameters. Biochemical plasticity and adaptability were better revealed on L. speciosa, F. religiosa and A. cadamba which will be suitable for green belt development in air pollution-affected areas.

Assessment of anticipated performance index of some deciduous plant species under dust air pollution

Green vegetation improvement is an economical strategy to mitigate dust air pollution. The anticipated performance index (API) is considered a main criterion to select the suitable plants of urban forests. API is calculated by taking air pollution tolerance index (APTI) and socio-economic and biological aspects into account. In the present work, API of four current deciduous tree species in urban areas of Iran was evaluated. The seedlings were soil-dusted by a dust simulator in plastic chambers at levels of 0, 300, 750, and 1500 μg/m³ at intervals of 1 week for 70 days. At 750 and 1500 μg/m³ dust concentrations (DCs), greatest dust collection capacity was observed with Morus alba and the lowest one with Melia azedarach. Increasing DC declined APTI of all species. At 750 μg/m³ DC, only Morus was tolerant, but at 1500 μg/m³ DC, this species and Melia were categorized as intermediate, and Celtis caucasica and Fraxinus rotundifolia as sensitive. Morus was assessed as a good performer under two higher DC. Celtis was recognized as a moderate under 750 μg/m³ DC and poor performer under 1500 μg/m³ DC. Thus, Celtis can be considered as a biomonitor for air quality or as sink for dust in high dusty areas because of its high capacity of dust deposition. At two higher DCs, Fraxinus and Melia showed very poor and poor performance; planting these species in high dust areas is not recommended. In contrast, Morus is the most suitable tree species for urban green spaces in dusty regions, due to its high dust collection capacity and high APTI and API values.

Assessing the response of five tree species to air pollution in Riyadh City, Saudi Arabia, for potential green belt application

Tree species (including Eucalyptus camaldulensis, Ziziphus spina-christi, Albizia lebbeck, Prosopis juliflora, Pithecellobium dulce, and Ficus altissima) were investigated to elucidate their appropriates for green belt application. Leaf samples were collected from four different locations in Riyadh: (1) residential; (2) dense traffic; (3) industrial; and (4) reference sites located approximately 20 km away from the city of Riyadh. Leaves collected from the industrial site showed the highest leaf area reduction. The smallest reduction of leaf areas was observed for F. altissima (11.6%), while the highest reduction was observed for P. juliflora (34.8%). Variations in the air pollution tolerance index (APTI) coupled with the anticipated performance index (API) for each species were examined. The APTI value of Z. spina-christi was highest (58.5) at the industrial site while the lowest APTI value was for P. juliflora (14) at the reference site. Correlation coefficient and linear regression analyses determined that the correlation between the ascorbic acid content and APTI is positive and significantly strong. Our findings indicate that urban green planning in Riyadh should include growing F. altissima on roadsides as well as in heavy industrial locations followed by Z. spina-christi and A. lebbeck according to their API and APTI performances.

Physiological and anatomical responses of a common beach grass to crude oil pollution

Oil pollution is one potential consequence of industry development, and oil contamination occurs in countries around the world. However, few studies have examined the detrimental effects of oil on plant anatomy. Therefore, the objectives of this study were (1) to determine the impacts of crude oil on the physiological and anatomical parameters of Ischaemum muticum L. (Poaceae) and (2) to examine its potential as a bioindicator of oil pollution. Experimental plants were treated with one of four concentrations of crude oil (1%, 2%, 3%, and 4% volume/weight) and compared to control plants (no oil applied). Four physiological and 23 anatomical parameters were measured 7, 15, 30, 45, and 60 days after treatment. Crude oil negatively affected both physiological traits (leaf width and chlorophyll content) and anatomical traits (midrib vascular bundle height, leaf cutin thickness, leaf vascular bundle width and height, abaxial and adaxial margin cutin thickness, adaxial stomata density, adaxial short cell width, and abaxial long cell width). In general, the affected traits were modified by even the lowest oil concentration tested (1%). We discuss the potential of I. muticum as a bioindicator of oil pollution, given its prevalence in coastal areas of the paleotropics and its sensitivity to oil contamination.

Bioindicator responses and performance of plant species along a vehicular pollution gradient in western Himalaya

Loss of green cover, and increasing pollution is a prime global concern. The problem calls for screening of pollution-tolerant tree species that can be integrated into plantation drives. Recognizing this, the study analyzed bio-indicator responses and performance of commonly occurring plant species along a pollution gradient in western Himalaya. Based on distance from the road, three sites viz., highly polluted (HP), moderately polluted (MP), and least polluted (LP), were identified. From these sites, leaves of commonly occurring 26 tree species were collected and analyzed for dust accumulation, total chlorophyll, relative water content (RWC), ascorbic acid, and pH using standard protocols. Later, assessment of Air Pollution Tolerance Index (APTI) and Anticipated Performance Indices (API) was carried out. The results revealed variations in biochemical characteristics. The pH, RWC, and total chlorophyll increased with decreasing pollution while ascorbic acid increased with increasing pollution. Dust capturing potential of Ficus carica (1.191 mg/m²) and Toona ciliata (0.820 mg/m²) was relatively higher. Based on the results of APTI, Grevillea robusta was classified as tolerant. It scored significantly higher values (21.06, 21.19, and 19.61 in LP, MP, and HP sites, respectively). Quercus floribunda, G. robusta (68.75% each), Juglans regia (68.7%), and T. ciliata (62.50%) were good performers in HP sites. Acer caesium, Betula utilis, and Morus alba that had low API scores (43.75%) were predicted as poor performers. Thus, G. robusta, Q. floribunda, J. regia, T. ciliata, and F. carica were evaluated as best performers. They could be integrated into plantations drives for environmental management.

Evaluation of air pollution tolerance index and anticipated performance index of plants and their application in development of green space along the urban areas

Air pollution due to vehicular emissions has become one of the most serious problems in the whole world and has resulted in huge threat to both the environment and the health of living organisms (plants, humans, animals, microorganisms). Plants growing along the roadsides get affected at the maximum as they are the primary recipients to different air pollutants and show varied levels of tolerance and sensitivity. Taking this into account, the present work was based on assessment of seasonal variation in air pollution tolerance index (APTI) and anticipated performance index (API) of four roadside plants, namely, Alstonia scholaris, Nerium oleander, Tabernaemontana coronaria, and Thevetia peruviana belonging to family Apocynaceae. APTI was calculated by the determination of four important biochemical parameters, viz., pH, relative water content (RWC), total chlorophyll (TChl), and ascorbic acid (AsA) content of leaves. The leaf samples were collected from plants growing at seven different sites of Amritsar (Punjab), India, for pre-monsoon and post-monsoon seasons. Highest APTI (82.14) was reported in N. oleander during the pre-monsoon season while the lowest was recorded in T. coronaria (18.59) in the post-monsoon season. On the basis of API score, A. scholaris was anticipated to be an excellent performer during the pre-monsoon and post-monsoon seasons followed by N. oleander, T. coronaria, and T. peruviana. Linear regression analysis and Pearson's correlation coefficient depicted significant positive correlation between APTI and ascorbic acid content during the pre-monsoon and post-monsoon seasons.

A new mathematical evaluation of smoking problem based of algebraic statistical method

Smoking problem is considered as one of the hot topics for many years. In spite of overpowering facts about the dangers, smoking is still a bad habit widely spread and socially accepted. Many people start smoking during their gymnasium period. The discovery of the dangers of smoking gave a warning sign of danger for individuals. There are different statistical methods used to analyze the dangers of smoking. In this study, we apply an algebraic statistical method to analyze and classify real data using Markov basis for the independent model on the contingency table. Results show that the Markov basis based classification is able to distinguish different date elements. Moreover, we check our proposed method via information theory by utilizing the Shannon formula to illustrate which one of these alternative tables is the best in term of independent.

The effects of applying sewage sludge into Jiangxi red soil on the growth of vegetables and the migration and enrichment of Cu and Zn

Jiangxi red soil was used as the tested soil and water spinach (Ipomoea aquatic) and Chinese chive (Allium tuberosum) were used as the tested vegetables in this study to investigate the effects of different amounts of sewage-sludge application on the growth of vegetables and the migration and enrichment patterns of Cu and Zn in vegetables using the potted method. The results indicated that the application of sewage sludge could improve the properties of red soil and promote vegetable growth. The dry weight of water spinach and Chinese chive reached the maximal levels when treated with the amount of sewage sludge at 4% and 10%, which was 4.38 ± 0.82 g and 1.56 ± 0.31 g, respectively. The dry weights after the application of sewage sludge were all larger than control treatment (CK) without sludge application. With increases in the applied amount of sewage sludge, the concentrations of Cu and Zu in red soil continued to increase, and the peak value was not reached. After the two vegetables were planted, the concentrations of Cu and Zn in red soil decreased by different degrees. The degrees of decrease of Zn were generally higher than those of Cu. The enrichment coefficient of water spinach on Cu showed a trend of increase followed by a decrease and reached the peak value of 1.04 ± 0.38 when the applied amount was 4%. The enrichment coefficient of Chinese chive on Cu overall showed a decreasing trend and did not reach the peak value under the treatment levels used in this experiment. The enrichment pattern of Chinese chive on Zn was not obvious, and the differences among all treatment levels were not significant (p < 0.05). However, the enrichment coefficient after the application of sewage sludge was significantly lower than that without the application of sludge.

Microbial contamination of vegetable crop and soil profile in arid regions under controlled application of domestic wastewater

Increasing lack of potable water in arid countries leads to the use of treated wastewater for crop production. However, the use of inappropriate irrigation practices could result in a serious contamination risk to plants, soils, and groundwater with sewage water. This research was initiated in view to the increasing danger of vegetable crops and groundwater contamination with pathogenic bacteria due to wastewater land application. The research was designed to study: (1) the effect of treated wastewater irrigation on the yield and microbial contamination of the radish plant under field conditions; (2) contamination of the agricultural soil profile with fecal coliform bacteria. Effluent from a domestic wastewater treatment plant (100%) in Jeddah city, Saudi Arabia, was diluted to 80% and 40% with the groundwater of the experimental site constituting three different water qualities plus groundwater as control. Radish plant was grown in two consecutive seasons under two drip irrigation systems and four irrigation water qualities. Upon harvesting, plant weight per ha, total bacterial, fecal coliform, fecal streptococci were detected per 100 g of dry matter and compared with the control. The soil profile was also sampled at an equal distance of 3 cm from soil surface for fecal coliform detection. The results indicated that the yield increased significantly under the subsurface irrigation system and the control water quality compared to surface irrigation system and other water qualities. There was a considerable drop in the count of all bacteria species under the subsurface irrigation system compared to surface irrigation. The bacterial count/g of the plant shoot system increased as the percentage of wastewater in the irrigation water increased. Most of the fecal coliform bacteria were deposited in the first few centimeters below the column inlet and the profile exponentially decreased with increasing depth.

Changes in the chemical composition of an acidic soil treated with marble quarry and marble cutting wastes

Soil acidity greatly affects the availability of plant nutrients. The level of soil acidity can be adjusted by treating the soil with certain additives. The objective of this study was to determine the effect of marble quarry waste (MQW) and marble cutting waste (MCW) on the chemical composition and the acidity of a soil. Marble wastes at different rates were applied to an acid soil. Their effectiveness in neutralizing the soil pH was compared with that of agricultural lime. The changes in the chemical composition of the soil were also evaluated with column test at the end of a 75-day incubation period. The results indicated that the MQW and MCW applications significantly increased the soil pH (from 4.71 up to 6.54), the CaCO3 content (from 0.33% up to 0.75%), and the exchangeable Ca (from 14.79 cmol kg(-1) up to 21.18 cmol kg(-1)) and Na (from 0.57 cmol kg(-1) up to 1.07 cmol kg(-1)) contents, but decreased the exchangeable K (from 0.46 cmol kg(-1) down to 0.28 cmol kg(-1)), the plant-available P (from 25.56 mg L(-1) down to 16.62 mg L(-1)), and the extractable Fe (from 259.43 mg L(-1) down to 55.4 mg L(-1)), Cu (from 1.97 mg L(-1) down to 1.42 mg L(-1)), Mn (from 17.89 mg L(-1) down to 4.61 mg L(-1)) and Zn (from 7.88 mg L(-1) down to 1.56 mg L(-1)) contents. In addition, the Cd (from 0.060 mg L(-1) down to 0.046 mg L(-1)), Ni (from 0.337 mg L(-1) down to 0.092 mg L(-1)) and Pb (from 28.00 mg L(-1) down to 20.08 mg L(-1)) concentrations decreased upon the treatment of the soil with marble wastes.