<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">OJAP</journal-id><journal-title-group><journal-title>Open Journal of Air Pollution</journal-title></journal-title-group><issn pub-type="epub">2169-2653</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ojap.2018.71001</article-id><article-id pub-id-type="publisher-id">OJAP-81589</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth&amp;Environmental Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  An Evaluation of Air Pollution Tolerance Index and Anticipated Performance Index of Some Tree Species Considered for Green Belt Development: A Case Study of Nandesari Industrial Area, Vadodara, Gujarat, India
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Dhruti</surname><given-names>Patel</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>J.</surname><given-names>I. Nirmal Kumar</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Department of Environmental Science &amp;amp; Technology (DEST), Institute of Science and Technology for Advanced Studies &amp;amp; Research (ISTAR), Vallabh Vidyanagar, India</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>dhrcho@gmail.com(DP)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>04</day><month>01</month><year>2018</year></pub-date><volume>07</volume><issue>01</issue><fpage>1</fpage><lpage>13</lpage><history><date date-type="received"><day>13,</day>	<month>June</month>	<year>2017</year></date><date date-type="rev-recd"><day>2,</day>	<month>January</month>	<year>2018</year>	</date><date date-type="accepted"><day>5,</day>	<month>January</month>	<year>2018</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  It is well renowned that trees have capacity to reduce the air pollution. It is mandatory to expand tree plantation in industrial area to minimize the threat of pollutants. For green belt development, it is necessary to use plants that are tolerant to air pollution. The present study includes Air pollution tolerance index (APTI) of selected plant species with the help of biochemical analysis. On the basis of APTI and some other socioeconomic and biological parameters of plants, Anticipated Performance Index (API) was calculated. Out of twelve species, 
  <em>Ficus benghalensis</em> showed to be the most efficient among others. As per classification of API, 
  <em>Ficus religiosa</em> tree species is classified into the moderate category. Based on the APTI and API, appropriate plant species for green belt development in industrial area were identified and recommended for mitigating the pollution.
 
</p></abstract><kwd-group><kwd>Air Pollution</kwd><kwd> APTI</kwd><kwd> API</kwd><kwd> Nandesari</kwd><kwd> Green Belt</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The status of air quality in every part of the world always parallels the changes in development of surrounding area [<xref ref-type="bibr" rid="scirp.81589-ref1">1</xref>] . Industrial area exhibits major sources of Particulate Matter, SOx and NOx. Depending upon the type of raw material used emission of one or more of these pollutants is obvious. The problem of declining air quality is mainly the result of anthropogenic emissions from traffic, industry and domestic heating, especially affecting the world’s urban residents [<xref ref-type="bibr" rid="scirp.81589-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.81589-ref3">3</xref>] . Air pollution can have profound effects on the health of the entire planet. Increasing human population with decreasing green environment has produced ambient air polluted. Mainly increasing number of industries, vehicular exhaust, and fossil fuels to nuclear energy produces air heavily polluted day by day [<xref ref-type="bibr" rid="scirp.81589-ref4">4</xref>] . The air pollution causes health problems in the workers and residents in places near the industrial area, therefore it is essential to study the air quality in the surroundings of the industries [<xref ref-type="bibr" rid="scirp.81589-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.81589-ref6">6</xref>] . To terminate the impact of air pollutants, environmentalists and decision makers have long been emphasizing the need for a “perennial green envelop” in and around industrial areas as well as along roadsides [<xref ref-type="bibr" rid="scirp.81589-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.81589-ref8">8</xref>] . The plant has capacity to provide one of the natural ways of cleaning the atmosphere by absorption, reflection, diffusion of gaseous through their leaves. Heumann (2002); Psaras and Christodoulakis (1987) have shown the interactions between plant and different types of pollutants with the influence of environmental pollution on physiological and ultrastructural aspects [<xref ref-type="bibr" rid="scirp.81589-ref9">9</xref>] [<xref ref-type="bibr" rid="scirp.81589-ref10">10</xref>] .</p><p>Based on responses of plants towards a particular stress as well as gaseous stress, they can be categorized into “sensitive” and “tolerant”. Sensitive species are early indicators of pollution, and the tolerant species help in reducing the overall pollution load [<xref ref-type="bibr" rid="scirp.81589-ref11">11</xref>] . Moreover, the present investigation is based on identification of stress tolerant plant species (noise and air pollution) from the study area to develop green belt. By the help of the Natural processes, air pollution level can be reduced by precipitation, Chemical reaction and sedimentation [<xref ref-type="bibr" rid="scirp.81589-ref12">12</xref>] .</p><p>In present study emphasis is given on evaluation of tolerance level in plant species against air pollution and calculation of air pollution tolerance index (APTI) [<xref ref-type="bibr" rid="scirp.81589-ref11">11</xref>] . Air Pollution Tolerance Index (APTI), an index developed by Singh and Rao (1983), is used for the evaluation of the tolerance level of plant species from leaf [<xref ref-type="bibr" rid="scirp.81589-ref13">13</xref>] . The parameters used in defining sensitivity or resistance of plants towards different air pollutant concentration includes, Total Chlorophyll, Ascorbic acid, leaf pH, relative water content. Plant sensitivity and tolerance to air pollutants vary with these above parameters. Chlorophyll content decreases due to production of reactive oxygen species (ROS) in the chloroplast underwater stress condition. (ROS is very small reactive molecules that can effect to cell structure during the stress condition). It also imparts leaf injury and causes change in stomatal movements, Changes in Chlorophyll content causes change in the rate of photo-synthesis. In the plant, higher ascorbic acid concentration of leaves might be an effective strategy to protect thylakoid membranes from oxidative damage under such water stress [<xref ref-type="bibr" rid="scirp.81589-ref14">14</xref>] . Alkaline particles such as limestone and dust particle may damage plant surfaces [<xref ref-type="bibr" rid="scirp.81589-ref15">15</xref>] , and high pH improves tolerance against air pollution [<xref ref-type="bibr" rid="scirp.81589-ref1">1</xref>] . Based on APTI (<xref ref-type="table" rid="table1">Table 1</xref>) and some relevant biological and socio-economic characters (<xref ref-type="table" rid="table2">Table 2</xref>), the Anticipated Performance Index (API) (<xref ref-type="table" rid="table3">Table 3</xref>), of various plant species was determined. By measuring these parameters we can predict the effectiveness of plant as possibly being suitable in terms of pollution abatement.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Air pollution tolerance index of tree species studied in Nandesari industrial area, Gujarat</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Sl. no.</th><th align="center" valign="middle" >Name of species</th><th align="center" valign="middle" >A</th><th align="center" valign="middle" >P</th><th align="center" valign="middle" >T</th><th align="center" valign="middle" >R</th><th align="center" valign="middle" >APTI</th></tr></thead><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >Michelia champaca L.</td><td align="center" valign="middle" >7.31</td><td align="center" valign="middle" >5.68</td><td align="center" valign="middle" >6.2</td><td align="center" valign="middle" >56</td><td align="center" valign="middle" >13.26</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >Polyalthia longifolia Sonn.</td><td align="center" valign="middle" >6.42</td><td align="center" valign="middle" >6.89</td><td align="center" valign="middle" >5.78</td><td align="center" valign="middle" >60.25</td><td align="center" valign="middle" >15.68</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >Azadirachta indica A. Juss.</td><td align="center" valign="middle" >6.79</td><td align="center" valign="middle" >6.2</td><td align="center" valign="middle" >3.87</td><td align="center" valign="middle" >54.21</td><td align="center" valign="middle" >12.98</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >Ficus religiosa</td><td align="center" valign="middle" >6.98</td><td align="center" valign="middle" >6.98</td><td align="center" valign="middle" >9.87</td><td align="center" valign="middle" >60.54</td><td align="center" valign="middle" >14.42</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >Ficus benghalensis</td><td align="center" valign="middle" >6.65</td><td align="center" valign="middle" >5.93</td><td align="center" valign="middle" >6.54</td><td align="center" valign="middle" >55.65</td><td align="center" valign="middle" >18.65</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >Cassia fistula L.</td><td align="center" valign="middle" >6.07</td><td align="center" valign="middle" >5.43</td><td align="center" valign="middle" >4.44</td><td align="center" valign="middle" >54.24</td><td align="center" valign="middle" >13.65</td></tr><tr><td align="center" valign="middle" >7</td><td align="center" valign="middle" >Spathodea campanulata P. Beauv.</td><td align="center" valign="middle" >5.54</td><td align="center" valign="middle" >6.65</td><td align="center" valign="middle" >4.65</td><td align="center" valign="middle" >55.24</td><td align="center" valign="middle" >11.46</td></tr><tr><td align="center" valign="middle" >8</td><td align="center" valign="middle" >Adina cordifolia Hook. f.</td><td align="center" valign="middle" >5.05</td><td align="center" valign="middle" >6.87</td><td align="center" valign="middle" >3.98</td><td align="center" valign="middle" >51.35</td><td align="center" valign="middle" >12.05</td></tr><tr><td align="center" valign="middle" >9</td><td align="center" valign="middle" >Cassia siamea Lamk.</td><td align="center" valign="middle" >6.19</td><td align="center" valign="middle" >5.68</td><td align="center" valign="middle" >4.55</td><td align="center" valign="middle" >52.18</td><td align="center" valign="middle" >12.05</td></tr><tr><td align="center" valign="middle" >10</td><td align="center" valign="middle" >Nerium odorum Sonnad.</td><td align="center" valign="middle" >4.08</td><td align="center" valign="middle" >6.54</td><td align="center" valign="middle" >3.52</td><td align="center" valign="middle" >53.54</td><td align="center" valign="middle" >8.65</td></tr><tr><td align="center" valign="middle" >11</td><td align="center" valign="middle" >Alstonia scholaris (L.) R.Br.</td><td align="center" valign="middle" >5.26</td><td align="center" valign="middle" >6.05</td><td align="center" valign="middle" >3.81</td><td align="center" valign="middle" >50.42</td><td align="center" valign="middle" >9.01</td></tr><tr><td align="center" valign="middle" >12</td><td align="center" valign="middle" >Cascabela thevetia L.</td><td align="center" valign="middle" >5.9</td><td align="center" valign="middle" >5.98</td><td align="center" valign="middle" >4.73</td><td align="center" valign="middle" >50.15</td><td align="center" valign="middle" >9.54</td></tr></tbody></table></table-wrap><p>A = Ascorbic Acid , P = pH, T = Total Chlorophyll, R = Relative Water Content (Average mean value).</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Gradation of plant species based on air pollution tolerance index (APTI) as well as biological parameters and socio-economic importance</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Grading characters</th><th align="center" valign="middle" ></th><th align="center" valign="middle" >Pattern of assessment</th><th align="center" valign="middle" >Grade allotted</th></tr></thead><tr><td align="center" valign="middle" >1) Tolerance</td><td align="center" valign="middle" >APTI</td><td align="center" valign="middle" >9.0 - 12.0</td><td align="center" valign="middle" >+</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >12.1 - 15.0</td><td align="center" valign="middle" >++</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >15.1 - 18.0</td><td align="center" valign="middle" >+++</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >18.1 - 21.0</td><td align="center" valign="middle" >++++</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >21.1 - 24.0</td><td align="center" valign="middle" >++++</td></tr><tr><td align="center" valign="middle" >2) Biological and socio-economic</td><td align="center" valign="middle" >Plant habit</td><td align="center" valign="middle" >Small</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Medium</td><td align="center" valign="middle" >+</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Large</td><td align="center" valign="middle" >++</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Canopy structure</td><td align="center" valign="middle" >Sparse/irregular/globular</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Spreading crown/open/semi-dense</td><td align="center" valign="middle" >+</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Spreading dense</td><td align="center" valign="middle" >++</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Type of plant</td><td align="center" valign="middle" >Deciduous</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Evergreen</td><td align="center" valign="middle" >+</td></tr><tr><td align="center" valign="middle" >3) Laminar structure</td><td align="center" valign="middle" >Size</td><td align="center" valign="middle" >Small</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Medium</td><td align="center" valign="middle" >+</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Large</td><td align="center" valign="middle" >++</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Texture</td><td align="center" valign="middle" >Smooth</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Coriaceous</td><td align="center" valign="middle" >+</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Hardiness</td><td align="center" valign="middle" >Delineate</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Hardy</td><td align="center" valign="middle" >+</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Economic value</td><td align="center" valign="middle" >Less than three uses</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Three or four uses</td><td align="center" valign="middle" >+</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Five or more uses</td><td align="center" valign="middle" >+ +</td></tr></tbody></table></table-wrap><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Anticipated performance index (API) of plant species</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Grade</th><th align="center" valign="middle" >Score (%)</th><th align="center" valign="middle" >Assessment category</th></tr></thead><tr><td align="center" valign="middle" >0</td><td align="center" valign="middle" >Up to 30</td><td align="center" valign="middle" >Not recommended</td></tr><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >31 - 40</td><td align="center" valign="middle" >Very poor</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >41 - 50</td><td align="center" valign="middle" >Poor</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >51 - 60</td><td align="center" valign="middle" >Moderate</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >61 - 70</td><td align="center" valign="middle" >Good</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >71 - 80</td><td align="center" valign="middle" >Very good</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >81 - 90</td><td align="center" valign="middle" >Excellent</td></tr><tr><td align="center" valign="middle" >7</td><td align="center" valign="middle" >91 - 100</td><td align="center" valign="middle" >Best</td></tr></tbody></table></table-wrap></sec><sec id="s2"><title>2. Materials and Methods</title><sec id="s2_1"><title>2.1. Study Area</title><p>The study was carried out in and around the Nandesari industrial area, which is situated in the Vadodara district. Nandesari has a large notified industrial area comprising of large amount of chemical factories. It homes Gujarat first GIDC (Gujarat Industrial Development Corporation) with concrete roads and storm water drains. Nandesari is a small town of Gujarat, located at 22.4103˚ north latitude and, 73.0913˚ east longitude. It has an average elevation of 34 meters. Climate is subtropical, with mild winters and warm summers. The city is situated between 18˚96' north latitude and 72˚81' east longitude. The weather is typical coastal sultry and humid. The city receives average rainfall in the range of 1500 mm to 2000 mm. The place experiences the onset of the monsoon in the month of June and experiences monsoon till the end of September. The average minimum temperature is recorded between 25˚C to 37˚C.</p></sec><sec id="s2_2"><title>2.2. Air Pollutants Sampling and Measurement</title><p>The study was carried out on twelve plant species growing along polluted and non-polluted sites during the year 2014-2015 (<xref ref-type="fig" rid="fig1">Figure 1</xref>). The road side was selected as a polluted area for case study, because numerous sources emit dust and smoke including vehicles. For ambient air quality monitoring three sites has been selected in and around the Nandesari industrial area. The control site was selected 3 km away from the Nandesari industrial area with good greenery and lesser nearby air pollutants. For collection of gaseous and particulate pollution, HVAS (2.5 High Volume air Sampler) was used for 24 Hours with flow rate of one liter per minute. PM<sub>2.5</sub> was sampled by PM2.5 HVAS and estimated by gravimetric analysis [<xref ref-type="bibr" rid="scirp.81589-ref16">16</xref>] . SO<sub>2</sub> was estimated by West-Geake method using sodium tetra-chloromercurate. In case of NO<sub>2</sub>, estimation was based on Jacob and Hoccheiser method using sodium Hydroxide as an absorbing medium. Rapid industrialization, expansion of the road network and infrastructure has resulted in severe air pollution problem and adverse effects on exposed residents.</p></sec><sec id="s2_3"><title>2.3. Biochemical Characteristics Analysis</title><p>In order to collect the plant leaf samples, a plant survey was made at the three selected sites, i.e., Site 1, Site 2, Site 3 and on that basis twelve common plants of same age were elected for the foliar biochemical studies. The matured leaves from each plant species were plucked from individual sites. These leaves were placed into the polythene bags and brought to the laboratory to preserve at 25 &#177; 0.5<sup>◦</sup>C until analysis. The plant samples were analyzed for different parameters within 24 hours of their harvesting. The leaf samples were analyzed for pH (P) of leaf extract [<xref ref-type="bibr" rid="scirp.81589-ref13">13</xref>] , Chlorophyll (T), Ascorbic acid (A) [<xref ref-type="bibr" rid="scirp.81589-ref17">17</xref>] [<xref ref-type="bibr" rid="scirp.81589-ref18">18</xref>] , and Relative Water Content (R) [<xref ref-type="bibr" rid="scirp.81589-ref19">19</xref>] . The APTI, an empirical value representing tolerance level of a Plant to air pollution, was used to interpret the impact of pollution on the plants [<xref ref-type="bibr" rid="scirp.81589-ref13">13</xref>] . The APTI was calculated by using the following formula for a given plant species.</p><p>APTI = A ( T + P ) + R 10</p><p>where, A = Ascorbic acid content (mg∙gm<sup>−1</sup>),</p><p>T = total chlorophyll (mg∙g<sup>−1</sup>),</p><p>P = pH of leaf extract, and</p><p>R = Relative water content of leaf (%).</p></sec><sec id="s2_4"><title>2.4. Evaluation of API</title><p>For determining which plant species are most suitable for the development of green belts, experiment needed to calculate the Anticipated Performance Index (API). All 12 plants selected for green belt development were evaluated in terms of their API. The API values were calculated by using various biological and socioeconomic, as well as some biochemical characteristics, such as APTI, plant habit, canopy structure and economic value (see <xref ref-type="table" rid="table1">Table 1</xref>). The method to calculate API value is in the table. Based on this pattern grading of 12 plant species, promising plants were recommended for green belt development.</p></sec></sec><sec id="s3"><title>3. Result and Discussion</title><p>As shown in <xref ref-type="table" rid="table1">Table 1</xref>, the highest chlorophyll content (mg∙g<sup>−1</sup> dry weight) was observed in Ficus religiosa (9.87) followed by Ficus benghalensis (6.54), Michelia champaca (5.45). Chlorophyll estimation is an important tool to evaluate the effects of air pollutants on plants as it plays an important role in plant metabolism so that any drop in chlorophyll content indicates direct impact on plant growth [<xref ref-type="bibr" rid="scirp.81589-ref20">20</xref>] . In the present investigation, the total chlorophyll content was found comparatively higher at control site and lower at polluted site. The higher the level of pollutants, the lower the chlorophyll content as certain pollutants diminishes the total chlorophyll content [<xref ref-type="bibr" rid="scirp.81589-ref21">21</xref>] . Many previous APTI studies have shown similar findings [<xref ref-type="bibr" rid="scirp.81589-ref22">22</xref>] . Agbaire et al., (2014) &amp; Prabhatkumar et al. (2013) also suggested that high levels industrial pollution reduces chlorophyll content of plant leaves around the industrial area [<xref ref-type="bibr" rid="scirp.81589-ref19">19</xref>] [<xref ref-type="bibr" rid="scirp.81589-ref23">23</xref>] .</p><sec id="s3_1"><title>3.1. Biochemical Analysis of Plants</title><p>Results from biochemical analysis of plants revealed that higher ascorbic acid contents were recorded in Michelia champaca (7.31), followed by Ficus religiosa (6.98), Azadirachta indica (6.79), Polyalthia longifolia (6.42), Cassia siamea (6.19), Cassia fistula (6.09)) [<xref ref-type="bibr" rid="scirp.81589-ref19">19</xref>] <xref ref-type="table" rid="table1">Table 1</xref> Ascorbic acid is concentrated mostly in chloroplasts that act as an antioxidant. It is mostly found in growing parts of the plant and enhances resistance to adverse environmental conditions, including air pollution [<xref ref-type="bibr" rid="scirp.81589-ref23">23</xref>] [<xref ref-type="bibr" rid="scirp.81589-ref24">24</xref>] . Earlier Air pollution and soil contamination results have showed a decrease in leaf ascorbic acid content in exposed Tibouchina pulchra samplings [<xref ref-type="bibr" rid="scirp.81589-ref25">25</xref>] .</p><p>In this study, Ficus religiosa has the maximum relative water content of 64% and followed by Polyalthia longifolia 60%, Spathodea campanulata 55%, Ficus benghalensis 55%. High water content within a plant body helps to maintain its physiological balance under stressful conditions, such as exposure to air pollution [<xref ref-type="bibr" rid="scirp.81589-ref26">26</xref>] (<xref ref-type="table" rid="table1">Table 1</xref>). The highest Relative Water Content (RWC) was found in response to the high availability of soil, water content and lower evaporation and transpiration rate. RWC of a leaf is the water present in response to its full turgidity. Under air polluted conditions, transpiration rates are frequently high, which leads to dryness. Therefore, the maintenance of RWC by the plant may determine its relative tolerance to pollution. Therefore, the high RWCs of plants in an industrial area sample may be responsible for the normal function of plant biological processes [<xref ref-type="bibr" rid="scirp.81589-ref27">27</xref>] .</p><p>The plant samples of the study exhibited an acidic pH. This might be due to presence of certain air pollution in the atmosphere. As leaf pH values increased in the polluted area compared with that of control. Similarly, rise in pH values in polluted site was observed [<xref ref-type="bibr" rid="scirp.81589-ref27">27</xref>] . The lowest pH concentration was found in case of Michelia champaca (5.68) followed by Cassia fistula (5.43), Cassia siamea (5.68), Cascabela thevetia (5.98). The plants were observed to have lower pH as washing of leaves lowers dust accumulation. On unalike, where dust accumulation is more, dust particle dissolution in cell sap is higher which results in rise in the pH [<xref ref-type="bibr" rid="scirp.81589-ref28">28</xref>] . It has been reported that the lower leaf pH is due to presence of acidic pollutants [<xref ref-type="bibr" rid="scirp.81589-ref29">29</xref>] . Swami et al., (2004) also observed similar results. The changes in leaf-extract pH might influence the stomata sensitivity in presence of air pollutants. Consequently, sensitive plants had higher leaf-extract pH than tolerant plants. Low leaf pH extract showed good correlation with sensitivity to air pollution and also reduces photosynthetic process in plants [<xref ref-type="bibr" rid="scirp.81589-ref30">30</xref>] .</p><p>The NO<sub>x</sub>, SO<sub>2</sub> and PM<sub>2.5</sub> content estimated in the ambient air of the study stations were within the NAAQS limits for residential area and industrial areas [<xref ref-type="bibr" rid="scirp.81589-ref31">31</xref>] . The main air pollutants in Nandesari industrial area are SO<sub>2</sub>, NO<sub>2</sub>, PM<sub>2.5</sub>. The concentrations of all of these pollutants were within the limits prescribed by CPCB. The average concentrations of three study area were SO<sub>2</sub>, NO<sub>2</sub>, PM<sub>2.5</sub> in the Nandesari industrial area are 52, 46, and 35 μg/m<sup>3</sup>, correspondingly. Higher concentrations in winter season may be credited to the atmospheric inversion [<xref ref-type="bibr" rid="scirp.81589-ref32">32</xref>] .</p><p>During inversion the normal atmospheric conditions i.e. cool air above and warm air below gets inverted. This condition leads to trap an intense layer of cold air under a layer of warm air. This dormant condition of atmosphere traps the pollutants close to the surface of the earth. Dust interception ability of plants depends on their surface geometry, phyllotaxy, leaf external characteristics (such as hairs, cuticle, etc.), and height and canopy of trees [<xref ref-type="bibr" rid="scirp.81589-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.81589-ref13">13</xref>] . The methodology of APTI and API can be used globally as they are based on parameters and universally significant biological and socio-economic characters. The planting of larger tree has been avoided because of their thick canopy structures and too close with each other, as this may lead to chances of obstructing the scattering of pollutants, thus provoking the pollution problem. Leaf petioles have more capacity to eliminate particulate than either twigs (stem) or leaf lamina [<xref ref-type="bibr" rid="scirp.81589-ref33">33</xref>] . Green belts offer one of the natural ways of cleaning the atmosphere by absorption of gaseous pollutants, particulates and noise through their leaves. Plants with bulky leaves can act as efficient pollutant trapping device.</p></sec><sec id="s3_2"><title>3.2. Air Pollution Tolerance Index</title><p>Presence of plants and trees in the industrial area can improve air quality through uptake of pollutant gases and particles. Air pollution tolerance index (APTI) was calculated for each plant. Species studied at different sites is mentioned in the above <xref ref-type="table" rid="table1">Table 1</xref>. The highest APTI value is found in the winter season. On the basis of calculated APTI with respect to season, the plants were found to follow this order; Ficus benghalensis showed the highest APTI value at all the sites followed by Polyalthia longifolia &gt; Ficus religiosa &gt; Cassia fistula &gt; Michelia champaca &gt; Azadirachta indica &gt; Adina cordifolia &gt; Cassia siamea &gt; Cascabela thevetia &gt; Alstonia scholaris &gt; Nerium odorum. Different plant species show substantial variation in their susceptibility towards air pollution. The plants with high and low APTI can serve as tolerant and sensitive species respectively. All other plants were found to be sensitive and accommodating as air pollution indicator [<xref ref-type="bibr" rid="scirp.81589-ref34">34</xref>] .</p><p>The linear regression plots of individual variables with APTI (<xref ref-type="fig" rid="fig2">Figure 2</xref>) show</p><p>that a significant correlation exists between APTI and ascorbic acid content (R<sup>2</sup> = 0.86387) while a positive correlation was found between APTI and total chlorophyll content (R<sup>2</sup> = 0.7853). On the contrary, a non-significant &amp; low correlation with leaf extract pH (R<sup>2</sup> = 0.2254) and relative water content (R<sup>2</sup> = 0.1952) were observed. It brings to knowledge that ascorbic acid and chlorophyll content of the leaf are responsible factors on which the APTI relies [<xref ref-type="bibr" rid="scirp.81589-ref35">35</xref>] .</p></sec><sec id="s3_3"><title>3.3. Estimation of API</title><p>Out of above mentioned Ficus benghalensis rank first among all plants studied and is a keystone species [<xref ref-type="bibr" rid="scirp.81589-ref24">24</xref>] . Keystone species can be expressed as species which play a key role in the sustenance of ecosystems; it has a consistent effect on its environment relative to its abundance. An ecosystem may experience a remarkable shift if a keystone species is removed, even if that species is a minute part of the ecosystem on account of productivity. Henceforth, it will be highly appropriate for planting this in industrial area to assist improvement in pollution. F. religiosa was judged to be in the “Very Good” category and was recommended for plantation (<xref ref-type="table" rid="table4">Table 4</xref>). These species have an intense canopy of evergreen foliage and is well known for its economic and aesthetic value [<xref ref-type="bibr" rid="scirp.81589-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.81589-ref36">36</xref>] . Apart from this investigation, 4 of the 13 tree species drops in the moderately suitable category, but can be recommended for plantation due to their aesthetic value (<xref ref-type="table" rid="table4">Table 4</xref>). The rest of the naturally growing species in the study area was not recommended for planting due to their particularly poor pollution tolerance indices or their very low API values (<xref ref-type="table" rid="table5">Table 5</xref>).</p><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Anticipated performance index (API) of different tree species in Nandesari industrial area</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Plant species</th><th align="center" valign="middle"  colspan="2"  >Grade</th><th align="center" valign="middle" >API value</th><th align="center" valign="middle" >Assessment</th></tr></thead><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Total Plus</td><td align="center" valign="middle" >Percentage</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Michelia champaca L.</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >52.94</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >Moderate</td></tr><tr><td align="center" valign="middle" >Polyalthia longifolia Sonn.</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >58.82</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >Moderate</td></tr><tr><td align="center" valign="middle" >Azadirachta indica A. Juss.</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >47.06</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >Poor</td></tr><tr><td align="center" valign="middle" >Ficus religiosa L.</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >70.59</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >Very good</td></tr><tr><td align="center" valign="middle" >Ficus Bengalensis L.</td><td align="center" valign="middle" >14</td><td align="center" valign="middle" >82.35</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >Excellent</td></tr><tr><td align="center" valign="middle" >Cassia fistula L.</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >41.18</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >Poor</td></tr><tr><td align="center" valign="middle" >Spathodea campanulata P. Beauv.</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >23.53</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >Not Recommended</td></tr><tr><td align="center" valign="middle" >Adina cordifolia Hook. f.</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >58.82</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >Moderate</td></tr><tr><td align="center" valign="middle" >Cassia siamea Lamk.</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >52.94</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >Moderate</td></tr><tr><td align="center" valign="middle" >Nerium odorum Sonnad.</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >29.41</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >Not Recommended</td></tr><tr><td align="center" valign="middle" >Alstonia scholaris (L.) R.Br.</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >35.29</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >Very Poor</td></tr><tr><td align="center" valign="middle" >Cascabela thevetia L.</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >41.17</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >Poor</td></tr></tbody></table></table-wrap><table-wrap id="table5" ><label><xref ref-type="table" rid="table5">Table 5</xref></label><caption><title> Assessment of plant species based on their APTI values and some biological and socio-economic characters</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >S. No.</th><th align="center" valign="middle" >Name of Plant</th><th align="center" valign="middle" >APTI</th><th align="center" valign="middle" >Tree Habit</th><th align="center" valign="middle" >Canopy Structure</th><th align="center" valign="middle" >Type of Tree</th><th align="center" valign="middle"  colspan="2"  >Laminar</th><th align="center" valign="middle" >Economic Importance</th><th align="center" valign="middle" >Hardiness</th><th align="center" valign="middle"  colspan="2"  >Grade Allotted</th><th align="center" valign="middle" >API Grade</th></tr></thead><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Size</td><td align="center" valign="middle" >Texture</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Total Plus (+)</td><td align="center" valign="middle" >% scoring</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >Michelia champace L.</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+ +</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >52.94</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >Polyalthia longifolia Sonn.</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+ +</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >58.82</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >Azadirachta indica A. Juss.</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >+ +</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >+ +</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >47.06</td><td align="center" valign="middle" >2</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >Ficus religiosa</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >+ +</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+ +</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >70.59</td><td align="center" valign="middle" >5</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >Ficus benghalensis</td><td align="center" valign="middle" >++++</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >+ +</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+ +</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >14</td><td align="center" valign="middle" >82.35</td><td align="center" valign="middle" >6</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >Cassia fistula L.</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >41.18</td><td align="center" valign="middle" >2</td></tr><tr><td align="center" valign="middle" >7</td><td align="center" valign="middle" >Spathodea campanulata P. Beauv.</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >23.53</td><td align="center" valign="middle" >0</td></tr><tr><td align="center" valign="middle" >8</td><td align="center" valign="middle" >Adina cordifolia Hook. f.</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >58.82</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >9</td><td align="center" valign="middle" >Cassia siamea Lamk.</td><td align="center" valign="middle" >++</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >52.94</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >10</td><td align="center" valign="middle" >Nerium odorum Sonnad.</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >29.41</td><td align="center" valign="middle" >0</td></tr><tr><td align="center" valign="middle" >11.</td><td align="center" valign="middle" >Alstonia scholaris (L.) R.Br.</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >35.29</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >12.</td><td align="center" valign="middle" >Cascabela thevetia L.</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >41.17</td><td align="center" valign="middle" >2</td></tr></tbody></table></table-wrap></sec></sec><sec id="s4"><title>4. Conclusion</title><p>For the green belt development in the industrial area, our study reveals that evaluation of anticipated performance of plants might be very useful in the selection of appropriate tree species. Some plants have been classified according to their degree of sensitivity and tolerance towards various air pollutants. The present study indicated that Ficus benghalensis L. species is most suitable sink for air pollution, which acts as key stone species. These plants can be utilized for green belt development in industrial area for reduction of the level of the air pollution. Further recommended species were of high aesthetic and socio-economic values. Plants with high APTI and API values are suggested for the development of green belts in the area. Therefore, these plant species may be integrated into a green belt design to assist in the long term air pollution planning of this industrial area.</p></sec><sec id="s5"><title>Cite this paper</title><p>Patel, D. and Nirmal Kumar, J.I. (2018) An Evaluation of Air Pollution Tolerance Index and Anticipated Performance Index of Some Tree Species Considered for Green Belt Development: A Case Study of Nandesari Industrial Area, Vadodara, Gujarat, India. Open Journal of Air Pollution, 7, 1-13. https://doi.org/10.4236/ojap.2018.71001</p></sec></body><back><ref-list><title>References</title><ref id="scirp.81589-ref1"><label>1</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Agarwal</surname><given-names> S.K. </given-names></name>,<etal>et al</etal>. 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