Heavy Metal Pollution from Vehicular Emissions and Its Phytomonitoring Along Two Roads I.E

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Heavy metal pollution from vehicular emissions and its phytomonitoring along two roads i.e. Pindi Bhattian to Kala Shah Kaku and Lahore to Gujranwala

NAILA HADAYAT

M. Sc. M. Phil. (UAF)

A thesis submitted in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY IN BOTANY

DEPARTMENT OF BOTANY, FACULTY OF SCIENCES UNIVERSITY OF AGRICULTURE, FAISALABAD, PAKISTAN 2018

Abstract The increase in heavy metal pollution along the roadside environment has become a major global concern recently. Therefore, current project was planned to monitor the level of heavy metals along the roads. For this study, five wild plant species (Calotropis procera, Cenchrus ciliaris, Cynodon dactylon, Nerium oleander and Parthenium hysterophorus) generally growing near the two roads [a segment of Motorway (M-2) from Pindi Bhattian to Kala Shah Kaku and a segment of Grand Trunk road (G.T. road) from Lahore to Gujranwala] in Punjab, Pakistan, were collected. The plant leaves and soil samples were collected from five sites along each road. The control samples of leaves and soil were collected at a distance of 50 meter away from roadside. The collected samples were analyzed during the four seasons of the year (2015-2016). Metals such as lead (Pb), cadmium (Cd), copper (Cu), nickel (Ni) and zinc (Zn) were examined in all the plant leaves and soil samples using Atomic Absorption Spectrophotometer (AAS). Some plant physiological parameters such as gas exchange characteristics [photosynthetic rate (A), stomatal conductance (gs), transpiration rate (E), sub- stomatal CO2 concentration (Ci) and water use efficiency (WUE)] were evaluated. Plant biochemical attributes such as the contents of photosynthetic pigments (chlorophyll a, chlorophyll b, total chlorophyll and carotenoids), total free amino acids, total soluble proteins and total antioxidant activity were also determined. Significantly higher contents of the studied metals were detected in soil and plants along the roadside as compared to their control samples and they indicated clear spatio-temporal variations. The highest contamination of metals in both plants and soil samples was noted during summer, whereas, minimum was observed during winter. The contents of metals were found in the order: Cd < Pb < Ni < Cu < Zn. The higher contents of all the metals were noted along G.T. road as compared to M-2. However, Kala Shah Kaku site along M-2 and Muridke site along G.T. road appeared as the more polluted sites. The correlation between metal contents in soil/plants and traffic density was significantly positive for almost all the sites during all the seasons. Significant positive correlation between metal contents in soil and metal content in plants was also observed. The high contents of metals were also obtained in petrol, diesel, soot and used motor oil samples. Physiological parameters such as A, E and gs were significantly lower while Ci and WUE were higher in all the plant species along the roadsides. The contents of photosynthetic pigments and total soluble proteins were significantly lower whereas total antioxidant activity and total free amino acids

were significantly higher in roadside plant species under metal stress. Among plant species, C. procera accumulated the maximum contents of Cd, Ni and Pb whereas, N. oleander had potential to accumulate high concentrations of Cu and Zn, hence, these plants can be suggested as the best choice as phytomonitors and/or phytoremediators of the metal pollution.

CHAPTER 1 INTRODUCTION Environmental pollution due to rapid urbanization and industrialization has become a major concern for living organisms almost all over the world. Anthropogenic activities emit a number of pollutants in huge quantity into the environment (Kho et al., 2007; Sarala and Vidya, 2012). Among these pollutants, metals particularly pose very deleterious effects on biota (Islam et al., 2015; Maanan et al., 2015; Pons-Branchu et al., 2015). Although metals are natural constituents of soil (Hutton and Symon, 1986), anthropogenic activities such as industrial discharges, metalliferous mining and smelting, agricultural materials (pesticides and fertilizers) and waste disposal activities, as well as roadside traffic also emit large quantities (Pam et al., 2013; Qin et al., 2014; Cao et al., 2014; Zhao et al., 2014; Ngole-Jeme, 2016). Traffic emissions being the largest source of metal pollution along the roadside has become a burning topic for study worldwide (UNEP/GPA, 2004; Modrzewska and Wyszkowski, 2014). It has been observed that several factors affect the emission of metals from vehicular sources. However, the quantity of metals emitted depends upon age of vehicle and quality of its maintenance, type of fuel (e.g. natural gas, diesel and gasoline), type of tire (e.g. friction or studded tires), quality of road infrastructure, road condition, implementations of assessment, maintenance and other emission control programs (Nirjar et al., 2002; EEA, 2011) as well as traffic density on road (Aslam et al., 2013; Rolli and Gadi, 2015). Therefore, a progressive degradation in roadside environment due to rapid urbanization, increase in number of motor vehicles, poor maintenance of vehicles, badly maintained roads and ineffective environmental regulations has become a global phenomenon (Joshi and Chauhan, 2008). The widespread use of automobiles for transportation, in the absence of enforcement of standards for pollution emission is resulting in release of huge amounts of metals besides other pollutants (Ibrahim, 2009; Irvine et al., 2009; Morton-Bermea et al., 2009) like oxides of nitrogen (NOX), carbon (CO, CO2) and sulphur (SOX) as well as hydrocarbons (Laschober et al., 2004). The unlimited population growth in Pakistan is accompanying rapid increase in number of vehicles and unchecked vehicular emissions. So the roadside environment in the entire country especially in the urban areas is plagued with metal pollution (Farrukh et al., 2005). As a consequence, Pakistan is included in the most polluted countries of the world NFEH report (2005).

Metals being non-biodegradable persist in the environment for long period of time (Babin-Fenske and Anand, 2011) and can pose many health hazards to both plants and animals (Wuana and Okieimen, 2011; Mathur and Kumar, 2013; Waoo et al., 2014; Mtunzi et al., 2015). Among metals, cadmium (Cd), nickel (Ni), copper (Cu), lead (Pb) and zinc (Zn) emitted by vehicular sources have been extensively examined along roadside environment. These metals have been found in petroleum products, tanks of fuel, engines and several other components of vehicles for example tires, catalytic converters, brake pads in addition to surface materials of roads (Zehetner, 2009; Popoola et al., 2012). Vehicular sector releases these metals during different operations such as from wearing and tearing of tires, mechanical abrasion of brake linings (Zhang et al., 2009; Ugwu et al., 2011; Raj and Ram, 2013), catalytic convertors (Zereini et al., 2007), abrasion of pavement, burning of fossil fuel in the internal combustion engines, leakage of oils, corrosion of batteries as well as metallic vehicle parts (Dolan et al., 2006; Aslam et al., 2013; Ghimire, 2015). Among the metals released by motor vehicles, Pb proves the major toxic element for biota along the roadside environment. It is mostly emitted from the exhaust pipes of the vehicles resulting after the combustion of fuel where it is deliberately added as an anti- knocking agent (Sheng and Peart, 2006; Suzuki et al., 2009; Atayese et al., 2009). Although, the use of leaded gasoline has been reduced in various countries of the world, however it is still being widely used in most developing countries like Pakistan (Parekh et al., 2002). Lead is used in some other products such as wheel weights (Root, 2000) and in yellow road paint (Adachi and Tainosho, 2004). Plants growing along road ways have relatively increased Pb content (Bu-Olayan and Thomas, 2002). Cadmium (Cd) is mostly emitted from consumption of lubricating oil, wearing of tires and the burning of fossil fuels (Suzuki et al., 2009; Chen et al., 2010). It has been listed as number 7 among the top 20 toxins (Yang et al., 2008) because it is highly mobile in soil and vegetation and is taken up readily by the root system (Ciecko et al., 2001; Renella et al., 2004; Popova, 2013), as a result disturbs the uptake of other elements (Ciecko et al., 2004, 2005). Nickel (Ni) in vehicular emission mainly comes from fluid leakage and wearing of engine. It is one of the most important metal pollutants because its concentration is rapidly increasing in the environment which adversely affects plant growth and development (Faryal et al., 2007; Atiq-ur-Rehman and Iqbal, 2008).

Zinc (Zn) is extensively emitted from tire abrasion, lubricating oil (Adachi and Tainosho, 2004) and galvanized parts of vehicles such as fuel tanks (Falahi-Ardakani, 1984). Abrasion of brake linings is a main source of Cu as well as Zn and Ni (Lough et al., 2005; Hjortenkrans et al., 2007). The wear and tear of various vehicular components is also a cause of Cu and Fe emission (Polkowska et al., 2001; Preciado and Li, 2006). Metals emitted from vehicles not only become deposited on the soil and vegetation along the roadside (Werkenthin et al., 2014) but may persist in the air for some time and can penetrate plants directly by dust or rain (Jozic et al., 2009). Plants growing near the roadsides show high concentrations of heavy metals as they are irreversibly incorporated into the cuticle of the plants (Corsmeier et al., 2005). The large amount of metals accumulated in the soil may also be transported to aerial parts of plants via roots (Gall and Rajakaruna, 2013; Nadgorska- Socha et al., 2013; Neilson and Rajakaruna, 2014; Bourioug et al., 2015). Although some metals (Zn, Ni, Fe, Cu) are essential micronutrients required by plants at low concentration for normal metabolic functions, growth and development (Dixon et al., 2004; Marschner, 2012) but at excess they become toxic (Seregin and Kozhevenikova, 2006; Chen et al., 2009; Chaffai and Koyama, 2011), cause metabolic abnormalities and growth reduction in plant species (Rengel, 2004; Sinha et al., 2005; Bragato et al., 2009). Some metals (Pb, Cd) are non-essential and have no role in biological functions of plants so cause toxicity even at trace concentrations (Zayed and Terry, 2003; Boyd and Rajakaruna, 2013). There are many reports on the interaction of metals and plants on roadsides (Berlizov et al., 2007; Suzuki et al., 2009; Malik et al., 2010; Turan et al., 2011). Some plants accumulate metals to concentrations non-toxic to them (Brooks, 1987) and/or may be toxic to other species (Merian et al., 1985). The high bioaccumulation of metals in plants has been reported well (Burt et al., 2003; Dai et al., 2004; Samecka-Cymerman et al., 2009). Their concentration in the different plants is, however, primarily linked with bioaccumulation potential specific for each species (Gaw et al., 2006; Hildebrandt et al., 2009). Metals greatly affect the physiological activities of plants and significantly reduce the photosynthetic rates (Hassan and Hashem, 2004), stomatal conductance, net carbon dioxide assimilation, transpiration, catalytic functions of enzymes and contents of chlorophyll (Heckathorn et al., 2004). Several studies have showed that heavy metals emitted by vehicles deleteriously influence growth of plants (Naveed et al., 2010; Nawazish et al., 2012; Khattak

et al., 2013). Metals impair important biochemical processes in plants and may enter animal and human body when they consume contaminated plant parts, thus circulating through entire food chain (Harmanescu et al., 2011; Ali et al., 2017). As a consequence, heavy metals may cause health disorders in animals and humans (Suzuki et al., 2009; Joshi and Kumar, 2011; Mtunzi et al., 2015) due to the absence of any appropriate mechanism for their removal from the body of living organisms (Alam et al., 2003; Arora et al., 2008). Metals amass in the adipose tissues and internal organs of human body. They can disturb the central nervous system and may act as cofactors in several other diseases (Rabitsch, 1997). Young children are mainly susceptible to metal poisoning because maximum growth and differentiation of brain occurs at this age. Metal poisoning may harm the lungs, kidneys, bones and reproductive systems in humans (Godt et al., 2006). So in order to keep the environment clean and to protect lives from metal toxicity, it is important to have thorough understanding of the nature and level of metal pollution. For monitoring the level of metals in the environment, it is important to determine the level of metals contents in soil and plants (Al-Khashman, 2012). However, phytomonitoring is a simple and cheap method which proves very useful. In this regard, a variety of cultivated and wild plants growing along the roads acting as sink can prove very useful for determining the extent of metals in the environment (Zhang et al., 2012). Plants remove metals from environment by three processes, namely deposition of particulates, absorption by leaves (Prajapati and Tripathi, 2008) and absorption from soil. Studies have revealed that plants along the roadsides for example Nerium oleander, Guaiacum officinale, Cannabis sativa, Ficus virens, Dalbergia sissoo, Ficus bengalensis and Ageratum conyzoides prove good indicators/monitors of metal pollution (Pirzada et al., 2009; Khattak et al., 2013; Deepalakshami et al., 2014). Leaves are the organs of plants where major physiological processes take place. They respond to alterations in the environment and thus can be an excellent material for monitoring level of metal pollution (Sheng and Peart, 2006; Turan et al., 2011). In the recent years, leaves of various higher plants growing along the roads have been used for this purpose (Bakirdere and Yaman, 2008; Tiwari et al., 2008; Pateriya and Verma, 2010; Falusi, 2010; Ogbonna et al., 2013).

Metal content in leaves mostly correlates with soil metal content (Kabata and Pendias, 2000). However, the content of metals varies spatially and temporally (Johansson et al., 2007; Sarasiab et al., 2014). Previous studies have shown higher concentrations of metals during warm periods of the year (Papafilippaki et al., 2007; Naveed et al., 2010; Ibrahim and Omar, 2013). Nevertheless, spatial variation in metal concentrations has been reported along the roadsides in various studies (Nawazish et al., 2012; Tanee and Albert, 2013). The contents of Cu, Pb and Zn were found varying spatially in Sydney, Australia, however there was no temporal variation (Davis and Birch, 2011). As metal pollution caused by automobiles is arising as a global phenomenon and at many places in the world has exceeded the permissible limits and threatening the living organisms, it needs to be studied extensively in terms of its current status and its effects on biota to chalk out its effective control measures. In this direction, very few studies have been carried out in Pakistan (Farrukh, 2005; Faiz et al., 2009; Naveed et al., 2010; Khan et al., 2011; Farooq et al., 2012). In Punjab, the most populated province in Pakistan, the number of vehicles is growing steadily because of growing population and thus various cities have been interconnected via a network of roads. Its Grand Trunk road (G.T. road) was built in the 16th century before the partitioning of subcontinent from Peshawar (Pakistan) to Kolkata (India) to connect together the remote provinces for military and administrative reasons. Lahore and Gujranwala, are among the large cities of the Punjab and have been connected via a single Grand Trunk road, where the intensity of traffic persists very high every day and consists of trucks, multiwheeler loaders, wagons, oil tankers, buses, auto rickshaws, suzuki and motor cycles. Moreover it passes through various villages and municipalities where animal driven carts are very common which mostly use worn over tires thus emit metals in huge amount. Keeping in view the high traffic intensity, National Highway Authority has initiated a project of Motorways for providing an efficacious and wide range of transportation. The project includes construction of 10 motorways. Motorway-2 completed in 1997 has distinct ecology. The volume of traffic on its Pindi Bhattian-Kala Shah Kaku section remains comparatively lower than Lahore-Gujranwala road. The type of traffic running on it includes vans, mini buses and air conditioned buses. Carts which are driven by animals are prohibited

on Motorway. This road is smoother, so wear and tear of tires is expected to be high due to their quick heating as a result of high speed of vehicles. As above mentioned two roads differ considerably not only in number of vehicles but also in the types of vehicles running on them, thus the extent of metal contamination caused by the transport sector is likely to differ both spatially as well as temporally between two roads. The level of metal contamination along these roads is not studied yet. Thus, current project was designed to examine and compare the degree of metal pollution produced by vehicular sector along a segment of Motorway-2 and a segment of G.T. road. Hypothesis Heavy metal pollution from vehicular emissions may vary spatially and temporally and can affect different plant attributes. Research questions Following research questions arise from this study. 1. Does the heavy metal pollution caused by vehicular traffic vary seasonally at different sites? 2. How does the heavy metals pollution alomg the roadside affects plant physiology? 3. How the plants growing along the roadside vary in their metal uptake potential? Objectives Main objectives of this study are given below. a) To determine the spatio-temporal variation in metal contents released from vehicles along two roads b) To investigate the effect of vehicular emitted metals on physiological and biochemical parameters of some plant species growing along roadside c) Assessment of potential phyto-monitors of metal pollution along the two roads

CHAPTER 2 REVIEW OF LITERATURE The increase of road traffic activities due to rapid industrial development and urbanization has is one of the major sources of heavy metals contamination in environment (Poszyler-Adamska and Czemiak, 2007; Zeng, 2008; Saeedi et al., 2009; Luo et al., 2011; Amato et al., 2011). The high metal accumulation has detrimental effects in the ecosystem due to their persistent toxicity (Pereira et al., 2017). The soil and plants along the roadsides are primary sinks for vehicular released heavy metals. Plants have been widely used to monitor the extent of metal pollution in the roadside environment (Atayese et al., 2009; Kaya et al., 2010; Al-Khashman et al., 2011; Iwuoha et al., 2015). Some literature relevant to current topic has been reviewed hereunder. 2.1. Vehicles: a source of metal pollution Vehicular traffic is a significant source of metal pollution in the environment (Kreider et al., 2010; Horaginamani and Ravichandran, 2010; Nath, 2015). Several scientists have reported heavy metals as the major pollutants of the roadside environments which are emitted from the leakage of oils, burning of fuel, pavement degradation, wear and tear of tyres and corrosion of metallic parts of vehicles for example radiators (Dolan et al., 2006; Nixon and Saphores, 2007; Wei et al., 2009; Rijkenberg and Depree, 2010). Most commonly released metals from vehicles on the roads were Cd, Pb, Cu, Ni and Zn (Elik, 2003; Sezgin et al., 2003; Han et al., 2007). Therefore, the continuous running of vehicles on roads can lead to augmented concentration of these metal contaminants along the roadside (Olukanni and Adeoye, 2012; Gworek et al., 2011). 2.2. Metal contents in soil and plants along the roadsides According to Chen et al. (2010), soil along the roadsides is the major reservoir of traffic-related metals which can easily effect residents near the roads through suspended dust or direct contact. In a study in Addis Ababa city, Ethiopia, Teju et al. (2012) reported much higher level of Pb contamination (418.6 mg kg-1) in roadside soils as compared to control samples (18.8 mg kg-1). The degree of metal contamination along the roads depends on numerous factors, such as distance from road, volume of traffic, wind direction, age of the vehicle and road (Ghimire,

2015). Scientists have observed that concentrations of the metals such as Cu, Cd, Pb, Ni and Zn decline rapidly within 10 to 50 m from the roadsides (Pagotto et al., 2001; Joshi et al., 2010). Various studies conducted in different parts of the world showed high metal contamination along the major highways (Mmolawa et al., 2010; Ekmekyapar et al., 2012; Akan et al., 2013; Mathews-Amune and Kekulus, 2013). Results of these studies showed that the contents of metals were highest near the edge of road, and then declined with increase in distance from road. Oyewale and Funtua (2002) observed that soil along kaduna-Zaria highway contained higher levels of Pb, Cu, and Zn as compared to soil from control site. Another study conducted in Dibrugarh district of Assam indicated that the contents of Cr, Cd, Ni and Pb in tea cultivated soil close to national highway decreased in a constant pattern as the distance from the road edge increased (Nath, 2015). In a comparative study, Voegborlo and Chirgawi (2007) observed that the contents of Zn, Cd, Pb, Ni, Cu, Mn and Cr in soil and vegetation near a major highway in Libya declined with increase in distance from road, showing their relation with vehicular traffic. In a study, Bhowmick et al. (2015) recorded the highest concentrations of Pb in soil (0.1931 ppm) and plants (0.1358 ppm) at 0 m distance from highway. In a comparative study, Naser et al. (2012) examined the Pb, Ni and Cd in soil and vegetables such as bottle gourd and pumpkin growing near a major road in Gazipur, Bangladesh.The results showed that metal contents reduced with distance from road. Joudah (2013) described the effect of heavy metal (Pb, Cd and Ni) concentrations on soil and plants along the roadside in Bab-Al-Maudham city center, Baghdad. He found a decrease in metal contents with increase in distance from highway. There was an obvious relationship between metal concentrations and traffic density. Matthews-Amune and Samuel (2012) conducted a study in Adogo, Nigeria and found higher amount of metals (Cu, Pb, Ni, Zn and Cd,) in roadside agricultural soils and cassava leaves as compared to reference samples. In a study, Atayese et al. (2009) found significantly higher metal contents (Pb, Cd) in Amaranthus viridis growing along the major highways as compared to those in the reference samples taken from some rural area in Logos, Nigeria. In another study, Akbar et al. (2006) found that contents of metals (Zn, Cd, Pb,) were higher in roadside soils of various areas of Northern England as compared to their background levels in British soils. Sharma and Prasad (2010) determined the Pb and Cd contents in soil and vegetable cropsalong a majorhighway in

Agra, India. They observed a strong negative correlation between metal content in soil and distance from the road. Another study carried out by Duong and Lee (2011) showed that contents of heavy metals were higher near the highways as compared to little farther away from the road. In a study conducted by Jaffar et al. (2017) in massively urbanized district Baoshan of Shanghai, higher contents of metals (Pb, Cd, Zn, Ni, Cr, Mn and Cu) were found in roadside topsoils as compared to residential and agricultural soils. The contents of all the metals were significantly higher than their background national values. Doabi et al. (2017) examined atmospheric dust samples from Kermanshah province of western Iran. They reported that high Ni and Cr concentrations were partly while high Zn and Cu concentrations in dust samples were mainly from traffic sources. In another study, Al-Chalabi and Hawker (2000) found that vehicular emissions were the key sources of Pb in the roadside soil along main roads of Brisbane, Australia. Hassan and Basahi (2013) also attributed high contents of metals in soil and leaves from urban and industrial areas to traffic sources and reported that the contents depend on levels of traffic and urbanization. Ali et al. (2017) found high degree of metal contamination in roadside dust collected from metropolitan area of Hefei, China. In a study carried out by Faiz et al. (2009) in Islamabad, Pakistan, high contamination of heavy metals Cd, Pd, Ni, Zn and Cu was noticed in the dust and soil collected from the roadsides. Enuneku et al. (2017) examined the soil and earthworm samples from high traffic areas in Benin Metropolis, Nigeria. They found that the soil samples were highly polluted by heavy metals which were in the following order; Cd < Pb

concentration of Cd (2.96 mg kg-1) and Pb (95 mg kg-1) in leaves of different plant species collected from some highly trafficked roads in Karachi, Pakistan. 2.3. Spatio-temporal variation in metal contents The level of metal contamination in the environment varies spatially and temporally (Imperato et al., 2003; Pathak et al., 2015). Ojha et al. (2016) observed temporal variation in heavy metal contents along the roadsides in southern Germany and Lanzhou, China, over two years. They found an overall increasing trend of metal contents during this period. Metal contents in roadside dust were in the order: Cd < Cu < Pb < Zn. Ahmed et al. (2016) observed spatial variation in soil metal pollution near a highway and used PCA/FA and CA to interpret spatial variability in soil metal contents. In a stusy, Pathak et al. (2013) reported spatial and seasonal varitation in content of metals (Ba, Cd, Cr, Co, Ti, Zn, Ni and Cu) in soil. Duman et al. (2006) found that the accumulation of different metals (Cu, Mn, Cr, Pb, Cd, Zn and Ni) in Potamogeton lucens varied during different seasons. In a comparative study, Duman and Obali (2008) observed seasonal variation in accumulation of metals (Ni, Pb, Cr, Mn, Zn and Cu) in Nuphar lutea. Maximum metal accumulation was noted during summer season which was followed by autumn and then spring season. Sun and Chen (2016) also observed spatial and temporal variation in Pb, Cd, Zn, Ni and Cu content in soil around Beijing metropolis in China. The contents of Pb, Zn and Ni augmented from the pre- to post- rainy season whereas Cu, Cd and Cr decreased. In another study, Baycu et al. (2006) noted variation in contents of metals (Pb, Ni, Cd and Zn) in the leaves of certain plant species during autumn and spring seasons in urban areas of Istanbul. 2.4. Correlation between traffic density and metal contents along the roadside Elevated levels of metals (Cu, Cd, Zn,Pd, Ni and Mn) in roadside soil and vegetation are mainly due to heavy vehicular traffic. The difference in heavy metal contentsalong the roads is due to variation in vehicular traffic density (Rolli and Gadi, 2015). The metal contents (Pb, Cd, Ni, Zn, V) in plants and soil were positively correlated to traffic densities, with plants and soil along high traffic density roads having significantly higher contents of all the examined metals than those along the low traffic density roads (Amusan et al., 2003). Abechi et al. (2010) found a significant positive correlation between traffic volume and contents of metals in roadside soil in Jos metropolis, Nigeria. The high vehicular traffic density led to

higher emission rates, causing pollution of the roadside soils (Kummer et al., 2009; Modrzewska and Wyszkowski, 2014). In a study carried out in Venezuela, the Pb concentration in the leaves and roots of plants collected from a heavy traffic roadside was higher than in those collected from a lighter traffic roadside (Elizabeth, 2003). In a comparative study, Uddin et al. (2014) found high contents of metals in both soil and grasses in the traffic congested area of Dhaka city, Bangladesh. The concentrations of Cu, Cd, Zn and Pb were determined to assess the impact of vehicles on heavy metal contents in plants growing along some roadways in India. The metal concentrations in plants were positively correlated to traffic density (Deepalakshmi et al., 2014). A study conducted in Mersin, Turkey has shown that metal contents (Pb Cd, Cu, Ni, Zn) in roadside soil were significantly higher than control samples and had a significant correlation with number of vehicles running along the roads. (Arslan and Gizir, 2004). Similarly, another study conducted by Jaradat and Momani (1999) in Jordan exhibited that roadside soils and plants contained high contents of heavy metals (Pb, Cd, Cu and Zn). Moreover, the contents of these metals augmented with increasing traffic densities. Ghimire (2015) also reported a significant positive correlation between volume of traffic based on vehicle counts and the contents of selected metals (Pb, Cu, Cr, Zn, Sn) in both soil and plants.The Pb ontent in soil and plants growing along the roadsides in Dar es Salaam, the main city of Tanzania, also showed strong correlation with the traffic density and it decreased with increase in distance from the road (Luilo and Othman, 2006). Joudah (2013) also reported that there is an obvious relationship between metal concentration in soil and traffic density. Pal et al. (2000) observed that the leaves of plants growing along the roadsides with high traffic density accumulated higher Pb content in comparison to plants growing along the roadside having low traffic density. Several other investigations have also indicated that the pollution of metals in roadside dust, soils and palnts is directly related to the traffic density on the roads (Viard et al., 2004; Grigalaviciene et al., 2005; Hjortenkrans et al., 2006; Nabulo et al., 2006; Khan et al., 2011; Bada and Oyegbami, 2012).

2.5. Effect of metals on physiological parameters of plants Heavy metal phytotoxicity may occur due to alterations of various physiological processes (Rascio and Navari-Izzo, 2010). A decline in gas exchange attributes was observed in plants under heavy metal stress (De Maria et al., 2013). Photosynthesis is probably the most important of plant processes and is known to be very sensitive to metals stress, as both light and dark reactions of this process can be directly or indirectly affected (Todeschini et al., 2011; Castagna et al., 2013; Zurek et al., 2014). The main effects from exposure to phytotoxic contents of metals include the restriction of the photosynthetic process, caused by the decline of stomatal conductance (Wahid et al., 2008; Sagardoy et al., 2010; Al-khatib et al., 2011), which subsequently leads to decrease in CO2 fixation. The pollutants in vehicular emissions along the roadside caus stomatal clogging. Zeb et al. (2017) noted 52%, 48%, 38% and 36% more clogging of stomata in Parkinsonia aculeata, Conocorpus erectus, Guaiacum officinale, and Nerium oleander respectively along the roadside in comparison to their control plants in Pakistan. Li et al. (2015) detected a significant decrease in net photosynthetic rate, stomatal conductance and transpiration rate of Elsholtzia argyi under Cd stress in comparison to control plants, however, intercellular CO2 concentration were increased significantly. In another study, Ahmad et al. (2008) noted inhibition of the transpiration rate, stomatal conductance and photosynthetic rate in mung bean (Vigna radiata) plants exposed to Pb. 2.6. Effect of metals on biochemical parameters of plants Vehicles directly or indirectly influence roadside plants due to emission of heavy metals (Viskari et al., 2000). The presence of high contents of metals in the environment exerts harmful effects on plants (Mishra and Tripathi, 2008). The exposure of plants to high levels of heavy metals commonly activates strong responses. The type of plant responses and their intensity primarily depend on the type and concentration of metal, the species of studied plants, as well as examined plant tissue (Cho and Park, 2000; Shainberg et al., 2000; Aldoobie and Beltagi, 2013; Chen et al., 2015). In a study, Rahul and Jain (2016) examined that traffic related metals (Zn, Cu, Cr, Cd, Ni and Pb,) detrimentally affectd the roadside plants (Cassia fistula, Polyalthia longifolia, Ficus religiosa, Bougainvillea spectabilis and Azadirachta indica) in India. Alterations in biochemical responses of plants, for example a decrease in the contents of photosynthetic pigments such as chlorophyll a and b, total chlorophyll as well as carotenoids

was observed as a communal indication of metal toxicityin different species of plants (Jiang et al., 2012; Rai and Panda, 2015; Zouari et al., 2016a). Chlorophyll contents decrease under heavy metal stress (Vijayaragavan et al., 2011) because these metals substitute the Mg2+ from its binding position in structure of chlorophyll molecule, producing a degraded chlorophyll (Otero et al., 2006). Metals also impede the activities of enzymes taking part in the biosynthesis of cholorophyll such as protochlorophyllide reductase, aminolevulinic acid dehydratase and porphobilinogen deaminase (Mysliwa-Kurdziel et al., 2004; Walley, 2005; Noriega et al., 2007; Skrebsky et al., 2008) thus disrupt the structure of chloroplast membranes, causing a reduction in chlorophyll contents (Sharma and Dubey, 2005) Iqbal et al. (2015) determined the effect of automobile pollution on chlorophyll content of leaves of different plant species viz. Guiacum officinale L., Conocarpus erectus L., Azadirachta indica A. and Eucalyptus sp. growing along some roads in Karachi, Pakkistan. The contents of chlorophyll a, chlorophyll b and total chlorophyll were lower in the leaves of trees along the roadside as compared to control plants. Similarly, in a study conducted in Haridwar, India, substantial alterations in photosynthetic pigments as well as relative water content and ascorbic acid content were observed in Eucalyptus citrodora, Shorea robusta, Tectona grandis and Mangifera indica exposed to roadside vehicular pollution as compared to control plants (Joshi and Swami, 2007). Saravana and Sarala (2012) examined the influence of roadside contaminants on Ficus religiosa, Pongamia pinnata, Delonix regia, Polyalthia longifolia and Azadirachta indica growing in Madurai City. Decline in contents of chlorophyll and carotenoids were noted alongwith reduction in leaf area. Lead (Pb) tocixity caused a reduction in chlorophyll content in Cynara scolymus as a consequence of disruption in photosynthetic apparatus which further caused a reduction in overall growth of plant (Karimi et al., 2012). The Pb and soot particles released from the vehicles get deposited on the surface of plant leaves, cause stomatal clogging and eventually lead to decline in the rate of photosynthesis, that in turn, results in a decrease in chlorophyll, proteins and sugars (Prajapati and Tripathi, 2008; Narwaria and Kush, 2012). Total soluble protein is metabolically active protein fraction in plants and generally considered as an index of metabolic alterations under stress conditions. Studies have revealed that high concentrations of metals cause reduction in total soluble protein contents in plants (Razmiafshari et al., 2001; Abass et al., 2016). The decrease in protein content was possibly

due to decrease in protein biosynthesis or enhanced degradation under metal stress (Blaestrasse et al., 2003; Lin and Kao, 2006; Maheshwari and Dubey, 2007). Proteins mainly as enzymes perform several vital functions in plants at cellular level. Heavy metals compete with and replace some essential divalent cations (Ca and Mg) from the enzymes thus disturb their activity (Tabaldi et al., 2007). Metals such as Cd cause structural modifications in proteins by reacting with the sulfhydryl (-SH) group, thus hinder their activity (Prasad and Strzałka, 2002). In a study, Kandziora-Ciupa et al. (2013) observed a strong positive correlation between total protein content and the contents of Zn, Cd and Pb in the leaves of Vaccinium myrtillus. The increase in protein content under metal stress conditions was explained by the form and concentrations of metals, as well as, the plant species in stress (Heiss et al., 2003; Sabatini et al., 2009). Increase in free amino acids in leaves of plants is considered as a common response to metal stress in several plant species (Shah and Dubey, 1998; Hsu and Kao, 2003; Chaffei et al., 2004). A wide range of cellular responses initiate to deal with and overwhelm the toxic effects of metal ions in plants (Dubey and Pessarakli, 2002). The role of amino acids as signaling molecules; osmolyte regulators, chelating and detoxification agents in plants is well known in response to heavy metal stress (Xu et al., 2012). Numerous previous investigations reported a significant increase in contents of free amino acids and reduction in total soluble proteins content in metal stressed plants (Wu et al., 2004; Pant et al., 2011; Vassilev and Lidon, 2012). The amount of total free amino acids tends to augment with rising concentrations of metals such as Cd and Pb (Bhardwaj et al., 2009). High concentrations of heavy metals either directly or indirectly cause a rise in generation of reactive oxygen species (ROS) in plants (Emamverdian et al., 2015), thus resulting in oxidative stress. The ROS disrupt normal cellular functions and metabolism by interfering with and damaging different macromolecules sach as lipids, proteins and DNA (Khan et al., 2015; Anjum et al., 2016). To minimize the damaging effects caused by ROS, plants have established antioxidant systems which involve a range of enzymatic and non- enzymatic mechanisms (Gratão et al., 2005; Kandziora-Ciupa et al., 2013). Non-enzymatic antioxidants including proline, glutathione, ascorbic acid, cysteine, non-protein compounds rich in –SH groups (Singh and Sinha, 2005) and enzymatic antioxidants such as glutathione reductase, catalase (CAT), guaicaol peroxidase (GPX) and superoxide dismutase (SOD) are

capable of scavenging, removing, or neutralizing ROS (Gill and Tuteja, 2010; Das et al., 2015). The activities of these ROS scavangers differ with the contents of heavy metals and the plant species (Gallego et al., 1996). Rastgoo and Alemzadeh (2011) reported a significant increase in non-enzymatic antioxidant molecules (proline and phenol) and enzymatic antioxidant (superoxide dismutase) in Aeluropus littoralis under heavy metal (Pb, Cd, Co, Ag) stress. Bhardwaj et al. (2009) found that the activities of glutathione reductase, guaiacol peroxidae and ascorbate peroxidase were increased while that of catalase was reduced in Phaseolous vulgaris under the effect of metals (Pb and Cd). Baycu et al. (2006) observed a positive correlation between the contents of Pb and activity of POD in some selected tree species in Istambul. Kandziora-Ciupa et al. (2017) reported that increased heavy metal (Cd, Zn) accumulation caused an increase in non-protein –SH groups, proline and GSHt contents in bilberry (Vaccinium myrtillus) while in lingonberry (Vaccinium vitis-idaea) the elevated heavy metal (Pb, Cd, Zn) concentration induced an increase in content of ascorbic acid, SOD activity, and a decline in GPX activity. Dubey and Pandey (2011) reported that increase in SOD, CAT and APX activity could be involved in the defense response of black gram (Vigna mungo) exposed to Ni toxicity. Several studies revealed that various plant species have efficient antioxidant systems containing high levels of glutathione which are beneficial for metal tolerance (Yadav, 2010; Nadgorska-Socha et al., 2013; Viehweger, 2014). However, in addition to non-enzymatic antioxidants (carotenoids, glutathione and ascorbate), the enzymatic antioxidant activity of plants under the effect of metals, particularly POD activity which reveals the total phytotoxicity have also been reported (Seth et al., 2012; Nadgorska-Socha et al., 2013). 2.7. Phytomonitoring of heavy metal pollution Biomonitoring methods are now being commonly used for the determination of environmental pollution. Many plant species play an essential role in sequestering huge quantities of metals from the environment due to their ability to uptake and accumulate metals in various tissues (Adams and Happines, 2010; Rafati et al., 2011) so can be used for remediation purposes. Studies revealed that different plant species differ in their ability to accumulate metals, and even though the same plant species have different characteristics to uptake and translocate metals in different plant parts (Baldantoni et al., 2004; Yang et al., 2008; Guala et al., 2010). Certain plant species which can grow in contaminated areas, amass

high concentrations of toxic metals and are capacable to tolearate metal toxicity which is crucial for effective monitoring or/and remediation of metal contaminaton (Pulford and Watson, 2003; Patra et al., 2004; Badr et al., 2012). Different plants belonging to approximately fourty five families of plants are potential accumulators of metals (Gosh and Singh, 2005). Almost five hundred plant species are recognized as accumulators of heavy metals (Jaffre et al., 2013). In recent few years, increasing use of leaves of higher plants as biomonitors of metal pollution in the environment, mainly in urban areas has been observed (Aksoy et al., 2000; Yilmaz et al., 2006; Yasar et al., 2010). Kaya et al. (2010) reported that the leaves of Robinia pseudoacacia L. can be used for biomonitoring of Cd and Pb, and Nerium oleander L. for biomonitoring of Pb pollution. Khairia and Al-Qahtani (2012) examined the accumulation of metals (Cr, Co, Pb, Cu, Cd, Ni, Zn and Fe) in different plant species (Senna italica, Cyperus laevigatus, Citrullus colocynthis, Calotropis procera, Argemone mexicana, Phragmites australis and Rhozya stricta). The increasing trend of metal concentration in plants was Cd, Pb, Co, Ni, Cr, Cu, Zn and Fe. According to the metal accumulation capability, P. australis and C. laevigatus proved as the best choices for phytomonitoring and phytormediation of contaminated sites. Aksoy and Demirezen (2006) reported that a wild plant species Fraxinus excelsior can be employed for biomonitoring of metal pollution in Turkey. Some medicinal plants of Apocynaceae growing along the roadside were used as a phytotool to monitor toxic metals (Venkateshwar et al., 2005). Shafiq et al. (2011) analyzed the leaves of Cassia siamea and Alstonai scholaris growing along some busy roads in Karachi city, Pakistan for heavy metals. They observed that Alstonai scholaris accumulated higher contents of Cd and Pb so can be used as bioindicators of these metals. Suzuki et al. (2009) reported that the leaves of Rhododendron pulchrum leaves growing along the roadsides can be used as bioindicators of traffic-related metal pollution in Okayama, USA. Okoronkwo et al. (2014) examined the metal uptake ability of two plants and observed that Synedrella nodiflora has higher metal accumulation potential than Chromolaena odorata. Thus S. nodiflora can be used and suggested for phytomonitoring and phytoremediation of metal polluted sites.

Akguc et al. (2010) measured the contents of Ni, Fe, Cu and Mn in leaves and branches of Pyracantha coccinea for assessing the metal pollution in Mugla Province. The results proved that P. coccinea might be employed as a biomonitor of metal (Ni and Cu) pollution. Severoglu et al. (2015) used leaf and bark of Juniperus virginiana, to assess the rate of metal pollution in the Bishkek City, Kyrgyzstan. They reported that metals were transported and stored within the leaves of J. virginiana, so for evaluation of metal accumulations, this plant could be used as a biomonitor. In several studies using different plant species, the level of metal pollution has been successfully monitored (Dogan et al., 2007; Onder et al., 2007; Kaya and Yaman, 2008: Ozyigit et al., 2010: Shafiq et al., 2012).

CHAPTER 3 MATERIALS AND METHODS

Vehicular traffic has become a major source of metal pollution along the roadside environment all over the world. Globally efforts are underway to examine the level of metals emitted by vehicles and their adverse effects on biota. In this regard, very few studies have been carried out in Pakistan. Therefore, the current project was designed to phytomonitor the extent of metal pollution caused by vehicles along the two roads i.e. a segment of Motorway (M-2) from Pindi Bhattian to Kala Shah Kaku and a segment of Grand Trunk road (G.T. road) from Lahore to Gujranwala in Punjab, Pakistan. The materials used and methods adopted during the execution of this project are as follows:

3.1. Survey of sampling sites

Two roads [A section of Motorway (M-2) from Pindi Bhattian to Kala Shah Kaku and a section of Grand Trunk road (G.T. road) from Lahore to Gujranwala] in Punjab, Pakistan were selected for the phytomonitoring of metal pollution from vehicular sources. For data collection survey was conducted during all the four seasons of the year i.e. winter, spring, summer and autumn at regular intervals. The meteorological data of the study area has been given hereunder (Table 3.1).

Table 3.1. Meteorological data

Winter Spring Summer Autumn

Average temperature ( ˚C) 15.4 20.8 32.5 27.9

Average precipitation (mm) 20.2 27.9 90.3 62.2

Five sites were randomly selected on each of both roads (Table 3.2, Fig. 3.1).

Table 3.2. Selected sites and their geographical co-ordinates along M-2 and G.T. road .

Pindi Bhattian to Kala Shah Kaku (M-2) Lahore to Gujranwala (G.T. road)

Sites Geographical Coordinates Sites Geographical Coordinates

Latitude:31° 53' 42.1″N Latitude: 31° 40' 8.98″N Pindi Bhattian Ferozewala Longitude: 73° 16' 14.3″E Longitude: 74° 16' 25″E

Latitude:31° 51' 59.5″N Latitude: 31° 48 8.91″N Sukheke Longitude: 73° 30' 7.14″E Muridke Longitude: 74° 15' 32.4″E Latitude:31° 49' 53.4'' N Latitude: 31° 54' 23.3″N Khanqah Dogran Longitude:73° 37' 27.07''E Sadhoke Longitude: 74° 14' 13.2″E Latitude: 31° 42' 59.9”N Latitude: 32° 3′ 14″ N Sheikhupura Longitude: 73° 59' 6.09''E Eminabad More Longitude: 74° 12′ 32.8″E Latitude: 31° 44′ 26.3''N Latitude: 32° 9' 15.7″N Kala Shah Kaku Longitude: 74°15′ 11.3''E Gujranwala Longitude: 74° 11' 3.21″E

Fig. 3.1. Map of study sites on M-2 and G.T. road; Along M-2: Pindi Bhattian, Sukheke, Khanqah Dogran, Sheikhupura, Kala Shah Kaku; Along G.T. road: Gujranwala, Eminabad More, Sadhoke, Muridke, Ferozewala,

Pindi Bhattian Khanqah Dogran

Sukheke Sheikhupura

Kala Shah Kaku Petrol station Fig. 3.2. An overview of study sites on Motorway (M-2)

An overview of traffic at G.T. road

Traffic density at G.T. road Petrol Station

Eminabad More Gujranwala Fig. 3.3. An Overview of G.T. road

3.2. Collection of samples i) Plants The following wild plant species commonly growing (Fig. 3.4) along both the roads were chosen. Plant Species Common Names Calotropis procera A. Ak Cenchrus ciliaris L. Anjan grass Cynodon dactylon L. Barmuda grass Nerium oleander L. Kaner Parthenium hysterophorus L. Parthenium Three plants of each plant species growing nearest to the roadside were selected and three leaves per plant were randomly collected from the top, middle and base of the plant from each selected site on both roads under study. Three leaves of a plant were mixed and considered as one sample. Control plant samples were collected at a distance of 50 m away from the roadside as documented by Jian-Hua et al. (2009). All the sampled leaves were packed in labelled polythene zipper bags, kept in the cooling container and brought into the laboratory for chemical analysis. ii) Soil The soil samples (Triplicate) from upto 10 centimeter depth were collected (Werkenthin et al., 2014) using hand driven stainless steel auger from each site along each road. Control soil samples were taken 50 m away from the roadside. Soil samples were also kept in labelled polythene bags and brought to the laboratory in the Department of Botany, University of Agriculture, Faisalabad.

a) Calotropis procera b) Cenchrus ciliaris

c) Cynodon dactylon d) Nerium oleander

e) Parthenium hysterophorus f) Soil sampling Fig. 3.4. Plant species and soil sampling

3.3. Determination of metal contents in plants and soil samples

The digestion of plant and soil samples was carried out with HNO3 following the methods of USEPA (1996) to determine the contents of five metals i.e. cadmium (Cd), copper (Cu) lead (Pb), nickel (Ni) and zinc (Zn). Digestion process Oven dried and crushed leaf samples (500 mg) were taken in 250 ml digestion flasks, then 5 ml nitric acid in 1:1 was added. The digestion flasks were placed on the hot plate at 95oC and allowed to reflux for ten minutes. Then the solution was cooled down, concentrated o HNO3 (2.5 ml) was added and allowed to reflux at 95 C for 30 min. Again the HNO3 (2.5 ml) was added into the solution and heated for two hours. The solution was allowed to cool. Then distilled water (2 ml) and 30 % hydrogen peroxide (3 ml) were added. Then the solution was heated upto effervescence diminished. After that, in aliquots (1 ml) 30 % hydrogen peroxide (5 ml) was added by warming. The aliquots were allowed to cool, then concentrated hydrochloric acid (5 ml) was added and heated (without boiling). The solution was allowed to cool at room temperature (20-25oC), filtered from each flask by using Whatman No. 40 filter paper, poured into small plastic bottles and diluted with distilled water upto 50 ml. The filtrate was analyzed for heavy metals contents. For digestion of soil, its oven dried sample (1 g) was taken and the above mentioned method was followed. The contents of metals i.e. Cd, Cu, Pb, Ni and Zn in all digested samples were determined using AAS (Atomic Absorption Spectrophotometer). The operating conditions of instrument for the selected metals are given in Table 3.3.

Table 3.3. Working conditions used during the analysis of metals by AAS

Metals Cd Cu Pb Ni Zn Burner Head Standard type

Flame Air-C2H2 Oxidant Gas Pressure (KPa) 160 Wavelength (nm) 228.8 324.8 283.3 232 213.9 Slit Width (nm) 1.3 0.2 1.3 0.2 1.3 Lamp Current (mA) 7.5 10 7.5 10 10 Burner Height (mm) 5 7.5 7 7 6 Fuel gas Pressure (KPa) 6 7 7 6

Preparation of Standard Solutions All the standards for calibration were made from the commercially available (Applichem®) stock solution (1000 ppm). Working standards were prepared using de-ionized water. All the glassware used during the whole analytical process was dipped overnight in 8 N

HNO3 and washed 3 times with de-ionized water before use. The calibrated standards were prepared following formula:

C1V1= C2V2

Where, C1= Concentration of stock solution

V1 = Volume of stock solution

C2 = Concentration of standard solution

V2 = Volume of standard solution 3.4. Determination of metal contents in fuel and used motor oil Fuel (gasoline and diesel) samples were obtained randomly from different fuel stations (Shell Helix and PSO) near the roads under study. Used motor oil (Mobile oil) samples were also taken from different vehicles running on the roads. The samples were homogenized in plastic bottles and to avoid volatilization, were stored in a refrigerator prior to analysis. Samples were analyzed according to the method of Akpoveta and Osakwe (2014). In beaker 10 mL of each sample was taken. Then, a mixture of 20 mL nitric acid and sulfuric acid (ratio 4:1) was added in each beaker and heated slightly in a water bath for 4 hours daily at 80 ˚C temperature for nine days, in order to substantiate complete digestion of the samples. The contents of metals in digested samples were examined by AAS (Atomic Absorption Spectrophotometer). 3.5. Determination of metal contents in soot The petroleum soot samples were taken from the exhaust pipes of various arbitrarily chosen vehicles running on roads using iron spatula. The soot samples were collected in triplicate and placed in labelled, clean plastic bags having seals and stored at room temperature. Different soot samples were separately homogenized. To prepare working solutions, distilled water and chemicals of high purity were used. The material was digested according to the procedure of Atiku et al. (2011). Soot sample (0.2 g) was taken in digestion flask and mixed well with potassium permanganate (0.2 g). Afterward, 2 mL of hydrogen peroxide (H2O2) was added and homogenized. Then in the resulting solution, 10 mL of concentrated nitric acid

(HNO3) was added and left for 60 minutes. The sample mixture was heated (200-300 ˚C) until it reduced to 3 to 5 mL. Then the sample mixture was left at room temperature to cool down, filtered by Whatman’s No. 42 filter paper. Finally, with distilled water 50 mL volume of filtrate was made and analyzed for metal contents using AAS (Atomic Absorption Spectrophotometer) 3.6. Traffic density Traffic density (number of vehicles/day) was noted at all the selected sites adjacent to both roads (M-2 and G.T. road) on specific days (weekends and midweeks) for 2 hours (morning, evening). 3.7. Photosynthetic pigments The procedure proposed by Arnon (1949) was followed to determine the contents of chlorophyll a, chlorophyll b and total chlorophyll while the procedure given by Davis (1976) was used to calculate the carotenoids contents. The contents of pigments were measured in mg g-1 leaf fresh wt. Fresh plant leaves (0.5 g) were crushed and pulverized using pestle and mortar. The ground leaf samples were extracted with 10 mL of acetone solution (80 %). Centrifugation of extract was carried out at 10,000 rpm for 5 min. at 4 ◦C. The optical density (OD) of separated supernatant was measured at 663, 645 and 480 nm using spectrophotometer (Hitachi-220, Japan). The contents of photosynthetic pigments were computed as follows:

Chlorophyll “a” = [(OD 663) 12.7 – (OD 645) 2.69] × V/1000×W

Chlorophyll “b” = [(OD 645) 22.9 – (OD 663) 4.68] × V/1000×W

Total Chlorophyll = [(OD 645) 20.2 – (OD 663) 8.02] × V/1000× W

Carotenoids = [OD 480 + 0.114 (OD 663) – 0.638 (OD 645) / 2500] × 1000 where, W denotes weight of fresh leaf sample (g) and V denotes volume of the supernatant (mL). 3.8. Total soluble proteins The procedure proposed by Bradford (1976) was followed to determine the total soluble protein in the plant material. Phosphate buffer having pH 7 was used for the extraction of plant material. The extract was centrifuged (Universal 320 R) at 10,000 rpm at 4◦C for 15 minutes, supernatant was collected and refrigerated until analyzed for the soluble proteins.

Bradford reagent was prepared by dissolving Coomassie Brilliant Blue G-250 (100 mg) in 50 mL of ethanol (95%). After that, 100 mL of phosphoric acid (85 %) was added. Then distilled water was used to make volume upto 1 L. The resulting solution was three times filtered by Whatman No. 1 filter paper. Bradford reagent was prepared freshly prior to procedure. Leaf extract (100 µL) and 5 mL of Bradford reagent were taken in a test tube. The solution was vortexed for half minute and incubated at room temperature for half hour. Spectrophotometer (Hitachi 220, Japan) was turned on to warm up prior to use and absorbance was noted at 595 nm. 3.9. Total free amino acids The procedure proposed by Hamilton and Van-Slyke (1943) was followed to determine the total free amino acids in plant samples. Phosphate buffer (pH 7.0) was used for the extraction of fresh leaf material. Then in a test tube, 1 mL of leaf extract was taken, in which 1 mL of ninhydrin solution (2 %=2 g ninhydrin + 100 mL distilled water) and 1 mL of pyridine solution (10 %=10 mL pyridine + distilled water to make volume upto 100 mL) were added. The test tubes containing the sample solutions were kept in boiling water bath and heated for 30 minutes. In each test tube, distilled water was added to make volume upto 50 mL. Absorbance of the resulting solution was recorded on spectrophotometer at 570 nm. Leucine was used for making a standard curve and the content of total free amino acids was estimated by the given formula: Total free amino acids = Volume of sample × Graph reading of sample × Dilution factor Weight of plant sample × 1000 3.10. Total antioxidant activity In a test tube, 1 g dried leaf sample was taken and 20 mL of salt solution (0.45 %) was added. Then, it was heated for 20 mins at 40◦C in the water bath. After the centrifugation of the sample at 3000 rpm for 30 mins, the supernatant was separated and preserved at -20 ◦C prior to start the analysis. The procedure of Rahmat et al. (2003) was followed for determining the total antioxidant activity in plant samples. Leaf extract and absolute ethanol (4 mL of each) were taken and mixed in a test tube. Then 2.52 % linoleic acid (4.1 mL) was added in this mixture. Afterwards, 0.05 M phosphate buffer (8 mL) having pH 7.0 and distilled water (3.9 mL) were added and placed for 24 hours in dark in an oven at 40◦C. Some of this sample solution (0.1

mL) was taken in another test tube, then 7.5 % ethanol (9.7 mL) and ammonium thiocyanate (0.1 mL) were added to the sample solution. After three minutes, in the reaction mixture, small quantity (0.1 mL) of 0.02 M ferrous chloride solution (in 3.5% HCl) was added and after that absorbance was noted on spectrophotometer (Hitachi-220, Japan) at a wavelength of 500 nm. Total antioxidant activity = (Absorbance of control on day maximum/Absorbance of sample on same day) ×100 3.11. Gas exchange parameters Gas exchange attributes were measured for fully expanded young leaves of each plant using portable infra-red gas analyzer (IRGA), [Model LC pro + photosynthetic system; Analytical Development Company (ADC) Bioscientific, Hoddesdon, England]. 3 The specifications of IRGA were as follows: leaf surface area 11.35 cm , ambient CO2 concentration 381.21 µmol/mol, ambient temperature ranged from 22.4-27.9, temperature of leaf chamber ranged from 31.5 to 37.8 ◦C, water vapor pressure in the chamber ranged 7-11 mbar, leaf chamber molar gas flow rate 313 µmol/sec, leaf chamber volume gas flow rate 389 ml/min, ambient pressure 99.95 KPa, molar flow of air per unit leaf area 404.3 mol/m2/sec, PAR at surface of leaf was maximum upto 1694 µmol/m2. The measured parameters were as following: -2 -1 a) Photosynthetic rate (µmol CO2 m s ) -2 -1 b) Transpiration rate (mmol H2O m s ) c) Stomatal conductance (mmol m-2 s-1) -1 d) Sub-stomatal CO2 concentration (µmol mol ) e) Water use efficiency = Photosynthetic rate/Transpiration rate 3.12. Statistical analysis The plant species and soil sample were collected by stratified random sampling during all the seasons. Analysis of variance (ANOVA) for all the attributes were calculated by COSTAT computer software package (Cohort Software, 2003, Monterey, California, USA). Means were compared using least significant difference (LSD) test at 0.05 significance level (Steel and Torrie, 1980). The sample number (n) for calculating means for plants, sites and seasons has been mentioned in the caption of each table in the results section. In order to evaluate spatio-temporal variation in the collected data, canonical correspondence analysis

(CANOCO 4.5) was used. However, in order to correlate different variables, Pearson’s correlation coefficient was used.

CHAPTER 4 RESULTS 4.1. Spatio-temporal variation in heavy metal contents along the roads 4.1.1. Spatio-temporal variation in lead (Pb) content in plant leaves growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The analysis of variance of data concerning the Pb concentration in leaves of plants sampled from different sites adjacent to M-2 is presented in Table 4.1. It showed highly significant differences among plants, sites as well as seasons, whereas the interactions between plants × sites and sites × seasons remained significant at p<0.01 and p<0.05, respectively. Nevertheless, the interactions between plants × seasons as well as plants × sites × seasons existed statistically non-significant. All the plants collected from sampling sites differed significantly from each other in mean Pb content in their leaves. Among plants, Calotropis procera exhibited the highest Pb contamination followed by Nerium oleander, Parthenium hysterophorus, Cenchrus ciliaris and Cynodon dactylon (Table 4.1 a). The Pb content in the leaves of plants growing at different sites differed significantly. The plants collected from Kala Shah Kaku site appeared highly contaminated with Pb (10.6 mg/kg dry wt.) in comparison to control. However, Pb contamination (5.20 mg/kg dry wt.) was minimum in the leaves of plants growing at Sukheke site (Table 4.1 a). Significantly different mean Pb content in plant leaves taken from selected sites adjacent to M-2 was observed in different seasons (Table 4.1 a). The Pb content in plants during the four seasons followed the order: winter

The mean Pb content in the leaves of various plants collected from sampling sites along G.T. road differed significantly except Parthenium hysterophorus and Cenchrus ciliaris. Among plants, Calotropis procera accumulated maximum amount of Pb (14.0 mg/kg dry wt.) followed by Nerium oleander (12.5 mg/kg dry wt.). However, minimum Pb contamination was noted in the leaves of Cynodon dactylon (9.56 mg/kg dry wt.) (Table 4.2 a). Among the sites along G.T. road, the highest Pb contamination (16.7 mg/kg dry wt.) in the leaves of plants was documented at Muridke site and the lowest (11.9 mg/kg dry wt.) at Sadhoke site as compared to control. The amount of Pb in plants at Eminabad More site differed non-significantly from those at Gujranwala and Ferozewala site (Table 4.2 a). Mean Pb content in the leaves of plants collected from various sites along G.T. road differed significantly in different seasons (Table 4.2 a). The highest amount of Pb (13.5 mg/kg dry wt.) in plants was noted during summer whereas minimum amount (10.0 mg/kg dry wt.) was noted during winter.

Table 4.1. Analysis of variance for lead (Pb) content in plants growing at different sites along M- 2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 746.37 186.59 41.34*** Sites 5 3640.12 728.02 161.29*** Seasons 3 537.75 179.25 39.71*** Plants × Sites 20 196.07 9.80 2.17** Plants × Seasons 12 18.78 1.56 0.35ns Sites × Seasons 15 136.14 9.08 2.01* Plants × Sites × Seasons 60 20.97 0.35 0.08ns Error 240 1083.27 4.51 Total 359 6379.48 ***, **, * = Significant at 0.001, 0.01 and 0.05 levels, respectively; ns = Non-significant

Table 4.1 a. Mean Pb content (mg/kg dry wt.) in plant leaves along M-2 (LSD =0.05)

Mean Pb content Calotropis procera A. 8.83 ± 5.09 a Nerium oleander L. 7.52 ± 4.25 b Plants Parthenium hysterophorus L. 6.41 ± 3.80 c Cenchrus ciliaris L. 5.52 ± 3.32 d Cynodon dactylon L. 4.77 ± 3.13 e Kala Shah Kaku 10.6 ± 4.09 a Sheikhupura 8.92 ± 2.90 b

Pindi Bhattian Sites 7.90 ± 2.84 c Khanqah Dogran 6.45 ± 2.55 d Sukheke 5.20 ± 2.55 e Control 0.62 ± 0.37 f Summer 8.41 ± 4.84 a Autumn 6.86 ± 4.09 b Seasons Spring 6.11 ± 3.73 c Winter 5.05 ± 3.39 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

Table 4.2. Analysis of variance for lead (Pb) content in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 844.74 211.18 48.89*** Sites 5 9436.31 1887.26 436.93*** Seasons 3 596.16 198.72 46.01*** Plants × Sites 20 185.00 9.25 2.14** Plants × Seasons 12 122.40 10.20 2.36** Sites × Seasons 15 138.46 9.23 2.14** Plants × Sites × Seasons 60 67.49 1.12 0.26ns Error 240 1036.65 4.32 Total 359 12427.22 *** and ** = Significant at 0.001 and 0.01 levels, respectively; ns = Non-significant

Table 4.2 a. Mean Pb content (mg/kg dry wt.) in plant leaves along G.T. road (LSD =0.05)

Mean Pb content Calotropis procera A. 14.0 ± 7.07 a Nerium oleander L. 12.5 ± 5.89 b Plants Parthenium hysterophorus L. 11.4 ± 5.44 c Cenchrus ciliaris L. 10.7 ± 5.11 c Cynodon dactylon L. 9.56 ± 4.77 d Muridke 16.7 ± 4.13 a Gujranwala 14.1 ± 2.83 b

Eminabad More Sites 13.6 ± 2.89 bc Ferozewala 12.9 ± 2.80 c Sadhoke 11.9 ± 3.02 d Control 0.65 ± 0.45 e Summer 13.5 ± 6.71 a Autumn 12.0 ± 6.02 b Seasons Spring 10.9 ± 5.32 c Winter 10.0 ± 4.83 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

4.1.3. Seasonal variation in lead (Pb) content in plant leaves growing along M-2 The biplot for Pb concentration in different species of plants during four seasons has been presented in Fig. 4.1. For autumn season, Pb content in Calotropis procera had strong association with Kala Shah Kaku site whereas, Nerium oleander showed association with Sheikhupura site for its Pb content. Likewise, Pb content in Cenchrus ciliaris was found to be associated with Khanqah Dogran and control sites. However, the Pb content in Cynodon dactylon indicated association with Khanqah Dogran site to some extent (Fig. 4.1 a). During spring season, the Pb content in Calotropis procera exhibited strong association with Kala Shah Kaku site, whereas, the Pb content in Nerium oleander showed association with Sheikhupura site. Nonetheless, Cenchrus ciliaris and Cynodon dactylon appeared weakly associated with control as well with Khanqah Dogran sites (Fig. 4.1 b). For summer season, the CCA biplot showed strong association of Nerium oleander with Kala Shah Kaku site for its Pb concentration. Similarly, Calotropis procera and Parthenium hysterophorus had association with Sheikhupura and Sukheke sites respectively, for their Pb content. Cenchrus ciliaris also appeared to be associated with Sukheke site for its Pb content (Fig. 4.1 c). During winter season, Pb concentration in Parthenium hysterophorus was strongly associated with Khanqah Dogran and Control sites. Similarly, Pb content in Nerium oleander had association with Sheikhupura site while, the Calotropis procera indicated association with Kala Shah Kaku and Pindi Bhattian sites for its Pb concentration. However, Cynodon dactylon and Cenchrus ciliaris was found to be weakly linked with Khanqah Dogran and Sukheke sites respectively for the Pb concentration (Fig. 4.1 d). 4.1.4. Seasonal variation in lead (Pb) content in plant leaves growing along G.T. road The canonical correspondence analysis (CCA) biplot showing the Pb content in plants during different seasons has been given in Fig. 4.2. During autumn season, Pb content in Parthenium hysterophorus showed strong association with Ferozewala site. Similarly, Pb content in Calotropis procera was associated with Muridke site while, Nerium oleander indicated association with Gujranwala site for its Pb concentration (Fig. 4.2 a). During spring season, Parthenium hysterophorus and Cenchrus ciliaris exhibited association with Ferozewala site for their Pb content while, Calotropis procera was associated with Sadhoke site for its Pb concentration (Fig. 4.2 b). For summer season, Nerium oleander had high Pb content at Eminabad More and Gujranwala sites. Similarly, Calotropis procera

appeared to be associated with Gujranwala and Ferozewala sites for its Pb content. However, Cynodon dactylon was not related with any one specific location for its Pb concentration (Fig. 4.2 c). The CCA biplot for Pb concentration in plants at different sites during winter showed the association of Nerium oleander and Calotropis procera with Muridke site for their Pb concentration. Similarly, Pb content in Cynodon dactylon exhibited association with Ferozwala site. Nonetheless, Parthenium hysterophorus seemed to be weekly related with Sadhoke for its Pb quantity (Fig. 4.2 d).

(a) (b)

(c) (d) Fig. 4.1. The CCA biplot illustrating the Pb content in plants relating to different sites along M-2 during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

(a) (b)

(c) (d) Fig. 4.2. The CCA biplot illustrating the Pb content in plants relating to different sites along G.T. road during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

4.1.5. Spatio-temporal variation in lead (Pb) content in soil at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) According to the statistical analysis (ANOVA) of data regarding the Pb concentration in soil sampled from various locations adjacent to M-2, highly significant differences were documented among the sites and seasons. Nevertheless, the interaction between sites and seasons remained significant at p<0.01 (Table 4.3). The quantity of Pb in soil at all the sites along the roadside differed significantly from control (Table 4.3 a). However, the soil collected from Kala Shah Kaku site had the highest Pb content (19.72 mg/kg dry wt.). Furthermore, Sheikhupura and Pindi Bhattian were not significantly different in their soil Pb content. Similarly, soil collected from Khanqah Dogran and Sukheke sites contained the Pb content which did not differ significantly. The significant variation in soil Pb content was observed during different seasons (Table 4.3 a). Among seasons, the highest amount of Pb (16.12 mg/kg dry wt.) was noted in soil sampled during the summer season while minimum (8.11 mg/kg dry wt.) was recorded during as well as from winter season. Nevertheless, the Pb content in soil collected during spring season did not differ significantly from autumn. 4.1.6. Spatio-temporal variation in lead (Pb) content in soil at different sites along G.T. road (Lahore to Gujranwala) The analysis of variance for data concerning to the amount of Pb in soil collected from different sites along G.T. road during different seasons has been illustrated in Table 4.4. It showed highly significant differences among sites and seasons, however, their interaction remained significant at p<0.01. The Pb content in soil taken from various sites adjacent to the roadside was significantly different from control (Table 4.4 a). Among sites, the highest Pb content was noted in the soil of Muridke (29.17 mg/kg dry wt.) followed by that in the soil of Gujranwala and Eminabad. Nevertheless, the soil Pb content of Ferozewala and Sadhoke sites did not differ significantly. The Pb content in soil differed significantly during different seasons (Table. 4.4 a). The soil collected during the summer season contained the highest amount of Pb (25.08 mg/kg dry wt.) followed by that noted during the autumn (19.50 mg/kg dry wt.), spring (17.06 mg/kg dry wt.) and winter seasons (14.27 mg/kg dry wt.).

Table 4.3. Analysis of variance for lead (Pb) content in soil at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Sites 5 2013.76 402.75 59.76 *** Seasons 3 636.41 212.14 31.48 *** Sites × Seasons 15 344.48 22.96 3.41 ** Error 48 323.50 6.74 Total 71 3318.15 *** and ** = Significant at 0.001 and 0.01 levels, respectively

Table 4.3 a. Mean Pb content (mg/kg dry wt.) in soil along M-2 (LSD = 0.05)

Mean Pb content Kala Shah Kaku 19.7 ± 3.47 a Sheikhupura 14.0 ± 2.52 b Pindi Bhattian 13.0 ±2.53 b Sites Khanqah Dogran 10.7 ± 2.72 c Sukheke 8.83 ± 2.16 c Control 2.33 ± 0.61 d Summer 16.1 ± 3.09 a

Autumn 11.6 ± 2.48 b Seasons Spring 9.91 ± 1.84 b Winter 8.11 ± 1.93 c Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

Table 4.4. Analysis of variance for lead (Pb) content in soil at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Sites 5 4885.46 977.09 136.54*** Seasons 3 1140.09 380.03 53.10*** Sites x Seasons 15 311.02 20.73 2.90** Error 48 343.49 7.16 Total 71 6680.07 *** and ** = Significant at 0.001 and 0.01 levels, respectively

Table 4.4 a. Mean Pb content (mg/kg dry wt.) in soil along G.T. road (LSD = 0.05)

Mean Pb content Muridke 29.2 ± 3.18 a Gujranwala 24.8 ± 2.90 b Eminabad More 21.8 ± 2.45 c Sites Sadhoke 18.4 ± 2.91 d Ferozewala 16.7 ± 2.43 d Control 2.98 ± 0.95 e

Summer 25.1 ± 3.19 a Seasons Autumn 19.5 ± 2.33 b Spring 17.1 ± 2.07 c Winter 14.3 ± 2.31 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

dry wt.)dry 1 1

- 25

10 Pb content (mg Pbcontent kg (mg 5

0 Summer Autumn Spring Winter Seasons

Control Pindi Bhattian Sukheke Khanqah Dogran Sheikhupura Kala Shah Kaku

Fig. 4.3. Seasonal variation in Pb content in soil at different sites along M-2. Bars represent “mean of three values ± standard error”.

50 45 40 35 30 25 20 15

10 Pb content (mg/kg Pbcontent (mg/kg wt.)dry 5 0 Summer Autumn Spring Winter Seasons

Control Ferozewala Muridke Sadhoke Eminabad More Gujranwala

Fig. 4.4. Seasonal variation in Pb content in soil at different sites along G.T. road. Bars represent “mean of three values ± standard error”.

4.1.7. Spatio-temporal variation in cadmium (Cd) content in plant leaves growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The analysis of variance of data pertaining to the Cd content in the leaves of plants sampled from various sites adjacent to M-2 revealed highly significant differences among plants, sites as well as seasons. Similarly, interactions between plants × sites and sites × seasons existed significant at p<0.05 and p<0.01, respectively. Nonetheless, the interactions between plants × seasons as well as plants × sites × seasons were non-significant (Table 4.5). Plant species differed significantly in mean Cd content in their leaves except Parthenium hysterophorus which did not differ significantly from Nerium oleander as well as Cenchrus ciliaris. However, the maximum Cd quantity (2.78 mg/kg dry wt.) was documented in the leaves of Calotropis procera while minimum (1.29 mg/kg dry wt.) was recorded in the leaves of Cynodon dactylon (Table 4.5 a). Mean Cd content in leaves of plants was significantly different among sites (Table 4.5 a). However, the maximum Cd contamination was recorded in the leaves of plants collected from Kala Shah Kaku interchange site followed by those in plants collected from Sheikhupura, Pindi Bhattian, Khanqah Dogran and Sukheke sites as compared to control. Significant seasonal variation in Cd content in the leaves of plants collected from various sites adjacent to M-2 was detected (Table 4.5 a). The leaves of plants collected during summer season had the highest Cd contamination (2.70 mg/kg dry wt.) while the plants collected during winter season contained the least Cd content (1.34 mg/kg dry wt.). The amount of Cd in leaves of plants during different seasons existed in the following order: summer>autumn>spring>winter. 4.1.8. Spatio-temporal variation in cadmium (Cd) content in plant leaves growing along G.T. road (Lahore to Gujranwala) The statistical analysis (ANOVA) of data relating to the Cd content in plant leaves collected from different sites adjacent to the G.T. road during all the four seasons has been given in Table 4.6. It depicted highly significant differences among plants, sites as well as seasons. Likewise, interactions between plants × sites and sites × seasons also remained significant at p<0.01 and p<0.05, respectively, however the interactions between plants × seasons as well as plants × sites × seasons remained non-significant.

The comparison among the plants collected from selected sites along G.T. road showed significant differences in the mean Cd content of their leaves, except Parthenium hysterophorus and Cenchrus ciliaris (Table 4.6 a). The leaves of Calotropis procera accumulated the highest amount of Cd followed by Nerium oleander. Nevertheless, the least amount of Cd was accumulated by leaves of Cynodon dactylon. The significant differences among sites along the G.T. road for mean Cd content in the leaves of plants were documented (Table 4.6 a). The maximum Cd contamination (4.73 mg/kg dry wt.) was noted in the leaves of plants growing at Muridke site and minimum (2.58 mg/kg dry wt.) was recorded in plants taken from Sadhoke site as compared to the control. The order of Cd contamination in plants at different sites was as follows: Muridke>Gujranwala>Eminabad More>Ferozewala>Sadhoke. The mean Cd content in the leaves of plants differed significantly during different seasons (Table 4.6 a). The highest amount of Cd (3.79 mg/kg dry wt.) was recorded in the plant leaves sampled during summer season and the least amount (2.30 mg/kg dry wt.) was documented in those collected in winter.

Table 4.5. Analysis of variance for cadmium (Cd) content in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 91.510 22.877 26.232*** Sites 5 454.486 90.897 104.224*** Seasons 3 91.225 30.408 34.867*** Plants × Sites 20 33.166 1.658 1.901* Plants × Seasons 12 7.694 0.641 0.735ns Sites × Seasons 15 27.931 1.862 2.135** Plants × Sites × Seasons 60 17.543 0.292 0.335ns Error 240 209.311 0.872 Total 359 932.867 ***, ** and * = Significant at 0.001, 0.01 and 0.05 levels, respectively; ns = Non-significant

Table 4.5 a. Mean Cd content (mg/kg dry wt.) in plant leaves along M-2 (LSD = 0.05)

Mean Cd content Calotropis procera A. 2.78 ± 2.01 a Nerium oleander L. 2.17 ± 1.60 b Plants Parthenium hysterophorus L. 1.88 ± 1.47 bc Cenchrus ciliaris L. 1.47 ± 1.32 c Cynodon dactylon L. 1.29 ± 1.14 d Kala Shah Kaku 3.54 ± 1.53 a Sheikhupura 2.78 ± 1.37 b

Pindi Bhattian Sites 2.32 ± 1.26 c Khanqah Dogran 1.79 ± 1.20 d Sukheke 1.25 ± 0.93 e Control 0.03 ± 0.01 f Summer 2.70 ± 1.95 a Autumn 2.06 ± 1.56 b Seasons Spring 1.71 ± 1.35 c Winter 1.34 ± 1.82 d

Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

Table 4.6. Analysis of variance for cadmium (Cd) content in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons S. O. V. d. f. S. S. M. S. F-value Plants 4 125.014 31.254 36.307*** Sites 5 821.540 164.308 190.877*** Seasons 3 116.471 36.824 42.778*** Plants × Sites 20 34.679 1.734 2.014** Plants × Seasons 12 9.241 0.770 0.895ns Sites × Seasons 15 26.824 1.788 2.077* Plants × Sites × Seasons 60 17.228 0.287 0.333ns Error 240 206.593 0.861 Total 359 1351.591 ***, ** and * = Significant at 0.001, 0.01 and 0.05 levels, respectively; ns = Non-significant

Table 4.6 a. Mean Cd content (mg/kg dry wt.) in plant leaves along G.T. road (LSD = 0.05)

Mean Cd content Calotropis procera A. 3.93 ± 2.32 a Nerium oleander L. 3.38 ± 2.01 b Plants Parthenium hysterophorus L. 2.98 ± 1.63 c Cenchrus ciliaris L. 2.69 ± 1.71 c Cynodon dactylon L. 2.20 ± 1.51 d Muridke 4.73 ± 1.54 a Gujranwala 4.20 ±1.34 b

Eminabad More Sites 3.52 ± 1.07 c Ferozewala 3.14 ± 1.36 d Sadhoke 2.58 ± 1.34 e Control 0.03 ± 0.02 f Summer 3.79 ± 2.20 a Autumn 3.26 ± 1.96 b Seasons Spring 2.79 ± 1.70 c Winter 2.30 ± 1.54 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

4.1.9. Seasonal variation in cadmium (Cd) content in plant leaves growing along M-2 The biplot displaying Cd content in the leaves of plants growing at various sites adjacent to M-2 during different seasons is presented in Fig 4.5. The biplot for content of Cd in different species of plants during autumn showed that Nerium oleander was strongly associated with Sheikhupura for its Cd content (Fig 4.5 a). Similarly, Cynodon dactylon and Parthenium hysterophorus showed association with Khanqah Dogran site for their Cd content. The high Cd concentration in Calotropis procera was associated with Sukheke and Kala Shah Kaku sites. However, Cd content in Cenchrus ciliaris was found to be weakly associated with Pindi Bhattian site. For spring season, the CCA biplot showed that Calotropis procera had association with Kala Shah Kaku site for its Cd content (Fig 4.5 b). Similarly, the concentration of Cd in Nerium oleander showed association with Khanqah Dogran site, whereas the Cd content in Cynodon dactylon was associated with Sheikhupura site. The Cd concentration in Parthenium hysterophorus exhibited association with Khanqah Dogran site to some extent. During summer season, CCA biplot indicated that Cd content in Cynodon dactylon and Cenchrus ciliaris had association with Sukheke site (Fig 4.5 c). However, Cd content in Calotropis procera and Nerium oleander revealed weak association with Pindi Bhattian and Kala Shah Kaku sites respectively. During winter season, the CCA biplot for Cd content in plants at different sites demonstrated that Cd concentration in Calotropis procera was associated with Kala Shah Kaku and Khanqah Dogran sites (Fig 4.5 d). Similarly, Nerium oleander and Parthenium hysterophorus showed association with Sheikhupura site for their Cd contents, whereas Cynodon dactylon exhibited association with Control site for its Cd content. 4.1.10. Seasonal variation in cadmium (Cd) content in plant leaves growing along G.T. road The biplot showing the content of Cd in plants growing at various locations adjacent to M-2 during different seasons is presented in Fig. 4.6. For autumn season, CCA biplot showed that Cynodon dactylon and Parthenium hysterophorus had strong association with Sadhoke site for their Cd contents, whereas Cenchrus ciliaris showed association with Eminabad More site for its Cd concentration (Fig. 4.6 a). Similarly, the Cd content in Nerium oleander was

associated with Muridke and Eminabad More sites. However, the concentration of Cd in Calotropis procera was found to be associated with Muridke site to some extent. For spring season, CCA biplot showed that Calotropis procera was associated with Muridke site for its Cd content, whereas Cd content in Nerium oleander showed association with Sadhoke site (Fig. 4.6 b). Similarly, the Cd content in Cenchrus ciliaris showed association with Control site. However, Parthenium hysterophorus appeared to be weakly associated with Sadhoke site while Cynodon dactylon exhibited week association with Gujranwala and Muridke sites. For summer season, the CCA biplot showed that Cd content in Nerium oleander had association with Eminabad More and Muridke sites (Fig. 4.6 c). Likewise, Calotropis procera was found to be associated with Gujranwala for its Cd content. The CCA biplot for Cd content in plants during winter showed that Cynodon dactylon and Nerium oleander were associated with Eminabad More and Ferozewala sites respectively for their Cd contents (Fig. 4.6 d). Similarly, high Cd content in Parthenium hysterophorus showed association with Eminabad More and Ferozewala sites, whereas Calotropis procera was found to be associated with Sadhoke and Gujranwala sites for its Cd concentration.

(a) (b)

(a) (d) Fig. 4.5. The CCA biplot illustrating the Cd content in plants relating to different sites along M-2 during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

(a) (b)

(c) (d) Fig. 4.6. The CCA biplot illustrating the Cd content in plants relating to different sites along G.T. road during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

4.1.11. Spatio-temporal variation in cadmium (Cd) content in soil at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) The ANOVA for data relating to the content of Cd in soil at various locations adjacent to M-2 is presented in Table 4.7. It revealed highly significant differences among sites and seasons. Nevertheless, interaction between sites and seasons remained significant at p<0.01. The Cd contents in soil at all the sites along the roadside were significantly different from Cd content in soil at control site (Table 4.7 a). However, the soil collected from Kala Shah Kaku site appeared maximally contaminated with Cd. Moreover, the amount of Cd in soil collected from Sheikhupura and Pindi Bhattian sites differed non-significantly. Similarly, the soil collected from Khanqah Dogran and Sukheke sites did not differ significantly in Cd content. Seasonal variation was observed in Cd quantity in soil taken from several different sites adjacent to M-2 (Table 4.7 a). The maximum Cd contamination (6.30 mg/kg dry wt.) was documented in soil gathered during summer season. Nonetheless, Cd content in soil collected during spring season differed non-significantly from autumn season as well as from winter. 4.1.12. Spatio-temporal variation in cadmium (Cd) content in soil at different sites along G.T. road (Lahore to Gujranwala) The statistical analysis (ANOVA) of data pertaining to the content of Cd in soil collected from several different sites adjacent to G.T. road depicted highly significant differences among sites as well as seasons. Similarly, sites × seasons interaction also remained significant (Table 4.8). The Cd content in soil from different sites was significantly different from control. The highest Cd contamination was noted in soil collected from Muridke (10.04 mg/kg dry wt.) and Gujranwala (9.49 mg/kg dry wt.) sites which were statistically non-significant with each other. The amount of Cd in soil collected from Ferozewala and Sadhoke sites also did not vary significantly (Table 4.8 a). The Cd quantity in soil was significantly different during different seasons (Table 4.8 a). The soil collected during the summer season contained the highest amount of Cd (8.53 mg/kg dry wt.) followed by that recorded during the autumn season (7.17 mg/kg dry wt.). However, the soil Cd content did not differ significantly during spring and winter seasons.

Table 4.7. Analysis of variance for cadmium (Cd) content in soil at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Sites 5 416.71 83.34 90.68*** Seasons 3 65.71 21.90 23.83*** Sites x Seasons 15 34.86 2.32 2.53** Error 48 44.11 0.92 Total 71 561.40 *** and ** = Significant at 0.001 and 0.01 levels, respectively

Table 4.7 a. Mean Cd content (mg/kg dry wt.) in soil along M-2 (LSD = 0.05)

Mean Cd content Kala Shah Kaku 7.54 ± 1.00 a Sheikhupura 6.62 ± 0.99 b

Pindi Bhattian Sites 5.90 ± 0.59 b Khanqah Dogran 4.39 ± 1.16 c Sukheke 4.10 ± 1.08 c Control 0.10 ± 0.05 d Summer 6.30 ± 0.78 a Autumn 4.81 ± 0.98 b Seasons Spring 4.18 ± 0.71 bc Winter 3.79 ± 0.77 c Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

Table 4.8. Analysis of variance for cadmium (Cd) content in soil at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Sites 5 759.99 151.10 167.41*** Seasons 3 101.84 33.94 37.39*** Sites x Seasons 15 61.27 4.08 4.50*** Error 48 43.58 0.91 Total 71 966.69 *** Significant at 0.001 level

Table 4.8 a. Mean Cd content (mg/kg dry wt.) in soil along G.T. road (LSD = 0.05)

Mean Cd content Muridke 10.0 ± 0.96 a Gujranwala 9.5 ± 1.13 a

Eminabad More Sites 7.71 ± 0.95 b Ferozewala 6.82 ± 0.10 c Sadhoke 6.44 ± 0.89 c Control 0.12 ± 0.05 d Summer 8.53 ± 1.01 a Autumn 7.17 ± 0.82 b Seasons Spring 5.81 ± 0.79 c Winter 5.56 ± 0.77 c Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

dry wt.) 1 1

- 8

4 Cd content (mg content Cd (mg kg 2

0 Summer Autumn Spring Winter Seasons

Control Pindi Bhattian Sukheke Khanqah Dogran Sheikhupura Kala Shah Kaku

Fig. 4.7. Seasonal variation in Cd content in soil at different sites along M-2. Bars represent “mean of three values ± standard error”.

4 Cd content (mg/kg content Cd (mg/kg dry wt.) 2

0 Summer Autumn Spring Winter Seasons

Control Ferozewala Muridke Sadhoke Eminabad More Gujranwala

Fig. 4.8. Seasonal variation in Cd content in soil at different sites along G.T. road. Bars represent “mean of three values ± standard error”.

4.1.13. Spatio-temporal variation in copper (Cu) content in plant leaves growing along M-2 (Pindi Bhattian to Kala Shah Kaku) Analysis of variance (ANOVA) of data pertaining to the Cu content in the leaves of plants collected from various sites adjacent to M-2 during different seasons is illustrated in Table 4.9. It showed highly significant (p<0.001) differences among plants, sites as well as seasons. Likewise, interactions between plants × sites and sites × seasons existed statistically significant at p<0.001. However, interactions between plants × seasons as well as among plants × sites × seasons remained were not significant (p>0.05). Different plant species growing at various sites along M-2 contained significantly different Cu content in their leaves. Among plants, maximum Cu content (19.6 mg/kg dry wt.) was recorded in the leaves of Nerium oleander while the leaves of Cynodon dactylon had least amount of Cu (6.63 mg/kg dry wt.) (Table 4.9 a). Mean Cu content in the leaves of plants differed significantly at different sites along M-2. Among sites, maximum Cu content (21.0 mg/kg dry wt.) was recorded in leaves of plants at Kala Shah Kaku site while the plants at Sukheke site contained the least Cu content (7.92 mg/kg dry wt.) as compared to control. Copper content in plants at various sites followed the order: Kala Shah Kaku>Sheikhupura>Pindi Bhattian>Khanqah Dogran>Sukheke>Control (Table 4.9 a). Seasonally significant variation in Cu content of different plants at various sites along M-2 was observed (Table 4.9 a). Among seasons, the highest Cu contamination was recorded in the leaves of plants collected during summer season (19.4 mg/kg dry wt.) followed by that noted during autumn season (14.1 mg/kg dry wt.), spring season (11.5 mg/kg dry wt.) and winter season (7.48 mg/kg dry wt.). 4.1.14. Spatio-temporal variation in copper (Cu) content in the plant leaves growing along G.T. road (Lahore to Gujranwala) The statistical analysis (ANOVA) of data regarding the Cu content in leaves of plants collected from various sites adjacent to the G.T. road depicted highly significant differences among plants, seasons and sites. Similarly, interactions between plants × sites, plants × seasons as well as sites × seasons also remained significant. Nevertheless, interaction among plants × sites × seasons appeared non-significant (Table 4.10).

Various plant species growing at selected sites along G.T. road showed significant differences in mean Cu content of their leaves (Table 4.10 a). However, Nerium oleander accumulated the highest amount of Cu (30.3 mg/kg dry wt.) while minimum Cu content (14.14 mg/kg dry wt.) was noted in the leaves of Cynodon dactylon. The order of Cu contamination in the leaves of different plants remained as follows: Nerium oleander>Calotropis procera>Parthenium hysterophorus>Cenchrus ciliaris>Cynodon dactylon. The significant differences among various sites along the G.T. road for mean Cu content in the leaves of plants were documented. However, the maximum Cu contamination (32.6 mg/kg dry wt.) was noted in plants growing at Muridke site while minimum (21.3 mg/kg dry wt.) was documented in plants growing at Sadhoke site as compared to control. The order of Cu contamination in plants at different sites was as follows: Muridke>Gujranwala>Eminabad More>Ferozewala>Sadhoke (Table 4.10 a). The mean Cu content in plants differed significantly during different seasons (Table 4.10 a). The highest amount of Cu (29.5 mg/kg dry wt.) was recorded in the leaves of plants sampled during the summer season and the least (16.3 mg/kg dry wt.) was noted in those collected during the winter.

Table 4.9. Analysis of variance for copper (Cu) content in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 7345.97 1836.49 189.73*** Sites 5 15389.70 3077.94 317.98*** Seasons 3 6724.01 2241.34 231.98*** Plants × Sites 20 1422.96 71.15 7.35 *** Plants × Seasons 12 147.62 12.30 1.27 ns Sites ×Seasons 15 1316.62 87.77 9.07*** Plants × Sites ×Seasons 60 202.01 3.37 0.35 ns Error 240 2323.11 9.68 Total 359 34872.00 *** = Significant at 0.001 level; ns = Non-significant

Table 4.9 a. Mean Cu content (mg/kg dry wt.) in plant leaves along M-2 (LSD = 0.05)

Mean Cu content Nerium oleander L. 19.6 ± 10.5 a Calotropis procera A. 15.8 ± 9.98 b Plants Parthenium hysterophorus L. 13.7 ± 9.28 c Cenchrus ciliaris L. 9.90 ± 7.38 d Cynodon dactylon L. 6.63 ± 6.03 e Kala Shah Kaku 21.0 ± 9.41 a Sheikhupura 19.4 ± 8.71 b

Pindi Bhattian Sites 16.8 ± 8.31 c Khanqah Dogran 10.9 ± 7.42 d Sukheke 7.92 ± 6.32 e Control 2.66 ± 1.29 f Summer 19.4 ± 11.1 a Autumn 14.1 ± 9.28 b Seasons Spring 11.5 ± 8.31 c Winter 7.48 ± 6.17 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

Table 4.10. Analysis of variance for copper (Cu) content in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 11905.57 2976.39 254.11*** Sites 5 29825.97 5965.19 509.28*** Seasons 3 8067.15 2689.05 229.58*** Plants × Sites 20 2207.67 110.38 9.42*** Plants × Seasons 12 426.68 35.56 3.03*** Sites × Seasons 15 1449.39 96.63 8.25*** Plants × Sites × Seasons 60 275.16 4.58 0.39ns Error 240 2811.10 11.71 Total 359 56968.70 *** = Significant at 0.001 level; ns = Non-significant

Table 4.10 a. Mean Cu content (mg/kg dry wt.) in plant leaves along G.T. road (LSD = 0.05)

Mean Cu content Nerium oleander L. 30.3 ± 14.5 a Calotropis procera A. 26.4 ± 12.6 b Plants Parthenium hysterophorus L. 23.2 ± 10.8 c Cenchrus ciliaris L. 18.5 ± 9.49 d Cynodon dactylon L. 14.1 ± 7.56 e Muridke 32.6 ± 10.4 a Gujranwala 29.1 ± 9.96 b

Eminabad More Sites 25.0 ± 9.17 c Ferozewala 23.3 ± 9.39 d Sadhoke 21.3 ± 8.89 e Control 3.97 ± 1.08 f Summer 29.5 ± 14.7 a Autumn 23.4 ± 12.0 b Seasons Spring 21.0 ± 10.78 c Winter 16.3 ± 8.52 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

4.1.15. Seasonal variation in copper (Cu) content in plant leaves growing along M-2 The CCA biplot demonstrating content of Cu in different plant species growing at various locations adjacent to the M-2 in different seasons is illustrated in Fig. 4.9. For autumn season, the CCA biplot showed that Cu concentration in Calotropis procera was associated with Khanqah Dogran and Kala Shah Kaku sites whereas Nerium oleander showed association with Khanqah Dogran site for its Cu content (Fig. 4.9 a). Similarly, the Cu concentration in Parthenium hysterophorus exhibited association with Sheikhupura site whereas Cenchrus ciliaris was associated with Control for its Cu content. However, Cynodon dactylon showed week association with Sukheke for its Cu content. The CCA biplot for Cu quantity in various plants during spring showed that Cu content in Calotropis procera had associated with Kala Shah Kaku and Sheikhupura sites whereas Nerium oleander and Parthenium hysterophorus were associated with Khanqah Dogran and Sheikhupura sites respectively for their Cu contents. Similarly, Cenchrus ciliaris showed association with Control for its Cu content (Fig. 4.9 b). For summer season, the CCA biplot showed that Parthenium hysterophorus was associated with Pindi Bhattian site for its Cu content, while Calotropis procera exhibited association with Pindi Bhattian as well as with Sheikhupura site for its Cu content. Similarly, Nerium oleander was observed to be associated with Khanqah Dogran for its Cu concentration (Fig. 4.9 c). For winter season, CCA biplot revealed that Cu content in Cynodon dactylon showed association with Sukheke site, while Calotropis procera was associated with Kala Shah Kaku and Sheikhupura sites for its Cu concentration (Fig. 4.9 d). 4.1.16. Seasonal variation in copper (Cu) content in plant leaves growing along G.T. road The CCA biplot showing the content of Cu in plants growing at different locations adjacent to the G.T. road has been presented in Fig. 4.10. During autumn season, Calotropis procera had strong association with Eminabad More as well as Ferozewala site for its Cu content. Similarly, Nerium oleander exhibited association with Muridke as well as Gujranwala site for Cu concentration in its leaves whereas Cynodon dactylon was associated with Control for its Cu content. However, Parthenium hysterophorus appeared to be weakly associated with Sadhoke site for Cu concentration in its leaves whereas Cenchrus ciliaris did not seem to be related with one specific location for its Cu content (Fig 4.10 a).

For spring, the biplot showed that content of Cu in Parthenium hysterophorus and Nerium oleander had association with Eminabad More site, whereas Cu content in Calotropis procera showed weak association with Gujranwala site (Fig. 4.10 b). However, Cenchrus ciliaris did not exhibit association with any specific location for its Cu quantity. During summer, the biplot for Cu quantity in plants at different locations showed that Parthenium hysterophorus and Calotropis procera had association with Eminabad More and Sadhoke sites respectively for their Cu content. However, Cu concentration in Nerium oleander showed association with Muridke site to some extent (Fig. 4.10 c). For winter season, the CCA biplot showed that Parthenium hysterophorus and Calotropis procera had high Cu content at Gujranwala site whereas Nerium oleander showed association with Muridke for its high Cu quantity (Fig. 4.10 d).

(a) (b)

(c) (d) Fig. 4.9. The CCA biplot illustrating the Cu content in plants relating to different sites along M-2 during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

(a) (b)

1.0 SA

FE 4

MU CO

EM 3

-1.0 -1.0 1.5 (c) (d) Fig. 4.10. The CCA biplot illustrating the Cu content in plants relating to different sites along G.T. road during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

4.1.17. Spatio-temporal variation in copper (Cu) content in soil at different sites along M- 2 (Pindi Bhattian to Kala Shah Kaku) According to the ANOVA for Cu quantity in soil at several different locations adjacent to the M-2, significant differences were observed among sites as well as seasons. However, interaction between sites and seasons remained significant at p<0.05 (Table 4.11). All the sites differed significantly from control in mean Cu content in their soil (Table 4.11 a). Among the sites, maximum Cu content was recorded in the soil of Kala Shah Kaku Interchange (38.0 mg/kg dry wt.) and Sheikhupura (35.2 mg/kg dry wt.) which were non- significantly different from each other. The Cu content in soil collected from Khanqah Dogran and Sukheke sites did not differ significantly, moreover it was less than that observed in soil of Pindi Bhattian. The Cu content in soil at different sites along M-2 varied significantly during different seasons. The soil collected during summer season contained the maximum Cu content (35.5 mg/kg dry wt.) followed by autumn (27.1 mg/kg dry wt.)>spring (24.2 mg/kg dry wt.)>winter (18.7 mg/kg dry wt.) seasons (Table 4.11 a). 4.1.18. Spatio-temporal variation in copper (Cu) content in soil at different sites along G.T. road (Lahore to Gujranwala) The statistical analysis of data concerning the amount of Cu in soil taken from different sites adjacent to the G.T. road is illustrated in Table 4.12. It depicted highly significant differences among sites and seasons. Furthermore, interaction between sites and seasons remained significant at p<0.01. Mean Cu content in soil at different sites along the roadside differed significantly from control. However, the maximum Cu content (50.8 mg/kg dry wt.) was noted in soil at Muridke followed by that observed in soil at Gujranwala and Eminabad More sites which were not significantly different from each other. The soil Cu content at Ferozewala and Sadhoke sites also did not vary significantly (Table 4.12 a). The Cu content in soil was significantly different during different seasons. The amount of Cu was highest (44.2 mg/kg dry wt.) in soil collected during summer season while the soil collected in winter season contained the least (26.4 mg/kg dry wt.). The overall order of Cu content in soil during different season existed as follows: winter

Table 4.11. Analysis of variance for copper (Cu) content in soil at different sites along M- 2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Sites 5 7166.12 1433.22 97.53*** Seasons 3 2670.01 890.00 60.57*** Sites × Seasons 15 465.67 31.04 2.11* Error 48 705.34 14.69 Total 71 11007.14 *** and * = Significant at 0.001 and 0.05 levels, respectively

Table 4.11 a. Mean Cu content (mg/kg dry wt.) in soil along M-2 (LSD = 0.05)

Mean Cu content

Kala Shah Kaku 38.0 ± 3.63 a Sheikhupura 35.2 ± 3.91 a Sites Pindi Bhattian 30.2 ± 4.55 b Khanqah Dogran 24.7 ± 3.83 c Sukheke 22.4 ± 3.79 c Control 7.67 ± 2.12 d Summer 35.5 ± 3.96 a

Autumn 27.1 ± 3.95 b Seasons Spring 24.3 ± 3.75 c Winter 18.7 ± 2.88 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

Table 4.12. Analysis of variance for copper (Cu) content in soil at different sites along G.T. road (Lahore to Gujranwala) during different season

S. O. V. d. f. S. S. M. S. F-value Sites 5 14474.21 2894.84 210.43*** Seasons 3 3079.34 1026.44 74.61*** Sites x Seasons 15 517.91 34.53 2.51** Error 48 660.33 13.76 Total 71 18731.79 *** and ** = Significant at 0.001 and 0.01 levels, respectively

Table 4.12 a. Mean Cu content (mg/kg dry wt.) in soil along G.T. road (LSD = 0.05)

Mean Cu content Muridke 50.8 ± 3.52 a

Gujranwala 45.9 ± 4.18 b

Eminabad More 44.0 ± 3.97 b Sites Sadhoke 32.8 ± 3.70 c Ferozewala 30.4 ± 4.35 c Control 7.93 ± 1.19 d Summer 44.16 ± 3.65 a

Autumn 37.86 ± 3.35 b Seasons Spring 32.74 ± 3.42 c Winter 26.39 ± 3.52 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

dry wt.)

1 1 -

Cu content (mg content Cu (mg kg 10

0 Summer Autumn Spring Winter Seasons

Control Pindi Bhattian Sukheke Khanqah Dogran Sheikhupura Kala Shah Kaku

Fig. 4.11. Seasonal variation in Cu content in soil at different sites along M-2. Bars represent “mean of three values ± standard error”.

20 Cu content (mg/kg content Cu (mg/kg dry wt.) 10

0 Summer Autumn Spring Winter Seasons

Control Ferozewala Muridke Sadhoke Eminabad More Gujranwala

Fig. 4.12. Seasonal variation in Cu content in soil at different sites along G.T. road. Bars represent “mean of three values ± standard error”.

4.1.19. Spatio-temporal variation in nickel (Ni) content in the plant leaves growing along M-2 (Pindi Bhattian to Kala Shah Kaku) Analysis of variance (ANOVA) for data regarding the Ni content in the leaves of plants growing at various sites adjacent to the M-2 during four different seasons is illustrated in Table 4.13. It indicated highly significant differences among plants, sites and seasons. The interactions like plants × seasons, plants × sites as well as sites × seasons remained statistically significant at p<0.05, p<0.01 and p<0.001, respectively. However, interaction among plants, sites and seasons was non-significant. All the plants collected from selected sites along M-2 exhibited significantly different Ni concentration in their leaves. Among plants, the highest Ni content (15.1 mg/kg dry wt.) was observed in the leaves of Calotropis procera while Cynodon dactylon had minimum Ni accumulation (9.93 mg/kg dry wt.) (Table 4.13 a). The comparison among sites for Ni concentration in plants demonstrated that Ni content in the leaves of plants at Pindi Bhattian and Khanqah Dogran sites differed non- significantly while it was significantly different among all other sites. Among sites, the highest Ni content (20.0 mg/kg dry wt.) was documented in the leaves of plants at Kala Shah Kaku site while the minimum (11.3 mg/kg dry wt.) was detected in plants at Sukheke site as compared to control (Table 4.13 a). Seasonally significant variation was observed in Ni content of different plant species growing at various sites adjacent to the M-2 (Table 4.13 a). The highest Ni content was recorded in the plant leaves collected during summer followed by that noted during the autumn season. However, the least Ni concentration in plants was observed during winter. 4.1.20. Spatio-temporal variation in nickel (Ni) content in plant leaves growing along G.T. road (Lahore to Gujranwala) Analysis of variance of data concerning the Ni concentration in the plant leaves collected from different sites along G.T. road during different seasons has been presented in Table 4.14. It depicted highly significant differences among plants, sites and seasons. Likewise, interactions between plants × sites and sites × seasons remained statistically significant at p < 0.001 and p < 0.01 respectively. Nevertheless, the interactions between plants × seasons as well as plants × sites × seasons were statistically non-significant.

A comparison among all the plants for mean Ni content in their leaves revealed significant differences except between Parthenium hysterophorus and Cenchrus ciliaris. Among plants, maximum Ni contamination (22.2 mg/kg dry wt.) was documented in the leaves of Calotropis procera which was followed by that (20.3 mg/kg dry wt.) in Nerium oleander. However, the leaves of Cynodon dactylon accumulated minimum Ni content (16.63 mg/kg dry wt.) (Table 4.14 a). A comparison among various sites adjacent to the G.T. road for Ni content in the plants growing at these sites illustrated significantly different Ni content in plants at different sites except the in the leaves of plants at Gujranwala and Eminabad More sites which differed non- significantly. The leaves of all the plants accumulated the maximum Ni content (25.6 mg/kg dry wt.) at Muridke site while the minimum amount of Ni (19.4 mg/kg dry wt.) was documented in plants at Sadhoke site as compared to control (Table 4.14 a). The Ni content in plants along G.T. road differed significantly during different seasons (Table 4.14 a). The leaves of plants collected during summer season had the maximum Ni quantity (21.4 mg/kg dry wt.) while the least Ni contamination (16.8 mg/kg dry wt.) in plants was observed in winter.

Table 4.13. Analysis of variance for nickel (Ni) content in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 1152.86 288.21 37.76*** Sites 5 12895.13 2579.02 337.93*** Seasons 3 2270.45 756.82 99.16*** Plants × Sites 20 256.06 12.80 1.68* Plants × Seasons 12 225.11 18.76 2.46** Sites × Seasons 15 489.61 32.64 4.28*** Plants × Sites × Seasons 60 211.87 3.53 0.46ns Error 240 1831.65 7.63 Total 359 19332.74 ***, ** and * = Significant at 0.001, 0.01 and 0.05 levels, respectively; ns = Non-significant

Table 4.13 a. Mean Ni content (mg/kg dry wt.) in plant leaves along M-2 (LSD = 0.05)

Mean Ni content Calotropis procera A. 15.1 ± 8.36 a Nerium oleander L. 14.0 ± 7.72 b Plants Parthenium hysterophorus L. 13.0 ± 6.98 c Cenchrus ciliaris L. 11.8 ± 6.32 d Cynodon dactylon L. 9.93 ± 6.16 e Kala Shah Kaku 20.0 ± 5.37 a Sheikhupura 16.6 ± 5.08 b

Pindi Bhattian 14.4 ± 4.19 c Sites Khanqah Dogran 13.4 ± 4.33 c Sukheke 11.3 ± 4.23 d Control 0.80 ± 0.48 e Summer 16.5 ± 8.71 a Autumn 13.1 ± 6.51 b Seasons Spring 11.9 ± 6.16 c Winter 9.52 ± 5.94 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

Table 4.14. Analysis of variance for nickel (Ni) content in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V d. f. S. S. M. S. F-value Plants 4 1353.23 338.31 37.09*** Sites 5 25470.27 5094.05 558.53*** Seasons 3 974.34 324.78 35.61*** Plants × Sites 20 492.29 24.61 2.70*** Plants × Seasons 12 36.32 3.03 0.33ns Sites × Seasons 15 316.52 21.10 2.31** Plants × Sites × Seasons 60 225.44 3.76 0.41ns Error 240 2188.91 9.12 Total 359 31057.32 *** and ** = Significant at 0.001 and 0.01 levels, respectively; ns = Non-significant

Table 4.14 a. Mean Ni content (mg/kg dry wt.) in plant leaves along G.T. road (LSD = 0.05)

Mean Ni content Calotropis procera A. 22.2 ± 10.4 a Nerium oleander L. 20.3 ± 9.31 b Plants Parthenium hysterophorus L. 18.7 ± 8.80 c Cenchrus ciliaris L. 18.0 ± 8.56 c Cynodon dactylon L. 16.6 ± 8.48 d Muridke 25.6 ± 4.94 a Gujranwala 24.0 ± 3.71 b

Eminabad More Sites 23.2 ± 3.29 b Ferozewala 22.0 ± 3.89 c Sadhoke 19.4 ± 5.51 d Control 0.86 ± 0.49 e Summer 21.4 ± 10.1 a Autumn 19.7 ± 9.21 b Seasons Spring 18.8 ± 8.82 c Winter 16.8 ± 8.58 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

4.1.21. Seasonal variation in nickel (Ni) content in plant leaves growing along M-2 The CCA biplot for content of Ni in plants growing at several different locations adjacent to the M-2 during different seasons is presented in Fig 4.13. For autumn season, CCA biplot showed that Ni content in Nerium oleander had strong association with Khanqah Dogran site, whereas Cynodon dactylon showed association with Pindi Bhattian site for its Ni concentration (Fig. 4.13 a). For spring season, the CCA biplot showed the association of Calotropis procera with Sheikhupura for its Ni quantity, whereas Cenchrus ciliaris and Parthenium hysterophorus exhibited association with Khanqah Dogran for their Ni concentration. Likewise, Ni content in Cynodon dactylon was associated with Pindi Bhattian site (Fig. 4.13 b). The CCA biplot for Ni concentration in plants during summer season indicated that Nerium oleander was associated with Kala Shah Kaku site for its Ni concentration. Similarly, Calotropis procera and Parthenium hysterophorus exhibited association with Sheikhupura and Sukheke sites respectively, for their Ni concentration. Cenchrus ciliaris was also associated with Sukheke site for its Ni concentration (Fig. 4.13 c). During winter season, the CCA biplot for Ni concentration in plants indicated that Ni concentration in Nerium oleander showed association with Sheikhupura and Khanqah Dogran sites. Similarly, Cenchrus ciliaris was found to be associated with Sukheke site for its Ni concentration. However, Ni content in Calotropis procera and Parthenium hysterophorus exhibited association with Khanqah Dogran and Kala Shah Kaku sites respectively, to some extent (Fig. 4.13 d). 4.1.22. Seasonal variation in nickel (Ni) content in plant leaves growing along G.T. road The CCA biplot for Ni content in leaves of plants growing at various sites adjacent to the G.T. road during different seasons has been given in Fig. 4.14. During autumn season, the CCA biplot showed that Calotropis procera was closely associated with Muridke site for its Ni concentration, whereas Cynodon dactylon showed association with Ferozewala site for its Ni content. Likewise, the Ni concentration in Nerium oleander was observed to be associated with Sadhoke site (Fig. 4.14 a). For spring season, the CCA biplot revealed that the Ni content in Calotropis procera had association with Muridke site, whereas Cynodon dactylon showed association with Ferozewala site for its Ni content. Similarly, Parthenium hysterophorus exhibited association

with Control and Eminabad More sites for its Ni content (Fig. 4.14 b). The CCA biplot for summer season indicated that Ni content in Nerium oleander and Parthenium hysterophorus was associated with Sadhoke site. Similarly, Ni concentration in Calotropis procera exhibited association with Gujranwala as well as Muridke site. However, Cenchrus ciliaris appeared to be associated with Sadhoke to some extent (Fig. 4.14 c). The CCA biplot for Ni concentration in plants during winter showed the association of Calotropis procera with Sadhoke for its Ni content, whereas Ni content in Nerium oleander showed association with Sadhoke and Ferozewala sites. However, Cenchrus ciliaris and Parthenium hysterophorus were observed to be weakly related with Eminabad More and Ferozewala locations respectively, for their Ni concentration (Fig. 4.14 d).

(a) (b)

(c) (d) Fig. 4.13. The CCA biplot illustrating the Ni content in plants relating to different sites along M-2 during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

(a) (b)

(c) (d) Fig. 4.14. The CCA biplot illustrating the Ni content in plants relating to different sites along G.T. road during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

4.1.23. Spatio-temporal variation in nickel (Ni) content in soil at different sites along M- 2 (Pindi Bhattian to Kala Shah Kaku) The statistical analysis of data regarding the Ni content in soil at different sites adjacent to the M-2 is given in Table 4.15. It revealed highly significant differences among sites and seasons. However, interaction between sites and seasons remained significant at p<0.01. All the sites differed significantly from one another in mean Ni content in their soil. However, the highest Ni content (35.6 mg/kg dry wt.) was documented in soil gathered from Kala Shah Kaku while the soil collected from Sukheke site had the least Ni content (19.2 mg/kg dry wt.) as compared to control. The Ni content in soil at other sites existed in the following order: Sheikhupura>Pindi Bhattian>Khanqah Dogran (Table 4.15 a). The soil Ni content at different sites adjacent to the M-2 varied significantly during different seasons except spring and winter (Table 4.15 a). The soil collected during the summer season contained the maximum Ni content (30.1 mg/kg dry wt.) followed by autumn season (24.1 mg/kg dry wt.). 4.1.24. Spatio-temporal variation in nickel (Ni) content in soil at different sites along G.T. road (Lahore to Gujranwala) The analysis of variance (ANOVA) for data regarding the Ni content in soil taken from different sites adjacent to the G.T. road showed that sites, seasons as well as their interaction were highly significant (p<0.001) (Table 4.16). Mean soil Ni content at various sites along the roadside differed significantly from control. The Ni content in soil collected from Muridke site was maximum (41.3 mg/kg dry wt.) while it was minimum in soil collected from Sadhoke site (27.2 mg/kg dry wt.). The overall trend of Ni concentration in soil at different sites existed as follows: Muridke>Gujranwala>Eminabad More>Ferozewala>Sadhoke (Table 4.16 a). The Ni content in soil appeared significantly different during different seasons. The highest amount of Ni (36.6 mg/kg dry wt.) was documented in soil collected during summer season while the least (24.0 mg/kg dry wt.) was documented in winter (Table 4.16 a).

Table 4.15. Analysis of variance for nickel (Ni) content in soil at different sites along M- 2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Sites 5 7736.52 1547.30 203.77*** Seasons 3 995.66 331.88 43.71*** Sites x Seasons 15 364.23 24.28 3.20** Error 48 364.49 7.59 Total 71 9460.89

*** and ** = Significant at 0.001 and 0.01 levels, respectively

Table 4.15 a. Mean Ni content (mg/kg dry wt.) in soil along M-2 (LSD = 0.05)

Mean Ni content Kala Shah Kaku 35.6 ± 2.33 a

Sheikhupura 31.3 ± 3.15 b

Pindi Bhattian 29.0 ± 3.72 c Sites Khanqah Dogran 25.6 ± 2.76 d Sukheke 19.2 ± 2.64 e Control 3.85 ± 0.31 f Summer 30.1 ± 2.82 a

Autumn 24.1 ± 2.44 b Seasons Spring 22.0 ± 2.61 c Winter 20.2 ± 2.07 c Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

Table 4.16. Analysis of variance for nickel (Ni) content in soil at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Sites 5 10676.27 2135.25 366.93*** Seasons 3 1533.04 511.01 87.81*** Sites x Seasons 15 374.15 24.94 4.29*** Error 48 279.32 5.82 Total 71 12862.78 *** = Significant at 0.001 level

Table 4.16 a. Mean Ni content (mg/kg dry wt.) in soil along G.T. road (LSD = 0.05)

Mean Ni content Muridke 41.3 ± 3.27 a

Gujranwala 37.9 ± 2.69 b

Eminabad More 34.8 ± 1.97 c Sites Ferozewala 30.2 ± 2.02 d Sadhoke 27.2 ± 1.60 e Control 4.09 ± 0.43 f Summer 36.6 ± 1.80 a

Autumn 29.2 ± 1.71 b Seasons Spring 27.3 ± 2.62 c Winter 24.0 ± 1.86 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

dry wt.)dry

1 1 -

Ni content (mg Ni content kg (mg 10

0 Summer Autumn Spring Winter Seasons

Control Pindi Bhattian Sukheke Khanqah Dogran Sheikhupura Kala Shah Kaku

Fig. 4.15. Seasonal variation in Ni content in soil at different sites along M-2. Bars represent “mean of three values ± standard error”.

Ni content (mg/kg Ni content (mg/kg wt.)dry 10

0 Summer Autumn Spring Winter Seasons

Control Ferozewala Muridke Sadhoke Eminabad More Gujranwala

Fig. 4.16. Seasonal variation in Ni content in soil at different sites along G.T. road. Bars represent “mean of three values ± standard error”.

4.1.25. Spatio-temporal variation in zinc (Zn) content in the plant leaves growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The statistical analysis (ANOVA) of data regarding the Zn content in the leaves of plant species collected from different locations adjacent to the M-2 depicted significant differences among plants, seasons as well as sites (Table 4.17). Likewise, interactions between plants × sites and sites × seasons were also significant while interactions between plants × seasons as well as plants × sites × seasons remained non-significant. The comparison among all the plants for mean Zn content in their leaves demonstrated significant differences among them. However, the maximum Zn content (83.2 mg/kg dry wt.) was observed in Nerium oleander while Cynodon dactylon exhibited the least amount of Zn (53.9 mg/kg dry wt.) (Table 4.17 a). The order of Zn accumulation in plants existed as follows: Nerium oleander>Calotropis procera>Parthenium hysterophorus>Cenchrus ciliaris>Cynodon dactylon The comparison among various sites for Zn concentration in the leaves of plants growing at these sites illustrated significant differences among them (Table 4.17 a). However, the maximum Zn accumulation was recorded in the leaves of plants sampled from Kala Shah Kaku site followed by those in plants collected from Sheikhupura, Pindi Bhattian, Khanqah Dogran and Sukheke sites as compared to control. Significant seasonal variation in Zn content in the leaves of plants growing at different sites adjacent to M-2 was detected (Table 4.17 a). The leaves of plants accumulated the highest amount of Zn (79.6 mg/kg dry wt.) during summer season while the plants collected during winter season contained the least Zn content (59.8 mg/kg dry wt.). The amount of Zn in plants during different seasons remained in the following order: summer>autumn>spring>winter. 4.1.26. Spatio-temporal variation in zinc (Zn) content in the plant leaves growing along G.T. road (Lahore to Gujranwala) The analysis of variance (ANOVA) of data concerning the Zn content in the leaves of plants growing at different sites along the G.T. road during the four different seasons has been presented in Table 4.18. It indicated highly significant differences among plants, sites and seasons. Similarly, interactions between plants × sites and sites × seasons were significant p<0.01 and p<0.001 respectively, however the interactions between plants × seasons and among plants × sites × seasons was non-significant.

All the plants collected from various sites along G.T. road exhibited significant differences in the mean Zn content of their leaves (Table 4.18 a). The leaves of Nerium oleander accumulated the highest (104 mg/kg dry wt.) amount of Zn while the least (72.1 mg/kg dry wt.) amount of Zn was noted in the leaves of Cynodon dactylon. Various sites along the G.T. road differed significantly in mean Zn content in the leaves of plants growing at these sites (Table 4.18 a). The highest Zn concentration (114 mg/kg dry wt.) was documented in the leaves of plants growing at Muridke site and minimum (89.0 mg/kg dry wt.) was found in plants sampled from Ferozewala site as compared to control. Zinc content in plants at different sites remained in the following order: Muridke>Gujranwala>Eminabad More>Sadhoke>Ferozewala. The mean Zn content in the leaves of selected plants differed significantly during different seasons (Table 4.18 a). The highest amount of Zn (98.8 mg/kg dry wt.) was noted in the leaves of plants sampled during summer season and the least amount (75.0 mg/kg dry wt.) was recorded in those sampled in winter.

Table 4.17. Analysis of variance for zinc (Zn) content in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 36963.05 9240.76 862.83*** Sites 5 236500.48 47300.09 4416.52*** Seasons 3 19131.33 6377.11 595.44*** Plants × Sites 20 4094.16 204.71 19.11*** Plants × Seasons 12 178.10 14.84 1.38ns Sites × Seasons 15 1189.52 79.30 7.40*** Plants × Sites × Seasons 60 698.20 11.64 1.08ns Error 240 2570.35 10.71 Total 359 301325.21 *** = Significant at 0.001 level; ns = Non-significant Table 4.17 a. Mean Zn content (mg/kg dry wt.) in plant leaves along M-2 (LSD = 0.05)

Mean Zn content Nerium oleander L. 83.2 ± 29.1 a Calotropis procera A. 75.4 ± 28.5 b Plants Parthenium hysterophorus L. 69.4 ± 27.0 c Cenchrus ciliaris L. 62.6 ± 26.4 d Cynodon dactylon L. 53.9 ± 25.1 e Kala Shah Kaku 98.5 ± 14.2 a Sheikhupura 91.6 ± 13.1 b

Pindi Bhattian Sites 77.2 ± 13.6 c Khanqah Dogran 64.7 ± 15.4 d Sukheke 61.6 ± 16.1 e Control 19.8 ± 6.61 f Summer 79.6 ± 29.9 a Autumn 70.7 ± 29.3 b Seasons Spring 65.5 ± 27.6 c Winter 59.8 ± 25.6 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

Table 4.18. Analysis of variance for zinc (Zn) content in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 42169.04 10542.26 296.73*** Sites 5 312100.11 62420.02 1756.94*** Seasons 3 26453.24 8817.75 248.19*** Plants × Sites 20 1446.16 72.31 2.03** Plants × Seasons 12 173.68 14.47 0.41ns Sites × Seasons 15 2069.66 137.98 3.88*** Plants × Sites × Seasons 60 934.48 15.57 0.44ns Error 240 8526.66 35.53 Total 359 393873.05 *** and ** = Significant at 0.001 and 0.01 levels, respectively; ns = Non-significant

Table 4.18 a. Mean Zn content (mg/kg dry wt.) in plant leaves along G.T. road (LSD = 0.05)

Mean Zn content Nerium oleander L. 104 ± 33.4 a Calotropis procera A. 93.1 ± 31.4 b Plants Parthenium hysterophorus L. 87.9 ± 31.3 c Cenchrus ciliaris L. 80.7 ± 30.5 d Cynodon dactylon L. 72.1 ± 30.7 e Muridke 114 ± 17.4 a Gujranwala 107 ± 15.9 b

Eminabad More Sites 98.5 ± 14.4 c Sadhoke 92.8 ± 16.2 d Ferozewala 89.0 ± 15.9 e Control 24.4 ± 10.3 f Summer 98.8 ± 34.6 a Autumn 90.2 ± 32.9 b Seasons Spring 86.1 ± 31.4 c Winter 75.0 ± 29.3 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 72 for plants, n = 60 for sites and n = 90 for seasons. Means in a sub- column sharing same letter differ non-significantly.

4.1.27. Seasonal variation in zinc (Zn) content in plants leaves growing along M-2 The CCA biplot for content of Zn in different plant species growing at various locations adjacent to the M-2 during different seasons is presented in Fig. 4.17. For autumn season, the CCA biplot showed that Zn content in Calotropis procera had association with Sukheke and Khanqah Dogran sites whereas Cenchrus ciliaris was associated with Sheikhupura for its Zn content. However, Zn concentration in Nerium oleander and Parthenium hysterophorus appeared to be weakly associated with Kala Shah Kaku and Sheikhupura sites, respectively (Fig. 4.17 a). The CCA biplot for Zn quantity in plants during spring showed the strong association of Calotropis procera with Sukheke for its Zn concentration. Similarly, Zn content in Cenchrus ciliaris was associated with Sheikhupura site, whereas Parthenium hysterophorus exhibited association with Sheikhupura as well as Sukheke sites for its Zn content (Fig. 4.17 b). During summer season, CCA biplot indicated that Zn content in Calotropis procera was associated with Sukheke and Khanqah Dogran sites whereas Cenchrus ciliaris showed association with Sheikhupura site for its Zn concentration. Similarly, Cynodon dactylon appeared to be related with Pindi Bhattian for Zn concentration in its leaves (Fig. 4.17 c). The biplot for content of Zn in different plant species during winter showed that Parthenium hysterophorus had association with Sheikhupura site for its Zn content whereas Calotropis procera was found to be associated with Sheikhupura as well as Sukheke sites for its Zn concentration (Fig. 4.17 d). 4.1.28. Seasonal variation in zinc (Zn) content in plants leaves growing along G.T. road The canonical correspondence analysis (CCA) biplot for Zn content in plants growing along G.T. road during different seasons has been given in Fig. 4.18. For autumn season, the CCA biplot depicted that Zn concentration in Parthenium hysterophorus had association with Sadhoke site, while Calotropis procera was associated with Sadhoke as well as Eminabad More sites for its Zn content. Similarly, Nerium oleander and Cynodon dactylon appeared to be associated with Muridke for their Zn concentration (Fig. 4.18 a). The CCA biplot for Zn content in plants during spring showed that both Parthenium hysterophorus and Nerium oleander had association with Gujranwala for their Zn concentration (Fig. 4.18 b). During summer, CCA biplot illustrated that Zn content in Calotropis procera was associated with Sadhoke while Cenchrus ciliaris, Cynodon dactylon

as well as Parthenium hysterophorus showed association with Control for their Zn concentration (Fig. 4.18 c). The CCA biplot for Zn content in plants during for winter season revealed that Zn concentration in Calotropis procera had strong association with Gujranwala site whereas Cynodon dactylon exhibited association with Eminabad More as well as Ferozewala sites for its Zn concentration. Similarly, Parthenium hysterophorus and Nerium oleander appeared to be associated with Eminabad More and Sadhoke sites respectively, for their Zn concentration. However, the level of Zn in Cynodon dactylon was weakly associated with Muridke site (Fig. 4.18 d).

(a) (b)

(c) (d) Fig. 4.17. The CCA biplot illustrating the Zn content in plants relating to different sites along M-2 during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

(a) (b)

(c) (d) Fig. 4.18. The CCA biplot illustrating the Zn content in plants relating to different sites along G.T. road during different seasons. Where, a: Autumn; b: Spring; c: Summer; d: Winter, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

4.1.29. Spatio-temporal variation in zinc (Zn) content in soil at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) The analysis of variance for data regarding the amount of Zn in soil at several different sites adjacent to the M-2 revealed highly significant differences among seasons as well as sites. However, interaction between sites and seasons appeared significant at p<0.05 (Table 4.19). Significantly different Zn concentration in soil taken from different sites was noted (Table 4.19 a). Among sites the maximum Zn quantity (151 mg/kg dry wt.) was documented in soil taken from Kala Shah Kaku while Zn content was minimum (92.2 mg/kg dry wt.) in soil from Sukheke site in comparison to control. Furthermore, the amount of Zn in soil was 129, 118 and 102 mg/kg dry wt. in soil sampled from Sheikhupura, Pindi Bhattian and Khanqah Dogran, respectively. The Zn content in soil differed significantly during different seasons (Table 4.19 a). The soil collected during the summer season had maximum Zn quantity (121 mg/kg dry wt.). The Zn content in soil during different seasons existed in the following order: winterEminabad More>Ferozewala>Sadhoke sites (Table 4.20 a). Seasonally significant variation was noted in the Zn content in soil collected from sampling sites (Table. 4.20 a). The soil collected during the summer season contained the highest amount of Zn (151.73 mg/kg dry wt.) in comparison to other seasons. The overall trend of soil Zn content during different seasons remained as follows: winter

Table 4.19. Analysis of variance for zinc (Zn) content in soil at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Sites 5 80447.15 16089.43 440.79 *** Seasons 3 7625.58 2541.86 69.64*** Sites × Seasons 15 1251.97 83.46 2.29* Error 48 1752.08 36.50 Total 71 91076.78 *** and * = Significant at 0.001 and 0.05 levels, respectively

Table 4.19 a. Mean Zn content (mg/kg dry wt.) in soil along M-2 (LSD = 0.05)

Mean Zn content Kala Shah Kaku 151 ± 6.64 a Sheikhupura 129 ± 5.76 b Pindi Bhattian 118 ± 5.30 c Sites Khanqah Dogran 102 ± 5.96 d Sukheke 92.2 ± 5.40 e Control 44.8 ± 6.60 f Summer 121 ± 6.58 a

Autumn 109 ± 5.92 b Seasons Spring 102 ± 5.81 c Winter 92.6 ± 5.45 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

Table 4.20. Analysis of variance for zinc (Zn) content in soil at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Sites 5 127740.43 25548.08 594.07 *** Seasons 3 8202.34 2734.11 63.58 *** Sites × Seasons 15 1346.45 89.76 2.09* Error 48 2064.25 43.00 Total 71 139353.47 *** and * = Significant at 0.001 and 0.05 levels, respectively

Table 4.20 a. Mean Zn content (mg/kg dry wt.) in soil along G.T. road (LSD = 0.05)

Mean Zn content Muridke 176 ± 6.08 a Gujranwala 164 ± 6.14 b Eminabad More 157 ± 6.98 c Sites Ferozewala 144 ± 6.54 d Sadhoke 124 ± 7.00 e Control 49.9 ± 6.76 f Summer 152 ± 6.71 a

Autumn 138 ± 6.05 b Seasons Spring 131 ± 7.14 c Winter 123 ± 6.24 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 12 for sites, n = 18 for seasons. Means in a sub-column sharing same letter differ non-significantly.

200 180 160

140

dry wt.) 1 1 - 120 100 80 60 40 Zn Zn content(mg kg 20 0 Summer Autumn Spring Winter Seasons

Control Pindi Bhattian Sukheke Khanqah Dogran Sheikhupura Kala Shah Kaku

Fig. 4.19. Seasonal variation in Zn content in soil at different sites along M-2. Bars represent “mean of three values ± standard error”.

220 200 180 160 140 120 100 80 60

40 Zn Zn content(mg/kg dry wt.) 20 0 Summer Autumn Spring Winter Seasons

Control Ferozewala Muridke Sadhoke Eminabad More Gujranwala

Fig. 4.20. Seasonal variation in Zn content in soil at different sites along G.T. road. Bars represent “mean of three values ± standard error”.

4.1.31. Metal contents in fuel, used motor oil and soot The contents of all the metals under study were high in petrol and diesel samples collected from different fuel stations along the roads (Table 4.21). The order of metal contents was as follows: Cd

Table 4.21. Metal contents in fuel, used motor oil and soot (Mean ± S.E)

Metals

Sources Pb Cd Cu Ni Zn

Fuel Petrol 6.89 ± 0.08 0.98 ± 0.03 13.9 ± 0.09 8.13 ± 0.08 25.1 ± 0.26 (mg/L) Diesel 5.38 ± 0.21 0.88 ± 0.07 12.4 ± 0.12 7.84 ± 0.04 22.9 ± 0.17

Used Truck 9.43 ± 0.13 2.16 ± 0.09 19.1 ± 0.10 11.1 ± 0.09 29.5 ± 0.16 Motor Oil Bus 6.16 ± 0.08 1.93 ± 0.05 12.7 ± 0.06 8.34 ± 0.08 27.9 ± 0.19 (mg/L) Car 2.11 ± 0.13 1.05 ± 0.10 7.36 ± 0.8 4.10 ± 0.06 14.2 ± 0.09 Truck 11.9 ± 0.25 3.57 ± 0.21 25.4 ± 0.16 15.4 ± 0.15 41.5 ± 0.23 Soot (mg/kg) Bus 7.68 ± 0.15 2.24 ± 0.09 16.7 ± 0.13 12.7 ± 0.11 34.9 ± 0.18 Car 3.35 ± 0.10 1.11 ± 0.07 10.4 ± 0.08 5.62 ± 0.07 19.9 ± 0.13 For calculating means and SE n = 3

Table 4.22. Traffic density (No. of vehicles/day) at different sites along M-2 and G.T. road

Sites Autumn Winter Spring Summer Pindi Bhattian 8335 7582 8123 8576 Sukheke 5656 4744 5211 5927 M-2 Khanqah Dogran 6121 5013 5686 6732 Sheikhupura 9035 8207 8776 9421 Kala Shah Kaku 10224 9215 9894 10653 Sadhoke 23751 23001 23524 24032 Muridke 25737 25104 25451 26125 G.T. road Ferozewala 24306 23255 23962 24431 Eminabad More 25008 24136 24768 25244 Gujranwala 25624 25063 25232 26017

Table 4.23 a. Pearson’s correlation coefficient between metal contents in soil and traffic density during different seasons along the roads

M-2 G.T. road Autumn Winter Spring Summer Autumn Winter Spring Summer Pb 0.951* 0.869ns 0.905* 0.943* 0.956* 0.960** 0.983** 0.877ns

Cd 0.962** 0.963** 0.955* 0.985** 0.907* 0.739ns 0.800ns 0.998***

Cu 0.993*** 0.967** 0.980** 0.967** 0.959** 0.984** 0.925* 0.991**

Ni 0.924* 0.899* 0.930* 0.976** 0.824ns 0.920* 0.926* 0.948*

Zn 0.963** 0.983** 0.990** 0.938* 0.877ns 0.773ns 0.862ns 0.877ns ***, ** and * = Significant at 0.001, 0.01 and 0.05, respectively; ns = Non-significant

Table 4.23 b. Pearson’s correlation coefficient between metal content in soil and traffic density at various sites along the roads M-2 G.T. road Autumn Winter Spring Summer Autumn Winter Spring Summer Pb ** ** * ns ns ns ns Calotropis procera 0.982 0.960 0.964 0.911* 0.775 0.707 0.602 0.817 Nerium oleander 0.984** 0.958* 0.979** 0.959** 0.869ns 0.760ns 0.812ns 0.858* Cynodon dactylon 0.977** 0.840ns 0.953* 0.969* 0.916* 0.823ns 0.928* 0.880* Parthenium hysterophorus 0.989** 0.934* 1.000*** 0.970** 0.906* 0.876ns 0.975** 0.768ns Cenchrus ciliaris 0.990** 0.898* 0.971** 0.974** 0.854ns 0.954* 0.929* 0.841ns Cd Calotropis procera 0.877ns 0.883* 0.784ns 0.989** 0.898* 0.958* 0.840ns 0.942* Nerium oleander 0.940* 0.992*** 0.924* 0.949* 0.923* 0.839ns 0.876ns 0.904* ** ** ** * ** *** ns Cenchrus ciliaris 0.967 0.959 0.980 0.992*** 0.947 0.976 0.994 0.808 Parthenium hysterophorus 0.891* 0.976** 0.883* 0.966** 0.939* 0.902* 0.897* 0.896* Cynodon dactylon 0.870ns 0.967** 0.903* 0.944* 0.950* 0.837ns 0.973** 0.892* Cu Nerium oleander 0.970** 0.956* 0.983** 0.985** 0.960** 0.709ns 0.958* 0.923* Calotropis procera 0.997*** 0.972** 0.982** 0.981** 0.984** 0.947* 0.800ns 0.954* ** ** ** ** ** ** ** Cynodon dactylon 0.982 0.858ns 0.978 0.981 0.978 0.961 0.981 0.974 Parthenium hysterophorus 0.971** 0.977** 0.952* 0.985** 0.871** 0.949* 0.863ns 0.937* Cenchrus ciliaris 0.984** 0.997*** 0.980** 0.973** 0.920* 0.864ns 0.890* 0.856ns Ni Calotropis procera 0.928* 0.869ns 0.911* 0.958* 0.885* 0.645ns 0.689ns 0.889* Nerium oleander 0.910* 0.921* 0.833ns 0.939* 0.936* 0.858ns 0.893* 0.799ns ** * ** ns * ns ns Cynodon dactylon 0.982 0.912 0.962** 0.968 0.846 0.952 0.838 0.839 Parthenium hysterophorus 0.971** 0.884* 0.817ns 0.876ns 0.960** 0.705ns 0.979** 0.923* * ns * *** ns * * Cenchrus ciliaris 0.967** 0.891 0.836 0.884 0.999 0.764 0.956 0.922 Zn Nerium oleander 0.990** 0.981* 0.999*** 0.979** 0.814ns 0.917* 0.881* 0.855ns Calotropis procera 0.953* 0.924* 0.918* 0.950* 0.871ns 0.942* 0.866ns 0.933* Cynodon dactylon 0.989** 0.981** 0.997*** 0.988** 0.899* 0.909* 0.920* 0.933* Parthenium hysterophorus 0.929* 0.959** 0.943* 0.954* 0.831ns 0.983** 0.907* 0.914* Cenchrus ciliaris 0.962** 0.971** 0.929* 0.981** 0.905* 0.954* 0.891* 0.907*

M-2 G.T. road

PB SU KD SH KSK FE MU SA EM GU

Pb 0.963* 0.994** 0.966* 0.889 ns 0.893 ns 0.782 ns 0.972* 0.980* 0.938 ns 0.989**

Cd 0.918ns 0.998** 0.998** 0.935 ns 0.933 ns 0.920 ns 0.920 ns 0.881 ns 0.791 ns 0.850 ns Cu 0.982* 0.976* 0.985* 0.918 ns 0.945 ns 0.946 ns 0.997** 0.999*** 0.995** 0.999*** Ni 0.954* 0.938 ns 0.952* 0.879 ns 0.852 ns 0.915 ns 0.831 ns 0.970* 0.974* 0.916 ns Zn 0.909 ns 0.970* 0.991** 0.979* 0.948 ns 0.979* 0.953* 0.866 ns 0.932 ns 0.986* ***, ** and * = Significant at 0.001, 0.01 and 0.05, respectively; ns = Non-significant Table 4.23 c. Pearson’s correlation coefficient between metal contents in plants and traffic density during different seasons ***, ** and * = Significant at 0.001, 0.01 and 0.05 respectively; ns = Non-significant Table 4.23 d. Pearson’s correlation coefficient between metal contents in plants and traffic density at various sites along roads M-2 G.T. road PB SU KD SH KSK FE MU SA EM GU Pb Calotropis procera 0.973* 0.935 ns 0.943 ns 0.995** 0.966* 0.829 ns 0.950* 0.887 ns 0.879 ns 0.996** Nerium oleander 0.922 ns 0.989** 0.928 ns 0.979* 0.986** 0.933 ns 0.984* 0.929 ns 0.978* 0.995** Cynodon dactylon 0.879 ns 0.928 ns 0.972* 0.998** 0.937 ns 0.855 ns 0.952* 0.956* 0.940 ns 0.949 Parthenium hysterophorus 0.958* 0.941 ns 0.949 ns 0.962* 0.899 ns 0.866 ns 0.967* 0.846 ns 0.937 ns 0.977* Cenchrus ciliaris 0.921 ns 0.990** 0.981* 0.964* 0.921 ns 0.942 ns 0.985* 0.923 ns 0.982* 0.997** Cd Calotropis procera 0.737 ns 0.993** 0.889 ns 0.884 ns 0.969* 0.874 ns 0.998** 0.822 ns 0.818 ns 0.982* Nerium oleander 0.965* 0.943 ns 0.897 ns 0.912 ns 0.857 ns 0.889 ns 0.941 ns 0.966* 0.842 ns 0.938 ns Cenchrus ciliaris 0.988* 0.973* 0.886 ns 0.987* 0.877 ns 0.980* 0.976* 0.951* 0.992** 0.799 ns Parthenium hysterophorus 0.995** 0.911 ns 0.924 ns 0.918 ns 0.883 ns 0.924 ns 0.975* 0.956* 0.855 ns 0.936 Cynodon dactylon 0.993** 0.915 ns 0.960* 0.958* 0.898 ns 0.887 ns 0.993** 0.916 ns 0.882 ns 0.954* Cu

Nerium oleander 0.981* 0.967* 0.997** 0.988* 0.993** 0.894 ns 0.975* 0.959* 0.969* 0.957* Calotropis procera 0.942 ns 0.976* 0.982* 0.977* 0.999*** 0.936 ns 0.987* 0.960* 0.950* 0.985* Cynodon dactylon 0.975* 0.836 ns 0.974* 0.982* 0.978* 0.911 ns 0.988* 0.860 ns 0.886 ns 0.955* Parthenium hysterophorus 0.962* 0.880 ns 0.970* 0.996** 0.979* 0.949 ns 0.989* 0.993** 0.971* 0.925 Cenchrus ciliaris 0.969* 0.882 ns 0.985* 0.996** 0.988* 0.885 ns 0.997** 0.928 ns 0.945 ns 0.993** Ni Calotropis procera 0.816 ns 0.931 ns 0.946 ns 0.905 ns 0.754 ns 0.979* 0.895 ns 0.985* 0.912 ns 0.992** Nerium oleander 0.882 ns 0.952* 0.996** 0.832 ns 0.774 ns 0.997** 0.837 ns 0.953* 0.971* 0.955* Cynodon dactylon 0.970* 0.971* 0.980* 0.999*** 0.946 ns 0.977* 0.931 ns 0.996** 0.995** 0.948 ns Parthenium hysterophorus 0.938 ns 0.993** 0.985* 0.956* 0.770 ns 0.920 ns 0.992** 0.979* 0.933 ns 0.950* Cenchrus ciliaris 0.976* 0.976* 0.919 ns 0.995** 0.971* 0.953* 0.946 0.951* 0.911 ns 0.979* Zn Nerium oleander 0.997** 0.936 ns 0.981* 0.968* 0.952* 0.958* 0.967* 0.976* 0.918 ns 0.947 ns Calotropis procera 0.965* 0.994** 0.978* 0.987* 0.978* 0.948 ns 0.980* 0.994** 0.986* 0.952* Cynodon dactylon 0.916 ns 0.990** 0.867 ns 0.991** 0.980* 0.943 ns 0.993** 0.974* 0.966* 0.936 ns Parthenium hysterophorus 0.895 ns 0.959* 0.991** 0.989* 0.992** 0.971* 0.992** 0.978* 0.985* 0.881 ns Cenchrus ciliaris 0.852ns 0.929 ns 0.972* 0.993** 0.990** 0.978* 0.991** 0.988* 0.969* 0.982* ***, ** and * = Significant at 0.001, 0.01 and 0.05 respectively; ns = Non-significant

Table 4.23 e. Pearson’s correlation coefficient between metal contents in plants and soil along the roads

M-2 G.T. road Autumn Winter Spring Summer Autumn Winter Spring Summer Pb Calotropis procera 0.992*** 0.945** 0.925* 0.995*** 0.894 ns 0.817 ns 0.700ns 0.993*** Nerium oleander 0.968** 0.903* 0.889* 0.980** 0.931* 0.831 ns 0.875 ns 0.992*** Cynodon dactylon 0.947* 0.747ns 0.788ns 0.994*** 0.938* 0.927* 0.850 ns 0.972** Parthenium hysterophorus 0.894* 0.832ns 0.893* 0.995*** 0.957* 0.939* 0.967** 0.974** Cenchrus ciliaris 0.937* 0.807ns 0.827ns 0.993*** 0.941* 0.985** 0.933* 0.997*** Cd Calotropis procera 0.806ns 0.956* 0.745ns 0.959** 0.707 ns 0.832 ns 0.991*** 0.863ns Nerium oleander 0.875ns 0.981** 0.782ns 0.965** 0.704 ns 0.769 ns 0.894* 0.862ns Cenchrus ciliaris 0.914* 0.994*** 0.956* 0.987** 0.732 ns 0.759 ns 0.741 ns 0.916* Parthenium hysterophorus 0.778ns 0.957* 0.705ns 0.949* 0.930* 0.568 ns 0.942** 0.855ns Cynodon dactylon 0.724ns 0.999*** 0.736ns 0.910* 0.848 ns 0.474 ns 0.713 ns 0.865ns Cu Nerium oleander 0.976** 0.977** 0.949* 0.960** 0.911* 0.771 ns 0.852 ns 0.960** Calotropis procera 0.996*** 0.991*** 0.987** 0.930* 0.905* 0.972** 0.612 ns 0.964** Cynodon dactylon 0.990** 0.878* 0.963** 0.914* 0.898 0.971** 0.852 ns 0.938* Parthenium hysterophorus 0.962** 0.996*** 0.959** 0.921* 0.833 ns 0.928* 0.756 ns 0.948* Cenchrus ciliaris 0.972** 0.972** 0.964** 0.898* 0.854 ns 0.920* 0.905* 0.901* Ni Calotropis procera 0.957* 0.937* 0.809ns 0.980** 0.778 ns 0.784 ns 0.696 ns 0.970** ** ns ** ns ns ns * Nerium oleander 0.971 0.956* 0.716 0.983 0.746 0.696 0.753 0.912 Cynodon dactylon 0.952* 0.951* 0.924* 0.964** 0.497 ns 0.803 ns 0.577 ns 0.682ns Parthenium hysterophorus 0.950* 0.885* 0.759ns 0.950* 0.866 ns 0.414 ns 0.837 ns 0.975** Cenchrus ciliaris 0.974** 0.822ns 0.769ns 0.920* 0.811 ns 0.482 ns 0.794 ns 0.933* Zn Nerium oleander 0.983** 0.967** 0.992*** 0.981** 0.831ns 0.633ns 0.796 ns 0.932* Calotropis procera 0.956* 0.942* 0.951* 0.941* 0.864ns 0.693ns 0.763 ns 0.922* Cynodon dactylon 0.948* 0.998*** 0.993*** 0.879* 0.914* 0.715ns 0.867 ns 0.917* Parthenium hysterophorus 0.953* 0.953* 0.971** 0.922* 0.817ns 0.808 ns 0.834 ns 0.948* Cenchrus ciliaris 0.951* 0.962** 0.961** 0.884* 0.921* 0.785 ns 0.916* 0.933* ***, ** and * = Significant at 0.001, 0.01 and 0.05 respectively; ns = Non-significant

4.2. Effect of vehicle-related heavy metals on biochemical parameters in plants 4.2.1. Photosynthetic pigments 4.2.1.1. Chlorophyll “a” content in plants at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) The analysis variance of data pertaining to chlorophyll “a” content in plants at different sites adjacent to the M-2 is presented in Table 4.24. It depicted highly significant differences among plants and sites however their interaction remained non-significant. All the plants differed significantly from one another in mean chlorophyll “a” content of their leaves. Among plants, the highest chlorophyll “a” content (1.67 mg/g leaf fresh wt.) was recorded in Nerium oleander whereas the leaves of Cynodon dactylon contained the minimum content (1.04 mg/g leaf fresh wt.). However, the chlorophyll “a” content in other plants existed in the following order: Parthenium hysterophorus>Calotropis procera >Cenchrus ciliaris (Table 4.24 a). The chlorophyll “a” content in plants growing at different sites under observation was significantly different. The chlorophyll “a” content in plant leaves at all the contaminated sites was less as compared to control plants (Table 4.24 a). However among sites, the minimum content of this pigment was noted in plants at Kala Shah Kaku site while the maximum was recorded in plants at Sukheke site. The leaves of plants growing at Pindi Bhattian site had chlorophyll “a” contents significantly less than that recorded in plants at Khanqah Dogran site but more than that found in plants growing at Sheikhupura site. 4.2.1.2. Chlorophyll “a” content in plants at different sites along G.T. road (Lahore to Gujranwala) The ANOVA for data regarding the chlorophyll “a” concentration in plant leaves collected from different sites showed highly significant differences among plants as well as sites. Likewise, plants × sites interaction also remained highly significant (Table 4.25). Chlorophyll “a” content in the leaves of all the plants differed significantly (Table 4.25 a). However, Nerium oleander had the highest chlorophyll “a” content (1.484 mg/g leaf fresh wt.) followed by Parthenium hysterophorus>Calotropis procera>Cenchrus ciliaris>Cynodon dactylon.

The chlorophyll “a” content in plant leaves collected from the contaminated sites along G.T. road differed significantly from control plants. It was lower in plants growing at all the sites along the roadside as compared to control. However, the plants growing at Sadhoke site contained the highest (1.31 mg/g leaf fresh wt.) whereas the plants at Muridke site had the least chlorophyll “a” content (0.88 mg/g leaf fresh wt.). The overall order of chlorophyll “a” content in leaves of plants at different sites remained as follows: Sadhoke>Ferozewala>Eminabad More>Gujranwala>Muridke (Table 4.25 a).

Table 4.24. Analysis of variance for chlorophyll “a” content in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 3.989 0.997 89.819*** Sites 5 6.817 1.363 122.798*** Plants × Sites 20 0.362 0.018 1.632ns Error 60 0.666 0.0111 Total 89 11.834 *** = Significant at 0.001 level, respectively; ns = Non-significant;

Table 4.24 a. Mean chlorophyll “a” content (mg/g leaf fresh wt.) in plant leaves along M- 2 (LSD = 0.05)

Mean chlorophyll “a” content Nerium oleander L. 1.67 ± 0.38 a Parthenium hysterophorus L. 1.47 ± 0.26 b Plants Calotropis procera A. 1.37 ± 0.25 c Cenchrus ciliaris L. 1.26 ± 0.28 d Cynodon dactylon L. 1.04 ± 0.32 e Control 1.83 ± 0.30 a

Sukheke 1.53 ± 0.21 b

Khanqah Dogran 1.44 ± 0.22 c Sites Pindi Bhattian 1.24 ± 0.19 d Sheikhupura 1.11 ± 0.27 e Kala Shah Kaku 1.01 ± 0.25 f Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

Table 4.25. Analysis of variance for chlorophyll “a” content in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 4.215 1.054 185.022*** Sites 5 6.918 1.384 242.961*** Plants × Sites 20 0.714 0.036 6.269*** Error 60 0.342 0.006 Total 89 12.189 *** = Significant at 0.001 level

Table 4.25 a. Mean chlorophyll “a” content (mg/g leaf fresh wt.) in plant leaves along G.T. road (LSD = 0.05)

Mean chlorophyll “a” content Nerium oleander L. 1.48 ± 0.40 a Parthenium hysterophorus L. 1.31 ± 0.27 b Plants Calotropis procera A. 1.24 ± 0.26 c Cenchrus ciliaris L. 1.04 ± 0.27 d Cynodon dactylon L. 0.86 ± 0.31 e Control 1.72 ± 0.36 a

Sadhoke 1.31 ± 0.20 b

Ferozewala 1.19 ± 0.17 c Sites Eminabad More 1.06 ± 0.17 d Gujranwala 0.96 ± 0.26 e Muridke 0.88 ± 0.28 f Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly. .

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4.2.1.3. Seasonal variation in chlorophyll “a” content of plant leaves growing at different sites along M-2 The CCA biplot displayingthe content of chlorophyll “a” in plant species relating to several different locations adjacent to the M-2 is presented in Fig. 4.21. It revealed that chlorophyll “a” content in Cenchrus ciliaris was strongly associated with Kala Shah Kaku site. Similarly. Parthenium hysterophorus also showed association with Kala Shah Kaku site whereas Calotropis procera appeared to be associated with Sheikhupura site for its chlorophyll “a” content. However, Cynodon dactylon was found to be associated with Pindi Bhattian as well as Sukheke sites for its chlorophyll “a” content. Nerium oleander exhibited association with Control site for its chlorophyll “a”content. 4.2.1.4. Seasonal variation in chlorophyll “a” content of plant leaves growing at different sites along G.T. road The CCA biplot demonstrating the chlorophyll “a” content in plants relating to different sites adjacent to the G.T. road is presented in Fig. 4.22. The CCA biplot indicated that content of chlorophyll “a” in Cenchrus ciliaris and Parthenium hysterophorus was strongly associated with Eminabad More and Muridke sites respectively. Likewise, the chlorophyll “a” content in Calotropis procera was associated with Gujranwala site, whereas Cynodon dactylon showed association with Ferozewala site for its chlorophyll “a” content.

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1.0 Cd SU

Cp Ph Cc

KSK

No CO

-1.0 -1.0 1.0

Fig. 4.21. The CCA biplot illustrating the chlorophyll “a” content in plants relating to various sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.22. The CCA biplot illustrating the chlorophyll “a” content in plants relating to various sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.2.1.5. Chlorophyll “b” content in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The analysis of variance (ANOVA) for data concerning to the chlorophyll “b” content in leaves of plants at different sites adjacent to the M-2 illustrated highly significant differences among plants and sites however their interaction was non-significant (Table 4.26). The chlorophyll “b” content was significantly different among all the plants except between Calotropis procera and Parthenium hysterophorus. Nevertheless, the content of chlorophyll “b” was maximum (0.98 mg/g leaf fresh wt.) in the leaves of Nerium oleander whereas Cynodon dactylon exhibited the minimum content (0.50 mg/g leaf fresh wt.). The chlorophyll “b” content in Cenchrus ciliaris was higher than that found in the leaves of Cynodon dactylon (Table 4.26 a). The content of chlorophyll “b” in leaves of plant growing at all the sites along the roadside differed significantly from control (Table 4.26 a). The chlorophyll “b” content in plant leaves from all the contaminated sites was lower as compared to control. However among sites, the plants at Sukheke site had the maximum chlorophyll “b” content (0.89 mg/g leaf fresh wt.). The content of chlorophyll “b” in plants at Khanqah Dogran site did not differ significantly from that recorded in plants at Pindi Bhattian site. Similarly the plants at Sheikhupura site contained the chlorophyll “b” content which was non-significantly different from that noted in the leaves of plants at Kala Shah Kaku site. 4.2.1.6. Chlorophyll “b” content in plants growing along G.T. road (Lahore to Gujranwala) The ANOVA for data regarding the chlorophyll “b” content in plant leaves collected from various sites adjacent to the G.T. road showed highly significant differences among plants as well as sites. However, plants × sites interaction remained non-significant (Table 4.27). All the plants differed significantly from one another in mean chlorophyll “b” content in their leaves except Calotropis procera and Cenchrus ciliaris (Table 4.27 a). Among plants, Nerium oleander had the maximum content of chlorophyll “b” (0.84 mg/g leaf fresh wt.) which was followed by Parthenium hysterophorus (0.75 mg/g leaf fresh wt.). However, the least content of chlorophyll “b” (0.39 mg/g leaf fresh wt.) was noted in the leaves of Cynodon dactylon.

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The content of chlorophyll “b” in plant leaves gathered from several different locations adjacent to the road differed significantly from control. It was lower in plant leaves collected from all the metal contaminated sites as compared to control plants. However, the leaves of plants growing at Sadhoke site contained the highest (0.78 mg/g leaf fresh wt.) whereas those at Muridke site had the least chlorophyll “b” content (0.37 mg/g leaf fresh wt.). The leaves collected from Ferozewala and Eminabad More sites did not differ significantly in chlorophyll “b” content. Moreover, the content of chlorophyll “b” in plant leaves collected from Gujranwala site was higher than that observed in plant leaves at Muridke site (Table 4.27 a).

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Table 4.26. Analysis of variance for chlorophyll “b” content in plants growing at different

S. O. V. d. f. S. S. M. S. F-value Plants 4 2.391 0.598 29.961*** Sites 5 3.456 0.691 34.642*** Plants × Sites 20 0.101 0.005 0.252ns Error 60 1.197 0.020 Total 89 7.145 sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons *** = Significant at 0.001 level; ns = Non-significant

Table 4.26 a. Mean chlorophyll “b” content (mg/g leaf fresh wt.) in plant leaves along M- 2 (LSD = 0.05)

Mean chlorophyll “b” content Nerium oleander L. 0.98 ± 0.25 a Calotropis procera A. 0.81 ± 0.21 b Plants Parthenium hysterophorus L. 0.74 ± 0.19 b Cenchrus ciliaris L. 0.64 ± 0.30 c Cynodon dactylon L. 0.50 ± 0.20 d Control 1.05 ± 0.18 a Sukheke 0.89 ± 0.27 b Sites Khanqah Dogran 0.77 ± 0.21 c Pindi Bhattian 0.68 ± 0.20 c Sheikhupura 0.56 ± 0.20 d Kala Shah Kaku 0.47 ± 0.17 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.27. Analysis of variance for chlorophyll “b” content in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 2.106 0.527 42.140 *** Sites 5 3.304 0.661 52.880*** Plants × Sites 20 0.120 0.006 0.482 ns Error 60 0.750 0.012 Total 89 6.281 *** = Significant at 0.001 level; ns = Non-significant;

Table 4.27 a. Mean chlorophyll “b” content (mg/g leaf fresh wt.) in plant leave along G.T. road (LSD = 0.05)

Mean chlorophyll “b” content Nerium oleander L. 0.84 ± 0.25 a Parthenium hysterophorus L. 0.75 ± 0.25 b Plants Calotropis procera A. 0.63 ± 0.20 c Cenchrus ciliaris L. 0.59 ± 0.22 c Cynodon dactylon L. 0.39 ± 0.17 d Control 0.96 ± 0.22 a Sadhoke 0.78 ± 0.19 b Sites Ferozewala 0.66 ± 0.20 c Eminabad More 0.59 ± 0.19 c Gujranwala 0.48 ± 0.17 d Muridke 0.37 ± 0.14 e Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.2.1.7. Spatial variation in chlorophyll “b” content of plants growing along M-2 The biplot showing the content of chlorophyll “b” in different species of plants relating to various locations adjacent to the M-2 is presented in Fig. 4.23. It indicated that chlorophyll “b” content in Calotropis procera had association with Pindi Bhattian site. However, chlorophyll “b” content in Parthenium hysterophorus and Cenchrus ciliaris was weakly associated with Pindi Bhattian and Khanqah Dogran sites respectively. However, chlorophyll “b” content in Cynodon dactylon and Nerium oleander didn’t seem to be associated with any specific site. 4.2.1.8. Spatial variation in chlorophyll “b” content of plants growing along G.T. road The CCA biplot displaying the chlorophyll “b” content in leaves of plants relating to different sites adjacent to the G.T. road has been given in Fig. 4.24. It showed that Parthenium hysterophorus and Cenchrus ciliaris were strongly associated with Sadhoke and Eminabad More sites respectively, for their chlorophyll “b” content. Cynodon dactylon showed association with Gujranwala site for its high chlorophyll “b” content. However, chlorophyll “b” content in Calotropis procera showed weak association with Eminabad More site whereas Nerium oleander did not exhibit relation with one location for its chlorophyll “b” quantity.

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Fig. 4.23. The CCA biplot illustrating the chlorophyll “b” content in plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.24. The CCA biplot illustrating the chlorophyll “b” content in plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.2.1.9. Total chlorophyll content in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The analysis of variance (ANOVA) for data relating to the content of total chlorophyll in leaves of different plant species at different locations adjacent to the M-2 indicated highly significant differences among plants and sites however their interaction remained non-significant (Table 4.28). All the plants under study differed significantly in total chlorophyll content of their leaves. The content of total chlorophyll was maximum (2.66 mg/g leaf fresh wt.) in the leaves of Nerium oleander whereas Cynodon dactylon exhibited the minimum content (1.54 mg/g leaf fresh wt.). The order of total chlorophyll content in leaves of different plant species existed as follows: Nerium oleander>Calotropis procera>Parthenium hysterophorus>Cenchrus ciliaris>Cynodon dactylon (Table 4.28 a). Total chlorophyll content in plant leaves collected from different sites along the roadside was significantly different from control (Table 4.28 a). The leaves of plants growing at all the contaminated sites exhibited lower content of total chlorophyll as compared to control plants. However, the plants at Sukheke site had the maximum total chlorophyll content (2.42 mg/g leaf fresh wt.) whereas those collected from the Kala Shah Kaku site had the minimum (1.48 mg/g leaf fresh wt.) as compared to other sites. The total chlorophyll content in the leaves of plants collected from different sites followed the order: Sukheke>Khanqah Dogran>Pindi Bhattian>Sheikhupura>Kala Shah Kaku. 4.2.1.10. Total chlorophyll content in plants growing along G.T. road (Lahore to Gujranwala) The ANOVA for data regarding the content of total chlorophyll in plant leaves collected from various locations depicted highly significant differences among plants as well as sites. However, plants × sites interaction remained non-significant (Table 4.29). All the plants differed significantly from one another in total chlorophyll content in their leaves (Table 4.29 a). However, Nerium oleander had the maximum total chlorophyll content (2.32 mg/g leaf fresh wt.) followed by Parthenium hysterophorus, Calotropis procera, Cenchrus ciliaris and Cynodon dactylon. The total chlorophyll content in plant leaves collected from different sites along G.T. road differed significantly from control. It was lower in plant leaves collected from all the

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metal contaminated sites as compared to control. However, the plant leaves at Sadhoke site contained the highest (2.09 mg/g leaf fresh wt.) whereas those at Muridke site had the least total chlorophyll content (1.26 mg/g leaf fresh wt.). The total chlorophyll content in plant leaves collected from various sites remained in following order: Sadhoke>Ferozewala>Eminabad More>Gujranwala>Muridke (Table 4.29 a).

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Table 4.28. Analysis of variance for total chlorophyll content in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons S. O. V. d. f. S. S. M. S. F-value Plants 4 12.549 3.137 65.419*** Sites 5 19.904 3.981 83.004*** Plants × Sites 20 0.420 0.021 0.437ns Error 60 2.877 0.048 Total 89 35.750 *** = Significant at 0.001 level; ns = Non-significant

Table 4.28 a. Mean total chlorophyll content (mg/g leaf fresh wt.) in plant leaves along M-2 (LSD = 0.05)

Mean total chlorophyll content Nerium oleander L. 2.66 ± 0.62 a Calotropis procera A. 2.28 ± 0.46 b Plants Parthenium hysterophorus L. 2.11 ± 0.50 c Cenchrus ciliaris L. 1.90 ± 0.54 d Cynodon dactylon L. 1.54 ± 0.51 e Control 2.88 ± 0.48 a

Sukheke 2.42 ± 0.45 b

Khanqah Dogran 2.22 ± 0.42 c Sites Pindi Bhattian 1.91 ± 0.39 d Sheikhupura 1.67 ± 0.46 e Kala Shah Kaku 1.48 ± 0.40 f Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.29. Analysis of variance for total chlorophyll content in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 12.127 3.032 101.412*** Sites 5 19.544 3.909 130.752*** Plants × Sites 20 0.823 0.041 1.376 ns Error 60 1.794 0.030 Total 89 34.288 *** = Significant at 0.001 level, ns = Non-significant

Table 4.29 a. Mean total chlorophyll content (mg/g leaf fresh wt.) in plant leaves along G.T. road (LSD = 0.05)

Mean total chlorophyll content Nerium oleander L. 2.32 ± 0.64 a

Parthenium hysterophorus L. 2.06 ± 0.50 b Plants Calotropis procera A. 1.88 ± 0.43 c

Cenchrus ciliaris L. 1.64 ± 0.48 d

Cynodon dactylon L. 1.25 ± 0.47 e Control 2.68 ± 0.57 a Sadhoke 2.09 ± 0.37 b Sites Ferozewala 1.86 ± 0.36 c Eminabad More 1.65 ± 0.35 d Gujranwala 1.44 ± 0.41 e Muridke 1.26 ± 0.40 f Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.2.1.11. Spatial variation in total chlorophyll content of plants growing along M-2 The biplot presenting the total chlorophyll content in different plant species relating to different locations adjacent to the M-2 is illustrated in Fig. 4.25. It depicted the association of Calotropis procera with Kala Shah Kaku and Sheikhupura sites for its total chlorophyll content. Similarly, Cenchrus ciliaris as well as Parthenium hysterophorus showed association with Sheikhupura site for their total chlorophyll content. Nerium oleander and Cynodon dactylon exhibited association with Control and Khanqah Dogran sites, respectively, for their total chlorophyll content. 4.2.1.12. Spatial variation in total chlorophyll content of plants growing along G.T. road The canonical correspondence analysis biplot demonstrating the total chlorophyll content in plant species relating to different sites along G.T. road has been given in Fig. 4.26. It showed that Calotropis procera and Cynodon dactylon were strongly associated with Gujranwala and Ferozewala sites respectively, for their total chlorophyll contents. Similarly, Cenchrus ciliaris also exhibited association with Ferozewala for its total chlorophyll content whereas total chlorophyll content in Parthenium hysterophorus was associated with Gujranwala to some extent. However, Nerium oleander didn’t exhibit association with any specific site for its total chlorophyll content.

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1.0 PB SU

CO Cp Cc No KSK Ph SH

-1.5 -1.0 1.5 Fig. 4. 25. The CCA biplot illustrating the total chlorophyll content in plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

GU 1.0 MU Cp

EM CO

Cc No

Cd FE

-1.5 -1.0 1.5

Fig. 4.26. The CCA biplot illustrating the total chlorophyll content in plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.2.1.13. Carotenoid content in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The statistical analysis (ANOVA) of data regarding the carotenoid content in plant leaves sampled from different sites adjacent to the M-2 depicted highly significant differences among plants and sites however their interaction remained non-significant (Table 4.30). A comparison amid different plant species for content of carotenoids in their leaves showed the highest content (0.05 mg/g leaf fresh wt.) in Nerium oleander which differed non- significantly from that recorded in Calotropis procera. The carotenoid content in the leaves of Calotropis procera also did not differ significantly from that in the leaves of Parthenium hysterophorus. Moreover, the carotenoid content in Cenchrus ciliaris and Cynodon dactylon was also not different statistically (Table 4.30 a). The carotenoid content in the plant leaves collected from all metal contaminated the sites differed significantly from control. The carotenoid content in plant leaves at all the sites along the roadside was less as compared to control (Table 4.30 a). However among sites, the leaves of plants growing at Sukheke and Khanqah Dogran sites contained the carotenoid content as 0.050 mg/g leaf fresh wt. and 0.046 mg/g leaf fresh wt., respectively which did not differ significantly. The carotenoid content in the leaves of plants growing at Pindi Bhattian site was lower than that recorded in leaves collected from above mentioned sites. Moreover, the least carotenoid content was found in the leaves collected from Sheikhupura and Kala Shah Kaku sites which was also not significantly different. 4.2.1.14. Carotenoid content in plants growing along G.T. road (Lahore to Gujranwala) According to the ANOVA for data regarding the carotenoid content in plant leaves collected from different sites, there were highly significant differences among plants and sites, however their interaction remained non-significant (Table 4.31). All the plants differed significantly from one another in carotenoid content in their leaves except Calotropis procera and Parthenium hysterophorus (Table 4.31 a). However, the leaves of Nerium oleander had the maximum carotenoid content (0.046 mg/g leaf fresh wt.) whereas the least content (0.033 mg/g leaf fresh wt.) was noted in the leaves of Cynodon dactylon. The carotenoid content in plant leaves collected from different sites along G.T. road differed significantly from control. It was lower in plant leaves collected from all the sites as

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compared to control. However among sites, the plant leaves collected from Sadhoke site contained the highest (0.046 mg/g leaf fresh wt.) whereas those at Muridke site had the least carotenoid content (0.022 mg/g leaf fresh wt.). The carotenoid content in plant leaves collected from different sites remained in the following order: Sadhoke>Ferozewala>Eminabad More>Gujranwala>Muridke (Table 4.31 a).

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Table 4.30. Analysis of variance for carotenoid content in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 0.002 6.172e-4 12.256*** Sites 5 0.012 0.002 49.304*** Plants × Sites 20 4.745e-4 2.373e-5 0.471ns Error 60 0.003 5.036e-5 Total 89 0.018 *** = Significant at 0.001 level; ns = Non-significant

Table 4.30 a. Mean carotenoid content (mg/g leaf fresh wt.) in plant leaves along M-2 (LSD = 0.05)

Mean carotenoid content Nerium oleander L. 0.050 ± 0.014 a Calotropis procera A. 0.046 ± 0.013 ab Plants Parthenium hysterophorus L. 0.043 ± 0.012 b Cenchrus ciliaris L. 0.037 ± 0.014 c Cynodon dactylon L. 0.036 ± 0.014 c Control 0.062 ± 0.010 a Sukheke 0.050 ± 0.007 b Khanqah Dogran 0.046 ± 0.008 b Sites Pindi Bhattian 0.037 ± 0.007 c Sheikhupura 0.031 ± 0.010 d Kala Shah Kaku 0.028 ± 0.009 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.31. Analysis of variance for carotenoid content in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 0.002 3.832 34.527*** Sites 5 0.013 0.003 238.300*** Plants × Sites 20 1.329 6.643 0.598ns Error 60 6.660 1.110

Total 89 0.015 *** = Significant at 0.001 level, ns = Non-significant

Table 4.31 a. Mean carotenoid content (mg/g leaf fresh wt.) in plant leaves along G.T. road (LSD = 0.05)

Mean carotenoid content Nerium oleander L. 0.046 ± 0.013 a Calotropis procera A. 0.041 ± 0.013 b Plants Parthenium hysterophorus L. 0.039 ± 0.012 b Cenchrus ciliaris L. 0.037 ± 0.013 c Cynodon dactylon L. 0.033 ± 0.013 d Control 0.060 ± 0.005 a Sadhoke 0.046 ± 0.005 b Sites Ferozewala 0.042 ± 0.004 c Eminabad More 0.034 ± 0.005 d Gujranwala 0.031 ± 0.006 e Muridke 0.022 ± 0.006 f Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.2.1.15. Spatial variation in carotenoid content of plants growing along M-2 The CCA biplot showing the content of carotenoids in plant species relating to various locations adjacent to the M-2 is presented in Fig. 4.27. It indicated that Nerium oleander and Cynodon dactylon were associated with Kala Shah Kaku and Khanqah Dogran sites respectively, for their carotenoid contents. Cenchrus ciliaris appeared to be weakly associated with Sukheke or its carotenoid content. However, Calotropis procera as well as Parthenium hysterophorus didn’t exhibit association with any site for their carotenoid content. 4.2.1.16. Spatial variation in carotenoid content of plants growing along G.T. road The CCA biplot demonstrating the carotenoid content in leaves of plants relating to different sites adjacent to the G.T. road is illustrated in Fig. 4.28. It revealed the association of Nerium oleander with Eminabad More site for its carotenoid content. Parthenium hysterophorus and Calotropis procera were weakly associated with Gujranwala and Ferozewala sites respectively, for their carotenoid content. However, Cenchrus ciliaris as well as Cynodon dactylon did not appear to be associated with any of the sites for their carotenoid content. 4.2.1.17. Correlation between metal contents and photosynthetic pigments in plants The metal content (Pb, Cd, Cu, Ni, Zn) in all the plant species exhibited significant negative correlation with photosynthetic pigments (chlorophyll a, chlorophyll b, total chlorophyll and carotenoid contents) of the plants along both roads (Table 4.32)

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Fig. 4. 27. The CCA biplot illustrating the carotenoid content in plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4. 28. The CCA biplot illustrating the carotenoid content in plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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Table 4.32: Pearson’s correlation coefficient between metal contents and photosynthetic pigments in plants along the roads Chlorophyll "a" Chlorophyll "b" Total chlorophyll Carotenoids M-2 G.T. road M-2 G.T. road M-2 G.T. road M-2 G.T. road Pb Calotropis procera -0.953* -0.990*** -0.927* -0.833* -0.945* -0.953* -0.962* -0.910* Nerium oleander -0.961* -0.966* -0.954* -0.911* -0.967* -0.957* -0.982*** -0.923* Cynodon dactylon -0.945* -0.794ns -0.948* -0.892* -0.965* -0.841* -0.919* -0.879* Parthenium hysterophorus -0.982*** -0.949* -0.951* -0.852* -0.980*** -0.936* -0.979*** -0.905* Cenchrus ciliaris -0.967* -0.890* -0.963* -0.870* -0.970* -0.886* -0.951* -0.926* Cd Calotropis procera -0.994*** -0.992*** -0.957* -0.927* -0.986*** -0.993*** -0.997*** -0.960* Nerium oleander -0.966*** -0.974*** -0.973** -0.974*** -0.977*** -0.986*** -0.955* -0.983*** Cenchrus ciliaris -0.986*** -0.913* -0.981*** -0.890* -0.989*** -0.908* -0.980*** -0.947* Parthenium hysterophorus -0.966*** -0.976*** -0.988*** -0.893* -0.985*** -0.971** -0.970* -0.913* Cynodon dactylon -0.942* -0.854* -0.989*** -0.937* -0.979*** -0.896* -0.913* -0.909* Cu Nerium oleander -0.980*** -0.962* -0.969* -0.927* -0.984*** -0.961* -0.996*** -0.936* Calotropis procera -0.997*** -0.986*** -0.947* -0.866* -0.985*** -0.964* -0.997*** -0.925* Cynodon dactylon -0.958* -0.907* -0.927* -0.956* -0.965* -0.939* -0.964* -0.950* Parthenium hysterophorus -0.997*** -0.974*** -0.969* -0.878* -0.992*** -0.962* -0.989*** -0.909* Cenchrus ciliaris -0.990*** -0.908* -0.975*** -0.899* -0.988*** -0.908* -0.980*** -0.940* Ni Calotropis procera -0.968* -0.992*** -0.937* -0.897* -0.960* -0.980*** -0.974*** -0.950* Nerium oleander -0.966* -0.953* -0.952* -0.873* -0.969* -0.934* -0.972** -0.891* Cynodon dactylon -0.894* -0.728ns -0.980*** -0.848* -0.945* -0.781ns -0.871* -0.824* Parthenium hysterophorus -0.933* -0.972** -0.897* -0.827* -0.929* -0.937* -0.931* -0.874* Cenchrus ciliaris -0.905* -0.845* -0.864* -0.805ns -0.890* -0.833* -0.866* -0.868* Zn Nerium oleander -0.973** -0.964* -0.942* -0.924* -0.969* -0.961* -0.975*** -0.935* Calotropis procera -0.952* -0.989*** -0.897* -0.823* -0.934* -0.948* -0.959* -0.895* Cynodon dactylon -0.947* -0.799ns -0.969* -0.913* -0.974*** -0.851* -0.947* -0.885* Parthenium hysterophorus -0.966* -0.973** -0.943* -0.865* -0.966* -0.955* -0.954* -0.904* Cenchrus ciliaris -0.991*** -0.881* -0.975*** -0.853* -0.989*** -0.873* -0.979*** -0.897* ***, ** and * = Significant at 0.001, 0.01 and 0.05 respectively; ns = Non-significant

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4.2.2. Total soluble proteins in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The statistical analysis of data concerning the content of total soluble proteins in different plant species growing at different locations adjacent to the M-2 exhibited highly significant differences among plants as well as sites, however, plants × sites interaction remained non-significant (Table 4.32). All the plants differed significantly from one another with respect to their total soluble proteins content except Calotropis procera and Nerium oleander which did not vary significantly from each other (Table 4.32 a). Among plants, Parthenium hysterophorus showed the highest (3.89 µg/g fresh wt.) whereas Cenchrus ciliaris had the least content of total soluble proteins (2.75 µg/g fresh wt.). The total soluble proteins in plants growing at different contaminated sites along the road differed significantly from control plants. The total soluble proteins in plants growing at all the contaminated sites under study were lower as compared to control. Among the contaminated sites, the plants growing at Sukheke and Khanqah Dogran sites exhibited the maximum content of total soluble proteins (4.23 and 4.15 µg/g fresh wt.) followed by that recorded in plants at Pindi Bhattian and Sheikhupura sites. Moreover, the least total soluble proteins content (1.29 µg/g fresh wt.) were recorded in plants growing at Kala Shah Kaku site (Table 4.32 a). 4.2.3. Total soluble proteins in plants growing along G.T. road (Lahore to Gujranwala) The ANOVA for data pertaining to the content of total soluble proteins in plants growing at different sites adjacent to the G.T. road depicted highly significant differences among plants and sites whereas their interaction was not significant (Table 4.33). The total soluble proteins in all the plants differed significantly. Among plants, the Cynodon dactylon contained the maximum (3.02 µg/g fresh wt.) while Calotropis procera exhibited the minimum content of total soluble proteins (1.89 µg/g fresh wt.). The overall order of total soluble proteins content in different plants existed as follows: Cynodon dactylon> Parthenium hysterophorus>Nerium oleander>Cenchrus ciliaris>Calotropis procera (Table 4.33 a). The plants growing at different sites along the roadside differed significantly from control plants in their total soluble protein contents. It was less in plants at all the contaminated

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sites under study as compared to control plants. However among sites, the maximum content of total soluble proteins (2.65 µg/g fresh wt.) was noted in plants growing at Sadhoke followed by that (2.44 µg/g fresh wt.) documented in plants growing at Ferozewala site. The content of total soluble proteins in plants growing at Eminabad More and Gujranwala sites differed non- significantly. Moreover, the least total soluble proteins content (0.88 µg/g fresh wt.) was recorded in the plants growing at Muridke (Table 4.33 a).

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Table 4.33. Analysis of variance for total soluble proteins in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 16.358 4.0895 70.90*** Sites 5 242.350 48.4700 840.32*** Plants × Sites 20 1.112 0.0556 0.96ns

Error 60 3.461 0.0577

Total 89 263.281 *** = Significant at 0.001 level; ns = Non-significant

Table 4.33 a. Mean total soluble proteins (µg/g fresh wt.) in plant leaves along M-2 (LSD = 0.05)

Mean total soluble proteins Parthenium hysterophorus L. 3.89 ± 1.85 a Nerium oleander L. 3.64 ± 1.70 b Plants Calotropis procera A. 3.55 ± 1.73 b Cynodon dactylon L. 2.99 ± 1.62 c Cenchrus ciliaris L. 2.75 ± 1.61 d Control 6.09 ± 0.64 a

Sukheke 4.23 ± 0.53 b

Khanqah Dogran 4.15 ± 0.55 b Sites Pindi Bhattian 2.65 ± 0.48 c Sheikhupura 1.77 ± 0.33 d Kala Shah Kaku 1.29 ± 0.41 e Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.34. Analysis of variance for total soluble proteins in plants growing at different sites along G.T. road (Lahore to Gujranwala) during different seasons

S. O. V. d. f. S. S. M. S. F-value Plants 4 14.766 3.6915 97.45*** Sites 5 227.147 45.4293 1199.28*** Plants × Sites 20 1.077 0.0539 1.42ns Error 60 2.273 0.0379 Total 89 245.263 *** = Significant at 0.001 level; ns= Non-significant

Table 4.34 a. Mean total soluble proteins (µg/g fresh wt.) in plant leaves along G.T. road (LSD = 0.05)

Mean total soluble proteins Cynodon dactylon L. 3.02 ± 1.61 a Parthenium hysterophorus L. 2.75 ± 1.73 b Plants Nerium oleander L. 2.57 ± 1.77 c Cenchrus ciliaris L. 2.17 ± 1.63 d Calotropis procera A. 1.89 ± 1.65 e

Control 5.77 ± 0.50 a Sadhoke 2.65 ± 0.58 b Sites Ferozewala 2.44 ± 0.43 c Eminabad More 1.56 ± 0.40 d Gujranwala 1.56 ± 0.49 d Muridke 0.88 ± 0.52 e Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.2.4. Spatial variation in total soluble proteins of plants growing along M-2 The CCA biplot depicting the total soluble proteins in different plant species relating to different locations adjacent to the M-2 is presented in Fig. 4.29. It revealed the strong association of Calotropis procera with Khanqah Dogran for its total soluble proteins, whereas Nerium oleander was found to be associated with Khanqah Dogran as well as Sukheke sites for its total soluble protein content. Cenchrus ciliaris and Parthenium hysterophorus exhibited association with Sheikhupura and Control sites respectively, for their high total soluble protein content. Nevertheless, Cynodon dactylon did not associate with any specific site for its total soluble protein content. 4.2.5. Spatial variation in total soluble proteins of plants growing along G.T. road The canonical correspondence analysis biplot illustrating the total soluble protein content in plants relating to different sites along G.T. road has been given in Fig. 4.30. It showed the association of Calotropis procera with Control for its total soluble proteins whereas Cynodon dactylon was linked with Eminabad More. However, Cenchrus ciliaris, Nerium oleander and Parthenium hysterophorus were not related to any specific location for total soluble proteins in their leaves.

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Fig. 4.29. The CCA biplot illustrating the total soluble proteins in plants relating to various sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.30. The CCA biplot illustrating the total soluble proteins in plants relating to various sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.2.6. Total free amino acids in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The ANOVA for data pertaining to the total free amino acids in leaves of plant species growing at different sites adjacent to the M-2 showed highly significant differences among plants as well as sites. However, plants × sites interaction existed non-significant (Table 4.34). All the plants differed significantly from one another in their total free amino acids content except Parthenium hysterophorus which was not significantly different from Cenchrus ciliaris and Calotropis procera (Table 4.34 a). However, Nerium oleander showed the maximum (18.1 µg/g fresh wt.) whereas Cynodon dactylon exhibited the minimum content of free amino acids (10.5 µg/g fresh wt.). The total free amino acids in plants growing at all the contaminated sites under observation differed significantly from control plants (Table 4.34 a). The plants growing at all the contaminated sites near the road had higher amount of free amino acids as compared to control plants. However, the plants growing at Kala Shah Kaku site exhibited the maximum amount of free amino acids followed by Sheikhupura and Pindi Bhattian sites. Moreover, free amino acids in plants growing at Khanqah Dogran and Sukheke sites did not vary significantly. 4.2.7. Total free amino acids in plants growing along G.T. road (Lahore to Gujranwala) The ANOVA for data relating to the total free amino acids in plants growing at different sites along the road has been given in Table 4.35. It demonstrated highly significant differences among plants and sites, however their interaction remained non-significant. The amount of total free amino acids in all the plants differed significantly except Cenchrus ciliaris which did not vary significantly from Parthenium hysterophorus and Cynodon dactylon. Among plants, Nerium oleander exhibited the maximum amount of total free amino acids (20.5 µg/g fresh wt.) followed by Calotropis procera (18.9 µg/g fresh wt.) (Table 4.35 a). The amount of free amino acids in plants growing at different contaminated sites under observation varied significantly from control plants. It was less in control plants than the plants at all the contaminated sites along the roadside. However among contaminated sites, the maximum content of free amino acids (22.9 µg/g fresh wt.) was noted in plants growing at Muridke site. However, the content of free amino acids in plants growing at Gujranwala and Eminabad More sites did not differ significantly. Likewise, free amino acids in plants growing at Ferozewala site were also not significantly different from those in plants at Sadhoke site (Table 4.35 a).

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Table 4.35. Analysis of variance for total free amino acids in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku)

S. O. V. d. f. S. S. M. S. F-value Plants 4 554.89 138.72 26.62*** Sites 5 3194.72 638.94 122.63*** Plants × Sites 20 105.54 5.28 1.01ns

Error 60 312.63 5.21 Total 89 4167.78 *** = Significant at 0.001 level, ns = Non-significant

Table 4.35 a. Mean total free amino acids (µg/g fresh wt.) in plant leaves along M-2 (LSD = 0.05)

Mean total free amino acids Nerium oleander L. 18.1 ± 8.08 a Calotropis procera A. 15.5 ± 6.83 b Plants Parthenium hysterophorus L. 14.4 ± 6.20 bc Cenchrus ciliaris L. 13.4 ± 5.64 c Cynodon dactylon L. 10.5 ± 5.48 d Kala Shah Kaku 21.2 ± 4.63 a

Sheikhupura 19.0 ± 3.79 b

Pindi Bhattian 17.3 ± 3.34 c Sites Khanqah Dogran 13.2 ± 3.27 d Sukheke 12.5 ± 3.27 d Control 2.93 ± 1.04 e Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.36. Analysis of variance for total free amino acids in plants growing at different sites along G.T. road (Lahore to Gujranwala)

S. O. V. d. f. S. S. M. S. F-value Plants 4 259.87 64.97 18.40*** Sites 5 3953.67 790.73 223.96*** Plants × Sites 20 81.99 4.10 1.16ns Error 60 211.84 3.53 Total 89 4507.36 *** = Significant at 0.001 level, ns = Non-significant

Table 4.36 a. Mean total free amino acids (µg/g fresh wt.) in plant leaves along G.T. road (LSD = 0.05)

Mean total free amino acids Nerium oleander L. 20.5 ± 7.91 a Calotropis procera A. 18.9 ± 7.40 b Plants Parthenium hysterophorus L. 17.5 ± 7.02 c Cenchrus ciliaris L. 16.6 ± 6.45 cd Cynodon dactylon L. 15.7 ± 6.44 d

Muridke 22.9 ± 3.72 a Gujranwala 21.4 ± 2.89 b Sites Eminabad More 21.0 ± 2.31 b Ferozewala 19.4 ± 2.58 c Sadhoke 19.0 ± 2.13 c Control 3.31 ± 0.90 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.2.8. Spatial variation in total free amino acids of plants growing along M-2 The CCA biplot depicting the total free amino acids in plants relating to different sites adjacent to the M-2 is illustrated in Fig. 4.31. It revealed strong association of Cenchrus ciliaris with Pindi Bhattian site for its total free amino acid content. Nerium oleander was associated with Kala Shah Kaku site for its total free amino acids. However, other plant species didn’t associate with any specific site for their total free amino acids. 4.2.9. Seasonal variation in total free amino acids of plants growing along G.T. road The CCA biplot presenting the total free amino acids content in different plant species relating to different sites adjacent to the G.T. road is given in Fig. 4.32. It revealed that Cynodon dactylon was associated with Sadhoke and Control sites for its total free amino acids content, while Cenchrus ciliaris and Parthenium hysterophorus showed association with Control site for total free amino acids in them. However, Calotropis procera and Nerium oleander was not obsered to be related to any particular site for total amino acids in their leaves.

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Fig. 4.31. The CCA biplot illustrating the total free amino acids in plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.32. The CCA biplot illustrating the total free amino acids in plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.2.10. Total antioxidant activity in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The statistical analysis of data regarding the total antioxidant activity in different plant species growing at several different locations along M-2 depicted highly significant differences among plants as well as sites (Table 4.36). Nevertheless, plants × sites interaction remained non-significant. A comparison among plants depicted maximum total antioxidant activity (35.0 %) in Calotropis procera which was significantly different from that observed in all other plants. However, the total antioxidant activity did not differ significantly between Cenchrus ciliaris and Nerium oleander as well as Parthenium hysterophorus and Cynodon dactylon (Table 4.36 a). It was observed that total antioxidant activity in plants at all the contaminated sites along the road differed significantly from control plants. The plants growing at all the contaminated sites exhibited higher total antioxidant activity than control plants. However, the plants growing at Kala Shah Kaku site showed the maximum total antioxidant activity followed by those growing at Sheikhupura and Pindi Bhattian sites. The total antioxidant activity in plants at Khanqah Dogran and Sukheke sites did not vary significantly (Table 4.36 a). 4.2.11. Total antioxidant activity in plants growing along G.T. road (Lahore to Gujranwala) The ANOVA for data concerning the total antioxidant activity in different plants growing at different locations under study has been given in Table 4.37. It illustrated highly significant differences among plants and sites, however their interaction was not significant. Among plants the maximum total antioxidant activity (40.0 %) was recorded in Calotropis procera followed by (36.3 %) Nerium oleander. However, total antioxidant activity did not differ significantly among, Cenchrus ciliaris, Parthenium hysterophorus and Cynodon dactylon (Table 4.37 a). The total antioxidant activity in plants growing at all contaminated sites along the road differed significantly from that observed in control plants. The plants growing at contaminated sites showed higher total antioxidant activity as compared to control plants. Among sites, the maximum total antioxidant activity (44.5 %) was noted in plants growing at Muridke site which did not vary significantly from that (42.8 %) recorded in plants at Gujranwala site. Moreover, the total antioxidant activity in the plants growing at Ferozewala

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site was not significantly different from that observed in plants growing at Eminabad More as well as Sadhoke site (Table 4.37 a).

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Table 4.37. Analysis of variance for total antioxidant activity in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku)

S. O. V. d. f. S. S. M. S. F-value Plants 4 517.8 129.44 10.45*** Sites 5 8999.2 1799.83 145.25*** Plants × Sites 20 113.4 5.67 0.46ns

Error 60 743.5 12.39 Total 89 10373.8 *** = Significant at 0.001 level; ns = Non-significant

Table 4.37 a. Mean total antioxidant activity (%) in plant leaves along M-2 (LSD = 0.05)

Mean total antioxidant activity Calotropis procera A. 35.0 ± 12.4 a Nerium oleander L. 32.6 ± 11.07 b Plants Cenchrus ciliaris L. 31.6 ± 10.7 b Parthenium hysterophorus L. 29.2 ± 9.84 c Cynodon dactylon L. 28.3 ± 9.47 c Kala Shah Kaku 42.2 ± 5.76 a

Sheikhupura 38.7 ± 4.69 b

Pindi Bhattian 35.0 ± 4.04 c Sites Khanqah Dogran 31.3 ± 3.67 d Sukheke 29.9 ± 3.56 d Control 11.0 ± 0.67 e Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.38. Analysis of variance for total antioxidant activity in plants growing at different sites along G.T. road (Lahore to Gujranwala)

S. O. V. d. f. S. S. M. S. F-value Plants 4 1098.3 274.58 13.31*** Sites 5 10665.6 2133.12 103.39*** Plants × Sites 20 353.7 17.69 0.86ns Error 60 1237.9 20.63

Total 89 13355.5 *** = Significant at 0.001 level; ns = Non-significant

Table 4.38 a. Mean total antioxidant activity (%) in plant leaves along G.T. road (LSD = 0.05)

Mean total antioxidant activity Calotropis procera A. 40.0 ± 14.2 a Nerium oleander L. 36.3 ± 12.3 b Plants Cenchrus ciliaris L. 33.1 ± 11.4 c Parthenium hysterophorus L. 31.1 ± 11.4 c Cynodon dactylon L. 30.7 ± 10.4 c

Muridke 44.5 ± 7.71 a Gujranwala 42.8 ± 5.51 a Sites Eminabad More 38.0 ± 5.91 b Ferozewala 35.1 ± 5.99 bc Sadhoke 33.6 ± 5.52 c Control 11.5 ± 0.88 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.2.12. Spatial variation in total antioxidant activity of plants growing along M-2 The CCA biplot describing the total antioxidant activity in different plant species relating to different locations adjacent to the M-2 is presented in Fig. 4.33. It indicated strong association of Parthenium hysterophorus with Sukheke site for total antioxidant activity whereas Cynodon dactylon was found to be associated with Sukheke as well as Control sites for its total antioxidant activity. Moreover, Cenchrus ciliaris and Nerium oleander showed association with Khanqah Dogran site for their total antioxidant activity. However, Calotropis procera apperaed to be weakly associated with Kala Shah Kaku and Pindi Bhattian sites for its total antioxidant activity. 4.2.13. Spatial variation in total antioxidant activity of plants growing along G.T. road The CCA biplot demonstrating the total antioxidant activity in plants relating to different sites adjacent to the G.T. road is presented in Fig. 4.34. It exhibited the strong association of Parthenium hysterophorus with Gujranwala site for its total antioxidant activity. Similarly, total antioxidant activity in Cenchrus ciliaris was asociated with Gujranwala as well as Control site, whereas Nerium oleander had asociation with Sadhoke and Eminabad More sites for its total antioxidant activity. However, Calotropis procera was weakly associated with Muridke for its total antioxidant activity, while Cynodon dactylon didn’t exhibit association with any specific site under study for its total antioxidant activity.

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Fig. 4.33. The CCA biplot illustrating the total antioxidant activity in plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.34. The CCA biplot illustrating the total antioxidant activity in plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.3. Effect of vehicle-released heavy metals on plants physiological parameters (Gas exchange parameters) The adverse effects of heavy metals emitted from the vehicular traffic on leaf gas exchange parameters of different plant species growing along a section of M-2 as well as G.T. road have been described below. 4.3.1. Photosynthetic rate (A) in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The statistical analysis of data (ANOVA) regarding the photosynthetic rate in leaves of plants growing at various sites illustrated highly significant differences among plants as well as sites. Nevertheless, plants × sites interaction remained non-significant (Table 4.38). All the plants species differed significantly in their photosynthetic rate except Cenchrus ciliaris and Cynodon dactylon (Table 4.38 a). The highest rate of photosynthesis (21.7 µmol -2 -1 CO2 m s ) was documented in the leaves of Nerium oleander followed by Parthenium -2 -1 -2 -1 hysterophorus (19.0 µmol CO2 m s ) and Calotropis procera (16.6 µmol CO2 m s ). All the sites differed significantly from control in mean photosynthetic rate in the leaves of plants growing at these sites. The rate of photosynthesis got reduced in plants at all the sites along the roadside as compared to control. The photosynthetic rate in the leaves of plants growing at Khanqah Dogran site differed non-significantly from that recorded in plants at Sukheke and Pindi Bhattian sites. However, minimum rate of photosynthesis was recorded in -2 -1 plants from Sheikhupura (12.6 µmol CO2 m s ) and Kala Shah Kaku sites (11.1 µmol CO2 m-2 s-1) which also did not vary significantly (Table 4.38 a). 4.3.2. Photosynthetic rate (A) in plants growing along G.T. road (Lahore to Gujranwala) The ANOVA for data relating to the photosynthetic rate in plant leaves has been given in Table 4.39. It revealed highly significant differences among plants and sites. Nevertheless, plants × sites interaction remained not significant. All the plants differed significantly from one another in mean photosynthetic rate in their leaves except Cenchrus ciliaris which differed non-significantly from Calotropis procera and Cynodon dactylon (Table 4.39 a). However, the leaves of Nerium oleander exhibited the -2 -1 highest photosynthetic rate (20.6 µmol CO2 m s ) followed by Parthenium hysterophorus -2 -1 (17.3 µmol CO2 m s ).

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The rate of photosynthesis got reduced in plants growing at different sites along the roadside in comparison to control (Table 4.39 a). Among sites, the maximum photosynthetic rate was noted in plants at Sadhoke site which differed non-significantly from that recorded in plants at Ferozewala site. However, the plants growing at Muridke site exhibited minimum photosynthetic activity which also did not vary significantly from that recorded in plants growing at Gujranwala site. Likewise, the rate of photosynthesis in plants at Eminabad More was statistically similar with that noted in plants at Ferozewala and Gujranwala sites.

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Table 4.39. Analysis of variance for photosynthetic rate (A) in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku)

S. O. V. d. f. S. S. M. S. F-value Plants 4 907.49 226.87 21.18*** Sites 5 1761.04 352.21 32.89*** Plants × Sites 20 46.95 2.35 0.22ns Error 60 642.58 10.71 Total 89 3358.07 *** = Significant at 0.001 level; ns = Non-significant

-2 -1 Table 4.39 a. Mean A (µmol CO2 m s ) in plants along M-2 (LSD = 0.05)

Mean A Nerium oleander L. 21.7 ± 6.00 a Parthenium hysterophorus L. 19.0 ± 5.56 b Plants Calotropis procera A. 16.6 ± 5.24 c Cenchrus ciliaris L. 14.4 ± 5.00 d Cynodon dactylon L. 12.8 ± 4.98 d Control 24.5 ± 4.77 a Sukheke 19.3 ± 4.91 b Khanqah Dogran 17.6 ± 4.36 bc Sites Pindi Bhattian 16.3 ± 4.43 c Sheikhupura 12.6 ± 3.84 d Kala Shah Kaku 11.1 ± 3.72 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.40. Analysis of variance for photosynthetic rate (A) in plants growing at different sites along G.T. road (Lahore to Gujranwala)

S. O. V. d. f. S. S. M. S. F-value Plants 4 1052.50 263.13 29.40*** Sites 5 1675.36 335.07 37.44*** Plants × Sites 20 24.60 1.23 0.14ns Error 60 536.93 8.95 Total 89 3289.39 *** = Significant at 0.001 level; ns = Non-significant

-2 -1 Table 4.40 a. Mean A (µmol CO2 m s ) in plants along G.T. road (LSD = 0.05)

Mean A

Nerium oleander L. 20.6 ± 5.72 a Plants Parthenium hysterophorus L. 17.3 ± 4.77 b Calotropis procera A. 14.1 ± 5.13 c Cenchrus ciliaris L. 12.8 ± 5.05 cd Cynodon dactylon L. 10.9 ± 4.92 d Control 23.2 ± 4.89 a Sadhoke 17.3 ± 4.16 b Sites Ferozewala 15.2 ± 4.60 bc Eminabad More 13.6 ± 4.20 cd Gujranwala 11.6 ± 4.33 de Muridke 9.97 ± 4.05 e Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.3.3. Spatial variation in photosynthetic rate of plants growing along M-2 The biplot demonstrating the photosynthetic rate in different species of plants relating to different locations adjacent to the M-2 is presented in Fig. 4.35. It indicated the association of Cenchrus ciliaris and Cynodon dactylon with Kala Shah Kaku site for their photosynthetic rate whereas Calotropis procera was found to be associated with Sheikhupura for its rate of photosynthesis. Likewise, Nerium oleander exhibited association with Control for photosynthetic rate. However, Parthenium hysterophorus was weakly associated with Sukheke as well as Khanqah Dogran site for its rate of photosynthesis. 4.3.4. Spatial variation in photosynthetic rate of plants growing along G.T. road The CCA biplot displaying the photosynthetic rate in plants relating to different sites along G.T. road has been given in Fig. 4.36. It revealed the strong association of Cynodon dactylon with Sadhoke site for photosynthetic rate, whereas Cenchrus ciliaris was associated with Eminabad More for its photosynthetic rate. However, Nerium oleander and Calotropis procera exhibited weak relation with Control and Muridke site respectively, for rate of photosynthesis in their leaves. Nevertheless, Parthenium hysterophorus did not appear to be related to any specific location for its rate of photosynthesis.

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Fig. 4.35. The CCA biplot illustrating the photosynthetic rate in plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.36. The CCA biplot illustrating the photosynthetic rate in plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.3.5. Transpiration rate (E) in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) According to the statistical analysis of data pertaining to the transpiration rate, the highly significant differences among plants and sites were documented, however their interaction remained non-significant (Table 4.40). All the plants differed significantly from one another in their transpirational rate (Table -2 -1 4.40 a). However, the maximum transpiration rate (4.61 mmol H2O m s ) was recorded in -2 -1 Nerium oleander and minimum (1.42 mmol H2O m s ) in Cynodon dactylon. The decreasing order of transpiration rate in different plants was as follow: Nerium oleander>Parthenium hysterophorus> Calotropis procera >Cenchrus ciliaris> Cynodon dactylon. All the sites along the roadside differed significantly from control in transpiration rate in plants growing at these sites. The rate of transpiration in plants growing at all the sites along the roadside was lower in comparison to control plants. However, the highest transpiration rate was recorded in plants at Sukheke site as compared to control. Minimum rate of transpiration -2 -1 i.e. 1.92 and 2.15 mmol H2O m s was recorded in plants at Kala Shah Kaku and Sheikhupura sites, respectively which were not significantly different from each other. Moreover, the transpiration rate in plants at Khanqah Dogran and Pindi Bhattian sites was also statistically similar (Table 4.40 a). 4.3.6. Transpiration rate (E) in plants growing along G.T. road (Lahore to Gujranwala) The ANOVA for data regarding the transpiration rate in different plant species at several different locations depicted highly significant differences among plants as well as sites whereas their interaction was not significant (Table 4.41). All the plants differed significantly from one another in transpiration rate in their leaves except Calotropis procera and Cenchrus ciliaris (Table 4.41 a). However, the Nerium -2 -1 oleander exhibited the highest rate of transpiration (5.83 mmol H2O m s ) followed by -2 -1 Parthenium hysterophorus (4.19 mmol H2O m s ). The least transpiration rate (2.10 mmol -2 -1 H2O m s ) was recorded in the leaves of Cynodon dactylon. The transpiration rate in plants growing at different sites along the roadsides differed significantly as compared to control. However among sites, the maximum rate of transpiration was noted in plants growing at Sadhoke site followed by that observed in plants at Ferozewala site. The plants at Muridke site exhibited the least transpiration rate which did not vary

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significantly from that documented in plant species growing at Gujranwala site. Furthermore, transpiration rate in plant species at Eminabad More site was also non-significant with that noted in plant species at Gujranwala site (Table 4.41 a).

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Table 4.41. Analysis of variance for transpiration rate (E) in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku)

S. O. V. d. f. S. S. M. S. F-value Plants 4 108.94 27.23 100.77*** Sites 5 51.31 10.26 37.97*** Plants × Sites 20 3.99 0.20 0.74ns Error 60 16.22 0.27 Total 89 180.45 *** = Significant at 0.001 level; ns = Non-significant

-2 -1 Table 4.41 a. Mean E (mmol H2O m s ) in plants along M-2 (LSD = 0.05)

Mean E Nerium oleander L. 4.61 ± 0.81 a Parthenium hysterophorus L. 3.39 ± 1.06 b Plants Calotropis procera A. 2.62 ± 1.08 c Cenchrus ciliaris L. 2.10 ± 0.86 d Cynodon dactylon L. 1.42 ± 0.71 e Control 4.21 ± 1.33 a Sukheke 3.24 ± 1.08 b Sites Khanqah Dogran 2.86 ± 1.15 c Pindi Bhattian 2.59 ± 1.23 c Sheikhupura 2.15 ± 1.36 d Kala Shah Kaku 1.92 ± 1.26 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.42. Analysis of variance for transpiration rate (E) in plants growing at different sites along G.T. road (Lahore to Gujranwala)

S. O. V. d. f. S. S. M. S. F-value Plants 4 144.04 36.00 68.53*** Sites 5 155.30 31.06 59.11*** Plants × Sites 20 9.10 0.45 0.87ns Error 60 31.53 0.53 Total 89 339.97 *** = Significant at 0.001 level, ns = Non-significant

-2 -1 Table 4.42 a. Mean E (mmol H2O m s ) in plants along G.T. road (LSD = 0.05)

Mean E Nerium oleander L. 5.83 ± 1.88 a

Parthenium hysterophorus L. 4.19 ± 1.68 b Plants Calotropis procera A. 3.32 ± 1.51 c

Cenchrus ciliaris L. 2.97 ± 1.27 c

Cynodon dactylon L. 2.10 ± 1.11 d

Control 6.16 ± 1.81 a Sadhoke 4.36 ± 1.64 b Sites Ferozewala 3.67 ± 1.67 c Eminabad More 3.12 ± 1.34 d Gujranwala 2.64 ± 1.27 de Muridke 2.14 ± 1.00 e Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.3.7. Spatial variation in transpiration rate of plants growing along M-2 The CCA biplot demonstrating the transpiration rate in different plant species relating to different locations adjacent to the G.T. road is presented in Fig. 4.38. It showed that Cenchrus ciliaris and Parthenium hysterophorus were strongly associated with Pindi Bhattian and Control respectively, for their transpiration rate. Similarly, Calotropis procera showed association with Control site, whereas Cynodon dactylon had association with Khanqah Dogran site for its transpiration rate. However, Nerium oleander appeared weakly associated with Sheikhupura site for its transpiration rate.

4.3.8. Spatial variation in transpiration rate of plants growing along G.T. road The CCA biplot showing the transpiration rate in plants relating to different sites adjacent to the M-2 is presented in Fig. 4.37. It indicated strong association of Cenchrus ciliaris with Muridke for its transpiration rate. Nerium oleander and Parthenium hysterophorus appeared to be weakly associated Sadhoke and Ferozewala site respectively, for their rate of transpiration. However, other species didn’t exhibit association with any specific location.

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Fig. 4.37. The CCA biplot illustrating the transpiration rate in plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.38. The CCA biplot illustrating the transpiration rate in plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.3.9. Stomatal conductance (gs) in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The statistical analysis (ANOVA) of data pertaining to the stomatal conductance in the leaves of plants growing at various sites adjacent to the M-2 is presented in Table 4.42. It showed highly significant differences among plants and sites whereas their interaction was not significant. A comparison among plants indicated the highest stomatal conductance (353 mmol m- 2 s-1) in the leaves of Nerium oleander followed by Parthenium hysterophorus which differed non-significantly from that noted in the leaves of Calotropis procera and Cenchrus ciliaris. However, the least stomatal conductance (209 mmol m-2 s-1) was recorded in the leaves of Cynodon dactylon which was also non-significant with that found in Cenchrus ciliaris and Calotropis procera (Table 4.42 a). All the sites along the road differed significantly from control in stomatal conductance in the leaves of plants growing at these sites. The stomatal conductance was decreased in all the plants growing at different sites along the roadside as compared to control. However, among sites the maximum stomatal conductance i.e. 317 and 294 mmol m-2 s-1 was noted in plants growing at Sukheke and Khanqah Dogran sites, respectively. The minimum stomatal conductance was detected in plants at Kala Shah Kaku site which did not vary significantly from that noted in plants at Sheikhupura site. Moreover, the stomatal conductance in the leaves of plants at Pindi Bhattian site also did not vary significantly from that recorded in the leaves of plants at Sheikhupura site (Table 4.42 a).

4.3.10. Stomatal conductance (gs) in plants growing along G.T. road (Lahore to Gujranwala) The ANOVA for data regarding the stomatal conductance in the leaves of plants growing at different sites has been given in Table 4.43. It revealed highly significant differences among plants and sites, however their interaction was non-significant. A comparison among plants revealed that stomatal conductance was maximum (292 mmol m-2 s-1) in the leaves of Nerium oleander whereas Cynodon dactylon exhibited the least stomatal conductance (183 mmol m-2 s-1) which did not differ significantly from Cenchrus ciliaris. Moreover, Parthenium hysterophorus and Calotropis procera also differed non-

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significantly from each other as well as from Cenchrus ciliaris in the stomatal conductance in their leaves (Table 4.43 a). The stomatal conductance in plants growing at different sites along G.T. road differed significantly from control. However among sites, the highest stomatal conductance was noted in the leaves of plants growing at Sadhoke site which differed non-significantly from that recorded in plants at Ferozewala site. The leaves of plants at Muridke site exhibited the minimum stomatal conductance which did not vary significantly from that recorded in plants at Gujranwala site. Likewise, the stomatal conductance in plants growing at Eminabad More site was not significantly different from that recorded in plants at Gujranwala as well as at Ferozewala site (Table 4.43 a).

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Table 4.43. Analysis of variance for stomatal conductance (gs) in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku)

S. O. V. d. f. S. S. M. S. F-value Plants 4 220244.2 55061.0 9.08*** Sites 5 660608.9 132121.8 21.78*** Plants × Sites 20 46913.2 2345.6 0.39 ns Error 60 364009.4 6066.8 Total 89 1291775.8 *** = Significant at 0.001 level; ns = Non-significant

-2 -1 Table 4.43 a. Mean gs (mmol m s ) in plants along M-2 (LSD = 0.05)

Mean gs Nerium oleander L. 353 ± 147 a Parthenium hysterophorus L. 279 ± 107 b Plants Calotropis procera A. 256 ± 105 bc Cenchrus ciliaris L. 233 ± 99 bc Cynodon dactylon L. 209 ± 95 c

Control 409 ± 117 a Sukheke 317 ± 100 b Sites Khanqah Dogran 294 ± 88 b Pindi Bhattian 226 ± 68 c Sheikhupura 201 ± 75 cd Kala Shah Kaku 146 ± 54 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.44. Analysis of variance for stomatal conductance (gs) in plants growing at different sites along G.T. road (Lahore to Gujranwala)

S. O. V. d. f. S. S. M. S. F-value Plants 4 119475.2 29868.8 9.03*** Sites 5 596075.2 119215.0 36.03*** Plants × Sites 20 35472.6 1773.6 0.54ns Error 60 198530.7 3308.8 Total 89 949553.6 *** = Significant at 0.001 level; ns = Non-significant

-2 -1 Table 4.44 a. Mean gs (mmol m s ) in plants along G.T. road (LSD = 0.05)

Mean gs Nerium oleander L. 292 ± 129 a Parthenium hysterophorus L. 235 ± 87 b Plants Calotropis procera A. 222 ± 97 b Cenchrus ciliaris L. 207 ± 90 bc Cynodon dactylon L. 183 ± 84 c Control 381 ± 111 a Sadhoke 263 ± 57 b Sites Ferozewala 236 ± 67 bc Eminabad More 196 ± 43 cd Gujranwala 158 ± 34 de Muridke 133 ± 46 e Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.3.11. Spatial variation in stomatal conductance of plants growing along M-2 The biplot describing the stomatal conductance of different species of plants relating to different locations adjacent to the M-2 is presented in Fig. 4.39. It revealed association of Calotropis procera with Khanqah Dogran, Sheikhupura, Pindi Bhattian as well as Kala Shah Kaku sites for stomatal conductance. Similarly, Nerium oleander was observed to be associated with Control site for its stomatal conductance. 4.3.12. Spatial variation in stomatal conductance of plants growing along G.T. road The CCA biplot demonstrating the stomatal conductance in plants relating to different sites adjacent to the G.T. road is presented in Fig. 4.40. It showed strong association of Cenchrus ciliaris with Ferozewala site for its stomatal conductance, whereas Parthenium hysterophorus was associated with Muridke site. Likewise, Nerium oleander appeared to be association with Control for its stomatal conductance. However, stomatal conductance in Cynodon dactylon displayed weak relation with Sadhoke.

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Fig. 4.39. The CCA biplot illustrating the stomatal conductance in plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.40. The CCA biplot illustrating the stomatal conductance in plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.3.13. Sub-stomatal CO2 concentration (Ci) in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku)

The statistical analysis (ANOVA) of data relating to the sub-stomatal CO2 concentration in the leaves of plants growing along M-2 depicted highly significant differences among plants as well as sites. Nevertheless, plants × sites interaction remained highly significant as well (Table 4.44).

All the plants differed significantly from one another in sub-stomatal CO2 concentration in their leaves (Table 4.44 a). However among plants, the leaves of Cenchrus ciliaris had the maximum (521.9 µmol mol-1) whereas Nerium oleander contained the -1 minimum (410.3 µmol mol ) sub-stomatal CO2 concentration. The overall order of sub- stomatal CO2 concentration in the leaves of different plants remained as follows: Cenchrus ciliaris>Cynodon dactylon>Calotropis procera>Parthenium hysterophorus>Nerium oleander. All the sites were significantly different from one another as well as from control in sub-stomatal CO2 concentration in plants growing at these sites (Table. 4.44 a). The sub- stomatal CO2 concentration was higher in all the plants growing at different sites along the road as compared to control. However among sites, the maximum sub-stomatal CO2 concentration was noted in the leaves of plants growing at Kala Shah Kaku site while the minimum was detected in plants at Sukheke site. The sub-stomatal CO2 concentration in plant leaves at different sites followed the order: Kala Shah Kaku>Sheikhupura>Pindi Bhattian>Khanqah Dogran>Sukheke.

4.3.14. Sub-stomatal CO2 concentration (Ci) in plants growing along G.T. road (Lahore to Gujranwala)

The ANOVA for data regarding the sub-stomatal CO2 concentration in the leaves of plants growing at different sites has been given in Table 4.45. It depicted highly significant differences among plants and sites, moreover, their interaction was also highly significant.

All the plants species differed significantly from one another in sub-stomatal CO2 concentration in their leaves (Table 4.45 a). The sub-stomatal CO2 concentration was maximum (597.1 µmol mol-1) in the leaves of Cenchrus ciliaris followed by Cynodon dactylon, Calotropis procera, Parthenium hysterophorus and Nerium oleander.

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The sub-stomatal CO2 concentration in the leaves of plants growing at different sites along the road differed significantly from control. It was higher in plants at all the sites along the roadside in comparison to control. However, the maximum sub-stomatal CO2 concentration (577.1 µmol mol-1) was noted in the leaves of plants growing at Muridke site while minimum (439.0 µmol mol-1) was recorded in plants growing at Sadhoke site. The plant leaves at

Eminabad More site contained the sub-stomatal CO2 concentration greater than that noted in plant leaves at Ferozewala site but lower than that observed in the leaves of plants at Gujranwala site (Table 4.45 a).

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Table 4.45. Analysis of variance for sub-stomatal CO2 concentration (Ci) in plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku)

S. O. V. d. f. S. S. M. S. F-value Plants 4 167372.70 41843.18 1209.21*** Sites 5 495235.28 99047.06 2862.32*** Plants × Sites 20 7795.70 389.78 11.26*** Error 60 2076.23 34.60 Total 89 672479.90 *** = Significant at 0.001 level

-1 Table 4.45 a. Mean Ci (µmol mol ) in plants along M-2 (LSD = 0.05)

Mean Ci Cenchrus ciliaris L. 522 ± 82.5 a Cynodon dactylon L. 497 ± 83.5 b Plants Calotropis procera A. 452 ± 76.0 c Parthenium hysterophorus L. 420 ± 71.2 d Nerium oleander L. 410 ± 71.4 e

Kala Shah Kaku 555 ± 49.51 a Sheikhupura 529 ± 46.9 b Sites Pindi Bhattian 493 ± 49.5 c Khanqah Dogran 437 ± 53.0 d Sukheke 409 ± 43.0 e Control 338 ± 29.9 f Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.46. Analysis of variance for sub-stomatal CO2 concentration (Ci) in plants growing at different sites along G.T. road (Lahore to Gujranwala)

S. O. V. d. f. S. S. M. S. F-value Plants 4 376708.85 94177.21 2034.16*** Sites 5 555568.26 111113.65 2399.98*** Plants × Sites 20 33576.31 1678.82 36.26*** Error 60 2777.87 46.30 Total 89 968631.29 *** = Significant at 0.001 level

-1 Table 4.46 a. Mean Ci (µmol mol ) in plants along G.T. road (LSD = 0.05)

Mean Ci Cenchrus ciliaris L. 597 ±105 a Cynodon dactylon L. 493 ± 84.7 b Plants Calotropis procera A. 464 ± 81.1 c Parthenium hysterophorus L. 433 ± 70.6 d Nerium oleander L. 412 ± 70.2 e Muridke 577 ± 75.4 a Gujranwala 548 ± 68.5 b Sites Eminabad More 515 ± 68.4 c Ferozewala 458 ± 80.8 d Sadhoke 439 ± 83.8 e Control 340 ± 29.7 f Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.3.15. Spatial variation in sub-stomatal CO2 concentration in plants growing along M-2

The CCA biplot displaying the sub-stomatal CO2 concentration in plants relating to various sites adjacent to the M-2 is presented in Fig. 4.41. It showed that sub-stomatal CO2 concentration in Cynodon dactylon was associated with Khanqah Dogran site, whereas Parthenium hysterophorus appeared to be associated with Pindi Bhattian site for its sub- stomatal CO2 concentration. However, Cenchrus ciliaris showed weak association with

Khanqah Dogran site for its sub-stomatal CO2 concentration. Calotropis procera and Nerium oleander were not observed to be linked with any specific location for their sub-stomatal CO2 concentration.

4.3.16. Spatial variation in sub-stomatal CO2 concentration in plants growing along G.T. road

The canonical correspondence analysis biplot displaying the sub-stomatal CO2 concentration in in plants relating to various sites along G.T. road has been presented in Fig. 4.42. The CCA biplot indicated strong association of Calotropis procera with Ferozewala for its sub-stomatal CO2 concentration. Cynodon dactylon and Cenchrus ciliaris showed association with Eminabad More site for its sub-stomatal CO2 concentration. Similarly,

Nerium oleander was associated with Control site for sub-stomatal CO2 concentration. However, Parthenium hysterophorus was not related to any one location for its sub-stomatal

CO2 concentration.

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Fig. 4.41. The CCA biplot illustrating the sub-stomatal CO2 concentration in plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.42. The CCA biplot illustrating the sub-stomatal CO2 concentration in plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala

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4.3.17. Water use efficiency (WUE) in plants growing along M-2 (Pindi Bhattian to Kala Shah Kaku) The statistical analysis (ANOVA) of data regarding the water use efficiency in plants along M-2 showed highly significant differences among plants as well as sites. Similarly, plants × sites interaction also existed highly significant (Table 4.46). All the plants differed significantly from one another in their water use efficiency (Table 4.46 a). However among plants, Cynodon dactylon exhibited the maximum (9.68) whereas Nerium oleander showed the minimum (4.65) water use efficiency. The overall order of water use efficiency in plants remained as follows: Cynodon dactylon>Cenchrus ciliaris>Calotropis procera> Parthenium hysterophorus>Nerium oleander. All the sites along the road differed significantly from control in water use efficiency of plants growing at these sites except Sadhoke (Table 4.46 a). The water use efficiency got increased in the plants growing at all the sites as compared to control. However, the plants growing at Kala Shah Kaku site exhibited the maximum water use efficiency which did not vary significantly from that recorded in plants at Sheikhupura and Pindi Bhattian sites. 4.3.18. Water use efficiency (WUE) in plants growing along G.T. road (Lahore to Gujranwala) The ANOVA for data relating to the water use efficiency in plants growing at various sites has been given in Table 4.47. It illustrated highly significant differences among plants and sites whereas their interaction was highly significant as well. It was observed that the water use efficiency of Calotropis procera was maximum (5.36) while it was minimum (3.59) in Nerium oleander. However, water use efficiency did not differ significantly among Cynodon dactylon, Parthenium hysterophorus and Cenchrus ciliaris (Table 4.47 a). The water use efficiency in plants growing at different sites along the roadside differed significantly from control. It got increased in plants at all the sites along the roadside as compared to control. However among sites, the maximum water use efficiency (4.77) was noted in plants growing at Muridke site which did not differ significantly from that recorded in plants at Gujranwala and Eminabad More sites. The water use efficiency of the plants growing at Ferozewala site was also non-significantly different from that observed in plants at Gujranwala and Eminabad More sites. Moreover, the water use efficiency of the plants growing at Sadhoke site was minimum (4.17) (Table 4.47 a).

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Table 4.47. Analysis of variance for water use efficiency (WUE) of plants growing at different sites along M-2 (Pindi Bhattian to Kala Shah Kaku)

S. O. V. d. f. S. S. M. S. F-value Plants 4 259.14 64.78 222.84*** Sites 5 19.22 3.84 13.22*** Plants × Sites 20 58.36 2.92 10.04*** Error 60 17.44 0.29 Total 89 354.16 *** = Significant at 0.001 level

Table 4.47 a. Mean WUE of plants along M-2 (LSD = 0.05)

Mean WUE Cynodon dactylon L. 9.68 ± 1.77 a Cenchrus ciliaris L. 7.11 ± 1.08 b Plants Calotropis procera A. 6.56 ± 0.74 c Parthenium hysterophorus L. 5.64 ± 0.52 d Nerium oleander L. 4.65 ± 0.68 e Kala Shah Kaku 7.23 ± 2.87 a

Sheikhupura 7.19 ± 2.60 a

Pindi Bhattian 7.07 ± 2.18 a Sites Khanqah Dogran 6.58 ± 1.41 b Sukheke 6.18 ± 0.90 c Control 6.11 ± 1.17 c

Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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Table 4.48. Analysis of variance for water use efficiency (WUE) of plants growing at different sites along G.T. road (Lahore to Gujranwala)

S. O. V. d. f. S. S. M. S. F-value Plants 4 28.34 7.09 107.56*** Sites 5 8.46 1.69 25.69*** Plants × Sites 20 14.29 0.71 10.85*** Error 60 3.95 0.07

Total 89 55.06 *** = Significant at 0.001 level

Table 4.48 a. Mean WUE of plants along G.T. road (LSD = 0.05)

Mean WUE Cynodon dactylon L. 5.36 ± 0.68 a Cenchrus ciliaris L. 4.43 ± 0.49 b Plants Calotropis procera A. 4.37 ± 0.80 b Parthenium hysterophorus L. 4.36 ± 0.40 b Nerium oleander L. 3.59 ± 0.24 c

Muridke 4.77 ± 0.79 a Gujranwala 4.62 ± 0.70 ab Sites Eminabad More 4.59 ± 0.70 ab Ferozewala 4.52 ± 1.03 b Sadhoke 4.17 ± 0.69 c Control 3.87 ± 0.44 d Each value is a mean ± SD. The sample size for calculating means and SD of different variables was as follows, n = 18 for plants, n = 15 for sites. Means in a sub-column sharing same letter differ non-significantly.

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4.3.19. Spatial variation in water use efficiency of plants growing along M-2 The CCA biplot describing the water use efficiency of plant species relating to different locations adjacent to the M-2 is presented in Fig. 4.43. It showed that water use efficiency of Cenchrus ciliaris was associated with Kala Shah Kaku as well as Pindi Bhattian sites, whereas Nerium oleander showed association with Control site for its water use efficiency. However, Calotropis procera found to be weakly associated with Khanqah Dogran site for its water use efficiency. 4.3.20. Spatial variation in water use efficiency of plants growing along G.T. road The CCA biplot showing the water use efficiency of plants relating to different sites adjacent to the G.T. road has been given in Fig. 4.44. It showed that Cenchrus ciliaris and Nerium oleander were associated with Sadhoke and Control sites respectively, for their water use efficiency. Calotropis procera showed association with Eminabad More site for its high water use efficiency. 4.3.21. Correlation between metal contents and gas exchange parameters in plants The correlation between metal contents in plants and their gas exchange parameters has been given in Table 4.48. The photosynthetic rate, transpiration rate, and stomatal conductance were negatively related to metal contents in plants. However, the sub-stomatal CO2 concentration in plants exhibited positive correlation with metal contents.

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Fig. 4.43. The CCA biplot illustrating the water use efficiency of plants relating to different sites along M-2. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as PB: Pindi Bhattian; SU: Sukheke; KD: Khanqah Dogran; SH: Sheikhupura; KSK: Kala Shah Kaku

Fig. 4.44. The CCA biplot illustrating the water use efficiency of plants relating to different sites along G.T. road. Where, Plant species have been abbreviated as Cp: Calotropis procera; Cc: Cenchrus ciliaris; Cd: Cynodon dactylon; No: Nerium oleander; Ph: Parthenium hysterophorus. Sites have been abbreviated as FE: Ferozewala; MU: Muridke; SA: Sadhoke; EM: Eminabad More; GU: Gujranwala.

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Table 4.49: Pearson's correlation coefficient between metal contents and gas exchange parameters in plants along the roads

A E gs Ci WUE M-2 G.T. road M-2 G.T. road M-2 G.T. road M-2 G.T. road M-2 G.T. road Pb Calotropis procera -0.970* -0.932* -0.967* -0.931* -0.958* -0.903* 0.928* 0.855* 0.865* 0.639 ns Nerium oleander -0.951* -0.952* -0.989*** -0.917* -0.972** -0.977*** 0.913* 0.852* -0.756 ns 0.606 ns Cynodon dactylon -0.978*** -0.916* -0.973** -0.914* -0.968* -0.922* 0.984*** 0.869* 0.843* 0.421 ns Parthenium hysterophorus -0.961* -0.953* -0.975*** -0.917* -0.986*** -0.915* 0.944* 0.881* 0.110 ns 0.253 ns Cenchrus ciliaris -0.975** -0.912* -0.938* -0.948* -0.977*** -0.935* 0.981*** 0.993*** 0.694ns 0.786 ns Cd Calotropis procera -0.994*** -0.987*** -0.996*** -0.982*** -0.977*** -0.971** 0.977*** 0.931* 0.931* 0.730 ns Nerium oleander -0.970* -0.991*** -0.922* -0.976*** -0.948* -0.972** 0.990*** 0.930* -0.883* 0.753 ns Cenchrus ciliaris -0.971** -0.931* -0.952* -0.934* -0.990*** -0.950* 0.989*** 0.981*** 0.733 ns 0.855* Parthenium hysterophorus -0.982*** -0.967* -0.971** -0.927* -0.980*** -0.950* 0.957* 0.910* 0.060 ns 0.303 ns Cynodon dactylon -0.983*** -0.952* -0.988*** -0.949* -0.958* -0.944* 0.984*** 0.893* 0.862* 0.481 ns Cu Nerium oleander -0.961* -0.963* -0.974*** -0.930* -0.987*** -0.978*** 0.939* 0.879* -0.790 ns 0.636 ns Calotropis procera -0.980*** -0.955* -0.994*** -0.960* -0.965* -0.932* 0.985*** 0.898* 0.963* 0.669 ns Cynodon dactylon -0.884* -0.943* -0.949* -0.916* -0.974*** -0.967* 0.954* 0.941* 0.990*** 0.377 ns Parthenium hysterophorus -0.983*** -0.966* -0.971** -0.927* -0.985*** -0.940* 0.994*** 0.913* 0.053 ns 0.286 ns Cenchrus ciliaris -0.945* -0.934* -0.946* -0.953* -0.978*** -0.953* 0.984*** 0.992*** 0.732 ns 0.829* Ni Calotropis procera -0.975*** -0.967* -0.988*** -0.968* -0.956* -0.947* 0.944* 0.909* 0.931* 0.718 ns Nerium oleander -0.959* -0.926* -0.994*** -0.883* -0.965* -0.965* 0.930* 0.807 -0.772 ns 0.539 ns Cynodon dactylon -0.980*** -0.868* -0.981*** -0.882* -0.931* -0.872* 0.972** 0.812* 0.814* 0.458 ns Parthenium hysterophorus -0.902* -0.940* -0.971*** -0.894* -0.947* -0.902* 0.877* 0.873* 0.279 ns 0.354 ns Cenchrus ciliaris -0.956* -0.860* -0.819* -0.924* -0.864* -0.896* 0.914* 0.978*** 0.445 ns 0.715 ns Zn Nerium oleander -0.948* -0.962* -0.993*** -0.927* -0.971** -0.977*** 0.921* 0.870* -0.748 ns 0.628 ns Calotropis procera -0.952* -0.935* -0.981*** -0.937* -0.920* -0.905* 0.918* 0.859* 0.937* 0.600 ns Cynodon dactylon -0.972** -0.934* -0.993*** -0.941* -0.978*** -0.925* 0.988*** 0.872* 0.901* 0.488 ns Parthenium hysterophorus -0.951* -0.961* -0.985*** -0.922* -0.981*** -0.930* 0.940* 0.904* 0.183 ns 0.295 ns Cenchrus ciliaris -0.990*** -0.899* -0.949* -0.948* -0.968* -0.930* 0.994*** 0.992*** 0.678ns 0.770 ns ***, ** and * = Significant at 0.001, 0.01 and 0.05 respectively; ns = Non-significant

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CHAPTER 5 DISCUSSION 5.1. Spatio-temporal variation in metal contents along roadsides Automobile traffic is a primary source of heavy metal pollution along the roadside environment (Mafuyai et al., 2015; Padoan et al., 2017). Lead (Pb), cadmium (Cd), zinc (Zn) copper (Cu) and nickel (Ni) have been reported to be major heavy metal pollutants present in the vehicular traffic emissions along the roads (Lough et al., 2005; Dolan et al., 2006; Zhang et al., 2015; Huber et al., 2016). The plants in the vicinity of roads are highly vulnerable to this vehicle-sourced metal contamination. In current study, higher contents of Cd, Pb, Ni, Cu and Zn were recorded in plant leaves and soil samples taken from different sites along both M-2 and G.T road in comparison to those of control site. These finding are in agreement with various previous studies (Osakwe and Okolie, 2015; Staszewski et al., 2015; Munyati, 2016). Plants have always been in practice as a tool to monitor environmental pollution, particularly soil contamination by heavy metals (Wiseman et al., 2013; Novo et al., 2017; Sidi et al., 2018). Metals are directly taken up by leaves of plants through atmospheric deposition or metals get deposited in the soil are taken up by plants via roots and then translocated to other parts through active uptake mechanism (Panda and Rai, 2015; Galal and Shehata, 2015). Metals taken up by plants are transformed, bio-concentrated and subsequently are passed on to animals and ultimately via food chain become a potential risk to human health (Atayese et al., 2009; Guala et al., 2010; Oyeleke et al., 2016). In present study, plant species growing at different sites under study responded differently to different heavy metals during different seasons. 5.1.1. Lead (Pb) It has been considered as the second most toxic metal after Arsenic by the agency for Toxic Substances and Disease Registry (ATSDR, 2011). This metal is non-essential and toxic to living organisms even in extremely low concentrations (Mendil and Tuzen, 2011). During present study, the Pb concentration was much higher in both plants and soil along the roadside as compared to their control samples. Increased Pb contamination along the roadside has also been reported by other researchers (Manno et al., 2006; Atayese et al., 2009; Sharma and Prasad, 2010). The Pb contamination along the roadside environment is likely to have derived from vehicle exhaust fumes comprising some lead-rich aerosols. (Zakir et al., 2014). High

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level of Pb along the roadside can also be attributed to wearing of brake linings and tyres of vehicle (Zhang et al., 2012). Metal contamination is highly dependent on traffic load and it decreases as the distance from the road increases (Adedeji et al., 2013). In present investigation, Pb was found at an alarming level in plants at various sites along both roads. Its content in various plants at different sites ranged from 4.77 to 8.83 mg/kg dry wt. along M-2 and from 9.56 to 14.0 mg/kg dry wt. along G.T. road. The Pb concentration in all the studied plant species was much higher than the maximum permissible limit (2 mg/kg) in plants (WHO, 1996). The highest level of Pb in the soil was 19.7 and 29.2 mg/kg dry wt. along M-2 and G.T. road, respectively. The Pb contamination in soil also exceeded the maximum allowable limits (3 mg/kg) recommended by WHO (Pirzada et al., 2009). Some plants growing on metal contaminated soil uptake metal from soil and act as tools for monitoring the extent of metal pollution (Atayese et al., 2010; Malizia et al., 2012; Joshi et al., 2016). During present study, the variation in Pb content in both plants and soil at various sites showed direct correlation with traffic density. The highest Pb contamination was documented in both soil and plants at Muridke site along G.T. road. The high contamination at this site may be ascribed to high volume of traffic and low atmospheric dispersion due to relatively congested road. Along M-2, the maximum Pb contamination both in soil and plants was documented at Kala Shah Kaku site. The high Pb content at this site might be attributed to high traffic density. Many previous studies support my results that high vehicular activity strongly contributes towards extent of metal contamination (Ijeoma et al., 2011; Rolli et al., 2015; Deepalakshmi et al., 2014). High speed of vehicles may also have contributed to high Pb content at this site moreover, grey, yellow and red road paints which have been used to mark M-2 also added to degree of Pb contamination (Adachi and Tainosho, 2004; Ozaki et al., 2004; Duong and Lee, 2011). However, a comparison between M-2 and G.T. road showed higher Pb contamination in both soil and plants collected from G.T. road which might be due to much higher traffic density at this road. As the surface of this road is not very smooth, so break use efficiency may be another contributing factor to Pb contamination (Duong and Lee, 2011). The heavy loaded trucks running on the G.T. road also added to Pb pollution along this road because they have numerous Pb containing substances linked with them such as wheel balance weights which tremendously contribute to Pb pollution caused by traffic (Suzuki et al., 2009). The Pb content in roadside plants mainly depends on the degree of Pb exposure

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(Salam et al., 2015). Greater vehicular exhaust emissions (Hamzeh et al., 2011; Rodríguez- Seijo et al. 2015) and high frequency of break use might also be contributing to high Pb contamination (Denier and Appelman, 2009; Zakir et al., 2014) along G.T. road. In the current study, the order of Pb accumulation in plants growing at all the studied sites during four seasons was as follows: Calotropis procera>Nerium oleander>Parthenium hysterophorus>Cenchrus ciliaris >Cynodon dactylon. The ability of these plants to accumulate high contents of Pb supported the idea to use them as good choice for monitoring environmental Pb pollution. However, Calotropis procera accumulated the highest Pb content as compared to other plant species along both M-2 and G.T. road. Hence, this study suggests that Calotropis procera can be the best choice for phytomonitoring of Pb pollution. Tiwari and Pandey (2016) also reported high Pb content in leaves of Calotropis procera growing along the roadside in Bilaspur city of India. The metal accumulation ability of different plant species depends on the plant genotype and ecological factors (Pottier et al., 2015). The results of current study are in corroboration with those described by D’Souza et al., (2010) who described that Calotropis procera has good phytoextraction potential as revealed by the accumulation ratios in natural conditions. They also found high Pb accumulation in leaves of C. procera growing at different contaminated sites. In another study, Barthwal et al. (2008) also observed that C. procera accumulated higher Pb content in comparison to other studied medicinal plants along highways with volume of traffic. In the present study, the level of Pb contamination was significantly different during different seasons along both M-2 and G.T road. The maximum level of Pb contamination was noted during summer season in both soil and plants along the roads. The Pb contamination in plants along both roads was in the following order: winter

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(Brekken and Steinnes, 2004; Eid, 2009). Similar to the current study, higher Pb content in plants during summer season was also reported by Begum et al. (2015). The level of Pb contamination along the roadsides noted during current study was much higher than those reported by some workers in other parts of the world (Adeniyi and Owoade, 2009; Christiana and Samuel, 2013; Ubwa et al., 2013; Osakwe and Okolie., 2015) but was still lower than some other studies (Christoforidis and Stamatis, 2009; Chen et al., 2010; Aslam et al., 2013; Nazzal et al., 2014; Rodriguez-Seijo et al., 2017). However Pb content recorded in current study was lower than those reported in other parts of the country which might be due to difference in road conditions and traffic density. For example, Farrukh et al. (2005) noted high contamination of Pb in plants growing along the roadsides in Karachi. Faiz et al. (2009) recorded much higher content of Pb (104 mg/kg) in dust collected from a busiest road in Islamabad. In another study carried out in Peshawar, Pakistan, Khan et al., 2011 observed high content of Pb in soil (53 mg/kg) and plants (49.1 mg/kg) growing along the roadside. Vehicular traffic is a major source of Pb pollution in soil and plants in Quetta, city of Pakistan (Khattak et al., 2013). The government of Pakistan has directed refineries to phase out the use of Pb in petrol. -1 The allowable limit of Pb in petrol is 0.02 gL (Khan et al., 2011). However, in current study, high content of Pb was detected in diesel and petrol although fuel suppliers claim for the supply of unleaded fuel. Moreover, low-quality leaded petrol is smuggled from the neighboring countries to Pakistan and its unmonitored sale continues, which may be the major cause of Pb contamination in soil along the roadside (Ilyas, 2009). The occurrence of Pb in fuel is one of the main causes of Pb contamination in the current study sites. Yang et al. (2016) also reported that Pb originated from the combustion of leaded-fuel is the primary pollution element along the roadside in China. In Bangladesh, the use of leaded gasoline in the vehicles has been observed as the key source of Pb contamination (Bhowmick et al., 2015). During current investigation, high content of Pb was also found in the soot and used motor oil from the vehicles which might be a strong contributing factor to high contamination of Pb in the roadsides environment. 5.1.2. Cadmium (Cd) Another significantly important metal pollutant along the roadsides is Cd, which is considered among the most toxic heavy metals for biota (Smolders and Mertens, 2013; Tran

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and Popova, 2013). In the present study, it was observed that Cd content in both soil and plants along roadsides was much higher than their control samples. Findings similar to this study have also been described by previous workers (Tanee and Albert, 2013; Hu et al., 2014; Çolak et al., 2016). The mean Cd content varied from 1.29 to 2.78 mg/kg in plants leaves and from 4.10 to7.54 mg/kg in soil along M-2 while along G.T. road it ranged 2.20-3.93 mg/kg in leaves of plants and 6.44-10.0 mg/kg in soil. The Cd content in the leaves of all the roadside plant species under study exceeded the maximum permissible limit (0.02 mg/kg) proposed by WHO (WHO, 1996). The Cd contamination in soil along both roads was also above the maximum allowable limit (0.4-1.0 mg/kg) for this metal in soil (European Commission Director General Environment, ECDGE., 2010). Cadmium is released into roadside environment by the burning of fuel, oil leakage, wearing out of tires and corrosion of batteries and radiators (Akbar et al., 2006; Ewen et al., 2009). German Informative Inventory Report (2017) also showed that a significant quantity of Cd is released from brake wear and tires of automobiles. The contents of Cd found during this study are consistent with the values obtained in previous studies (Shi et al., 2008; Khan et al., 2011; Shafiq et al., 2011). However, Deska et al. (2011) reported much lower Cd content (0.195-0.303 mg/kg) in soils adjacent to the road (European Track) as compared to that noted in our study. Similarly, the Cd content ranged 0.08-0.53 and 0.00-0.10 mg/kg in soils and plants along the roadside in Elazig, Turkey (Bakirdere and Yaman 2008). An average of 1.72 mg/kg Cd concentration was noted in road dust collected from Düzce, Turkey (Taspinar et al., 2015). The content of Cd ranged from 0.06-0.59 mg/kg in roadside soil of Melbourne city, Australia (De-Silva et al., 2016). Rolli et al., (2016) found that concentration of Cd varied from 1.51-2.08 and 1.15 to 1.52 mg/kg in soil and Cynodon dactylon respectively along a road in Bagalkot, India. Some plants growing on the metal polluted sites uptake metal and accumulate in different organs. During the current study, the highest Cd contamination in both soil and plants was noted at Muridke site along G.T. road, while along M-2, Cd contamination was maximum at Kala Shah Kaku site as compared to other sites. These are the sites with the highest traffic load and Cd contamination at each site showed a linear relation with traffic density along both roads. The Cd content in plant leaves also positively correlated with soil Cd content. Previous studies also reported a strong correlation between plant metal content and soil metal content ( Galal and Shehata, 2015). Several studies have shown that the level of Cd accumulation along

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the roadside directly correlates with the traffic intensity (Falusi, 2010; Sharma and Prasad, 2010; Ogbonna et al., 2013; Ozturk et al., 2017). Differential spatial distribution of Cd along the roadside depends on volume of traffic, proximity to road, differential land use (Wang et al., 2014) and vehicle emissions (Zhang et al., 2012). The soil and plants along G.T. road exhibited more Cd contamination as compared to those along M-2. Higher traffic load at this road is a major cause of higher Cd contamination along this road. Moreover, heavy loaded trucks, trailers and vehicles using old worn over tires are frequently travelling on G.T. road which is roughly surfaced and thus increases the wearing of tires. All these factors contribute to high Cd content along this road (Abechi et al., 2010). The volume and type of vehicular traffic as well as the condition of the road affect the distribution and enrichment of metal along the roadside (Chen et al., 2010; Wiseman et al., 2013). The intensity of vehicular traffic also remains very high along G.T. road. Very old age of the G.T road may also be a contributing factor to high Cd contamination. The level of metal contamination highly depends on the age of the road. The old aged roads have high risk of significant metal deposition and retention in soils for long period of time (De-Silva et al., 2016). Strong spatial variation in Cd concentration in soil along the roadside in a region of Yunnun province, China was reported by Jian-Jun et al. (2006). In current study, Cd content varied among plant species. Among plants, Calotropis procera amassed the maximum Cd content in comparison to the other plant species whereas Cynodon dactylon accumulated the minimum amount of Cd. Jankowski et al. (2015) reported that different species of plants differ in their capacity to accumulate Cd. Thus, present study suggests that Calotropis procera is the best choice for biomonitoring of Cd pollution in the environment. Nevertheless, contrary to my results, Deepalakshmi et al. (2014) found highest Cd content in Cynodon dactylon as compared to other plant species in their investigation and suggested that this plant can be used as indicator of Cd pollution along busy roadways. However, similar to the results of this study, Gajbhiye et al. (2016) also found that Calotropis procera had high potential for foliar uptake of Cd, so it is suitable for monitoring of Cd pollution along the roadsides. Cadmium concentration in plants also depends on the Cd content in soil and the intensity of the dust emission containing this metal (Abollino et al., 2002; Li et al., 2008; Petrotou et al., 2012). Significantly positive correlations were noticed among the contents of Cd in C. procera and C. colocynthis and those in sediments, indicating the potential

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use of these two plants for monitoring of Cd in polluted area (Al-Yemni et al., 2011). Al- Qahtani, (2012) has reported that C. procera has high capacity for the uptake and accumulation of heavy metals into its tissues due to its ability to absorb and tolerate metals without severe physiological damage. During current study, the concentration of Cd showed significant seasonal variation along both roads. The highest concentration of Cd was recorded during summer season in soil as well as in plants growing along both roads. As Cd is mainly emitted from burning of fuels in vehicles and vehicle tires (Chen et al., 2010), so the high level of Cd contamination in summer could be attributed to greater wear and tear of tires due to the high temperature of the region and high number of vehicles. The results of this study are in agreement with Harmens et al. (2007). Sharma et al. (2007) also reported higher Cd concentration in Beta vularis during summer than during winter season. Spatial as well as temporal variation in Cd content has also been documented by several other workers, for example, Backstorm et al. (2004) found temporal variation in Cd content in soils along the roadsides of Sweden whereas Feng et al. (2012) reported spatial variation in amount of Cd in soil and plants along a highway in East China. Pathak et al. (2013) also reported spatio-temporal variation in soil Cd concentration. In this study, traces of Cd were observed in petrol (0.984±0.027), diesel (0.884±0.070), used motor oil (1.05-2.16) and soot (1.11-3.57) samples which also contributed to the high Cd contamination along the roadside. Lin et al. (2005) also reported a strong association of Cd with diesel fuel. Davis et al. (2001) found 20 µg/L Cd in used motor oil. Ramadass et al. (2015) noted 0.04 µg/L Cd in used motor oil while it was not observed in unused motor oil indicating that Cd is emitted from vehicles during different operations. Nevertheless, the contents of Cd observed in the present investigation were less than those noted by Atiku et al. (2011) in diesel (3.316 ppm) and gasoline (10.708 ppm) samples in Nigeria. The high Cd content in soot may add to the environmental metal contamination (Atiku et al., 2011). 5.1.3. Copper (Cu) Copper is a micronutrient essential for many physiological processes necessary for growth and development of plants (Burkhead et al., 2009) but may become toxic to plants when it is in excess concentration (Cuypers et al., 2011). In present investigation, Cu was found to be the second most abundant metal pollutant along the roadside. Copper concentration was higher in soil and plant leaves collected from all the sites along the roads as compared to

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control samples. Increased level of Cu in plants and soil subjected to vehicular pollution has also been reported in earlier studies (El-Khawas, 2011; Hassan and Basahi, 2013; Dao et al., 2014; Wang et al., 2014; Naderizadeh et al., 2016). These results propose that the plants and soil adjacent to the roads get highly polluted with Cu metal. The source of this high Cu concentration could be ascribed to the corrosion of metallic components of vehicles such as brush wear, engine wear and thrust bearing (Al-Khashman, 2004; Al-Khashman and Shawabkeh, 2006). Copper can also be emitted into the roadside environment because of deterioration of the oil pump or rusting of metal parts of automobiles (Lu et al., 2010; Yang et al., 2016). Brake emissions through vehicle-related activities are the major source of elevated levels of Cu along the roadside (Yesilonis et al., 2008; Amato et al., 2010; Zhang et al., 2015). The order of Cu contamination in plants was as follows: Nerium oleander>Calotropis procera >Parthenium hysterophorus>Cenchrus ciliaris>Cynodon dactylon. During present investigation, Cu content in almost all the plant species exceeded the maximum permissible limit of Cu (10 mg/kg) in plants (WHO, 2005). As Nerium oleander accumulated the highest amount of Cu as compared to other plant species under study, this species can be considered as the best choice for monitoring and remediation of Cu contaminated sites. Similar findings were also reported by Oliva and Epinosa (2007). However, Deepalakshmi et al. (2014) reported Ageratum conyzoides and Terminalia catappa as the possible Cu pollution indicators as compared to other plant species in their study along the roadways in India. Abdullatif et al. (2016) observed Calotropis procera as a good accumulator of Cu and they proposed that this plant could be employed as a protecting belt at polluted sites. Cynodon dactylon also has bioaccumulation potential, so is also a suitable choice for decontamination purposes (Lion et al., 2016). Significant spatial variation in roadside soil and plant Cu contents was observed during this study. The Cu contamination in roadside plant leaves and soil varied from 6.63-19.59 mg/kg and 22.40-38.03 mg/kg respectively along M-2 while along G.T. road it ranged from 14.14-30.35 mg/kg and 30.36-50.76 mg/kg respectively. The Cu content in plants showed a linear correlation with soil Cu content. The results of this study are supported by Galal and Shehata, 2015. The highest Cu contamination was recorded at Muridke site along G.T. road while along M-2 maximum Cu contamination was recorded at Kala Shah Kaku site as compared to other sites. Variation in Cu content at various sites was associated with traffic

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density. The traffic density was also highest at Kala Shah Kaku site along M-2 and Muridke site along G.T. road. A significant positive correlation of metal contents in plant leaves and soil with traffic density at various sites was observed. High volume of traffic lead to the elevated emissions of metal (Ozturk et al., 2017). Previous studies also showed positive relations of plant and soil heavy metal contents with traffic density (Chen et al., 2010; Azeez et al., 2014; Assirey and El-Shahawi, 2015). A comparison between roads for Cu contamination showed that plants and soil along G.T. road were more contaminated than those along M-2. Higher traffic density along G.T. road might be a major factor responsible for high Cu contamination. Moreover, vehicles along G.T. road have to perform more driving manoeuvres, such as break and turn. High frequency of brake use leading to more abrasion of breaks and tyres is responsible for high level of Cu contamination (Roubicek et al., 2008; Bukowiecki et al., 2009; Crosby et al. 2014; Ferreira et al., 2016). Low atmospheric dispersion due to relatively congested road might also be a contributing factor to high metal contamination. Strong spatial variation in Cu content was also reported by Sun et al. (2010) in Shenyang, China and Dao et al. (2014) in Dublin, Ireland. Copper concentration in both plants and soil along the roadside varied significantly during different seasons. Highest quantity of Cu in both plants and soil was noted during summer season while lowest was recorded during winter season. Overall trend of Cu content during four seasons was as follows: summer> autumn> spring> winter. High Cu contamination during summer season could be due to very high temperature of the region which might have led to the increased metal emissions from the vehicles. There is always more abrasion of tyres at high temperature (Guangchang, 2016) which might have resulted in high heavy metal content during summer season. Similar to my findings, Bozdoğan (2016) also found high level of Cu in the leaves of Melia azedarach growing along the roadside during summer season as compared to autumn season. However, results of this study are contrary to the findings of Norouzi et al. (2017). Some quantities of Cu were also found in petrol, diesel, soot and used motor oil samples analyzed during the present study. The presence of Cu content in these materials might have significantly contributed to the Cu contamination along the roadside soil and plants. Betha et al. (2012) also observed traces of Cu in fuel and used motor oil. Pulles et al. (2012) reported that fuel and lubricating oil in vehicles are responsible for higher Cu content

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in soil along the roadside Lin et al. (2005) reported strong association of Cu with gasoline fuel which contributed to metal pollution in the environment. The level of Cu found along the roadsides soil and plants in present study is in agreement with the results of other studies (Kakulu, 2003; Abdul-Wahab, 2004; Bakirdere and Yaman, 2008). However, the content of Cu found during this study was lower than the content reported by some workers in others parts of the world (Ahmed and Ishiga, 2006; Okunola et al., 2007; Yahaya et al., 2009) while it was higher than some other studies (Bai et al., 2008; Abechi et al., 2010; Dao et al., 2014) which might be due to the use of poor quality fuel or differences in road conditions/traffic density in those areas. 5.1.4. Nickel (Ni) It is a micronutrient, required by plants in very low quantity and is a part of urease and several other enzymes involved in plant metabolism. However, in high concentrations it becomes toxic for plants (Chen et al., 2009) and its phytotoxicity is considered to be more significant than its deficiency (Shafeeq et al., 2012). In the present study, Ni concentration was higher in both soil and plants growing along the roadside as compared to their control samples. Several earlier researcher have also reported high contamination of Ni in soil and plants along the roadside (Osakwe and Okolie, 2015; Abass et al., 2016; Ma et al., 2016). During the current study, high Ni concentration might be ascribed to several Ni valves, shafts, bearings and crankshafts in vehicles, which after rusting can emit metal into environment (Al-Kashman, 2004; Christoforidis and Stamatis, 2009; Techenomics International, 2016). However, some researchers are of the view that exhaust fumes produced by the combustion of oil mainly contribute to Pb and Ni in roadside environment (Johansson et al., 2009; Pey et al., 2010; Khan et al., 2011). Significant spatial variation in Ni content in roadside soil and plant leaves was noted along both roads. Both soil and plant samples exhibited the maximum Ni contamination at Muridke site along G.T. road, and at Kala shah Kaku site along M-2. The level of Ni contamination in roadside plant leaves was 9.93-15.07 mg/kg dry wt. while in soil it was 19.2- 35.6 mg/kg dry wt. along M-2. The Ni concentration in various plants ranged from 16.63-22.23 mg/kg dry wt. and in soil it varied from 27.2-41.3 mg/kg dry wt. along G.T. road. All the plant species exhibited Ni content higher than the maximum permissible limit (10 mg/kg) for plants established by WHO (WHO, 2005). The Ni contamination at each site directly related to the

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traffic density at that particular site. Highest traffic density was recorded at Kala Shah Kaku site along M-2 and Muridke site along G.T. road. As far as roads are concerned, more traffic flow was observed along G.T. road justifying the higher Ni contamination along this road as compared to M-2. Degree of Ni contamination along the roadways strongly correlates with the traffic load (Naser et al., 2012). The results of this study are in conformity with many previous reports (Arslan and Gizir, 2004; Assirey and El-Shahawi, 2015; Galal and Shehata, 2015). High Ni content along G.T. road could also be due to differences in type of traffic, rate of brake usage, as well as proximity of various towns (Modrzewska and Wyszkowski, 2014). Among plant species studied during present investigation, the leaves of Calotropis procera accumulated the highest Ni content as compared to other plants. Hence, this plant species can be considered as a good phytomonitor/phytoremediator of Ni pollution. Tiwari and Pandey (2016) also reported that among three roadside plant species studied in India, Calotropis procera had the highest metal accumulation capacity. Lottermoser (2011) also suggested C. procera as Ni accumulator. Badr et al. (2012) suggested Phragmite australis and Cyperus laevigatus as the best candidates for phytomonitoring/phytoremediation of soil Ni pollution in contrast to C. procera, which was proposed as good phytoremediator of Cu, Cd and Zn polluted soils in Riyadh City, Saudi Arabia. Akguc et al. (2010) reported Pyracantha coccinea as biomonitor species for Cu and Ni pollution. In another study, Karaaslan and Yaman (2013) found highest Ni concentration in the leaves of Cidrus libani among the studied plant species and concluded that this plant species can be employed as a biomonitor of Ni contamination in Elazig, Turkey. Soleimani et al. (2009) stated that Cynodon dactylon has ability to accumulate significant quantity of Ni in shoots but cannot be labelled as Ni hyperaccumulator. In the present study, Ni concentration differed significantly during the four seasons. Maximum contamination of Ni was recorded during summer. The high Ni concentration in plants and soil during summer may be attributed to very high temperature of the region. The results of this study are parallel to the findings of Bozdogan (2016) who found high Ni content during summer season in comparison to autumn in the leaves of Melia azedarach growing along the roads in Antakya, Turkey. In another study, Moreki et al. (2013) found high content of Ni in the roadside plants in Botswana during hot and dry season in comparison to rainy season.

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The Ni concentrations recorded during the present study are comparable to those reported by Awadh (2015) and De-Silva et al. (2016). The values of Ni obtained during this study are, however, higher than those reported by some researchers in other parts of the world, which might be due to differences in traffic density and other road conditions. For example, average Ni content was 4.47 mg/kg dry wt. in plants species growing along urban roadsides in Istanbul, Turkey (Yasar et al., 2010). Mathew and Orie (2015) found an average amount of Ni i.e. 2.4 mg/kg in deposits of sand along some main roads in Nigeria. Radziemska and Fronczyk (2015) also reported a much higher concentration of Ni in soil along an expressway in Poland. Rolli et al. (2016) reported Ni content in the range of 69.5-108.6 mg/kg in roadside soil, 7.9- 13.1 mg/kg in Caesalpinnia pulcherrima and 8.1-15.1 mg/kg in Cynodon dactylon growing along the roadside in Bagalkot, India. In another study, Wang et al. (2014) found average concentrations of 32.4 mg/kg Ni in soils and 4.03 mg/kg Ni in wild grasses along the roadside in the Qinghai-Tibet Plateau, China. Considerable quantities of Ni were also noted in petrol, diesel, used motor oil and soot samples analyzed during current study. The high content of Ni in fuels may be mainly responsible for high Ni concentration in roadside environment (Al-Shayeb and Seaward, 2001; Iwegbue et al., 2013). Kurian and Gupta (2016) also found high Ni content in soot. It was also reported that burning of Ni containing petrol and diesel contributes a considerable quantity of Ni to the atmosphere (Baralkiewicz and Siepak, 1999; Kacar et al., 2002). Ramadass et al. (2015) also found high Ni content in used motor oil. The highest amount of Ni was recorded in soot and used motor oil from trucks. So, trucks pose a greater risk of Ni pollution as compared to cars and buses along the road. 5.1.5. Zinc (Zn) Zinc as an essential micronutrient for plants is a constituent of numerous proteins and enzymes required for different metabolic pathways. Nevertheless, in excessive quantities above the nutritional threshold, Zn is a potentially toxic metal pollutant (Khudsar et al., 2004; Ozdener and Aydin, 2010). Among all the metals investigated during current study, Zn was found to be the most abundant metal in both soil and plants along the roadside. Significantly higher Zn contents were observed in soil and leaves of plants growing at all the sites along both M-2 and G.T. road as compared to those at their control sites (~ 50 m away from road). The Zn contamination of roadside plants and soil has also been reported in previous studies

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(Matthews-Amune and Kingsley, 2013; Nwachukwu et al., 2013; Ubwa et al., 2013; Zakir et al., 2014; Osakwe and Okolie., 2015; Iwuoha et al., 2015; Trujillo-González et al., 2016). Tyre treads contain natural rubber copolymers and Zn that is added to the tyres during vulcanization (Chen et al., 2012; Pant and Harrison, 2013), so wear and tear of vulcanized vehicle tires has been recognized as a significant source of Zn in roadside environment (Zhang et al., 2015). Zinc, because of its heat conducting properties is usually used in brake linings of vehicles and can be released during mechanical abrasion and from combustion of fuel in engine (Manno et al., 2006; Świetlik et al., 2013; Christiana and Samuel, 2013). Loss of oil and cooling liquid of vehicles as well as wearing of road surface may also contribute to Zn contamination along the roads (Saeedi et al., 2009). Significant spatial variation in Zn content in both soil and plant leaves was noted along both roads (M-2 and G.T. road). The highest Zn contamination along G.T. road was noted at Muridke site, while along M-2, Zn contamination was maximum at Kala Shah Kaku site. The high quantity of Zn at these locations may be ascribed to the high intensity of traffic at these sites. Several studies have reported that metal contamination along the roadsides strongly correlates with the volume of traffic (Popescu, 2011; Adengala et al., 2016; Crosby et al., 2014; Zhang et al., 2017). A comparison between roads showed higher Zn contamination along the G.T. road in comparison to M-2. This might be due to higher traffic density at G.T. road. Another reason for this high contamination may be that the surface of G.T. road is not so smooth thus more abrasion with tires could have contributed to the higher content of Zn (Abechi et al., 2010; Pant and Harrison, 2013) which run off the road and become incorporated into the soil along the roadside after precipitation. Metal emissions from vehicles depend upon the age, engine type and also the maintenance of vehicles (Peltier et al., 2011). Moreover, along G.T. road, comparatively old vehicles having worn over tires are commonly used and vehicles use brakes more frequently. Therefore the wearing of brake linings, corrosion of galvanized vehicle body parts and wearing of moving engine parts contribute significant quantities of Zn along the roadside (Al-Khashman, 2007; Wei et al., 2010; Malinowska et al., 2015). The level of Zn contamination along road also depends upon the age of the road and is positively related to the lifetime traffic count (Morse et al., 2016). In the present study, Zn concentration varied from 53.9-83.2 mg/kg dry wt. in roadside plant species and 92.2-151.4 mg/kg dry wt. in soil along M-2 while along G.T. road it ranged

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from 72.1-103.9 mg/kg dry wt. and 124.0-176.4 mg/kg dry wt. in a roadside plants and soil, respectively. Nevertheless, the range of values for Zn found in this study is higher in comparison to those reported in various other regions of the world, for instance, Sanyaolu et al. (2011) noted a much lower Zn content (4.85 mg/kg) in the leaves of plants growing along a very busy road in Ikorodu- Lagos, Nigeria. Zinc concentration ranged from 23.2-67.0 mg/kg in roadside soil along a highway in Egypt (Elnazer et al., 2015), while level of Zn varied from 65.8 to 712 mg kg⁻¹ in soils along the highway in the Ashanti region of Ghana and was higher than those observed in this study (Adengala et al., 2016). Similarly, in another study conducted along a road with heavy traffic in Kwara State, Nigeria, the Zn concentrations in plants and soil ranged from 13.0-120 mg/kg and 30.8-219 mg/kg respectively (Ogundele et al., 2015). The allowable limit of Zn in soil is 100-150 mg/kg (European Commission Director General Environment, ECDGE., 2010) The uptake of Zn by plants at different sites showed a linear relationship with Zn content in soil most of the times. These results are in conformity with Kabata-Pendias (2011). The order of Zn accumulation in different plant species was: Nerium oleander>Calotropis procera>Parthenium hysterophorus>Cenchrus ciliaris>Cynodon dactylon along both M-2 and G.T. road. Zinc concentration in all the plant species under investigation exceeded the maximum permissible limit i.e. 50 mg/kg for plants established by WHO (WHO, 2005), except at the control sites. Among plant species, Nerium oleander accumulated the highest content of Zn in comparison to other species of plants. Hence, curent study suggests Nerium oleander as the best biomonitor of Zn contamination among studied plant species. It has the Zn accumulation potential and can be used as a good choice for the remediation of polluted sites (Elloumi et al., 2017). Different plant species differ in their ability to accumulate heavy metals and even same plants species have different potential of different metals uptake and translocation to their parts (Zabin and Howladar, 2015). Nerium oleander has previously been recognized as a suitable plant species to be used as a biomonitor for metal pollution (Oliva et al., 2007; Rossini and Mingorance, 2004) and it has been reported to be a valuable bioindicator for the Zn pollution (Mingorance et al., 2007). In ecological sensitive regions, plantation of tolerant plant species along the roadsides is appropriate and can be used for the refurbishment of ecosystems in urban areas (Rai, 2016). Such plants species have ability to accumulate contaminants and protect the soil and water bodies from adulteration (Heintzma et al., 2015).

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In a study, Bae et al. (2016) identified Lotus corniculatus as potential candidate for the remediation of Zn contaminated sites along the roadside. In another study, Ageratum conyzoides and Ricinus communis accumulated the highest Zn content along some busy roadways in India, and thus these plants were suggested as indicators of Zn pollution (Deepalakshmi et al., 2014). A significant temporal variation in Zn concentration was recorded during different seasons in both plants and soil along the roadside. The highest Zn concentration was noted during summer season while the lowest was recorded in winter season along both roads. The Zn contamination in both plants and soil along the roadside during different seasons existed in the following order: winter

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soot varied from 0.5 to 3 mg/kg. Therefore, it can be concluded that considerable magnitude of Zn in roadside environment derives from the soot of the vehicles (Malinowska et al., 2015). 5.2. Effects of metals on biochemical and physiological parameters of plants 5.2.1. Photosynthetic pigments Plants respond to environmental adversities, so they can be used as indicators for assessing the environment quality. In this regard, the biochemical parameters such as contents of chlorophyll and carotenoid are used as reliable indicator of the toxicity of heavy metals in plants (Paulus et al., 2010; Gomes et al., 2014). Heavy metals cause deleterious effects on chlorophylls and carotenoids which are involved in photosynthetic mechanism in plants, thus indirectly reducing the photosynthetic activity (Aggarwal et al., 2012). Decline in photosynthetic pigments is observed as a communal response to metal stress in different species of plants (Jiang et al., 2012; Liu et al., 2013; Chen et al., 2015; Zouari et al., 2016). According to the results of the current study, the contents of chlorophyll a, chlorophyll b, total chlorophyll and carotenoids were significantly lower in plants growing at all the sites along the roadside as compared to their control plants. Among plant species, Cynodon dactylon contained the lowest content of almost all the studied photosynthetic pigments. Along G.T. road, the least content of photosynthetic pigments was recorded in plants growing at Muridke site, recognized as the most heavy metal polluted site. Among sites along M-2, the minimum content of chlorophyll pigments was noted in plants at Kala Shah Kaku site along with Sheikhupura site while carotenoid content was minimum in plants at Kala Shah Kaku and Sheikhupura sites which did not differ significantly. The decrease in chlorophyll and carotenoid contents under the influence of heavy metals has also been reported by various researchers (Jamers et al., 2009; Pooja et al., 2012; Zhang et al., 2014; Abass et al., 2016). Elevated levels of heavy metals obtained in present study could be responsible for the reduction in chlorophyll content, which might be the consequence of the disruption in chlorophyll biosynthesis caused by the inhibition of enzymes i.e. δ-aminolevulinic acid dehydratase and protochlorophyllide reductase being crucial for the synthesis of chlorophyll (Pourraut et al., 2011; Huang et al., 2013; Parmar et al., 2013; Elloumi et al., 2014; Rai et al., 2016). Moreover, significant negative correlation between metal contents in plants and chlorophyll pigments demonstrated the stress caused by metlas. Findings of this study are also supported by Nadgorska-Socha et al., 2016.

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Moreover, metals (Cd, Cu) can replace the labile bonded central Mg atom of chlorophyll molecules, resulting in its degraded structure (Kupper et al., 2003; Gillet et al., 2006; Touiserkani and Haddad, 2012; Gomes et al., 2015) and can also cause direct oxidative damage to the pigments (Oláh et al., 2010) thus decreasing their content. Degradation of chlorophyll has been interrelated with different heavy metals stresses in several plant species (Cozzolino et al., 2010; Gupta et al., 2013). Metals can also reduce the chlorophyll content by disrupting the synthesis of proteins involved in chlorophyll and photosynthesis, for example chlorophyll a/b binding proteins as well as subunits of photosystem II (Duquesnoy et al., 2009; Walliwalagedara et al., 2010; Zeng et al., 2011). Decrease in carotenoid contents might have severe consequences because carotenoids serve as non-enzymatic antioxidants against free radicals and the photochemical damage (Strzalka et al., 2003; Sengar et al., 2008). Carotenoids quench the oxidizing species, triplet chlorophyll and other excited molecules in the pigment bed, which can disrupt metabolism by causing oxidative damage to cellular components (Candan and Tarhan, 2003). However under stress the protective function of carotenoids modifies, leading to the pigment degradation and cellular destruction (Sharma and Tripathi, 2009). In a former study, Panda et al. (2015) reported that environmental pollution caused by soot can decrease the contents of photosynthetic pigments in plants. In another study, Iqbal et al. (2015) reported that pollutants from vehicular activities reduced the amount of chlorophyll a, b and total chlorophyll in roadside plants in Karachi, Pakistan. 5.2.2. Total soluble proteins During the present investigation, the total soluble proteins in all plant species growing along the roads were significantly lower as compared to those in control plants. High metal contamination found in this study might be responsible for decrease in protein content of roadside plants. The reduction in protein content of plants in response to heavy metals stress has also been reported by several scientists (Doganlar et al., 2010; Ashraf et al., 2011; Srivastava et al., 2011; Ashraf et al., 2016). This decline in protein content may be ascribed to inhibition of protein formation or to enhanced protein degradation induced by the accumulation of heavy metal in plants (Monteiro et al., 2009; Wang et al., 2009; Chen et al., 2010). Heavy metals cause various functional and structural modifications by the fragmentation and denaturation of proteins (John et al., 2009) and bind to the sulfhydryl group (SH-group) of

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proteins, causing modifications in their structures thus impede the protein activity (Prasad and Strzalka, 2002; Pal et al., 2006; Vinod et al., 2012). The reduction in total soluble protein concentration may also be due to enhanced protease activity (Palma et al., 2002) or enhanced protein hydrolysis (Kumar et al., 2011) caused by catalytic activity of metals accumulated in plants (Bhardwaj et al., 2009). Proteins are recognized as the vital constituents of the cell, and have been identified to be damaged easily under environmental stresses (Prasad, 1996; Wu et al., 2010). Protein content was found to be well correlated with the heavy metals contamination (Bauddh and Singh, 2015). So, decrease in protein content is an indication of heavy metal toxicity in plants (Seregin and Kozhevenikova, 2006). 5.2.3. Total free Amino acids Amino acids are the precursors to and constituents of proteins, and serve a substantial role in stress metabolism of plants. In the present investigation, the content of total free amino acids was higher in all the selected plant species growing at different sites adjacent to both M- 2 and G.T. road as compared to that in control plants. This higher content of free amino acids in plants along the roadside could be attributed to elevated levels of heavy metals. The findings of this study are in in conformity with several previous studies that have reported an increase in content of free amino acids in plants as a consequence of metal toxicity (Bhardwaj et al., 2009; Zemanova et al., 2013; Shackira et al., 2017). Plant under heavy metals stress accumulate various metabolites for example betaine, antioxidants, nicotianamine, polyamines, proline and several free amino acids, which help in reducing the stress by binding to the metallic particles. These metabolites accumulate due to the activation of defense system of plants in response to metal stress (Sharma and Dietz, 2006) thus protect the plant from metal toxicity (Clemens, 2001). Pavlikove et al. (2014) found an increase in amount of free amino acids (methionine, proline, leucine and γ-aminobutyrate) in tobacco plant under Zn stress. They also concluded that metal tolerance ability of plants is associated with accumulation of amino acids under metal stress. Therefore, increase in free amino acids in plants under metal stress indicates the ability of those particular plants to tolerate metals (Xu et al., 2012). During present investigation the highest amount of free amino acids was noted in Nerium oleander followed by Calotropis procera indicating that these plants have high metal tolerance abilities and could be used for phytomonitoring and/or phytoremediation of metal polluted sites.

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5.2.4. Total antioxidant activity During the current study, total antioxidant activity was found to be higher in the leaves of all the selected plants growing at different sites adjacent to M-2 and G.T. road as compared to their control plants. The high heavy metal contamination found at these sites might be responsible for the elevated level of antioxidant activity in plants. Several previous studies have also reported the increased antioxidant activity in plants under heavy metal stress (Zhang et al., 2014b; Balestri et al., 2014; Ehsan et al., 2014; Sidhu et al., 2017; Hussain et al., 2017). Excessive accumulation of heavy metals induces the generation of ROS that cause oxidative stress in plants (Kaur et al., 2015; Petrov et al., 2015). To ease the detrimental effects of ROS under stress conditions, plants have developed antioxidant defense systems (Bhaduri and Fluekar, 2011; Saidi et al., 2013; Zouari et al., 2016; Akhtar et al., 2017) which restrains and reduces the oxidative damage, and enhances the stress resistance in plants (Suzuki et al., 2012). Among plants under present study, Calotropis procera showed the highest total antioxidant activity along both M-2 and G.T. road. The order of total antioxidant activity in different plant species along both roads was as follows: Calotropis procera > Nerium oleander > Parthenium hysterophorus > Cenchrus ciliaris > Cynodon dactylon. The robust and efficient response of antioxidants helps to evaluate the capability of plants to tolerate the environmental stress (Sharma et al., 2012; Sidhu et al., 2016). The production and activity of antioxidants in plants under stressful conditions depends not only on the level of the stress, but also on the plant species, the duration of stress exposure, the extent of plant tolerance and the prevailing ecological conditions (Ahmed et al., 2010). Nadgorska et al., 2013 reported increase in antioxidant responses of Plantago lanceolata and Cardaminopsis arenosa growing on metal (Pb, Cd, Cu, Zn) contaminated sites. The antioxidant response in these plants directly correlated with the metal contents (Cd, Pb, Zn) concentrations. Mohasseli et al. (2016) also noticed an elevated antioxidant activity of maple leaves due to heavy metal contamination along the roads with high volume of traffic. Patidar et al. (2016) reported that traffic-associated pollution caused oxidative stress in plants along the roadside. Therefore, high antioxidant activity in plants at the roadside was a defensive response to stress injuries. This conclusion is in agreement with findings of Al-Hassan et al. (2017).

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5.2.5. Gas exchange parameters Regarding the physiological attributes of plants, gas exchange parameters are of great importance (Ashraf, 2009). In the current study, photosynthetic rate, stomatal conductance, and transpiration rate were significantly lower, while, water use efficiency and sub-stomatal

CO2 concentration were significantly higher in all plant species growing at different sites along the roadside as compared to their control plants. Similar findings had also been reported by other researchers (Hassan et al., 2013; Muhammad et al., 2014; Bao et al., 2015; Khalid et al., 2017). Elevated levels of heavy metals found during present study might be responsible for the reduction in gas exchange parameters of plants growing at the roadside. Moreover, significant correlations observed between metal contents in plants and their gas exchange parameters suggest the stress caused by metals. According to Vassilev and Yordanov (1997) and Varone et al. (2012), the decline in photosynthetic activity in plants under metal stress could be attributed to either (1) stomatal closure, which caused a reduction in stomatal conductance and thus diffusion of carbon dioxide or (2) the non-stomatal limitations. The non-stomatal limitations of photosynthetic activity might be described by modifications in chloroplast ultrastructure, photosynthetic electron transport reactions, structure of thylakoid membranes, efficiency of Rubisco for fixation of CO2 and quenching ability of excessive energy (Monteiro et al., 2009; Asgher et al., 2014; Zhang et al., 2014a). Under the influence of pollutants, the stomatal conductance was low which led to a decline in photosynthetic rate and rise in internal CO2 concentration of plant leaves (Qadir et al., 2016). In another study, Moradi and Ehsanzadeh (2015) also reported a decrease in net photosynthetic rate as well as stomatal conductance and increase in sub-stomatal CO2 concentration in plants under metal stress. Photosynthetic activity was inhibited in various plants under Cd stress (Asgher et al., 2013; Li et al., 2013; Zhang et al., 2014b). The increase in water use efficiency was found in plants under Cd stress (Li et al., 2015), because plants close their stomata to minimize the rate of transpiration (Greger and Johansson, 2006). The lower transpiration rate and higher water use efficiency in plants along roadsides might be due to storage of water reserves by plants under metal stress which restricts the water uptake efficiency of plants via roots (Veselov et al., 2003). The decrease in gas exchange attributes of plants growing near the roadside might be due to the deposition of Pb and Cd which block the stomatal aperture resulting in decreased photosynthetic activity (Nawazish et

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al., 2012). The physiological parameters studied during the current investigation revealed their use as biomarkers for estimating and monitoring the preliminary effects of metal pollution. 5.3. Conclusion  Heavy metal (Cd, Cu, Ni, Pb and Zn) contents in soil and plants along the roadsides was significantly higher in comparison to their control samples. Almost all the metals were above the permissible limits set by WHO/ECDGE.  Spatial variation in metal concentrations was also recorded. The concentrations of all tested heavy metals were higher in plant and soil samples collected close to the G.T. road as compared to those of M-2.  Kala Shah Kaku site at M-2 and Muridke site at G.T. road were identified as the most heavy metal polluted sites. These sites were placed at the top priority level in terms of possible ecological threat.  The highest contents of studied metals in roadside plant species and soil were noted in summer and least during winter. These results showed that metal contents also varied temporally and the summer season can be suggested as good for the phytomonitoring studies.  Heavy metal pollution in vicinity of roads was found to be positively correlated with traffic density.  The heavy metal contamination along roads significantly decreased the contents of chlorophyll a, b, total chlorophyll, carotenoids and total soluble proteins in roadside plants. Photosynthetic rate, stomatal conductance and transpiration rate were also lower in roadside plants. Nevertheless, total antioxidant activity, total free amino acids water

use efficiency and sub-stomatal CO2 concentration, were higher in roadside plants as compared to control plants (~ 50 m away from road).  The results also showed that Calotropis procera is a potential accumulator of Pb, Cd, and Ni whereas, Nerium oleander has a potential to accumulate Cu and Zn metal. So these plants are recommended as good choice for phytomonitoring purposes. Recommendations / Future perspectives . Vehicular traffic emissions are the major cause of metal accumulation in roadside environment including plants and soil, which could have an ecological influence on them. The examination of heavy metals in the environment along the roadside is

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important in evaluating the potential ecological effects of vehicular emissions on the soil and plants. Therefore, it is necessary to evaluate the amount of metals in the surrounding areas of roads with high volume of traffic in other parts of the nation as well. . The usage of antiknock agent in the motorvehicles alternative to tetraethyl lead could be useful for reducing the lead (Pb) pollution produced from smoke of automobiles. . The use of motor-oil additives having large amounts of Ni and Zn, used particularly by truck drivers in order to improve engine performance

should be prohibited. . Moreover, the use of old and studded tires should be avoided. . The spatial and seasonal distribution of heavy metals indicates that risk avoidance and alleviation actions must be directed keeping all these considerations in account. . Despite the stress induced by metals, the studied plants particularly Nerium oleander and Calotropis procera were flourishing well in the polluted roadside environment. Thus, these species of plants can be used as biomonitors or/and for the remediation of heavy metal contaminated sites in all those areas which have prevailing environmental conditions similar to the studied area.

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CHAPTER 6 SUMMARY Vehicular sector has become a major source of metal pollution along the roadside environment all over the world and Pb, Cd, Cu, Ni and Zn are most common metal pollutants present in the vehicular emissions. Therefore, the current project was designed to phytomonitor the extent of metal pollution caused by vehicles running along two roads i.e. a segment of Motorway (M-2) from Pindi Bhattian to Kala Shah Kaku and a segment of Grand Trunk road (G.T. road) from Lahore to Gujranwala in Punjab, Pakistan. Five sites on each of both roads and five commonly growing wild plant species i.e. Calotropis procera, Cenchrus ciliaris, Cynodon dactylon, Nerium oleander and Parthenium hysterophorus along both roads were selected for data collection. Samples of soil and plant leaves were also collected at a distance of 50 meter away from the roadside (Control). For sampling and collection of data, survey was conducted in the four seasons i.e. autumn, spring, summer and winter of the year 2015-16. All the collected soil and plant leaf samples were digested following appropriate protocol and Pb, Cd, Cu, Ni and Zn were determined using Atomic Absorption Spectrophotometer (AAS). Fuel i.e. diesel and petrol samples obtained from different fuel stations near the roads, soot samples taken from the exhaust pipes of different vehicles and the used motor oil samples from automobiles were examined for Cd, Cu, Pb, Zn and Ni contents as well. Traffic density at all the sites along both roads was also recorded during the four seasons for specific period of time. In order to evaluate the effects of vehicular released metal pollutants on roadside plants, several physio-biochemical parameters were studied. Among physiological parameters, photosynthetic rate, stomatal conductance, transpiration rate, sub-stomatal CO2 concentration and water use efficiency were measured by IRGA (Infrared Gas Analyzer). Among biochemical parameters, the contents of photosynthetic pigments such as chlorophyll a and b, total chlorophyll and carotenoids, as well as total soluble proteins, total free amino acids and total antioxidant activity were determined using spectrophotometer. The results revealed significantly higher contents of all the studied metals in both soil and plants collected from various sites along the roadside in comparison to their control samples. The contents of metals in both soil and plants were in the order: Cd

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The contents of all the metals in almost all the roadside plants and soil samples were above the maximum permissible limits proposed by WHO/ECDGE. The highest contents of all the metals in both the soil and plants were noted during summer while the least contents were recorded during winter. The high contents of metals were also obtained in petrol, diesel, soot and used motor oil samples. The contents of metals in plants and soil indicated significant positive correlation with traffic density most of the times. Physiological attributes i.e. photosynthetic rate, transpiration rate and stomatal conductance got significantly reduced while sub-stomatal CO2 concentration and water use efficiency were increased in all the plant species along the roadsides. The contents of chlorophyll a, chlorophyll b, total chlorophyll, carotenoids and total soluble proteins were also significantly lower whereas total antioxidant activity and free amino acids were higher in roadside plant species under metal stress. The higher contents of all the metals were noted along G. T. road as compared to M-2. However, Kala Shah Kaku site along M-2 whereas Muridke site along G.T. road appeared as the most polluted sites. The highest accumulation of Pb, Cd and Ni was noted in Calotropis procera while Nerium oleander accumulated the highest concentrations of Cu and Zn. Hence, these plant species can be suggested as the good choice as phytomonitors and/or phytoremediators of the metal pollution.

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