Dedicated
to
my Family
Table of Contents
Chapter #. Title. Page Acknowledgments ii List of Tables iii List of Figures iv List of Plates vii List of Abbreviations viii List of published/accepted/submitted research papers xi Abstract xii 1. Introduction 1 2. Literature Review 9 3. Materials and Methods 40 4. Results 47 5. Discussion 96 6. Conclusion 102 7. Recommendation 103 8. References 104 Appendix I Plates Appendix II Research paper (Published) Appendix III Research paper (Published) Appendix IV Research paper (Published) Appendix V Research paper (submitted) Appendix VI Supplementary graphs Appendix VII Details of selected species according to e-flora of Pakistan
i
ACKNOWLEDGEMENTS
All praises and thanks are to Almighty ALLAH, Who is entire source of knowledge and wisdom endowed to mankind and all respects are for His Last Prophet Hazrat Mohammad Peace Be Upon Him.
Special thanks to my praiseworthy supervisor, Dr. Safdar Ali Mirza for his guidance, valuable suggestions, inspirations and moral buck up in all situations during PhD.
I want to cordially thank respectable Dr. Ghazala Yasmeen Butt for her ever- lashing kindness and time-to-time technical tips. I am thankful to Botany faculty particularly Dr. Zaheer-ud-din Khan and Mr. Umer Hayyat for their support and cooperation in the study. I extend my thanks to the administrative, technical and other staff of my department.
I am grateful to my fellows Mr. Saad Ullah and Mr. Sohaib Mohammad for their heartfelt cooperation and buck up.
Heartiest gratitude to my parents, family members and friends for their prayers.
Thanks to my husband, Dr. Muhammad Farhan and our little tot, Taha Farhan and Dua Farhan for their continuous love and stress bearing attitude.
Amina Kanwal
ii
List of Tables
Table Title Page # Table 4.1. Average physio-chemical characteristics of wastewaters 47 Table 4.2. Impact of wastewaters on seed germination (%) of selected 49 tree species Table 4.3. Impact of WWs on height (cm) of selected tree species 62 Table 4.4. Impact of WWs on FW (g) of selected tree species 65 Table 4.5. Impact of different wastewaters on DW (g) of selected tree 68 species Table 4.6. Impact of different wastewaters on photosynthetic rate of 73 selected tree species Table 4.7. Impact of different wastewaters on stomatal conductance 76 of selected tree species Table 4.8. Impact of different wastewaters on transpiration rate of 79 selected tree species Table 4.9 MDA content (µmol/g FW) in leaf of selected tree species 82 in different wastewater concentrations Table 4.10 Proline (µg/g FW) content in leaf of selected tree species 85 in different wastewater concentrations Table 4.11 Heavy metals uptake rate of selected tree species in 86 different wastewater concentrations Table 4.12 Heavy metal translocation factor of selected tree species in 92 different wastewater concentrations
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List of Figures
Figure Caption Page # Figure 4.1. Germination response of selected five tree species in 50 DWW Figure 4.2. Germination response of selected five tree species in 50 HWW Figure 4.3. Germination response of five tree species in IWW 51 Figure 4.4. “Mean time to germination” of selected plant species in 52 DWW Figure 4.5. “Mean time to germination” of selected plant species in 52 IWW Figure 4.6. “Mean time to germination” of selected plant species in 53 HWW Figure 4.7. Seedling fresh weight of selected plant species in DWW 54 Figure 4.8. Seedling fresh weight of selected plant species in HWW 54 Figure 4.9. Seedling fresh weight of selected plant species in IWW 55 Figure 4.10. Seedling length of selected five plant species in DWW 56 Figure 4.11. Seedling length of selected five plant species in HWW 56 Figure 4.12. Seedling length of selected five plant species in IWW 57 Figure 4.13. Vigor Index of selected plant species in DWW 58 Figure 4.14. Vigor Index of selected plant species in IWW 58 Figure 4.15. Vigor Index of selected plant species in HWW 59 Figure 4.16. Tolerance Index of selected plant species in DWW 60 Figure 4.17. Tolerance Index of selected plant species in IWW 60 Figure 4.18. Tolerance Index of selected plant species in HWW 61 Figure 4.19. Height response of selected five plant species in DWW 63 Figure 4.20. Height response of selected five plant species in HWW 63 Figure 4.21. Height response of selected five plant species in IWW 64 Figure 4.22. Fresh weight response of selected five plant species in 66 DWW Figure 4.23. Fresh weight response of selected five plant species in 66 HWW
iv
Figure Caption Page # Figure 4.24. Fresh weight response of selected five plant species in 67 IWW Figure 4.25. Dry weight response of selected five plant species in 69 DWW Figure 4.26. Dry weight response of selected five plant species in 69 HWW Figure 4.27. Dry weight response of selected five plant species in IWW 70 Figure 4.28. Change in photosynthetic rate of selected five plant 71 species in DWW Figure 4.29. Change in photosynthetic rate of selected five plant 72 species in HWW Figure 4.30. Change in photosynthetic rate of selected five plant 72 species in IWW Figure 4.31. Change in stomatal conductance of selected five plant 74 species in DWW Figure 4.32. Changes in stomatal conductance of selected five plant 75 species in HWW Figure 4.33. Changes in stomatal conductance of selected five plant 75 species in IWW Figure 4.34. Change in Transpiration rate of selected five plant species 77 in DWW Figure 4.35. Changes in Transpiration rate of selected five plant species 78 in HWW Figure 4.36. Changes in Transpiration rate of selected five plant species 78 in IWW Figure 4.37 Changes in MDA content of selected five plant species in 80 DWW Figure 4.38 Changes in MDA content of selected five plant species in 81 HWW
Figure 4.39 Changes in MDA content of selected five plant species in 81 IWW
v
Figure Caption Page # Figure 4.40 Changes in proline content of selected five plant species in 83 DWW Figure 4.41 Changes in proline content of selected five plant species in 84 HWW
Figure 4.42 Changes in proline content of selected five plant species in 84 IWW
Figure 4.43 Chromium bioaccumulation in selected five plant species 88 in IWW Figure 4.44 Copper bioaccumulation in selected five plant species in 88 IWW Figure 4.45 Manganese bioaccumulation in selected five plant species 89 in IWW Figure 4.46 Lead bioaccumulation in five selected plant species in 89 IWW Figure 4.47 Chromium bioaccumulation in selected five plant species 90 in HWW Figure 4.48 Copper bioaccumulation in selected five plant species in 90 HWW Figure 4.49 Manganese bioaccumulation in selected five plant species 91 in HWW Figure 4.50 Lead bioaccumulation in selected five plant species in 91 DWW
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List of Plates
Table Title Plate 1 Collection of DWW Plate 2 Collection site of DWW at River Ravi Plate 3 Collection of HWW
Plate 4 Collection of HWW
Plate 5 Collection of IWW
Plate 6 Collection of IWW
Plate 7 Response of Albizia lebbeck in HWW
Plate 8 Response of Albizia lebbeck in DWW
Plate 9 Response of Albizia lebbeck in IWW
Plate 10 Response of Millettia peguensis in IWW
Plate 11 Response of Millettia peguensis in DWW
Plate 12 Response of Millettia peguensis in HWW
Plate 13 Response of Bauhinia purpurea in HWW
Plate 14 Response of Bauhinia purpurea in IWW
Plate 15 Response of Bauhinia purpurea in DWW
Plate 16 Response of Dalbergia sissoo in HWW
Plate 17 Response of Dalbergia sissoo in IWW
Plate 18 Response of Dalbergia sissoo in DWW
Plate 19 Response of Pongamia pinnata in IWW
Plate 20 Response of Pongamia pinnata in HWW
Plate 21 Response of Pongamia pinnata in DWW
vii
List of Abbreviations
µgg -1 Microgram per gram
µg/ml Microgram per milliliter APX Ascorbate peroxidase
As Arsenic Ba Barium BCF Bio-concentration factor BF Bioaccumulation factor BOD Biological oxygen demand CAT Catalase
Cd Cadmium CMR Chlorophyll meter readings Co Cobalt COD Chemical oxygen demand Cr Chromium Cu Copper DW Dry weight
DWW Domestic Wastewater
EC Electrical conductivity F Transfer factor FA Fly ash Fe Iron FW Fresh weight
GB Glycine betaine
GR Glutathione reductase
GST Glutathione S-transferase
GW Ground water
H2O2 Hydrogen per oxide Hg Mercury
viii
HgCl 2 Mercuric chloride HM Heavy metals
HM/R Heavy metal / radionuclide Hsp70 Heat Shock Proteins 70 HWW Hospital Wastewater
IWW Industrial Wastewater
LPO Lipid peroxidation
MDA Malondialdehyde Mg Magnesium mgg -1 Milligram per gram mgkg -1 Milligram per kilogram mgL -1 Milligram per liter min Minute Mn Manganese Mo Molybdenum MTG Mean time to germination
MWW Municipal wastewater NEQS National Environmental Quality Standards Ni Nickel nm Nanometer nmolg -1 Nanomole per gram
OCPs Organo-chlorine pesticides OM Organic matter Pb Lead pH -ve log of H + concentration ppm Parts per million R Correlation coefficient RF Remediation factor ROS Reactive oxygen species SC Stomatal conductance Se Selenium
ix
SL Seedling length
SOD Superoxide dismutase
SW Sewage wastewater TDS Total dissolved solids TEM Transmission electron microscopy TF Translocation Factor
Tha -1 Tons per hectare TI Tolerance index
TSS Total suspended solids VI Vigor index
WW Wastewater
WWT Wastewater types xg Resolution Zn Zinc
x
Published Research paper
S. # Title Appendix
1. Amina Kanwal , Safdar Ali Mirza And Muhammad Farhan. II 2015 . Exploring Germination Potential of tree species in DWW for use in urban Forestry. Pakistan Journal of Botany ., 47(SI): 275-280.
2. Amina Kanwal and Safdar Ali. 2017. Germination response of III five tree species on hospital wastewater. International Journal of Bioscience ., 10(1): 81-90.
3. Amina Kanwal , Safdar Ali Mirza and Muhammad Farhan. 2017. IV Natural plant based solution for industrial wastewater. Journal of Biodiversity and environmental sciences., 10(6): 83-91
Submitted paper
S. # Title Appendix
Amina Kanwal , Safdar Ali, Muhammad Farhan. Exploring 1. V sustainability of Heavy Metal Phytoextraction by Indigenous Tree Species of Family Fabaceae. International Journal of phytoremediation
xi
Abstract
The present study highlights the possibility of using wastewater for forest irrigation. This study was conducted in 2 phases, first phase was the seed germination study of the five selected species and the second phase was of growth of plants through pot experiment. Five tree species selected for the study were, Dalbergia sissoo Roxb ., Albizia lebbeck (L.) Benth,
Pongamia pinnata (L.) Pierre, Bauhinia purpurea L. and Millettia peguensis Ali. Three types of wastewater were collected, first from industrial wastewater (IWW), second from hospital wastewater (HWW) and third from domestic wastewater (DWW). Germination experiment was set up in Petri dishes and seeds were irrigated with different concentrations of WWs. In pot experiment the five tree species were planted in pots and were irrigated with 5 different concentrations (0%, 25%, 50%, 75% and 100%) of WWs. Germination study results revealed that the five plant species survived in the WW irrigation and showed sufficient tolerance. The maximum germination was of Dalbergia sissoo i.e. 74%. The toxicity of different WWs is as follows: IWW > HWW > DWW
The mean time to germination of Millettia peguensis was 95 hrs and of Albizia lebbeck was 80 hrs. Similarly, all the five species showed positive increase in seedling fresh weight, dry weight and seedling length. Maximum fresh weight was observed in
Dalbergia sissoo (0.64 g) and the lowest fresh weight was reported in Millettia peguensis (0.35). The order of tolerance index and vigor index among the five species is as follows; Dalbergia sissoo > Albizia lebbeck > Bauhinia purpurea > Pongamia pinnata > Millettia peguensis
In pot experiment, the DWW showed positive impact on height, fresh and dry weight, where as, the HWW showed positive impact on height upto 50% concentration and the further increase in concentration decreased the height. The maximum negative impact was observed with IWW irrigation. Pongamia pinnata showed 90% increase
xii in height in DWW compared to control set up. Albizia lebbeck showed 35% increase in fresh weight, 45% increase in fresh weight by Dalbergia sissoo . The photosynthetic rate, transpiration rate and stomatal conductance of all the five species decreased significantly. In HWW the decrease in photosynthetic rate was as follows; Pongamia pinnata (-80%), Albizia lebbeck (-60%), Dalbergia sissoo (-45%), Millettia peguensis
(-45%) and Bauhinia purpurea (-58%). The proline content in all treatments was measured as a sign of oxidative stress. Maximum proline was observed in Bauhinia purpurea (6.33) in IWW, where as the least quantity of proline was observed in
Pongamia pinnata (3.89). The metal uptake and translocation results are also very promising. Maximum uptake was observed for Pb in IWW by Dalbergia sissoo
(107.06 mg/day). Uptake of Cr and Cu uptake was slow in all species. Translocation factor of Albizia lebbeck was maximum i.e. 3.03 in HWW. Untreated IWW seems to create number of problems in ecosystem by disturbing both biotic and abiotic (soil properties, soil osmotic potential) components. This study seems to be successful in combating wastewater problem. This study indicates that, Dalbergia sissoo , Albizia lebbeck , Bauhinia purpurea , Pongamia pinnata and Millettia peguensis are much tolerant in IWW and can be successfully used for phytoextraction processes. The tolerance index is as follows: Dalbergia sissoo > Albizia lebbeck > Bauhinia purpurea > Pongamia pinnata > Millettia peguensis
The idea is to utilize WW to generate urban forests with the said five species. This idea can reduce multiple and serious problems like, IWW toxicity, WW treatment, and air pollution through urban forestry. The most prominent benefit is that this urban forest is eco-friendly and sustainable solution for multiple problems.
xiii
1. Introduction
Fresh water comprises 3% of the total water on earth. Only a small percentage (0.01%)
of this fresh water is available for human use. Unfortunately even this small proportion
of fresh water is under acute stress due to rapid population growth, urbanization and
unsustainable use of water in industry and agriculture. With the rapidly increasing world
population, the availability of fresh water is declining. Many countries in Africa, Middle
East and South Asia will have serious threats of water shortage in the next two decades.
In developing countries the problem is further aggravated due to the lack of proper
management, lack of professionals and financial constraints (Shtangeeva . et al ., 2004).
Like other developing countries of the world, Pakistan is also facing critical water shortage and rapidly increasing pollution, it is considered as water stressed and is likely
to have a water scarcity in the near future. In developing countries like Pakistan,
industries are increasing haphazardly without proper environmental management plan
(including wastewater treatment). Wastewater (WW) contains number of toxic
chemicals, and their entry in natural water streams creates hazards through food chain.
An alarming imbalance caused by the increasing rate of human activities is causing
extraordinary threats to biosphere (Wong, 2003). The main human activities are
extensive agriculture and urbanization, which are responsible for polluting the
environment (Freitas et al ., 2004). The intensive industrialization and urbanization is
contaminating the soil with different heavy metals (HMs). A global problem of
contamination of HM in the environment is affecting the fertility, crop yields and soil
biomass causing food chain to be affected by the bioaccumulation of metals (Rajkumar
et al ., 2009). The rising dependencies on chemical fertilizers are contaminating the
agricultural soils as the environmental health facing with continuing risk (Wong et al .,
2002). The developed countries of the world have a controlled system for the discharge
1 of toxic substances, but there is an enormous increase in the contamination of HMs in
agricultural soils of the developing countries with vigorous industrial growth, rapid
increase in population and a less control on pollution (Ji et al ., 2000). Heavy metal
contaminated soils impose a threat to the health of all animals, plants and humans. In
consequence, for the sustainability of agro-ecological system and including human
society, the soil should be maintained as uncontaminated from the HMs (Bhargava et al .,
2012).
1.1. Environmental effects of HMs and their sources
Most commonly found HMs are Cu, Co, Zn, Ni, Mn, Cd, Hg, Pb and Cr. A few of these naturally occurring components (Lasat, 2000) such as Cu, Co, Mn, Zn and Ni are the micronutrients, necessary for the growth of plants whereas, other metals such as Pb, Hg and Cd have unknown biological functions (Gaur and Adholeya, 2004).
The biological systems are detrimentally affected by the pollution of metals like Co, Cd and Pb may accumulate within the living organisms because they cannot undergo the process of bio-degradation, therefore, different disorders/diseases are caused even due to low concentrations (Pehlivan et al ., 2009). Negative impact on soil micro flora imposed, along with ground cover and growth of plants due to HM contamination (Roy et al .,
2005). It is acknowledged that HMs cannot undergo chemical degradation, and it is needed to be transformed into nontoxic compounds, or physically removed (Gaur and
Adholeya, 2004).
1.2. Techniques for removal/reduction of HMs
To uncontaminate the environment from these HMs, many methods/techniques are already being exercised but there is almost no method/technique with optimum performance and these methods are not cost effective. The most important nutrients/constituents of soils could be degraded by these methods (Hinchman et al .,
2 1998). The HM contaminated soils undergo the traditional process of remediation which involves excavation or onsite management followed by its dumping to a landfill site.
This disposal method of contaminated soil does not manage the pollution but instead it increases the problem with the transportation of contaminated soil associated with chemical hazards from landfill to a contiguous environment. For the dumping and excavation of contaminated soil, an alternative way of soil washing is used. This method of soil washing produces a filtrate affluent of HMs, which is very expensive and involve an additional treatment (Gaur and Adholeya, 2004). Chemical methods produce huge amount of sludge, whereas chemical and thermal treatment methods are technically not appropriate to conduct (Rakhshaee et al ., 2009).
1.3. Phytoremediation technology
Initiative steps have been taken for the development of suitable methods in regard to contamination of the environment to access the occurrence and transportation of HMs in water and soil (Shtangeeva. et al ., 2004). Currently, the technological solution is phytoremediation in which plants are being used to remove the pollutants in water, sediments and soils. This technology (phytoremediation) is ecologically suitable as well as inexpensive, such plants which have an excellent capacity to accumulate metals are called hyper-accumulators (Cho-Ruk et al ., 2006). In the process of phytoremediation, the entire plant body is being used for its distinctive and discerning capabilities e.g. bioaccumulation, translocation and the capabilities to degrade the contaminants
(Hinchman et al ., 1998).
1.4. Mechanism of HM uptake by plant
Numerous researchers have discovered the mechanism of the uptake of the contaminants by plants. It could be used to improve the uptake ability of the plant by modifying the factors of its mechanism. The plant plays both the roles; ‘excluders’ and the
3 ‘accumulators’ (Sinha et al ., 2004). The contaminants bio-transform or biodegrade into inert forms in the aerial tissues of accumulators and plants still survive. The uptake of contaminants into the biomass of the excluders is restricted.
To acquire necessary micronutrients from the environment, plants have advanced in a very precise and resourceful mechanism even when the ppm levels are very low. Plant roots are capable to take up and solubilize micronutrients from precipitates that are almost insoluble and in the soil at a very low intensity and all this is aided by redox reactions, plant-induced pH changes and plant-produced chelating agents. To accumulate micronutrients, plants have also developed mechanisms that are very precise and implicated processes such as storage, translocation and uptake of toxic elements which comprise the chemical properties that simulate to those of necessary elements. Therefore, mechanisms for the uptake of the micronutrients are of complimentary importance to phytoremediation (Ginneken et al ., 2007).
In the process of uptake and translocation of the ions, there is a series of specialized proteins or mechanisms of transportation or uptake, which include
(1) “Proton pumps” (ATPases generate electrochemical gradients and consume that
energy)
(2) “Co-transporters and anti-transporters” (to force the energy dependent active
uptake of ions, proteins are involved, that utilize the electrochemical gradients
generated by ATPases)
(3) “Channel proteins” (to assist ions uptake by cell).
Every method of transportation is expected to take up variety of ions, including different
HM contaminants. The translocation of HM contaminants towards shoots after the uptake by roots is advantageous, as root biomass harvesting is not feasible every time.
Very little is known about metal ions which are transferred to the shoots from the roots.
4 The mechanisms of the plant uptake and translocation are probably synchronized
strongly. Usually, plants do not hoard trace elements additional than approaching
metabolic needs. These supplies are minute from 10 to 15 ppm which is enough for most
of the necessary requirements for trace elements. ‘Hyper-accumulator’ plants are the
only exception which can take up the toxic metal ions, thousand times more than the
needs. Particularly hyper-accumulating plants store and avoid the toxicity caused by
these metals. Several mechanisms are involved amongst which storage in the vacuole is
the primary one.
The following mechanisms are being used for the uptake of heavy metals through
Phytoremediation technologies:
Phytoextraction is the mechanism in which plant roots absorb or uptake the contaminants and translocate to upper parts of the plants (shoots) and these can be further used to gain the energy and recovering the metal from the ashes (Erdei et al .,
2005).
Phytostablisation is the mechanism in which the process of absorption or adsorption
is used for the restriction of the pollutants/contaminants in ground water and in
agricultural soils. Root zone helps in precipitation and thus restricts the movement in
soils. It also adsorbs pollutants on root cells, their movement by deflation and erosion, as
well as accumulation in plant tissues (US EPA, 2005).
Rhizofiltration is the mechanism which is used for the cleanup of collective
wastewater and this acquires the precipitation or adsorption against plant roots or
squesterization and absorption of the contaminants to the roots that are surrounded by a
solution constructed by wetland.
Phytovolatilization is the mechanism in which the modified form of the contaminants
is released into the atmosphere by transpiration from the plant surface.
5 Phytovolatilization occurs along with the uptake of the contaminants present in the water
of growing trees and plants. At relatively low concentrations, some of these
contaminants pass all the way through the plants and then to its leaves and finally
volatilize into the atmosphere.
1.5. Advantages of Phytoremediation
As compared to the current techniques of chemical and physical process,
Phytoremediation is more aesthetically pleasing, publically acceptable and less
disruptive (Salido et al ., 2003). This method is not as much of expensive, effective in
diminution of contaminants, appropriate for an extensive variety of contaminants and
taken as a whole, it is an ecologically welcoming method.
In phytoremediation production of low cost biosorbent materials and the efficiency of the
concentrated HM ions being reduced cost effectively are the two main rewards of the
“adsorption technology” of HMs by plant biomass (Rakhshaee et al ., 2009).
Phytoremediation technology is possibly the far less expensive and clean which can be
used in the remediation of selected contaminated sites. A variety of methods are included
in phytoremediation which can lead to the degradation of the contaminants (Rodriguez et al ., 2005).
Phytoremediation is an economical option for the remediation of ecological media and has comparatively low levels of contaminations which are perfectly appropriate for large cities (Ginneken et al ., 2007). This technology is far more resourceful, inexpensive and an effective choice for the establishment of the treatment methods used at the contaminated sites and has recently established a vast attention (Srivastava et al ., 2009).
Phytoremediation is eventually a distinctive and inexpensive method that provides solutions to various problems for the contaminated soils (Liu et al ., 2000). As compared to the conventional physiochemical methods, it is less expensive (60 to 80% or even less
6 costly), because it does not need costly equipment or highly specialized personnel. This
method is used for low concentrated water with large volumes and for the contaminants
of huge areas having low to moderately contaminated surface soils (Mwegoha, 2008).
A reusable plant residue which is rich in metal is generated in phytoremediation which is
certainly another advantage (Liu et al ., 2000). The technique of Phytoextraction could
only be successful if the plant species are correctly recognized that are appropriate and
can produce huge amounts of biomass and can hyperaccumulate heavy metals
(Rodriguez et al ., 2009). Phytoremediation is considered as an advanced method
(Ginneken et al ., 2007). This research is very resourceful and can contribute for the improvement of contaminated soils specifically those with high concentration levels of aluminum and salts. This method is appropriate to be used for a variety of toxic metals and radionuclide, removal of secondary air or water-borne wastes, negligible ecological disturbance and public recognition (Liu et al 2000). To remove the metals from contaminated soils in situ, the process of phytoextraction is regarded as an ecologically responsive method. To clean-up at huge scale, this method is very useful and has been used for the removal of various heavy metals (Wang and Greger, 2006). It is a very resourceful and cost-effective method that uses solar-energy-driven cleanup technology and there is nominal disturbance in the environment and in situ treatment preserves topsoil. For the removal of ecological contamination, there is degradation of organic pollutants into H 2O and CO 2 (Mwegoha, 2008). This technology is better also known as a green technology.
The most economical and largely essential family of flowering plants is the bean family, or Fabaceae or Leguminosae (commonly known as legume) or simply called ‘pea family’. Plants belonging to this family are growing around the world in numerous environments and atmosphere (Steven, 2001). With the passage of time these plants have
7 developed numerous techniques for their protection from the pollutants which cause them a lot of damage.
1.6. Hypothesis
Plants of the Fabaceae or Leguminosae (commonly known as legume) or simply called
‘pea family’ are growing around the world in different environments. It was assumed that plants of family Fabaceae may be tolerant to wastewater, acting as hyper- accumulators.
1.7. Objectives
To assess the potential of tree species to remediate the contamination of HMs, the present study was designed to: and it consecutively suggest the utilization of these species in urban forestry and can be irrigated with wastewaters and it’s not used to grow crops. The objectives of the present study were to:
1. Study the potential of the five plant species to grow under three types of
polluted water i.e. domestic, hospital and industrial containing HMs for
a. Seed germination response
b. Seedling vigor index
c. Tolerance index
2. Study and compare the bio-accumulation potential of the five selected plant
species in terms of phytoextraction and phytoremediation.
3. Assess the effects of stress of HMs or wastewaters on the self-protective
mechanisms of plants species under study such as alteration in:
a. Lipid per-oxidation levels
b. Proline contents
4. Compare the impact of three different wastewaters on growth of selected
plant species
8 2. Literature Review
Tauqeer et al., (2016) studied the morphological, chemical and physiological changes in
Alternanthera bettzickiana under metal stress. The study aimed to test the A. bettzickiana
for use in metal phytoremediation. The whole experiment was conduced in pots filled
with clay loam soil and plantlets were collected from local nurseries. The pots were
irrigated with CdCl 2 and Pb (NO 3)2 in different concentrations ranging from 0.5 to 2.0
mM. The whole experiment was set up in “Completely Randomized Block Design”.
Results indicated that the plants grew better in Pb solution compared to the Cd solution.
Root length, leaf area, plant height and number of leaves all differed significantly from
one another. The maximum plant height recorded was 15 cm, maximum root length was
27 cm, maximum leaf area was 3.78 cm -2 and maximum number of leaves was 411/plant.
Leaf fresh weight showed very less variation among different Cd and Pb concentrations.
Maximum leaf FW was 12 g in presence of Cd. How the maximum leaf dry weight was observed in Pb solution. Maximum carotenoid, total chlorophyll, chlorophyll a and chlorophyll b were 14, 24, 17 and 4 mgkg -1, respectively. Maximum pigment concentrations were observed with Pb solution than Cd solution. Lead accumulation in root, stem and leaf was 448, 377 and 38.4 mgkg -1 DW, respectively, whereas, Cd
accumulation in root, stem and leaf was 395, 272 and 19.5 mgkg -1 DW, respectively.
Results of the study showed that plant biomass, plant height, pigments (photosynthetic)
of A. bettzickiana increased with increasing metal concentration upto 1.0 mM of HM
concentration. Below this limit all the parameters of the plants increases and above 1
mM concentration the plant showed negative impacts. The ability of this plant to
accumulate and tolerate metal stress makes this specie an excellent candidate to recover
metal contaminated soils.
9 Cicero-Fernández et al. (2016) investigated the long-term (i.e., two consecutive annual
cycles) ability of Phragmites australis to remediate estuarine sediments contaminated with heavy metals (Co, Ni, Mo, Cd, Pb, Cr, Cu, Fe, Mn, Zn and Hg) and trace elements of concern (As, Se, Ba). The investigation was based on an experimental approach on a pilot plant scale. The accumulation of these elements on belowground and aboveground tissues was monitored during vegetative and senescence periods for two populations of
P. australis, originally from contaminated (MIC) and non-contaminated (GAL) estuaries.
The initial concentration of the elements in the contaminated estuarine sediment
decreased in the following order: Fe > Mn > Zn > Pb > Ba > Cr > As > Cu > Ni > Co >
Mo > Cd > Se > Hg. A similar trend was recorded in the belowground biomass following
bioremediation, suggesting the potential role of P. australis as an effective biomonitoring
tool. Mercury was not detected in any plant tissue. Overall, this study suggested that P.
australis populations are more efficient in taking up Ni, Mo and Cr during the second annual cycle in both belowground and aboveground tissue. Calculated bio-concentration factors (BCF) suggested a clear metal excluder strategy for Co, Cd, Pb, Cu and Fe, with accumulation and stabilization below ground, with limited translocation into aerial tissues observed during the length of this study. Lowest BCF values in belowground tissue ranged between 0.01 to 0.09 for Se, As, Pb, Fe, Co, Cd and Ba. The highest values in belowground tissues ranged 1.47 to 1.97. An excluder behavior for Zn, Ba and Mn was detected during the second annual cycle, which coincides with a substantial increase of concentration below ground. This study demonstrated first time the long term efficacy of P. australis for phytoremediation of heavy metal contaminated.
Das and Mazumdar (2016) conducted study to remediate paper mill effluent with
Salvinia cucullata (an aquatic fern). Paper mill effluent had high level of Cd, Ni, Pb, Cu,
Cr, Mg, Mn, Fe and Zn. The plant survived and flourished well under concentration
10 range of 25 to 100%, v/v. The most effective concentration was 25% where plant resisted
membrane injury, hydrogen peroxide generation was reduced, and growth was better and increased antioxidant enzymes (lipid peroxidation). The metal tolerance was high and mostly metals were higher in concentration e.g, Fe. For Cr, Cu, Pb, Zn, Mg and P, greater metal concentration was reported in leaf than in root. The maximum root biomass was observed with 50% of wastewater and it was 0.07g, further increase in the wastewater concentration decreased the biomass. Total protein increased upto 25% WW
-1 and was 18 mgg FW. Maximum quantity of MDA, H 2O2 and O 2 was 9, 530 and 820
µmolg -1 FW, respectively. The bioaccumulation of Ni was more in leaf (55.2 mgkg -1)
than in root (44.6 mgkg -1). Similarly, Cd was more in leaf (11.4 mgkg -1) than in root (8.0 mgkg -1). This plant was well suited for the wastewater treatment as it effectively reduced
BOD, DO, Zn, Ni, Fe, Mg. this study recommends Salvinia cucullata for phytoremediation of industrial effluents especially with multi-contaminants.
Fernández et al . (2016) studied phytoremediation capability of native plant species which are growing in close vicinity of mining sites in Spain. The idea of the research was to propose low cost technique for recovering contaminated soils. Second objective to this research was to identify native specie, as non-native species may pose ecological risks.
118 plant samples and soils were collected from close vicinity of mining sites, where soils are contaminated with Pb, Zn, As and Hg. Mostly mines are located in Asturias
(northern Spain). Out of 118 plant samples only eighty samples were selected for further studies due to overlapping and irrelevance. These plant samples were test for metal concentration, metalloid concentration and soil characteristics. Result identified Coincya
monensis as a Zn hyperaccumulator with high soil to pant transfer factor. Among
grasses, the endemic Agrostis durieui tolerated high Pb concentrations in tissues. Holcus
lanatus and Festuca rubra excluded Hg and As more efficiently than Dactylis glomerata .
11 Among the legume species, Cytisus striatus , Cytisus scoparius , Genista legionensis and
Lotus corniculatus were efficient excluders. Prevailing tree species also were efficient
excluders. Salix atrocinerea exhibited high soil to plant transfer factors for Cd, Zn, and
Hg, while S. caprea had high transfer factors for Cd and Zn but not for Hg. Acer
pseudoplatanus growing on Hg-As spoil heaps efficiently excluded Hg and As. Betula
celtiberica also efficiently excluded Hg and As from its leaves, while exhibiting high soil
to leaf transfer factors for Zn. The study recommended that mining areas of the northern
Spain are important reservoirs of a large number of plants species with high potential of
phytostabilization or phytoextraction of soils contaminated by Hg, As, Zn and/or Pb. The
genetic resources of these sites must be protected or conserved.
Ghaderian and Ravandi (2012), collected soil and plant samples from four mining sites
(China). They estimated the metal concentrations in soil and plant. Metal studied were
Pb, Zn, Ni and Cu. The minimum and maximum concentration of metal (µgg -1) in soil is as follows; Cu (0.28 - 1330), Ni (0.005 – 0.15), Zn (0.3 - 1500) and Pb (0.42 - 700).
From plant samples only leaf were studies and in leaf the range of metal accumulation
(µgg -1) is as follows; Cu (1 - 4012), Ni (0.1 - 22), Zn (2 -1074) and Pb (1- 76). Total 146 plants were collected which belong to 40 families and 118 genera. The maximum concentration of Cu was found 4012 (µgg -1) in Epilobium hirsutum , 1518 (µgg -1) in
Polypogon fugax and 657 (µgg -1) in Onosma stenosiphon . Based on these results
Polypogon fugax and Epilobium hirsutum were declared as hyper-accumulators, as both
accumulated more than 1000 (µgg -1) of Cu. The important families in this study were,
Solanaceae, Salicaceae, Rosaceae, Malvaceae, Poaceae, Fabaceae, Euporbiaceae,
Brassicaceae and Asteraceae. Based on their conclusion and recommendation E. hirsutum and P. fugax is suitable for phytoremediation of Cu.
12 Auda et al . (2011) studied phytoextraction of heavy metals by collecting soil and plant samples from Gaza strip, Palestine. Samples were collected from 3 areas, firstly from rural, secondly from urban and thirdly from industrial sites. Metal under investigation were Fe, Cd, Zn and Ni. Plants studied were, spinach, wheat, strawberry, carrot, onion, cucumber, cabbage, potato and faba bean. The minimum concentration of Pb was 0.11
(mgkg -1), Zn was 25.4 (mgkg -1) and Cd was 0.001 (mgkg -1) in spinach leaf. Whereas,
minimum concentration of Fe was in seed of faba bean (22.4 mgkg -1). All the species behave differently for maximum concentration of heavy metals and is as follows, onion bulb accumulated 95 (mgkg -1) of Pb, wheat leaf accumulated 90 (mgkg -1) of Zn, potato
tuber accumulated 0.04 (mgkg -1) and cabbage leaf accumulated 114.0 (mgkg -1) of Fe.
From soil samples the minimum and maximum concentration (mgkg -1) were as follow,
Pb (5.8 – 24.5), Zn (5.80 – 65.2), Cd (000.1 – 0.3) and Fe (71.0 – 711.0). The study
concluded that vegetables show negative growth in presence of HM and the chlorophyll
concentration also decrease.
Agnello et al . (2016) collected different soil samples at various depth ranging from 0 to
100 cm. Area selected was near fuel station and is reported to be contaminated with heavy metal and petroleum hydrocarbons. Pot experiment was set up for Alfalfa seeds germination and phytoextraction analysis. Each pot dimension was of 8 x 10cm and the experiment last for 21 days. Parameters analyzed were, plant biomass, concentration of metal in different tissues and total metal uptake per pot. Translocation factor show negative trend and it was 0.49 for Cu at day 30, it dropped to 0.36 at day 60 and finally at day 90 it was 0.29. The TF pattern of Pb and Zn was different from Cu, their TF initially increases, then decreases in the middle of the experimentation and finally it again increased. For Pb the TF were, 0.83, 0.69 and 0.87 at day 30, 60 and 90, respectively.
Similarly, for Zn the TF were, 0.46, 0.37 and 0.40 at day 30, 60 and 90, respectively.
13 Metal concentration was analyzed in dry weight of root and shoot. Amount of Zn was
169 mgKg -1 in root and 78 mgKg -1 in shoot. Root also accumulated Cu up to 71 mgKg -1
and Pb up to 23 mgKg -1. Similarly, in shoot Cu and Pb was accumulated up to 21 mgKg -
1 and 17 mgKg -1, respectively. The MDA contents were highest (25nmolg -1) at day 30, and it decreased onward. The minimum value of MDA was 15nmolg -1 at day 90. The study suggested the use of Alfalfa ( M. sativa L.) for phytoremediation and
phytoextration of heavy metals.
Tariq and Ashraf (2013) investigated phytoremediation potential of firing range soil.
Firing range soil is contaminated with different heavy metals like (Pb, Ni, Cu, Cr, Co).
For this they selected 4 species, Helianthus annuus , Brassica campestris , Zea maize , and
Pisum sativum . To test the phytoremediation of heavy metal, pot experiment was set up.
Soil was collected from firing range of “Rangers Lahore” and shifted to green house.
Plantlets from firing range were shifted to pots. After 15 days the plants were harvested and heavy metals in their parts were analyzed. The metal concentration (mgKg -1) in firing range soil is as follows; Cu 84.50, Cd 7.250, Ni 2.830, Co 0.650, Cr 0.950 and Pb
1331. The heavy metal accumulation in 4 different species is significantly different. In
Zea maize , Cu was up to 21.11, Cd 3.558, Co 0.262, Cr 0.033, Ni 0.634 and Pb 36.04
(mgKg -1). Similarly, Helianthus annuus accumulated Cu, Pb, Ni, Cd, Co, and Cr up to
13.17, 64.96, 0.646, 3.055, 0.274 and 0.208 (mgKg -1), respectively. Concentration of
heavy metals in Pisum sativum is as follows; Cu 14.18, Cd 3.529, Pb 82.26, Co 0.211, Ni
0.623 and Cr 0.395 (mgKg -1). More over, Brassica campestris accumulated Cu, Pb, Ni,
Cd, Co, and Cr up to 14.48, 27.71, 0.625, 2.779, 0.208 and 0.438, respectively. Effect of
EDTA was also experimented and results indicated that EDTA enhanced the uptake of
Pb more and results of the metals do not respond significantly in presence of EDTA.
Presence of more than one metals in soil pose negative effect on different metal uptake.
14 The study evidenced that Z. maize efficiently extracted Cu and Co. Similarly, H. annuus is a efficient in removing Cd. B. campestris and P. sativum are very effective for Cr and
Pb removal, respectively. This study recommends the use of above mentioned 4 species for phytoextraction of heavy metals.
Rungwa et al. (2013) designed a study in search of eco-friendly and sustainable technique for heavy metal management. The study design consisted of site survey, data collection, identification of potential phytoremediation species and studying closed mine conditions. Samples of water, soil and food were collected from 19 year old closed mine site. The metals investigated were, Cd, Cu, Pb, Fe, Hg and Zn. There was significantly high amount of heavy metals in soils as evidence from the average results. Other areas like ponds water and garden foods showed fewer heavy metals. In comparison to control, all sample showed high metal contents. Study suggested further investigation on phytoextraction with selective plant species. In soil the concentration of Cadmium,
Copper, iron, lead, mercury and Zinc was 9.5, 39.3, 38742, 56.1, 33.14 and 249.34 µgg -1.
Results identified Piper anduncum , Brachiariareptans and Phragmiteskarka (pitpit) as potential candidate for phytoextraction. A further sampling and analysis of these plant species is required to investigate their absorption rate and heavy metal content that were absorbed after mine closure. This green technology is suitable and highly recommended for cleaning of Papua New Guinea mining sites.
Goswami and Das (2016) studied role of Calandula officinalis in phytoremediation of
Cu and its antioxidant enzymes. In pot experimentation C. officinalis seeds were used for
sowing purpose. Copper sulphate was mixed with dry soil in different concentrations and
4 kg of soil was filled in each pot. Pots were placed in net house. Concentration of
-1 CuSO 4 ranged from 150 to 400 mgkg of soil. All the experiments were run in
triplicates. No organic amendment or fertilizer was added. Results indicated that the Cu
15 impose negative impact on plant weight and height. The dry weight of control was 2.01
and it decreased with the increase in Cu concentration. Minimum dry weight was
observed with 400 mgkg -1 of Cu and it was 0.55 g. Similarly, shot length dropped from
2.11 (control) to 0.57 g (maximum Cu concentration). Leaf area shows 55.3% reduction
as compared to control. The root length of control plant was 22.5 cm and it decreased
with Cu toxicity and it was 5.33 cm at 400 mg of CuSO 4. Tolerance index (T.I) also exhibited negative correlation with Cu concentration; it was 94.2 at 150 mgkg -1 and 62.7
at 400 mgkg -1 of Cu. The amount of carotenoid, total chlorophyll, chlorophyll ‘a’ and
chlorophyll ‘b’ were 1.376, 3.372, 2.69 and 0.40 nmolg -1 respectively, at higher Cu concentration. These pigments amount was significantly reduced as compared with control. Compared to control the MDA content in root was 110% higher and in shoot it was 172% higher. Similarly SOD activity increased by 8 times in root and 7.3 times in shoot, compared to control. The Cu uptake capacity of root was more than leaf. In root
Cu concentration reported (at 300 mgkg -1) was 3995 µgg -1 (dry wt) and in shoot it was maximum i.e. 4675 µgg -1 (dry wt). Cu uptake at 400 mgkg -1 was low due to higher toxicity. The extraction coefficient of root was 13.3 and that of leaf was 15.8.
Translocation factor (TF) for Cu was 1.36 at 200 mgkg -1. The study strongly recommend
C. officinalis for use in Cu phytoremediation, based on its high tolerance index, high
translocation factor and high accumulation of metal in root.
Chávez et al. (2012) studied Tula Valley in Mexico, this valley is under wastewater
irrigation since 1989. This study was planned to study the long term effect of domestic
wastewater irrigation. Wastewater was used in two ways, one was without treatment
(WW u) and second was with partial treatment (WW p). Experiment was setup in net
house and for that 24 soil columns were collected having 200mm length, from Tula
Valley. The columns of soils were covered in sheet (plastic) and transported to net house
16 where they were placed in steel columns. The base of the steel column was perforated to
collect leachate. Alfalfa ( Medicago sativa ) was also collected from Tula Valley and planted in soil columns. The alfalfa was irrigated with WW u and WW p at different rates.
Wastewater analysis revealed that the COD, BOD, EC, pH, Na, K, P, Ca and N is
significantly higher in WW u than in WW p. The plant sample testing indicated that the
NPK value of WW p was more, compared to WW u. The organic matter in soil does not
show any significant difference with WW u or WW p. the results obtained in this study
indicate, that under current conditions of Wastewater management in the ‘Tula Valley’,
the domestic wastewater usage was reduced by 43% to 1.5 m/cycle. Irrigation with
wastewater can be used without imparting negative effect on plant nutrition. Organic
matter (OM) was decreased by 35% and slats (K and Na) leaching by 40%. Howerev,
further validation of these results are needed before applying to full field scale. This
study recommends that use of domestic wastewater in irrigation, with or with out
treatment.
Tripathi et al . (2016) surveyed and reported that the use of municipal wastewater
(MWW) for irrigation is increasing in peri urban arrears of New Delhi, India. To test the negative and long term effects of wastewater irrigation, this study was designed and conducted. Municipal wastewater was collected from industrial drain and ground water
(GW) was collected from tube well. These wastewaters were tested for different physio- chemical parameters and showed significant difference. Cauliflower nursery was raised in tray and than transferred to the pot. Pots were irrigated with different concentration of
MWW and GW. Leaf area, dry matter, yield and metals in cauliflower were tested at final harvest. Yield of cauliflower was 62.1 Tha -1 and percentage of dry matter was 9.64
with MWW irrigation. The concentration of different metals in cauliflower was as
follows (mgkg -1 DW), 10.2 of Cu, 0.31 of Cr, 585 of Fe, 28.2 of Mn, 1.28 of Pb, 20.7 of
17 Zn. Other studies also reported the up take of metal (mgkg -1 DW) by cauliflower, Cu 5.3,
Zn 29.3 (Sharma et al ., 2009), Cu 12.3, Mn 68.3 (Kiziloglu et al., 2008), Cr 40.1, Fe
879, Mn 28.4 (Sinha et al ., 2006) and 450.7 (Ahmad and Goni, 2010)
Tekaya et al . (2016) conducted research to study the effect of wastewater irrigation for
photosynthetic parameter on olive tree. For this purpose they selected the orchard of
mature olive trees (69) which were 12 x 12 m apart from each other. For comparison, 2
different types of irrigation water was used, one wastewater and second rain water. Total
irrigation per year was 10m 3 per tree. The results were very promising. Irrigation with
wastewater improved the photosynthetic rate by 9.36%, transpiration by 35.16% and
stomatal conductance by 33.4%. These results differ significantly with control and rain
water irrigation. The physio-chemical analysis revealed that the chlorophyll a was 0.81
mgg -1, chlorophyll b was 0.61 mgg -1 and total carbohydrates were 23.47 mgg -1.
Comparison of the oil quality revealed that the total phenol quantity decreased by
49.38% and β carotene decreased by 29.52%. Soluble sugars accumulated especially in
the block of trees grown under rain fed conditions and No-tilled soil as an adaptive
metabolic response to water stress. The production of these osmo-protectant compounds
and their accumulation ensures osmotic adjustment between the cytosol and the vacuole
of leaf cells. Based on the above finding the study strongly recommended the use of
wastewater for olive tree irrigation with the addition of soil tillage. This will improve the
soil quality, olive tree health, oil quality and help in decrease the fertilizer cost.
Minhas et al . (2015) studied the effect of sewage wastewater irrigation to Eucalyptus
(Eucalyptus tereticornis Sm.). The study lasted for 10 year in “Research Farm of Central
Soil Salinity Research Institute, Haryana, India”. Tree saplings were planted in soil with
different densities and were irrigated with ground water (GW) and sewage water (SW).
Trees irrigated with SW attained 164.0 m 3ha -1 of stock volume, whereas those irrigated
18 with GB attained 127.1 m 3ha -1 of stock volume. Estimated analysis suggested that the use of SW results in the water use efficiency up to 40%. The most important information this study highlighted is that the soil do not under go any degradation with 10 years of
SW irrigation. “The changes in soil properties monitored after 10 years showed benefits in terms of lowering soil pH, improved contents of available nitrogen and phosphorus, with marginal increase in salinity. The major benefit was incurred via improvement in organic matter that too down to almost 1.0 m depth. Amongst various tree parts, tree bole contributed more than 90% of the above ground C absorption and 61 - 71% of the total C absorbed (including below ground); while contribution of below ground biomass ranged between 23 and 33% of the total C stock . Small branches, leaves and twigs contributed only 2.9 and 3.3% towards total C removal. The total C removed was about 7% more in plantation irrigated with SW. The C sequestered per tree was more in LD and RD compared with HD and VHD and the differences increased with age of the trees. In spite of better C removal per tree in lower densities, total C absorbed per hectare increased with stocking densities. While increasing tree density can increase carbon storage, raising densities too high can reduce net C absorption due to an increase of suppressed trees. The only caution to this is the measurement of SW loading rate. This study recommended the use of SW for tree irrigation and ecological restoration of sites. It also emphasized the multiple uses of trees grown with SW like, timber production, fuel wood production and environmental sanitation ”.
Ma et al . (2015) conducted pot experiment on Triticum aestivum L. cv. “Zhengmai
9023” (winter wheat) and irrigated the pots with 3 different coal mine wastewater for one year. The wastewaters were, leachate of coal gangue (LC), precipitated coal washing wastewater (PC) and coal washing wastewater (CW). Plants in control were irrigated with well water (WW). Results indicated that the maximum Zn concentration (mgkg -1) in
19 soil after the final harvest was 131 with LC, where as the maximum concentration of Cu was 13.9 with CW. Lead accumulation in soil was at 33.4 mgkg -1 with LC. Maximum yield traits were observed with irrigation of CW. Grain yield was 30.1 g/pot, kernel per spike was 36.9, 1000 kernel weight was 53.7 g and above ground biomass recorded was
63.8 g/pot. “Long term mine waste water irrigation resulted in the accumulation of Cr and Pb in soil which improved the contents of Cr and Pb in wheat grain of three mine waste water treatments. The uptake of heavy metals by plants is closely related with the modality of heavy metals besides and their total contents in soil. Generally, many factors affect the modality of heavy metals in soil and their uptake by plants, such as pH, organic matter and redox conditions; among these factors, pH is considered to be the most important one. The acidic mine water reduce the soil pH value, and then decrease the contents of carbonate bound and residual form of heavy metal, while the levels of exchangeable and available heavy metal are increased, which promote uptake of heavy metals by plants. ”The study concludes that the irrigation of wheat plant with mine waste water result in more up take of Zn and Cr, as compared to the control.
Belouchrani et al . (2016) conducted phytoremediation of zinc contaminated soils using canola ( Brassica napus L). The whole experiment was conducted in green house using pots filled with top soils of garden. To maintain the zinc concentration from 0 to 500 mg/250g in soil, Zinc sulphate heptahydrate (ZnSO 4. 7H 2O) was mixed. The experiment lasted for 12 weeks. Interestingly the stem height increased with the increase in zinc concentration without any negative effect. Maximum stem height recorded after 12 week was 22 cm. Similarly, no negative effect was shown by roots and maximum root length observed was 25cm at the end of experiment. Canola yield also improved when Zn amount increased, maximum yield i.e. 6 g/pot was reported with 500 g of zinc. Tolerance index is one of the good indicators to test weather the plant specie can be used for
20 phytoremediation or not. The tolerance index showed by canola in this study was 2.6.
The study concludes that the canola is potential specie for zinc phytoremediation.
Abreu et al . (2012) studied phytoremediation potential of castor oil plants for heavy
metals and boron. Number of studies had reported that the automobile scrap shredder is
the source of Zn and Cu and their illegal dumping near agricultural fields. In their study
they applied automobile scrap shredder on soil with some organic amendments like peat
and filter cake. These organic amendments were added with the intention to restrict the
movement (vertical and horizontal) of HMs. This experiment was set up in net house,
using pots and lasted for 72 days. Seed were sown in pots in triplicates and their growth
parameters were monitored on regular bases. The results showed that the addition of
organic amendments does increase the dry weight of root and shoot but if the amounts of
peat increase above 40 mg then the increase in dry weight become non-significant. The
root and shoot dry weight recorded were, 5.57 g and 20.8 g, respectively. In castor oil
shoot, the maximum accumulation of Cu, Fe, Mn and Zn was 7, 47, 13.5 and 124 mgkg -
1, respectively. The transfer factor (F) in presence of peat was 10.3 and in presence of
filter cake ‘F’ was 8.1. Translocation index (T.I) was almost same in presence and
absence of organic amendments. Recorded ‘T.I’ was 98%. The study concluded that the
castor oil plant is tolerant enough to be used for phytoremediation.
Sun et al . (2011) conducted a research project on phytoremediation of benzo-pyrene and co-contamination of benzo-pyrene / heavy metals. Pot experiment was set up using an ornamental plant ( Tagetes patula ), benzo-pyrene was added in variable concentration up to 50 mgkg -1. In another set up cadmium and zinc salts were added in pot soil up to 500
mgkg -1. Rhizo-degradation of benzo-pyrene and uptake of heavy metal was recorded regularly. Presence of benzo-pyrene show positive sign on plant growth and maximum degradation observed was 49.7%, compared to control. Similarly, presence of Cd and Zn
21 did not effected plant growth parameters at low concentration. How ever, at high
concentration of metal the negative effects started appearing. Total cadmium
accumulated in shoot, root and leaf was 1400, 200 and 900 µg/pot respectively. Copper
accumulation was 210, 220 and 135 µg/pot in shoot, root and leaf, respectively.
Maximum quantity of lead was accumulated in root i.e. 980 µg/pot and the least quantity
of lead was accumulated in leaf i.e. 275 µg/pot. The study also calculated
bioaccumulation factor (BF), transfer factor (TF) and remediation factor (RF) for heavy
metals. Result shows that the maximum BF value was for Cd (4.95), and the least BF
was of Pb (0.05). The same trend was observed for TF where the order from maximum
to minimum was Cd > Cu > Pb. For Cd the TF value was 2.30 and for Pb the TF value
was 0.16. Remediation factor is also a good indicator to select the plants for
phytoremediation. The RF for T. patula was 3.76 for Cd. The research concludes that the
T. patula is effective in phytoremediation of Cd but not very much effective for
phytoremediation of Cu and Pb.
Meng et al. (2016) studied the effect of irrigation of manure wastewater to plants by
designing a study in Tianjin China. The alternative use of sewage water reduces the
constrains on fresh water. In view of this fact, manure wastewater had been in use since
three decades, mainly in the northern areas of China. There is a gradual increase in the
issues regarding the safety of the food. As compared to the results of the clean water,
high amount of Cr, Zn, Ni, Pb, Cu, As and Cd were present in soil irrigated with sewage
water. The content of the heavy metal in the top soil was as high as 0-20cm as that of the
contents present in the subsoil. Compared concentration of other heavy metals, Hg had
the lowest concentration i.e. 5.33 mgkg -1 and other metal concentration is variable i.e. Cd
(8.19 mgkg -1), As (34.7 mgkg -1), Ni (56.4 mgkg -1), Pb (460.7 mgkg -1), Cr (537.8 mgkg -
1), Cu (836.4 mgkg -1). Highest concentration found was of Zn (2646.1 mgkg -1). The
22 contents in the roots are higher than other parts of the wheat plant which are Cr, As, Cd
and Pb respectively. This indicates the ability of the roots to function as evident barrier
and have a strong ability to translocate. It was observed that at the mature stage of the
plant, the concentration of Pb was lower in stems (6.52 mgkg -1) and higher in leaves
(8.36 mgkg -1). Out of all the vegetables that were tested, tomatoes were the only ones that had the highest concentration of Zn (23.46 mgkg -1). The national safety limit of Cd
was surpassed by nearly 24-30 times because of the highest concentration of Cd in
cabbage (3.02 mgkg -1) and in soybean (2.40 mgkg -1). There is a strong effect of
accumulation of Cd in vegetables which is because of the HM transfer from polluted soil
to autotrophs. On the whole, the concentrations of Pb, Cr, Ni, As and Cd were lower, as
compared to the national permitted safety limits. According to the research, it was
suggested that the sewage water should not be used for food crops and requires an
persistent monitoring for the assurance of food safety.
A research work was carried to assess the potential of phytoremediation by canola
biomass, which was grown on a contaminated soils (numerous metals) (Dhiman et al.
2016). Different parts of the growing biomass were measured to study the HM amount.
The roots of the canola accumulated almost 95 mg zinc/kg. From the observation of the
root biomass of canola, the lowest metal detected was As +2 (0.735 mgkg -1 DW). A
considerable difference was shown in the roots of canola for lead (8.71mgkg -1 DW) and
cadmium (2.79 mgkg -1 DW). The biomasses of leaf, root and stem reported elevated concentration of As and Cd, then Pb (lowest accumulation). Therefore, Pb 2+ can be
removed more efficiently, as compared to other soils contaminated with heavy metals.
The maximum amount of Cd 2+ observed in the root was (2.79 mgkg -1 DW) and as for the
leaf it was (2.55 mgkg -1 DW). The maximum concentration of As was observed to be
0.243 mgkg -1 DW in leaf. The stem had the least capability of As absorption amongst
23 other six heavy metals. For the production of bioethanol from metal phytoextracted
biomass, saccharification was performed. The samples of Armillaria gemina KJS114 and
Pholiota adiposa SKU714 were isolated from Sorak Mountain of the Republic of Korea.
To obtain a highly active cocktail of lignocellulase, Pholiota adipose and Armillaria gemina were co-cultured. With the biomass contaminated with copper and nickel,
Saccharification yields (SY) of 74.4% and 71.8% was gained, respectively. Under the same conditions, to obtain the SY of 73.4%, commercial b-glucosidase was combined with celluclast (1.5L). This research was declared to be the first in which the phytoremediation biomass was tested through saccharification for the production of bioethanol.
Doni et al. (2015) set up an experiment to study the application of phytoremediation, for
sustainable decontamination of marine water from the polluted sediments. Different
species of plants such as Tamarix gallica L., Spartium junceum L. and Paspalum
vaginatum were used in the treatment along with other organic matter (compost). For elimination of both petroleum hydrocarbons and HMs, synchronized action of compost and plants were studied. In addition to make a rational evaluation of the efficiency of phytoremediation, the chemical distribution in the sediment phases of metals (residual minerals, exchangeable organic matter, manganese and iron oxides) were also measured.
By examining the mass-balance of metals in the treated sediments, a comprehensive image of the metal flux was obtained. In different fraction each metal was predominated and there was no uniform distribution of the metal content in different sediment phases.
The decreasing order of the treated sediments at 0 to 20 cm and the bioavailability of the metals were as follows: Cd > Zn > Cu > Pb > Ni. The reason for the lower translocation of HM in the plant tissues is the higher proportion of Pb and Ni in the residual phase. Conversely, the higher bioavailability for the plants was established by
24 Cu, Cd and Zn which could translocate more easily in plant tissues (both aboveground
and roots). After the completion of the experiment, a higher contamination of metals was
still found, which was indicated by the outcome of mass balance. Phytostablisation was
recognized as the supreme contributor in the decontamination of metals. For the
reduction of contamination of metals and the toxicity, an alternative selection of
rhizosphere was suggested by this study, having the ability to precipitate heavy metals.
Wahsha et al. (2012) examined the bioaccumulation of HMs in willows which were
growing on neglected “Imperina Valley Mine, Italy”. Results showed that the main
reasons for the contamination in the environment were all the human activities such as
milling and mining operations. An important source of toxic elements could be the
abandoned mines. The main intend of this research was to examine the total sum of all
six potentially contaminated metals (Fe, Cd, Cr, Zn, Cu and Pb) in top soil and three
willow (Salix) species ( S. caprea L., S. eleagnos Scop and S. purpurea L.). These plants
were collected from the abandoned mine dumps. According to the statistical analysis it
was discovered that the contamination of metals in the soils was notably (p.0.05) higher
than the Italian limits. The averages of these potential metals were as follows; Fe
299,973 mgkg -1, Zn 1243 mgkg -1, Cu 2267 mgkg -1, Pb 9552 mgkg -1 and Cd was 2.12
mgkg -1. The bioaccumulation coefficient (BCF) and the transfer factor (TF) of the chosen metals varied from different sites and among the plant species. Examination of some species revealed that they have the ability for the extraction of heavy metals and stabilization of soil. Concentration of metals remained under 1000 mgkg -1 but species
had TF more than one and BCF less than one. The study concluded that there is a need of
additional projects in which research could be extended on the mechanism in which the
ability of willows to survive within the contaminated soils should be studied.
25 Chen et al. (2015) calculated the concentrations of HMs and the physiological responses of arsenic in Medicago sativa L. which were growing on acidic copper mine tailings in arid lands. Both the humans and environment are at an immense risk because of the higher contamination of arsenic which is coming from acidic copper mine tailings. The seed germination of M. sativa was improved by 5 to 10% but decreased at higher proportions i.e. 30% and 50%. When the plants were grown in the soils consisting of high proportions of HMs, there was an adverse effect on the cell membrane, photosynthesis and the growth. The system of antioxidant makes the plant tolerant against toxicity. Antioxidant enzymes found were superoxide dismutase, guaiocol peroxidase and catalase. The soil consisting of 50% of acidic copper mine tailings was very suitable for the growth of the plants. Arsenic and other HMs were tremendously immobilized in roots, except Hg. For the phytostablisation and re-vegetation of acidic copper mine tailings in arid land, M. sativa proved to be a competent plant species. On
the other hand, higher mobility of Hg from root to shoot could be harmful to animals.
The bioaccumulation of metals in roots was as follows; Cu (372.4 mgkg -1), Zn (328.1
mgkg -1), Cd (7.3 mgkg -1), Hg (0.15 mgkg -1), Pb (5.6 mgkg -1) and As (9.1 mgkg -1). This
research work recommended that in highly acidic copper mine M. sativa can stabilize Zn,
Cd and Cu due to its strong bioaccumulation of heavy metals in root.
Chang et al . (2013) highlighted in their study that nitrogen fertilization promotes the
phytoremediation of cadmium in Pentas lanceolata . An experiment was held in which P.
lenceolata was cultivated in soil containing different concentration of Cd and nitrogen.
Cadmium (Cd) range was from 0 – 25 mgkg -1 and nitrogen range from 0 mM to 32 mM.
In presence of Cd, thickness of leaves, length of stems, number nodes and the length of roots were decreased. In the beginning the chlorophyll meter readings (CMR) of plants were reduced to a various levels because of the presence of Cd in the soil. CMR of the
26 injured plants were recovered to normal levels after 28 days with 32 mM or 24 mM
addition of nitrogen (CMR levels 29.4 and 25.7, respectively), whereas the controls had
only 15.7 CMR. The highest Cd concentration (622.9 mgkg -1) obtained with 32 mM of nitrogen. The DW of shoots of non Cd treated plants was higher as compared to the treated ones. The shoot growth, specifically of non-Cd treated seedlings was also affected by the amounts of N-fertilizers. The decrease in shoot DW with nitrogen was as follows: 0 mM (0.14 g) > 8 mM (0.10 g) >16 mM (0.09 g), 24 mM (0.07 g) > 32 mM
(0.05 g). In the absence of N-fertilizer, the roots of the Cd treated seedlings had half dry weight then that of the non-Cd treated ones. During the research, when any amount of N- fertilizer was added the differences were reduced. In short, the phytoremediation of Cd can be improved by the nitrogen treatment and it can also promote the recovery of chlorophyll in leaves. The research work concluded that P. lanceolata could conserve
their role in nature without the inhibition of flowering.
In order to study the phytoremediation of nickel, lead and zinc from aquatic
environments, Harguinteguy et al. (2015) exposed the aquatic plants Myriophyllum
aquaticum and Egeria densa to different concentrations of these metals (Ni: 0.05 - 10
mgL -1, Pb: 0.05 - 15 mgL -1, Zn: 0.15 - 20 mgL -1) for 7 days. Both plant species showed
strong bioaccumulation of Pb, Zn and Ni in their leaves. The plants showed good health
signs based on the physiological parameters i.e. lipid peroxidation, malondialdehyde and
total chlorophyll. A higher capacity was shown by M. aquaticum for the accumulation of
Zn and Pb as compared to E. densa , especially at the higher concentration. During the
time period of research, it was observed that the physiological changes occurring in these
species did not affect their ability to survive in contamination. Results showed that after
7days, the accumulation of Pb, Zn and Ni in both E. densa and M. aquaticum were
dependent on the metal concentration. In E. densa and M. aquaticum, the highest level of
27 Nickel (Ni) reported was 10 mgL -1. There were no statistical difference (p > 0.01) shown in the average accumulation of Ni in both species. The highest accumulation of Pb was in M. aquaticum (3798.9 mgkg -1) and it was non-significant (p < 0.01) compared to E.
densa (2302.5 mgkg -1). In the same way the accumulation of Zn found in M. aquaticum
was 2348.4 mgkg -1 and in E. densa it was 1083.6 mgkg -1. The study concludes that M.
aquaticum is more appropriate for phytoremediation of Pb, Zn and Ni from marine
environment, due to the tolerance of heavy metals and bioaccumulation capacity.
In order to evaluate the potential of swiss grass for phytoextraction of heavy metals,
Chen et al. (2012) developed a model. To remove Chromium, Zinc and Cadmium, a
perennial grass ( Panicum virgatum L.) was deeply studied. A model was developed
between HM amount and plant biomass yield, for find relationship between different
variables. To show the connection between dry weight and plant, exponential and linear
decay models are more appropriate. As visualized by the exponential decay and linear
models, by using switch grass the highest removal of cadmium approached 34 and 40
mgpot -1, respectively. The model which was better in visualizing the connection between dry weight and plant chromium was the ‘log normal model’. The highest removal of chromium by switch grass was about 56 mgpot -1. Study recommends that the log normal
and exponential decay models were more efficient as compared to the linear model. from
log normal and exponential decay models, Zn removal predicted was 254 and 358
mgpot -1, respectively. For Cr, Zn and Cd removal efficiency approaches to 526 and 450
mgkg -1, 3022 mgkg -1, 5000 mgkg -1 and 266 mgkg -1, respectively. As a result of high biomass production of switch grass and recognized agronomic characteristics it is recommended for in situ phytoremediation/phytoextraction of HMs.
For the phytoremediation of hydroponic solution of Cr, Fe, As, Cd and Ni, a hyperaccumulator ( Helianthus Annus ) was tested by January et al . (2008). H. Annus
28 (sunflower) were given solutions consisting individual HM and combimation (2 & more
than 2) of HMs, in presence and absence of EDTA. The uptake of metals by the
sunflowers was in the following order;
Absence of EDTA “Cd = Cr > Ni, Cr > Cd > Ni > As and Fe >> As > Cd > Ni > Cr”
Presence of EDTA “Cr > Cd > Ni, Fe >> As > Cd > Cr > Ni”
Since other metals did not affect the uptake, there was a decrease in the concentrations of
Ni and Cd in stems. In EDTA presence, the other metals translocation was improved. On
the whole, EDTA served as a barrier for the uptake of metal. EDTA reduced Cd in stems
and the roots from 2.1 to 1.4 and from 2.8 to 2.3 mgg -1 biomass, respectively. When
experimented with heavy metals. In similar conditions, total metal uptake decreased from
15 to 13.9 mg, Ni decreased from 1.9 to 0.9 mgg -1 in stems and total biomass decreased from 2.4 to 2.01 g. On the whole, negative effect in addition to EDTA was observed in results. Though it is unfamiliar whether the harmful effect was as a result of the breaking of phytochelatin-metal bonds or the toxicity caused by EDTA. The research highlighted the sunflowers ability to achieve a hyperaccumulator status for both Cd and As. Without
EDTA, Ni achieved the hyperaccumulator status. A significant achievement was made in this research that dwarf sunflower was a hyperaccumulator.
For the phytoremediation of the contaminated areas, the potential of monosilicic acid was examined by Ji et al. (2016). There is a negative influence on human health and food quality of agricultural areas contaminated with HMs. For elimination or control of HMs in the polluted agri-soils, a variety of remediation procedures have been developed. This study exceedingly recommended the use of phytoremediation, as this can a ground- breaking technology with advantages such as easy examining, high selectivity and inexpensive. The two major limitations in phytoremediation may be negative impacts of
HMs plants and long time duration. One kg of sieved and dried soil was placed in 1L
29 plastic pots for the experimental setup. In each pot, Hordeum vulgare L. (barley) send
were sown. monosilicic acid was mixed in water for irrigation in different
concentrations, ranging from 5 to 100 mgL -1, volume for daily irrigation was 50 ml. For
regulation of the HM (Zn, Pb, Cr and Cd) mobility in the soil-plant system, monosilicic
acid could be used. The HM bioavailability was improved by 30% to 150%, in presence
of 0 to 20 mg of monosilicic acid in soil. On the other hand, monosilicic acid application
also reduced the negative effects on barley, however, the HM mobility in the soil
decreased by 40 to 300%, when monosilicic acid amount was above 20 mgL -1. Detailed
investigation revealed that the HM transport via plant sap using gate-bearing transport in
apoplast. To enhance the phytoremediation effectiveness, use of the monosilicic acid was
finally recommended by this study.
Phytoremediation by using Azolla caroliniana for heavy metals from fly ash (FA) pond
was evaluated by Pandey (2012). Azolla caroliniana (water fern) reveals characteristics of tolerance while growing naturally in abundance on metal enriched surface of FA pond.
For the results it is clear that the A. caroliniana has high bioconcentration factor and
show great capability for phytoremediation. In roots and fronds, the metals accumulated
ranged from 86 to 753 mgkg -1 and 175 to 538, respectively. In root, the HM
accumulation (mgkg -1 dw) trend was like: “Fe (538) > Zn (347) > Ni (299) > Cu (286) >
Mn (274) > Cr (232) > Pb (190) > Cd (165)”
While, metal accumulation in frond was as follows: “Fe (753) > Zn (210) > Ni
(161) > Mn (144) > Cr (137) > Cu (106) > Pb (92) > Cd (86) ”
Compared to non-essential (Pb, Cd) heavy metals, less toxicity is caused by the surplus amount of essential heavy metals. There is a significant correlation between concentrations of Cr in frond next to concentrations of Pb in root which is highly positive
(r = 1, p < 0.01). Concentration of Pb in frond and concentration of Cr in root also had
30 the same correlation coefficient (r). A highly positive significant correlation was also
found between the Fe and Cr (r = 0.99, p < 0.01). All the values of BCF
(Bioconcentration factor) for all metals in frond and root ranged from 1.8 to 11.0 and 1.7
to 18.6, respectively. For different heavy metals, the translocation factors (TF) vary from
0.37 to 1.4. The study concluded that A. caroliniana can be used for phytoremediation of
FA ponds and is a potential accumulator of heavy metals.
In a pilot-scale study, the distribution of Zn, Pb, Cu and Cd between Paulownia tomentosa (tree) and a contaminated soil as investigated by Doumett et al . (2008). P. tomentosa was grown in contaminated soils with following metal concentrations: Cu
2081, Zn 4680 mgkg, Pb 3362 mgkg -1 and Cd 64.9 mgkg -1. The addition of glutamate,
tartrate and EDTA was at 1.0 to 10.0 mM as complexing agent. The metal accumulation
highly depends on concentration and nature of complexing agent. The concentration
ratios of metals in roots/shoots were in the range of 11 to 39 for Pb, 7 to 17 for Cu, 5 for
Zn and 9 to 18 for Cd. Improvement in metal uptake was observed in reaction to
complexing agent addition. This was primarily obtain in roots with the exclusion of
glutamate, also for Zn (670 mgkg -1 for tartrate 10 mM and 237 mgkg -1 for the
control).and for Cu (594 mgkg -1 for glutamate 10 mM and 146 mgkg -1 for the control)
and Pb (359 mgkg -1 for EDTA 10 mM and 128 mgkg -1 for the control). EDTA still facilitate HM bioaccumulation in plants, similar to glutamate and tartrate. The results of the present studies suggest that in HM bioaccumulation metal concentration between soil and plants is not important factor. Eventually, the metal bioavailability was lower in the trials treated with tartrate and glutamate and higher in the trials treated with EDTA. The glutamate results were not much dissimilar from the control. The use of this chelator was associated with the risk leaching, negative impacts on environment and their persistence.
The research proved experimentally that the use of above mentioned ligands did not
31 cause bio-leaching of metals. For phytoremediation of heavy metal, Paulownia
tomentosa may be a promising species as signified by the results of the research.
The remediation of contaminated areas with large heavy metal/radionuclide (HM/R) is
too much costly as compared to the remediation of organic waste (Willscher et al .,
2013). For such areas prolonged and sustainable technique of remediation is desirable.
At a former uranium mining site in East Germany, experiments on phytoremediation of
HM/R were carried out on site. The experimental field site is reasonably contaminated
with HM/R. The phytoremediation was performed in combination of phytostabilization
and phytoextraction methods using microbes, soil and plant in lab and in field. Plant
investigated were Triticale , Helianthus annuus and Brassica juncea . Influence of
biological additives (fungi, bacteria) and soil amendment strategies (increasing pH and
organic matter, fertilizer) on biomass production and plant tolerance to heavy metals was
also investigated. In lysimeter experiments, a minimization of HM/R accumulation in
soil was observed. The final utilization of HM/R loaded plant residues after harvests was
studied for biogas, ethanolic fermentations and combustion of the plant material. The
fate of HM/R in the different by-products was investigated. The HM/R loaded biomasses
subsequently be utilized in a biogas process. An inhibition of the biogas formation by
HM/R contaminated plants was not observed. The digested sludge of the biogas process
represented a sink for HM/R. This study recommended the use of phytoextracted
biomass for thermal utilization and 14,150 KJkg −1 of bioenergy could be achieved from the shoot parts. After the combustion experiments, 70 to 99% of U accumulated before by the plant were measured in the ashes of Triticale . As a general result of this
comprehensive research work, the harvested plant biomass from phytoremediation of the
test field site subsequently be utilized for the winning of bioenergy; the useful
combination of both methods will be innovative and sustainable.
32 Sorghum bicolor L. shoots contaminated with heavy metals, were investigated for its
proper disposal through flash and slow pyrolysis (Chami et al ., 2014). The disposal or treatment of biomass contaminated with metal is still an unsolved problem. In relation to the application of pyrolysis metal distribution is also very important. Sorghum bicolor
(L.) was cultured in a semi-hydroponic to evaluate its potential use in phytoremediation.
In green house S. bicolor was grown on perlite as substrate, the control plants were irrigated with half-strength Hoagland’s solution and other plants were irrigated with solution supplemented with Zn and Ni (CTM; 10 gm -3 each). The Zn and Ni
concentrations in shoots were 58 mgkg -1 and 11 mgkg -1, respectively. Ni was the
prevalent metal in the roots (1217 mgkg -1) whereas, Zn was the dominant metal in the
shoots (179 mgkg -1). At 450 0C, flash and slow pyrolysis was carried out on S. bicolor
shoots. Focusing on metal distribution pyrolysis and biomass products was examined.
With comparatively reasonable concentrations of Zn and Ni, S. bicolor delivered good shoot biomass. Almost all metals accumulate in the char and metal concentrations in the pyrolysis oils were lower than detection limits. When a slow pyrolysis process was applied, 98% of Zn and 99% of Ni were recovered in the char. Moreover, compared to flash pyrolysis, the percentages of char and oil were higher in slow pyrolysis. Removing the bottleneck for executing further phytoremediation cleanup procedures, energy recovery in the char from slow pyrolysis was higher than flash pyrolysis. It also permit decontamination of soils and economical production of energy and/or other products with a higher added value.
To remove heavy metals in an assorted polluted site (metals and organochlorine pesticides (OCPs), a creative on-site soil washing technology was developed (Ye et al.,
2014). For the removal of contaminants from the soil, high temperature (60 oC) was combined with 45gL -1 carboxylmethyl-β-cyclodextrin and ultrasonication (40 kHz, 20
33 min). After two succeeding washing cycles, the revoval rates for total endosulfans,
OCPs, chlordanes, Pb, mirex and Cd were approximately 98.5%, 94.7%, 92.3%, 87.3%,
87.2% and 91.6%, respectively. in the second phase of the experiment vetiver grass was cultivated and it further enhanced the OCPs degradation by 34.7%. the soil micro flora also started restoring and increased the fertility of soil. This outcome was signified as it increased the microbial number, biomass C and N. all the results were statistically significant (p < 0.05). In addition, the minor environmental hazard of remaining contaminants in the remediated soil was at a suitable level. The collective cleaning tactic is an ecologically best technology that is essential for risk reduction and managing the mixed polluted sites.
Basile et al . (2015) studied the effect of polluted river water on morpho-physiological alteration in aquatic plant Lemna minor (Lemnacee, Arales). These plants were grown in fresh water (7 days) from river Sarno (Campania, Southern Italy), which contain high load of pollution. Changes in vacuoles and chloroplasts (organization and shape) were observed. To confirm the time and dose dependent effects, some specimens were grown in lab by irrigating them with the same amount of toxic water. Concentrations range from
10 4 to 10 6M. Transmission electron microscopy (TEM) observations revealed the modifications/destructions in plastids, vacuoles and other sub-cellular structures. The level of “Heat Shock Proteins 70 (Hsp70)” also got elevated irrespective to the HM concentration. Based on the data it was clear that Co presence increased Hsp70 levels, while Pb and Cd presence do not cause any change in Hsp70. L. minor showed a positive association between Hsp70 and HMs concentration. The study proposed L. minor as an organism capable to study heavy metals contamination negative impacts. The study also recommends the use of Hsp70s as indicator of HM pollution/contamination.
34 Bini et al. (2012) investigated the effect of mine soil (Italy) on Physio-chemical and
morphological characteristics of Taraxacum officinale . Mine soil contains various
elements and their presence exert negative health and morphology constrains. Plants
growing on metal polluted soils can uptake heavy metals and accumulate them in their
tissues. In order to evaluate the levels of potentially contaminated heavy metals (Cr, Zn,
Cu, Cd, Pb, Fe) in plants were grown in soil (sulphides of (Fe, Zn, Pb, Cu)). T. officinale
accumulated high amounts of various HMs in both underground and above ground parts,
with highly positive “translocation factor” (TF > 1). Micro-morphological examination
revealed major reduction in leaf thickness, changes in intercellular structures and spaces,
un-contaminated soils do not damage cell structures. Plants show strong correlation with
metal concentration and damage level. In both shoot and root, cadmium is lower than the
phytotoxicity threshold level and below the control value (up to 1.46 mgkg −1 ). In shoot
Co and Pb accumulated in much elevated levels (Pb upto 193 mgkg −1 and Cu upto 64
mgkg −1 ). Iron accumulation was quite variable in concentration and maximum was found
in leaves (890 mgkg -1). Below 1000 mgkg -1 Fe is not considered as pollutant. This
research work designates T. officinale as good candidate for phytoextraction/phytoremediation of HM contaminated soils.
Salam et al. (2016) conducted a pot experiment using soil contaminated with different
HMs (Cr, Zn, Co, Ni and petroleum hydrocarbons) to investigate metal tolerance and
uptake. Plant tested was Salix schwerinii. Pots were filled with soil collected from land
fill site (Finland) and peat soil was also added in different concentrations. Plants were
segregated into 2 groups, first group was irrigated with municipal wastewater (MWW)
and the second group was irrigated with tap water. The experiential set up was for 141
days. Addition of peat soil speed up the plant growth and phytoremediation rate. Heavy
metal concentrations are like; Cr from 17 – 250 mgkg -1, Zn from 142 – 1616 mgkg -1, Co
35 from 12 – 223 mgkg -1 and Ni from 10 – 76 mgkg -1. The concentration from maximum to
minimum is al follows; Cr > Zn > Co > Ni. Over the course of time the reduction in total
petroleum hydrocarbons was also noted by Salix. Results of this experiment advocate
that S. schwerinii is potential specie for HMs removal. Results also recommended the use
of municipal waste water for irrigation and as it increased soil nutrients, increased
growth/biomass, as a substitute of fertilizers.
Sharmin et al. (2012) claimed that despite the widespread occurrence of chromium
toxicity, its molecular mechanism is poorly documented in plants compared to other
heavy metals. To investigate the molecular mechanisms that regulate the response of
Miscanthus sinensis roots to elevated level of chromium, seedlings were grown for 4
weeks and exposed to potassium dichromate for 3 days. Physiological, biochemical and
proteomic changes in roots were investigated. Lipid peroxidation and H 2O2 content in roots were significantly increased. Protein profiles analyzed by two-dimensional gel electrophoresis revealed that 36 protein spots were differentially expressed in chromium- treated root samples. Of these, 13 protein spots were up-regulated, 21 protein spots were down-regulated and 2 spots were newly induced. These differentially displayed proteins were identified by MALDI-TOF and MALDI-TOF/TOF mass spectrometry. The identified proteins included known heavy metal inducible proteins such as carbohydrate and nitrogen metabolism, molecular chaperone proteins and novel proteins such as inositol monophosphatase, nitrate reductase, adenine phosphoribosyl transferase, formate dehydrogenase and a putative dihydrolipoamide dehydrogenase that were not known previously as chromium responsive. Taken together, these results suggest that Cr toxicity is linked to heavy metal tolerance and senescence pathways, and associated with altered vacuole sequestration, nitrogen metabolism and lipid peroxidation in Miscanthus roots.
36 Vollenweider et al. (2011) explained in a study, the distribution of heavy metals, macro- and micronutrients and the metal micro-localisation as a function of the leaf position and heavy metal treatment were analysed in poplars grown on soil with mixed metal contamination. Zinc was the most abundant contaminant in both soil and foliage and, together with cadmium, was preferentially accumulated in older foliage whereas excess copper and lead were not translocated. Changes in other element concentrations indicated acceleration in aging as a consequence of the metal treatment. Excess zinc was irregularly accumulated inside leaf tissues, tended to saturate the veins and was more frequently stored in cell symplast than apoplast. Storage compartments including metabolically safe and sensitive subcellular sites resulted in sizable metal accumulation as well as stress reactions. In the leaf blade, excess Zn was irregularly and discretely distributed and the Zn was characteristically 1) stronger in the abaxial than adaxial tissues, 2) strongest inside of and directly next to veins, 3) progressively decreasing away from veins and 4) regularly missing within some leaf blade segments. It suggests that metal translocation in leaves was impaired due to an excessive supply of Zn. Leaf tissues stored Zn either exclusively in the symplast or in the symplast/apoplast. The main apoplastic compartment for Zn storage was found in the lower epidermis, especially next to veins. Zinc detoxification by storage in vein collenchyma. The study concludes that using a wild poplar provenance from an unpolluted site, Zn contaminants were allocated to safe as well as stress-prone subcellular sites such as the vacuole and cell wall on one hand and the cytoplasm and chloroplasts on the other with an apparent prevalence to the symplastic sites.
Siwik et al . (2010) studied the total mercury distribution (THg) in native deciduous trees.
The basic idea is to access the practicability to use these trees as biomonitors for historical sites which are known to have high mercury. One of the sites selected for tree
37 sampling was Kingston Ontario, and these plants were compared with reference site
(non-contaminated). Wood and bark samples of Quercus spp., Salix spp., Acer spp. And
Populus spp. Correlation between THg between wood, bark and soil was analyzed.
Results indicated that the THg among is highly correlated for wood and bark samples
and is not correlated for soil and wood samples. Data did not support any temporal
variation and accumulation of THg in 4 species. Salix and Populus (shoreline species)
accumulated high contents of THg which reaches up to 18.2 ngg -1 and 19.4 ngg -1, respectively. Where as, inland species ( Acer spp. and Quercus spp) reported 7.2 and 1.3 ngg -1, respectively. Detailed investigation showed that that the source of THg in wood and bark is air not the soil as the soil samples did not showed significant amount of THg.
It was also highlighted that the most THg accumulated in heart wood (inactive) and less in sap wood (active), as most of the THg is translocated from sap wood. Statistically very significant difference was found between fall and spring cores (wood) of the same specie. The bioaccumulation of THg is specie related and depends on different bio- chemical pathways. The research concludes that Quercus and Acer are not vary good to be used as bio-monitor, where as, Populus and Salix are very good and can be used as spatial and temporal bioindicator.
Miao et al. (2012) studied the impact of different amendments like citric acid (CA), sepiolite, acetic acid (AA), ethylene di-amine tetraacetic acid (EDTA) and phosphor- gypsum on HM uptake and growth of Arundo donax L (giant reed). This plant was grown in garden soil with added Cd, As and Pb. Plants showed remarkable increase in biomass (root and shoot) up to 24%. The quantity of SOD (superoxide mutase) and CAT
(catalase) also increased. All the treatments of experimental set up showed positive
Physio-chemical signs as compared to the control. Addition of EDTA, AA and CA increased the metal uptake at low concentration. Maximum positive limit for CA was 5
38 mmolkg -1, for EDTA it was 2.7 mmolkg -1. Interestingly, the bioaccumulation of Cd and
As is improved in presence of EDTA, citric acid and acitic acid and these amendments
do not significantly increase Pb uptake and bioaccumulation. Maximum Pb was
observed/reported with the addition of sepiolite (4 gkg -1) and phosphogypsum (8 gkg -1).
Despite the fact that EDTA enhance the metal uptake but it use in not highly recommended in this research, as it is non-degradable and form soluble complexes with metals. These soluble complexes pose serious threat to ground water as they may percolate downward (leaching). This study recommends the use of acetic acid, sepiolite and citric acid for increasing the phytoextraction and phytoremediation ability of giant reed.
Singh and Singh, (2006) studied Dalbergia sissoo plantlets for different parameters in
water stress. Parameters studied were photosynthetic rate, reductase activity in leaf,
temperature of leaf, proline content, nodulation pattern, nutrient translocation and fresh
weight. Plants were planted in plastic containers having 120 kg of loamy soil and were
given different treatment of water stress. Water stress was established by adding different
salts of lead in soil and by decreasing the amount of irrigation water. Results indicated
that the water stress cause decrease in photosynthetic rate (-25%), stomatal conductance
(-32%), leaf area (15%), water potential in leaf (-21%), number of nodules in root (-
22%), mass of nodules (-18%), mineral uptake (especially nitrogen) (-20.1%), CO 2
assimilation (-13%). However, reductase activity in leaf and biomass of seedling
increased. Proline was only detected in seedling with high water stress. The study
concludes that the Dalbergia sissoo is quite resistant plant and can with stand minor
water stress and is recommended to be used in area where water scarscity is a major
problem.
39 3. Materials and Methods
3.1. Selection of plant species
Five tree species of Family Fabaceae were selected as test species to conduct this
research work. Morphological details are given in appendix VII. The species name is;
1. Millettia peguensis Ali
2. Pongamia pinnata (L.) Pierre
3. Albizia lebbeck (L.) Benth.
4. Bauhinia purpurea L.
5. Dalbergia sissoo Roxb.
3.2. Collection of germplasm
Seeds of above mentioned species were collected from Forest Department (Cooper Road
Lahore). Healthy seeds were selected and unhealthy were discarded. Only healthy seeds
were used in germination experiment. Plantlets of experimental tree species were
collected from Nursery of Punjab Forest Department, Lahore. Healthy and equal
heighted plantlets were selected and used in pot experiment.
3.3. Wastewater collection and analysis
Three types of wastewater were collected as under
A. Domestic Wastewater (DWW)
B. Hospital Wastewater (HWW)
C. Industrial Wastewater (IWW)
Domestic wastewater was collected from sewage drain near River Ravi, Lahore.
Industrial waste water was collected from Quaid-e-Azam Industrial State, Lahore.
Hospital waste water was collected from Combined Military Hospital, Mayo Hospital
and Services Hospital, Lahore. The collections and physicochemical analyses of
wastewaters were done according to the standard Protocols of APHA (American Public
40 Health Association, 1989). Following five dilutions of each type of wastewater were
prepared;
T0 (100% Tap water),
T1 (75% tap water + 25% WW),
T2 (50% tap water + 50% WW),
T3 (25% tap water + 75% WW) and
T4 (100% WW).
3.4. Experimentation
The research project was divided into three steps
Germination Experiment
Pot Experiment
After-harvest Analysis
3.4.1. Germination experiment
The 1 st step towards in vitro germination was to stirlize all the equipment, appratus as
well as the seeds. Glass jars, Petri plates and their lids were washed with detergent and
rinsed with tap water until detergent was completely removed then these jars were dried
in oven at 180 oC for 6 hours. In each glass jar, one gram cotton and Wattsman filter paper were placed as a base for the germinating seeds in glass jars and Petri plates respectively. From each dilution (above described) of all the three types of wastewaters,
15 ml was poured in each experimental container and closed their lids tightly and autoclaved at 120 oC and 15lb for 15 minutes.
Seed sterilization: Healthy seeds of each species were surface sterilized by
detergents and tap water. Later seeds were washed with the mixture of 0.2% HgCl 2 and tween-20 (2 drops) for 5 minutes. Seeds were then rinsed three times with distilled water.
Sterilized seeds were placed in each glass jar, covered properly and were placed in
41 growth room with photoperiod of 8 hrs at 26 oC. Each treatment had 3 replicates and all were placed in completely randomized block design for 15 days and were keenly observed on daily basis. Emergence of radicals was taken as germination of seeds.
Parameters recorded were:
% Germination (%)
Root length (cm)
Shoot length (cm)
Seedling length (cm)
Seedling fresh weight (g)
Seedling dry weight (g)
Seedling vigor index ( S.V.I ) (Bewly and Black, 1982)
Seedling vigor index = Germination (%) X seedling length (cm)
Tolerance Index ( T.I ) (Iqbal and Rahmati, 1992; Meszaros et al., 2013)
Tolerance Index = Wastewater treated seedling FW (g) x 100 Control seedling FW (g) and
Mean time to germination ( MTG )
MTG = Σn x d N Where:
n = number of germinated seeds
d = time to incubate
N = total number of seeds
3.4.2. Pot experimentation
Pot experiment was conducted in GCU Botanic garden, under natural environmental growth conditions.
42 Pot filling: Plastic sheets were pasted on the inner walls of each pot to avoid the
horizontal seepage but the base of each pot was left uncovered that insured the 100%
vertical seepage of wastewater for irrigation of roots and filled with soil (5.5 Kg/12” pot)
and humus (in 3 is to 2 ratio) which was properly mixed with soil before filling. The pot
size in this research work for each plant of each species was changed (12”, 14”, 18” and
24”) after every 6 month as such.
Plantlets were planted in pots. Three replicates were arranged for each treatment.
Tree species Wastewaters Dilutions Replicates Total number
of plants
5 3 5 3 225
Permanent ink marker was used to tag the dilution of each wastewater on each pot. Pots
were arranged in 3 groups in completely randomized block under full sunlight so that
those should receive equal climatic conditions.
Wastewater irrigation: First group was irrigated with different dilution of domestic
wastewater (DWW), 2 nd and 3 rd groups were irrigated with different dilutions of industrial (IWW) and hospital wastewater (HWW), respectively. Wastewater was supplied thrice in a week during winter, daily in summer with the help of measuring jug and no wastewater was given during rainy season. a. Growth measurements:
Growth measurements include the following
Plant Height (cm)
Stem diameter (cm)
Both were recorded after 3 months (4 times in a year) during this research experiment.
43 b. Eco-physiological record:
Following eco-physiological attributes were recorded two times total during 2 years with
the help of IRGA "Infra Red Gas Analyzer" (LCA4 Model) (Vernay et al ., 2008).
Photosynthetic rate
Transpiration rate
Stomatal conductance
c. Destructive Measurements: After the completion of 2 years the tree species were
harvested/uprooted, shifted them in to Botany Department at GC University, Lahore and
following parameters were recorded for the half samples of each species
Tree fresh weight (g)
The harvested plants were dried in oven at 180 oC till complete dryness and after recording following parameter those were used for heavy metal estimation
Tree dry weight (g)
Fresh samples of each species were preserved in freezer at 4 oC for further analysis like estimation of;
Lipid peroxidation
Free proline levels.
I. Lipid Peroxidation Estimation
Frozen plant tissue, 0.1 g weight was homogenized with 0.5 ml TCA (0.1%) and centrifuged that for 10 min at 15000 xg, 4 oC. The mixture of supernatant (0.5 ml), 0.5%
TBA (1.5 ml) and 20% TCA (8 ml for dilution) was heated at 95 oC for 25 min. in water bath, transferred to ice bath. The absorbance was measured at 532 nm and 600 nm by spectrophotometer (Health & Packer, 1968).
Where,
TCA = 2,4,6-Trichloroanisol
44 TBA = Tertiary butyle acetate
II. Determination of free proline levels
Frozen plant tissue of 0.5 g weight was homogenized with 5 ml Sulphosalicylic acid
(3%) in mortar and pestle. Extract, glacial acetic acid (2ml) and ninhydrin reagent (2 ml)
was heated in a test tube at 100 oC for 1 hr in water bath. Brick red coloured extract was cooled and 4 ml toluene was added, mixed (thoroughly) and filtered. The absorbance at
520 nm was measured by spectrophotometer (Bates et al ., 1973).
III. Heavy Metal Determination
The dried plants were grinded in electrical grinding mill into powdered form and ashed
in a muffle furnace at 460 °C for 6 h. One gram ash was digested in 10 ml of
concentrated HNO 3 and heat for 5 min., diluted to 20 ml with distilled water and then
filtered. The concentration of heavy metals was analyzed from PINSTECH (Pakistan
Institute of Nuclear Science and Technology), Islamabad by ICP-OES technique.
Heavy metal uptake rate (1g plant -1d-1) was calculated using following formula:
Heavy metal uptake = M2 x W 2 - M 1 x W 1 T2 - T 1 Where:
M1 and M2 = Concentration of metal in plant tissue and
W1 and W2 are the plant biomass at time T1 and T2.
The translocation factor (TF) was calculated using the following formula:
TF = Hagp Hbgp Where;
Hagp and Hbgp are heavy metal concentrations in above and
below ground plant parts, respectively
45 IV. Statistical analysis
The data for each parameter was analyzed for Analysis of Variance (two-way ANOA).
Microsoft excel was used for the calculation of means, standard errors, standard deviations and least significance difference (LSD). The means were checked at 5% probability level by Duncan’s Mutiple Range (DMR) test using SPSS and CoSTAT.
46 4. Results
4.1. Wastewater analysis
The physiochemical analysis of IWW, DWW and HWW is given in Table 4.1. It is clear from the results that all the 3 types of wastewater are highly contaminated and is unfit for any use in agriculture and industry. All the parameters like, COD, BOD, TSS and HMs are above the permissible limits. Currently in Lahore no hospital has any wastewater treatment system. Similarly, some of the industries have installed their treatment plants but they either do not operate them or their efficiency is not up to the mark. In terms of toxicity of wastewater types (WWT) the order is as follows: Industrial > Hospital >
Domestic
Table 4.1. Average physio-chemical characteristics of wastewaters Parameters Domestic Industrial Hospital pH 6.9 5.6 7.9 EC (µs) 88 112 94 COD (mgL -1) 372 1198 654 BOD (mgL -1) 234 673 335 N (%) 1.76 2.87 2.16 K (ppm) 679 843 732 P (ppm) 422 543 487 Cl -1 (mgL -1) 340 402 367 Mg +2 (mgL -1) 71 113 98 Ca +2 (mgL -1) 156 232 201 Pb (µg/ml) 351 856 -- Cr (µg/ml) -- 6.3 5.43 Cu (µg/ml) -- 2.5 1.78 Mn (µg/ml) -- 29.4 21.32
47 4.2. Germination studies
4.2.1. Effect on Germination percentage
Data for % seed germination is given in table 4.2 which shows that D. sissoo and A. lebbeck showed the maximum percentage of seed germination in all the three types of
WW, even in the tap water i.e. 99.6%, while, the minimum percentage seed germination is showed by M. peguensis i.e. 89.6%. The data showed that percentage seed germination decreased significantly with the increase in wastewater concentration. This decreased pattern was exhibited by all 5 tree species. Percent reduction in germination was calculated in response to control and the results are given in figure 4.1, 4.2 and 4.3. For
D. sissoo the decrease in % germination was less up to 75% DWW and then there was the sharp decline. The maximum reduction was observed with IWW. For A. lebbeck all the 3 WW types impacted negatively and maximum decrease of about 45% was reported with IWW. Other plants like B. purpurea , M. peguensis and P. pinnata also showed some what the same toxicity pattern. The order of WW toxicity was as follows:
Domestic < Hospital < Industrial
Supplementary graphs are given in appendix VI, Fig VI.1 - VI.5.
48 Table 4.2: Impact of wastewaters on seed germination (%) of selected tree species Wastewater Name of Species Wastewater concentration 0% 25% 50% 75% 100% Domestic D. sissoo 99.6 97.6 95.2 88.8 74.2 + 2.39 + 1.95 + 2.86 + 2.58 + 2.37 A. lebbeck 99 94.9 90.8 81.3 67.1 + 2.79 + 2.85 + 2.54 + 1.63 + 2.15 B. purpurea 95.2 92.2 82.3 68.4 55.5 + 2.67 + 3.04 + 2.63 + 2.05 + 1.17 P. pinnata 92.6 87.8 74.2 55.5 47.7 + 2.78 + 2.28 + 1.34 + 1.83 + 1.05 M. peguensis 89.1 83.4 69.8 52.8 41.6 + 2.58 + 2.34 + 2.16 + 1.48 + 1.50 Hospital D. sissoo 99.6 95.8 90.0 82.0 70.2 + 2.39 + 2.68 + 2.79 + 2.30 + 2.53 A. lebbeck 99 92.4 84.9 73.1 63 + 2.79 + 3.05 + 2.72 + 2.19 + 1.32 B. purpurea 95.2 88.5 76.8 61.6 51 + 2.67 + 3.01 + 2.30 + 1.79 + 1.63 P. pinnata 92.6 83.2 67.8 48.8 37.6 + 2.78 + 2.33 + 2.10 + 1.37 + 1.50 M. peguensis 89.1 76.5 61.6 43.7 33.6 + 2.58 + 2.45 + 1.72 + 0.87 + 1.51 Industrial D. sissoo 99.6 91.0 82.0 72.4 64.5 + 2.39 + 3.82 + 2.46 + 2.10 + 2.77 A. lebbeck 99 87.1 74.0 66.0 57.3 + 2.79 + 2.44 + 2.29 + 1.85 + 2.06 B. purpurea 95.2 82.0 66.5 54.4 41.2 + 2.67 + 2.71 + 2.13 + 1.63 + 0.87 P. pinnata 92.6 77.7 56.0 43.6 31.8 + 2.78 + 2.56 + 1.79 + 1.31 + 0.67 M. peguensis 89.1 69.0 44.5 33.1 20.4 + 2.58 + 1.38 + 1.34 + 0.96 + 0.92
Two way ANOVA Source of Variation SS df MS F P-value Significance Species 9156.52 14 654.0371 19.58342 1.22 x 10 -16 *** Wastewater concentrations 19724.04 4 4931.01 147.6461 4.74 x 10 -29 *** Error 1870.26 56 33.3975 Total 30750.82 74 Significant result, F (19.58) > F critical (1.87), P-value (1.22 x 10 -16 ) < α (0.05)
49
Wastewater concentration (% ) 25% 50% 75% 100% 0
-10
-20
-30 D. sissoo A. lebbeck -40 B. purpurea P. pinnata -50 M. peguensis Germinationdifferencevs control (%)
-60
Figure 4.1: Germination response of selected five tree species in DWW
Wastewater concentration (% ) 25% 50% 75% 100% 0
-10
-20
-30
D. sissoo -40 A. lebbeck
-50 B. purpurea P. pinnata -60 M. peguensis Germinationdifferencevs control (%)
-70
Figure 4.2: Germination response of selected five tree species in HWW
50 Wastewater concentration (% ) 25% 50% 75% 100% 0
-10
-20
-30
-40
-50 D. sissoo -60 A. lebbeck -70 B. purpurea P. pinnata Germinationdifferencevs control (%) -80 M. peguensis -90
Figure 4.3: Germination response of selected five tree species in IWW
4.2.2. Effect on “Mean Time to Germination”
‘Mean time to germinate (MTG)’ is represented in figure 4.4, 4.5 and 4.6 for DWW,
IWW and HWW, respectively. The seed of D. sissoo required least germination time
(72hrs) where as maximum time was required by M. peguensis seeds (97 hrs) in DWW.
Similarly in IWW the minimum MTG is 87 hrs for D. sissoo and the minimum MTG is
116 hr for M. peguensis . Similar, trends for MTG is exhibited in HWW. All the 5 species
showed less MTG in DWW and high MTG in HWW. The 2 way ANOVA depicts that
all the 3 wastewaters and all the 5 tree species differ significantly from one another.
Supplementary graphs are given in appendix VI, Fig VI.6.
51
100 a 95
90 b
85 c d 80
75 e
Mean time Mean to germination (hrs) 70 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.4: “Mean time to germination” of selected species in DWW
120 a 115
110 b 105 100 c d 95
90 e 85
Mean time Mean to germination (hrs) 80 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.5: “Mean time to germination” of selected species in IWW
52
155 a 150 145 b 140 135 130 c d 125 120 115 e
Mean time toMean germination (hrs) 110 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.6: “Mean time to germination” of selected species in HWW
4.2.3. Effect on seedling fresh weight
The data for seedling fresh weight in Figure 4.7, 4.8 and 4.9 clearly show that the
seedling fresh weight increased with the increase in WW concentration up to a
certain level, beyond that level the seedling fresh weight declined. In DWW the
maximum seedling FW was shown by D. sissoo . The general trend observed was
first increase in FW with increase in WW concentration and then decrease in FW.
Rate of increase and decrease varied among species. For instance in D. sissoo the
decrease in FW starts after 75%., whereas in B. purpurea the FW become almost
equal at 50% and 75%. Similarly in M. peguensis the decrease rate was too slow. It
is clear for figure 4.7, 4.8 and 4.9 that the WWs do not show negative impacts at low
concentrations.
53
0.70 a b c 0.60 d 0% DWW a 25% DWW e b b 0.50 50% DWW c d a a 75% DWW 0.40 b c 100% DWW a a b c 0.30 d d a a b b 0.20 c
Seedling fresh fresh weightSeedling (g) 0.10
0.00 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.7: Seedling fresh weight of selected species in DWW
0.40 0% HWW a 0.35 b c 25% HWW d a 50% HWW 0.30 e b b 75% HWW c 100% HWW 0.25 d a a b b a a 0.20 b c c a 0.15 d b b d c 0.10
Seedling fresh weight(g) 0.05
0.00 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.8: Seedling fresh weight of selected species in HWW
54
0.45 a b c 0% IWW d 25% IWW 0.40 a e b b 50% IWW 0.35 75% IWW d c 0.30 a a 100% IWW b b 0.25 a a b c 0.20 c d a a b b 0.15 c 0.10
Seedling fresh weightSeedling fresh (g) 0.05 0.00 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.9: Seedling fresh weight of selected species in IWW
Supplementary graphs are given in appendix VI, Fig VI.7 - VI.11.
4.2.4. Effect on seedling length
Effect on root length and shoot length can be observed in Figure 4.10, 4.11 and 4.12. The data revealed that the maximum seedling length (SL) is of D. sissoo i.e. (11.4cm) in
DWW. The HWW is most toxic and imparted the maximum damage in terms of SL. It is observed that in low WW concentration the SL increased and then at high WW concentrations the seedling length decreased. All WW treatments and all the species differ significantly from each. The maximum SL of A. lebbeck was at 75% of DWW
(11cm) and the minimum SL of 8.1cm was observed at 25% of HWW. In case of B. purpurea , all the WW concentrations and all the species differ significantly from each other and with control. The trend of WW toxicity and decrease in SL was almost same as compared with other 4 species. The negative effects of DWW, IWW and HWW on P. pinnata SL are quite obvious from figure 4.12. P. pinnata showed less SL compared to
D. sissoo and B. purpurea (figure 4.13). P. pinnata resisted the WW toxicity up to 50%
and then gradual decrease in SL was observed in all WWs (appendix VI, Fig VI.12-16)
55
14 Root length Shoot length
12 a b c 10 d a c b e 8 d a a e b c a b 6 d c d e a 4 b b b
Seedling Seedling length (cm) c 2
0 0 0 0 0 0 25 50 75 25 50 75 25 50 75 25 50 75 25 50 75 100 100 100 100 100 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.10: Seedling length of selected five species in DWW
12 Root length Shoot length
10 a b c d a d b b 8 c c a a b 6 c c a b c e d 4 a Seedling Seedling length (cm) b c 2 c c
0 0 0 0 0 0 25 50 75 25 50 75 25 50 75 25 50 75 25 50 75 100 100 100 100 100 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.11: Seedling length of selected five species in HWW
56
12 Root length Shoot length
10 a b c d a d b b 8 c c a a b 6 c c a b c e d 4 a Seedlinglength (cm) b c 2 c c
0 0 0 0 0 0 25 50 75 25 50 75 25 50 75 25 50 75 25 50 75 100 100 100 100 100 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.12: Seedling length of selected five species in IWW
4.2.5. Effect on “Vigor Index (V.I)”
Very promising results were obtained when different dilutions of WWs were compared
for vigor index (VI). The data in Figure 4.13, 4.14 and 4.15 shows that order of VI is as
follows: D. sissoo > A. lebbeck > B. purpurea > P. pinnata > M. peguensis
D. sissoo is more vigorous in terms of health and it showed positive signs up to 75% of
DWW, where as A. lebbeck and B. purpurea started showing negative signs from 50% of
DWW. M. peguensis had least vigor index for only up to 25% of DWW and further increase in DWW concentration cause decrease in VI. Statistical analysis reveled that all the 5 species were significantly different from each other for VI. By comparing figure
4.13, 4.14 and 4.15 it was reveled that DWW had less toxic effect compared to IWW and
HWW was most toxic. A. lebbeck response in IWW was quite strange; with the increase
in IWW concentrations the vigor index neither increased nor decreased but almost
57 remains same up to 50% concentration. For HWW only D. sissoo VI increased initially and then decreased. Other species showed negative impact right from the start and their
VI decreased with increase in HWW concentration. Again the growth of the five species was significantly different from one another for HWW irrigation (appendix VI, Fig
VI.17 - 21.
1100 0% DWW 25% DWW 900 50% DWW 75% DWW 100% DWW 700
500
Germination Index Vigor 300
100 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.13: Vigor index of selected species in DWW
1050 0% IWW 950 25% IWW 850 50% IWW 75% IWW 750 100% IWW 650 550 450 350 Germination Index Vigor 250 150 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.14: Vigor index of selected species in IWW
58
1000 0% HWW 900 25% HWW 800 50% HWW 75% HWW 700 100% HWW 600 500 400 300 GerminationVigor Index 200 100 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.15: Vigor index of selected species in HWW
4.2.6. Effect on Tolerance index
Tolerance index (TI) is the ability of the plants to with stand the stress conditions. The results for TI are presented in figure 4.16, 4.17 and 4.18 for DWW, IWW and HWW, respectively. In DWW, the maximum TI is shown by B. purpurea i.e. 163 and the least
TI is of A. lebbeck and M. peguensis . statistical analysis revealed that all the treatments of DWW are significantly different from one another. The maximum TI in HWW is 120 by B. purpurea . In HWW (fig 4.17) some of the treatments are non-significant and some are significant (Appendix VI, Fig VI.21 - 26).
The order of treatment significance is as follows;
D. sissoo 75% > 50% > 100% > 25%
A. lebbeck 75% > 50% > 100% > 25%
B. purpurea 75% = 50% > 100% = 25%
P. pinnata 75% = 50% > 100% > 25%
M. peguensis 25% = 50% > 75% > 100%
59
180 25% DWW 50% DWW 160 75% DWW 100% DWW 140
120
100 80
60 ToleranceIndex 40
20
0 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.16: Tolerance index of selected species in DWW
195 25% IWW 185 50% IWW 175 75% IWW 165 100% IWW 155 145 135
Tolerance Index Tolerance 125 115 105 95 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.17: Tolerance index of selected species in IWW
60
140 25% HWW 50% HWW 120 75% HWW 100 100% HWW
80
60
ToleranceIndex 40
20
0 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.18: Tolerance index of selected species in HWW
4.3. Growth studies
4.3.1. Effect on tree height
Statistical analysis reveled that all the species, wastewater types and wastewater
concentrations differ significantly from one another at significant level of 0.05, Figure
4.19 reveles that the P. pinnata was more tolerant for DWW. In DWW P. pinnata height
increased very sharply with the increase in DWW concentration up to 75% and then the
height started decreasing. At 75% P. pinnata showed 95% more height then control. In
HWW the same pattern of increase and decrease was observed. Whereas in case on IWW the increase in height was observed only up to 50% and at 75% and 100% the height showed negative trends. A. lebbeck also showed increased in height for DWW and
HWW (fig 4.20) and in IWW the height did not increased too much when compared with control. From figure 4.21 the height response of B. purpurea can be evaluated. In case of
IWW the height did not increased and a sharp decline was observed. However in HWW
61 the height only increased at 25% and then decline in height was observed which was less sharp as compared to IWW. Similarly in case of DWW a very steep decline was observed from 75% to 100%. The M. peguensis responded least in IWW and sharp decline was visible at 75% and onward concentration (Fig 4.20 & appendix VI, Fig
VI.27 - 31.
Table 4.3: Impact of WWs on height (cm) of selected tree species Wastewater Name of Species Wastewater concentration Type 0% 25% 50% 75% 100% Domestic P. pinnata 135.00 180.00 210.00 270.00 150.00 + 2.70 + 5.94 + 4.20 + 5.40 + 6.60 A. lebbeck 195.00 240.00 285.00 315.00 210.00 + 3.90 + 4.80 + 4.28 + 6.62 + 3.15 D. sissoo 240.00 270.00 300.00 360.00 300.00 + 2.88 + 4.05 + 6.30 + 6.12 + 6.30 B. purpurea 300.00 315.00 330.00 360.00 180.00 + 6.00 + 3.15 + 3.30 + 7.20 + 3.96 M. peguensis 60.00 63.00 72.00 30.00 30.00 + 2.04 + 3.72 + 2.45 + 1.77 + 1.02 Hospital P. pinnata 135.00 150.00 180.00 210.00 90.00 + 5.00 + 7.95 + 6.66 + 4.83 + 3.33 A. lebbeck 195.00 210.00 240.00 270.00 150.00 + 4.29 + 4.41 + 4.80 + 5.67 + 4.65 D. sissoo 240.00 255.00 285.00 255.00 210.00 + 4.80 + 5.87 + 5.70 + 5.87 + 5.67 B. purpurea 300.00 315.00 240.00 210.00 165.00 + 4.20 + 5.99 + 4.80 + 3.99 + 5.12 M. peguensis 60.00 63.00 63.00 30.00 24.00 + 2.22 + 1.26 + 2.33 + 1.59 + 1.20 Industrial P. pinnata 135.00 150.00 168.00 90.00 75.00 + 1.76 + 3.00 + 3.36 + 5.49 + 3.38 A. lebbeck 195.00 204.00 219.00 165.00 105.00 + 6.44 + 8.57 + 4.38 + 6.93 + 3.47 D. sissoo 240.00 240.00 285.00 225.00 150.00 + 5.52 + 7.92 + 5.70 + 7.43 + 4.05 B. purpurea 300.00 255.00 225.00 150.00 120.00 + 6.00 + 5.10 + 4.50 + 5.25 + 3.72 M. peguensis 60.00 61.50 57.00 45.00 30.00 + 3.84 + 2.64 + 3.65 + 1.94 + 1.92
Two way ANOVA Source of Variation SS df MS F P-value Significance Species 496106 14 35436.14 25.73587 2.36 x 10 -19 *** Wastewater concentrations 56540.88 4 14135.22 10.26585 2.63 x 10 -06 *** Error 77107.32 56 1376.916 Total 629754.2 74 Significant result, F (25.73) > F critical (1.87), P-value (2.36 x 10 -19 ) < α (0.05)
62 120 D. sissoo 100 A. lebbeck B. purpurea 80 P. pinnata M. peguensis 60
40
20
0
Differencevs Control (%) 25% 50% 75% 100% -20
-40
-60 Wastewater concentration
Figure 4.19: Height response of selected five species in DWW
60
40
20
0 25% 50% 75% 100% -20 D. sissoo A. lebbeck -40 Difference Controlvs (%) B. purpurea P. pinnata -60 M. peguensis
-80 Wastewater concentration
Figure 4.20: Height response of selected five species in HWW
63
30
20
10
0 25% 50% 75% 100% -10
-20
-30 D. sissoo -40 A. lebbeck Differencevs Control(%) B. purpurea -50 P. pinnata -60 M. peguensis
-70 Wastewater concentration
Figure 4.21: Height response of selected five species in IWW
4.3.2. Effect on fresh weight (FW)
The sequence of maximum FW in DWW is as follows: B. purpurea (364 gm) > D. sissoo
(313 gm) > A. lebbeck (225 gm) > P. pinnata (197 gm) > M. peguensis (58 gm)
Table 4.4, Figure 4.22, 4.23 and 4.24 shows similar trend in maximum and minimum
FW was observed in HWW and IWW. The maximum increase in FW was observed in P. pinnata at 50% of DWW which was about 70% more as compared to control (figure 4.22
- 4.24). FW increased only up to 50% of DWW and started decreasing onward. in response to DWW the decrease in FW was slow and even the FW at 100% of DWW was more then the control. Where as in case on IWW the decrease in FW was quite steep and rapid. The A. lebbeck resisted the WW toxicity up to 75% (fig 4.24) and the maximum increase was at 50% of DWW. From the figure 4.23 it is evident that the B. purpurea
FW is very sensitive towards IWW and HWW and the FW showed negative trend as compared to the control. M. peguensis is quite resistant for DWW and HWW (up to
64 50%) and sensitive for IWW (fig 4.24). Increase in FW of D. sissoo is quite significant for all 3 types of WW. The maximum increase of about 48% was observed in DWW.
The most interesting fact is D. sissoo FW at 100% of DWW is still high as compared to the control (appendix VI, Fig VI.32 – 36).
Table 4.4: Impact of WWs on FW (g) of selected tree species Wastewater Name of Species Wastewater concentration Type 0% 25% 50% 75% 100% Domestic P. pinnata 114 154 197 167 140 +3.42 +4.62 +3.94 +3.34 +2.80 A. lebbeck 166 194 225 213 169 +4.98 +5.82 +4.50 +4.90 +3.55 D. sissoo 217 257 287 313 270 +3.47 +4.11 +5.45 +5.01 +5.67 B. purpurea 270 306 330 364 249 +5.67 +4.28 +3.30 +5.82 +4.98 M. peguensis 40 54 58 37.5 35 +1.60 +1.62 +3.48 +1.88 +1.40 Hospital P. pinnata 110 140 169 135 97 +2.64 +5.60 +5.58 +3.65 +2.23 A. lebbeck 160 175 190 192 138 +4.48 +5.60 +3.99 +4.61 +4.42 D. sissoo 210 236 258 228.2 194.7 +5.04 +4.72 +4.13 +5.25 +4.09 B. purpurea 270 268 263 254 238 +4.86 +4.56 +5.52 +5.33 +3.33 M. peguensis 40 45.9 50.4 35 30 +1.60 +2.75 +1.51 +1.05 +0.90 Industrial P. pinnata 110 126 146 102 60 +2.53 +2.65 +3.65 +3.26 +3.30 A. lebbeck 160 167 174 166 120 +3.20 +3.34 +3.48 +4.32 +2.40 D. sissoo 210 220.5 232.1 200 153.4 +4.20 +6.62 +5.80 +4.20 +3.84 B. purpurea 270 262 256 237 192 +6.21 +5.76 +5.38 +4.27 +3.07 M. peguensis 40 41.7 39.2 34.2 27.5 +1.60 +2.50 +1.57 +1.03 +1.10
Two way ANOVA Source of Variation SS Df MS F P-value Significance Species 508217.7 14 36301.27 104.2922 8.38 x 10 -35 *** Wastewater concentrations 23182.46 4 5795.614 16.65059 4.8 x 10 -09 *** Error 19492.07 56 348.0727 Total 550892.3 74 Significant result, F (104.2) > F critical (1.87), P-value (8.38 x 10 -35 ) < α (0.05)
65 80 D. sissoo 70 A. lebbeck B. purpurea 60 P. pinnata M. peguensis 50
40
30
20
10 Differencevs Control (%) 0 25% 50% 75% 100% -10
-20 Wastewater concentration
Figure 4.22: Fresh weight response of selected five species in DWW
60 D. sissoo A. lebbeck 50 B. purpurea 40 P. pinnata M. peguensis 30
20
10
0
Differencevs Control(%) 25% 50% 75% 100% -10
-20
-30 Wastewater concentration
Figure 4.23: Fresh weight response of selected five species in HWW
66 40 D. sissoo A. lebbeck 30 B. purpurea 20 P. pinnata M. peguensis 10
0 25% 50% 75% 100% -10
-20 Difference vsControl (%) -30
-40
-50 Wastewater concentration
Figure 4.24: Fresh weight response of selected five species in IWW
4.3.3. Effect on dry weight (DW)
The trend in DW increase and decrease was similar to that of FW (Table 4.5 and Figure
4.25, 4.26 and 4.27.). The maximum DW was observed in DWW and the least DW was in IWW. For P. pinnata the decline in DW was slow in response to DWW and was quite steep in response to IWW. In DWW all the treatments showed more DW compared to the control (fig 4.25). Similarly, for A. lebbeck the DW in response to HWW was positive up to 75% and then shape decline was observed (fig 4.26). In response to IWW the DW remain almost constant for 25%, 50% and 75% and then decreased at 100%. B. purpurea showed negative trend in HWW and IWW, but for DWW the response was positive as compared to the control (fig 4.26). M. peguensis showed 53% increase in
DWW at 50% concentration and at higher concentrations the FW decreased (fig 4.25). D. sissoo is quite tolerant for DWW and HWW in both low and high concentrations (fig
4.27), even in IWW the FW did not decreased up to 75%. This is a very good sigh for
WW irrigation.
67 Table 4.5: Impact of different wastewaters on DW (g) of selected tree species Wastewater Species Wastewater concentration Type 0% 25% 50% 75% 100% Domestic P. pinnata 45.60 63.91 81.76 69.31 58.10 +1.82 +3.20 +2.45 +2.08 +1.74 A. lebbeck 64.74 78.57 91.13 86.27 68.45 +2.59 +2.36 +1.82 +1.98 +1.44 D. sissoo 80.94 99.72 111.36 121.44 104.76 +1.30 +1.60 +2.12 +1.94 +2.20 B. purpurea 108.00 126.99 136.95 151.06 103.34 +2.27 +1.78 +1.37 +2.42 +2.07 M. peguensis 16.40 22.95 24.65 15.94 14.88 +0.66 +0.69 +1.48 +0.80 +0.60 Hospital P. pinnata 44.00 53.20 57.46 55.35 40.26 +1.06 +2.13 +1.90 +1.49 +0.93 A. lebbeck 62.08 70.53 76.57 77.38 55.61 +1.74 +2.26 +1.61 +1.86 +1.78 D. sissoo 83.58 97.47 106.55 94.25 80.41 +2.01 +1.95 +1.70 +2.17 +1.69 B. purpurea 108.00 111.22 109.15 105.41 98.77 +1.94 +1.89 +2.29 +2.21 +1.38 M. peguensis 15.60 18.59 20.41 14.18 12.15 +0.62 +1.12 +0.61 +0.43 +0.36 Industrial P. pinnata 41.03 48.89 56.65 39.58 23.28 +0.94 +1.03 +1.42 +1.27 +1.28 A. lebbeck 64.00 69.31 72.21 68.89 49.80 +1.28 +1.39 +1.44 +1.79 +1.00 D. sissoo 86.10 93.71 98.64 85.00 65.20 +1.72 +2.81 +2.47 +1.79 +1.63 B. purpurea 108.00 99.56 87.04 97.17 79.68 +2.48 +2.19 +1.83 +1.75 +1.27 M. peguensis 15.52 16.81 15.80 13.78 11.08 +0.62 +1.01 +0.63 +0.41 +0.44
Two way ANOVA Source of Variation SS Df MS F P-value Significance Species 83526.88 14 5966.206 95.95672 7.74 x 10 -34 *** Wastewater concentrations 3583.657 4 895.9144 14.40933 3.77 x 10 -08 *** Error 3481.856 56 62.17601 Total 90592.39 74 Significant result, F (95.95) > F critical (1.87), P-value (8.38 x 10 -35 ) < α (0.05)
(Supplementary graphs are given in appendix VI, Fig VI.37 - 41).
68 80 D. sissoo A. lebbeck 70 B. purpurea 60 P. pinnata M. peguensis 50
40
30
20
10 Differencevs Control(%) 0 25% 50% 75% 100% -10
-20 Wastewater concentration
Figure 4.25: Dry weight response of selected five species in DWW
60 D. sissoo A. lebbeck 50 B. purpurea 40 P. pinnata M. peguensis 30
20
10
0
Differencevs Control(%) 25% 50% 75% 100% -10
-20
-30 Wastewater concentration
Figure 4.26: Dry weight response of selected five species in HWW
69 50 D. sissoo A. lebbeck 40 B. purpurea 30 P. pinnata M. peguensis 20
10
0 25% 50% 75% 100% -10
-20 Difference Controlvs (%) -30
-40
-50 Wastewater concentration
Figure 4.27: Dry weight response of selected five species in IWW
4.4. Eco-physiological studies
4.4.1. Effect on photosynthetic rate
The data for photosynthetic rate is given in Table 4.6. The sequence of maximum to minimum photosynthetic rate is as follows: M. peguensis > P. pinnata > B. purpurea
> A. lebbeck > D. sissoo
The toxicity of different wastewaters is as follows: HWW > IWW > DWW
P. pinnata showed sharp decline in photosynthetic rate in response to HWW, whereas in
DWW the decrease is quite slow (fig 4.28). The percentage decrease for P. pinnata is as follows: DWW (-35%) < IWW (-48%) < HWW (-84%)
From figure 4.29 it is clear that A. lebbeck showed non-significant difference for DWW and IWW (fig 4.29) and the maximum decrease was -22% (compared to control). In presence of HWW the difference was quite huge but again the different treatments of
HWW (75%and 100%) differ less significantly from one another. For D. sissoo the
70 photosynthetic rate decreased with the increase in WW concentrations, minimum
decrease was observed at 25% and maximum decrease was observed at 100% (fig 4.30).
M. peguensis had non-significant difference for DWW and IWW and very significant difference for HWW (fig 4.29). Initially the decrease was less up to concentration of
75% but then a Sharpe decline was observed. The IWW had less toxic effect of B. purpurea as compared to DWW (fig 4.30). With the irrigation of IWW the
photosynthetic rate decreased about 15% and when irrigated with DWW the decrease
observed was about 30%.
Wastewater concentration 25% 50% 75% 100% 0
-5
-10
-15
-20
-25
-30
Difference controlvs (%) -35 D. sissoo A. lebbeck -40 B. purpurea P. pinnata -45 M. peguensis
Figure 4.28: Change in photosynthetic rate of selected five species in DWW
71 Wastewater concentration 25% 50% 75% 100% 0
-10
-20
-30
-40
-50
-60
Difference vs control(%) D. sissoo -70 A. lebbeck B. purpurea -80 P. pinnata M. peguensis -90
Figure 4.29: Change in photosynthetic rate of selected five species in HWW
Wastewater concentration 25% 50% 75% 100% 0
-10
-20
-30
-40 D. sissoo A. lebbeck
Differencevs control (%) B. purpurea -50 P. pinnata M. peguensis
-60
Figure 4.30: Change in photosynthetic rate of selected five species in IWW
72 Table 4.6: Impact of different wastewaters on photosynthetic rate on selected tree species
Wastewater Name of species Wastewater concentration 0% 25% 50% 75% 100% Domestic P. pinnata 81.30 59.30 53.6 50.30 48.07 +3.25 +2.97 +3.22 +1.51 +2.40 A. lebbeck 68.13 62.50 58.90 56.40 50.47 +2.73 +1.88 +3.53 +2.82 +2.02 D. sissoo 55.20 49.20 46.10 42.00 38.90 +1.32 +2.46 +2.03 +2.31 +1.67 B. purpurea 71.28 59.30 53.92 51.20 47.60 +2.85 +2.97 +3.24 +1.54 +2.38 M. peguensis 87.13 85.10 83.50 81.90 66.18 +3.49 +2.55 +5.01 +4.10 +2.65 Hospital P. pinnata 81.30 51.20 49.35 31.80 13.85 +3.25 +3.07 +4.44 +0.95 +0.28 A. lebbeck 68.13 42.17 31.80 28.00 26.90 +2.73 +1.77 +2.07 +2.13 +1.48 D. sissoo 55.20 38.00 32.80 32.10 31.30 +1.32 +1.90 +1.44 +1.77 +1.35 B. purpurea 71.28 51.60 44.78 34.50 31.80 +2.85 +2.17 +2.19 +2.38 +1.75 M. peguensis 87.13 78.60 73.84 68.18 48.70 +3.49 +3.93 +3.25 +3.75 +2.09 Industrial P. pinnata 81.30 70.80 66.60 64.00 39.92 +3.25 +4.25 +5.99 +1.92 +0.80 A. lebbeck 68.13 62.17 60.00 57.80 50.30 +2.73 +3.73 +3.00 +1.73 +3.52 D. sissoo 55.20 50.90 41.30 38.60 33.40 +1.32 +2.14 +2.68 +2.93 +1.84 B. purpurea 71.28 65.12 63.30 61.40 57.30 +2.85 +3.91 +3.17 +1.84 +4.01 M. peguensis 87.13 85.00 83.20 81.29 67.30 +3.49 +5.10 +7.49 +2.44 +1.35
Two way ANOVA Source of Variation SS df MS F P-value Significance Species 13246.88 14 946.206 22.24735 6.88 x 10 -18 *** Wastewater concentrations 7000.382 4 1750.096 41.14853 4.67 x 10 -16 *** Error 2381.746 56 42.53118 Total 22629.01 74 Significant result, F (22.24) > F critical (1.87), P-value (6.88 x 10 -35 ) < α (0.05)
73 4.4.2. Effect on stomatal conductance
All the wastewater treatments were compared with control and found significantly different from one another (Table 4.7). Stomatal conductance of P. pinnata increases very slowly in presence of IWW and decreases in presence of DWW and HWW (Fig
4.31). All the WWs and concentrations imparted negative effect on A. lebbeck . HWW caused 65% decrease in SC (Fig 4.32). In case of D. sissoo the SC decrease very slowly from 25% to 100% concentration of DWW. Where as, for HWW the decrease rate is very sharp and up to -53% (Fig 4.32). M. peguensis showed increase in SC at 25% / 50% and decrease at 75% / 100%. Maximum change observed was -68% in IWW (Fig 4.33).
The B. purpurea response is quite variable i.e. In case of IWW all the treatments are almost similar with very minimum difference (non-significant). In DWW the decrease was very sharp and the maximum decrease was up to 58%. In presence of HWW SC first increase and then decreased. Maximum increase observed was up to 22%.
Wastewater concentration 25% 50% 75% 100% 10
0
-10
-20
-30
-40
Differencevs control (%) -50 D. sissoo A. lebbeck -60 B. purpurea P. pinnata -70 M. peguensis
Figure 4.31: Change in stomatal conductance of selected five species in DWW
74 Wastewater concentration 25% 50% 75% 100% 40
20
0
-20
-40
-60 Difference vscontrol (%) D. sissoo -80 A. lebbeck B. purpurea P. pinnata -100 M. peguensis
Figure 4.32: Changes in stomatal conductance of selected five species in HWW
Wastewater concentration 25% 50% 75% 100% 20
10
0
-10
-20
-30
-40
-50 Differencevscontrol (%) -60 D. sissoo A. lebbeck -70 B. purpurea P. pinnata -80 M. peguensis
Figure 4.33: Changes in stomatal conductance of selected five species in IWW
75 Table 4.7: Impact of different wastewaters on stomatal conductance on selected tree species Wastewater type Name of species Wastewater concentration 0% 25% 50% 75% 100% Domestic P. pinnata 0.50 0.34 0.27 0.26 0.19 +0.010 +0.010 +0.005 +0.008 +0.008 A. lebbeck 0.40 0.28 0.24 0.23 0.21 +0.008 +0.006 +0.005 +0.009 +0.004 D. sissoo 0.24 0.23 0.22 0.21 0.18 +0.007 +0.008 +0.004 +0.006 +0.004 B. purpurea 0.31 0.29 0.21 0.19 0.13 +0.006 +0.006 +0.006 +0.007 +0.003 M. peguensis 0.77 0.77 0.76 0.67 0.34 +0.015 +0.015 +0.030 +0.020 +0.007 Hospital P. pinnata 0.50 0.35 0.31 0.25 0.10 +0.015 +0.015 +0.009 +0.005 +0.004 A. lebbeck 0.40 0.29 0.22 0.21 0.15 +0.008 +0.006 +0.009 +0.008 +0.003 D. sissoo 0.24 0.22 0.19 0.14 0.11 +0.005 +0.008 +0.006 +0.003 +0.004 B. purpurea 0.31 0.33 0.38 0.26 0.19 +0.009 +0.007 +0.019 +0.005 +0.006 M. peguensis 0.77 0.39 0.34 0.25 0.21 +0.015 +0.015 +0.010 +0.005 +0.008 Industrial P. pinnata 0.50 0.51 0.53 0.56 0.27 +0.010 +0.010 +0.023 +0.014 +0.009 A. lebbeck 0.40 0.28 0.25 0.23 0.20 +0.012 +0.006 +0.006 +0.007 +0.008 D. sissoo 0.24 0.18 0.16 0.14 0.12 +0.005 +0.004 +0.003 +0.005 +0.004 B. purpurea 0.31 0.23 0.23 0.22 0.21 +0.009 +0.007 +0.009 +0.004 +0.008 M. peguensis 0.77 0.79 0.79 0.61 0.23 +0.015 +0.016 +0.024 +0.024 +0.005
Two way ANOVA Source of Variation SS Df MS F P-value Significance Species 1.623 14 0.115999 16.81872 3.43x 10 -15 *** Wastewater concentrations 0.530 4 0.132566 19.22089 5.34 x 10 -10 *** Error 0.386 56 0.006897 Total 2.540 74 Significant result, F (16.81) > F critical (1.87), P-value (3.43 x 10 -35 ) < α (0.05) (Supplementary graphs are given in appendix VI, Fig VI.47 - 51).
76 4.4.3. Effect on transpiration rate
Impact of different wastewaters on transpiration rate (Table 4.8), all the treatments were
significantly different form one another and with control. The maximum increase in
Transpiration rate was observed DWW and was up to 45% and then it decreased up to
5%, interestingly all the treatments were above control. Similarly, HWW showed more
transpiration rate then IWW. For A. lebbeck the transpiration decreases very rapidly from
75% concentration (Fig 4.34). For D. sissoo only 25% of DWW show positive effect and all other treatments were below control (Fig 4.34). Maximum decrease observed was
69% at HWW. M. peguensis showed sharp decline in transpiration rate which reaches up to -68% (Fig 4.35)
Wastewater concentration 60
40
20
0 25% 50% 75% 100%
-20 D. sissoo Differencevs control (%) A. lebbeck -40 B. purpurea P. pinnata M. peguensis -60
Figure 4.34: Change in transpiration rate of selected five species in DWW
77 Wastewater concentration 60 D. sissoo A. lebbeck B. purpurea 40 P. pinnata M. peguensis 20
0 25% 50% 75% 100% -20
-40 Differencevs control (%)
-60
-80
Figure 4.35: Changes in transpiration rate of selected five species in HWW
Wastewater concentration 20
10
0 25% 50% 75% 100% -10
-20
-30
-40 D. sissoo
Differencevs control (%) A. lebbeck -50 B. purpurea -60 P. pinnata M. peguensis -70
Figure 4.36: Changes in transpiration rate of selected five species in IWW
78 Table 4.8: Impact of different wastewaters on transpiration rate of selected tree species Wastewater Species Wastewater concentration 0% 25% 50% 75% 100% Domestic P. pinnata 0.680 0.796 0.885 0.960 0.729 + 0.027 + 0.026 + 0.023 + 0.009 + 0.011 A. lebbeck 0.410 0.486 0.573 0.632 0.448 + 0.016 + 0.010 + 0.019 + 0.013 + 0.007 D. sissoo 0.520 0.587 0.397 0.375 0.327 + 0.012 + 0.023 + 0.017 + 0.021 + 0.014 B. purpurea 0.740 0.774 0.858 0.951 0.520 + 0.030 + 0.032 + 0.030 + 0.013 + 0.019 M. peguensis 0.880 0.917 1.008 0.583 0.370 + 0.035 + 0.022 + 0.038 + 0.029 + 0.015 Hospital P. pinnata 0.680 0.750 0.821 0.887 0.629 + 0.016 + 0.028 + 0.018 + 0.014 + 0.007 A. lebbeck 0.410 0.448 0.507 0.583 0.368 + 0.011 + 0.012 + 0.011 + 0.012 + 0.006 D. sissoo 0.520 0.336 0.249 0.220 0.150 + 0.012 + 0.017 + 0.011 + 0.012 + 0.006 B. purpurea 0.740 0.764 0.628 0.566 0.476 + 0.037 + 0.026 + 0.018 + 0.008 + 0.015 M. peguensis 0.880 0.896 0.929 0.529 0.333 + 0.018 + 0.034 + 0.040 + 0.010 + 0.005 Industrial P. pinnata 0.680 0.717 0.800 0.700 0.504 + 0.016 + 0.018 + 0.022 + 0.019 + 0.010 A. lebbeck 0.417 0.434 0.448 0.358 0.250 + 0.008 + 0.020 + 0.024 + 0.007 + 0.003 D. sissoo 0.520 0.400 0.350 0.330 0.300 + 0.026 + 0.024 + 0.018 + 0.010 + 0.021 B. purpurea 0.740 0.635 0.587 0.434 0.316 + 0.017 + 0.022 + 0.028 + 0.026 + 0.015 M. peguensis 0.885 0.887 0.825 0.629 0.292 + 0.018 + 0.040 + 0.049 + 0.014 + 0.008
Two way ANOVA Source of Variation SS Df MS F P-value Significance Species 1.964568 14 0.14033 10.2057 7.8 x 10 -11 *** Wastewater concentrations 0.718359 4 0.17959 13.0612 1.4 x 10 -07 *** Error 0.769992 56 0.01375 Total 3.452918 74 Significant result, F (10.20) > F critical (1.87), P-value (7.8 x 10 -11 ) < α (0.05)
Supplementary graphs are given in appendix VI, Fig VI.52 - 56.
79 4.5. Biochemical studies
4.5.1. Effect on lipid peroxidation content
For lipid peroxidation level, quantification of all the species behaves significantly
different from one another (Table 4.9). Maximum difference was found in P. pinnata , as compared to control. Millettia peguensis and B. purpurea showed almost the same trend of increasing lipid peroxidation level. The amount of MDA was maximum in IWW and least in DWW. The maximum amount of MDA found was 6.5 µmol/g in Bauhinia
purpurea when irrigated with DWW (Figure 4.37, 4.38 and 4.39).
30 P. pinnata A. lebbeck D. sissoo 25 B. purpurea M. peguensis
20
15
10 Differencevscontrol (%)
5
0 25% 50% 75% 100% Wastewater concentration
Figure 4.37: Changes in MDA content of selected five species in DWW
80 45
40
35
30
25
20
15 Differencevscontrol (%) 10 P. pinnata A. lebbeck 5 D. sissoo B. purpurea M. peguensis 0 25% 50% 75% 100% Wastewater concentration
Figure 4.38: Changes in MDA content of selected five species in HWW
70
60
50
40
30
20 Differencevscontrol (%) P. pinnata A. lebbeck 10 D. sissoo B. purpurea M. peguensis 0 25% 50% 75% 100% Wastewater concentration
Figure 4.39: Changes in MDA content of selected five species in IWW
81 Table 4.9. MDA content (µmol/g) in leaf of selected tree species in different wastewater concentrations
Wastewater Species Wastewater Concentration Type 0% 25% 50% 75% 100% Domestic P. pinnata 2.83 3.36 3.50 3.53 3.56 +0.057 +0.101 +0.070 +0.106 +0.142 A. lebbeck 2.88 3.20 3.36 3.42 3.50 +0.058 +0.064 +0.067 +0.137 +0.070 D. sissoo 4.12 4.42 4.6 4.75 4.8 +0.124 +0.146 +0.092 +0.143 +0.096 B. purpurea 6.00 6.24 6.40 6.47 6.50 +0.120 +0.125 +0.192 +0.259 +0.130 M. peguensis 4.96 5.15 5.32 5.38 5.38 +0.099 +0.103 +0.213 +0.161 +0.108 Hospital P. pinnata 2.83 3.67 3.89 3.98 4.09 +0.085 +0.154 +0.117 +0.080 +0.164 A. lebbeck 2.88 3.40 3.60 3.84 3.98 +0.058 +0.068 +0.144 +0.154 +0.080 D. sissoo 4.12 4.73 4.87 5.09 5.11 +0.082 +0.175 +0.146 +0.102 +0.204 B. purpurea 6.00 6.52 6.72 6.85 6.88 +0.180 +0.130 +0.336 +0.137 +0.206 M. peguensis 4.96 5.38 5.57 5.66 5.66 +0.099 +0.210 +0.167 +0.113 +0.226 Industrial P. pinnata 2.83 4.03 4.32 4.44 4.78 +0.057 +0.081 +0.186 +0.111 +0.163 A. lebbeck 2.88 3.70 3.94 4.13 4.30 +0.086 +0.074 +0.091 +0.136 +0.176 D. sissoo 4.12 4.97 5.18 5.42 5.45 +0.082 +0.099 +0.104 +0.206 +0.191 B. purpurea 6.00 6.88 7.10 7.26 7.33 +0.180 +0.206 +0.284 +0.145 +0.293 M. peguensis 4.96 5.68 5.91 6.05 6.10 +0.099 +0.114 +0.177 +0.242 +0.122
Two way ANOVA Source of Variation SS Df MS F P-value Significance Species 101.919 14 7.279931 272.008 4 x 10 -46 *** Wastewater concentrations 9.695715 4 2.423929 90.56788 8.9 x 10 -24 *** Error 1.498765 56 0.026764 Total 113.1135 74 Significant result, F (272.008) > F critical (1.87), P-value (4 x 10 -45 ) < α (0.05)
(Supplementary graphs are given in appendix VI, Fig VI.57 - VI.61).
82 4.5.2. Effect on proline content
Proline content is the indication of stress level in response to environment. Table 4.10 represents the data for proline content in 5 species at different WW concentrations. From the data it is reveled that the proline content increases with the increases in WW concentration (Figure 4.40, 4.41 and 4.42). Which means that the lower concentrations impart less toxicity and higher concentrations impart more toxicity to different plants.
All the WWs, treatments and species differ significantly from one another and with controls. The order of maximum to minimum proline content (µgg -1 FW) in presence of
DWW is as follows: B. purpurea (5.60) > M. peguensis (5.24) > D. sissoo (4.58) >
A. lebbeck (4.37) > P. pinnata (3.89)
The order of WW toxicity is as follows: IWW > HWW > DWW
350
300 P. pinnata 250 A. lebbeck D. sissoo B. purpurea 200 M. peguensis
150
100 Differencevscontrol (%)
50
0 25% 50% 75% 100% Wastewater concentration
Figure 4.40: Changes in proline content of selected five species in DWW
83 400
350 P. pinnata 300 A. lebbeck D. sissoo 250 B. purpurea M. peguensis 200
150
Differencevscontrol (%) 100
50
0 25% 50% 75% 100% Wastewater concentration
Figure 4.41: Changes in proline content of selected five species in HWW
500
450
400 P. pinnata A. lebbeck 350 D. sissoo 300 B. purpurea M. peguensis 250
200
150 Differencevscontrol (%) 100
50
0 25% 50% 75% 100% Wastewater concentration
Figure 4.42: Changes in proline content of selected five species in IWW
84 Table 4.10. Proline (µg/g FW) content in leaf of selected tree species in different wastewater concentrations
Wastewater Name of Species Wastewater Concentration Type 0% 25% 50% 75% 100% Domestic P. pinnata 1.04 1.20 1.60 3.00 3.89 +0.021 +0.024 +0.032 +0.060 +0.078 A. lebbeck 1.00 1.46 2.20 3.30 4.37 +0.020 +0.029 +0.044 +0.066 +0.087 D. sissoo 1.28 1.71 2.20 3.50 4.58 +0.026 +0.034 +0.044 +0.070 +0.092 B. purpurea 1.73 2.27 2.85 4.12 5.60 +0.035 +0.045 +0.057 +0.082 +0.112 M. peguensis 1.32 1.88 2.49 3.53 5.24 +0.026 +0.038 +0.050 +0.071 +0.105 Hospital P. pinnata 1.04 1.55 2.00 3.60 4.30 +0.021 +0.031 +0.040 +0.072 +0.086 A. lebbeck 1.00 1.80 2.88 4.00 5.00 +0.020 +0.036 +0.058 +0.080 +0.100 D. sissoo 1.28 1.92 2.60 4.08 4.92 +0.026 +0.038 +0.052 +0.082 +0.098 B. purpurea 1.73 2.60 3.44 4.60 5.91 +0.035 +0.052 +0.069 +0.092 +0.118 M. peguensis 1.32 2.26 3.00 3.96 5.66 +0.026 +0.045 +0.060 +0.079 +0.113 Industrial P. pinnata 1.04 2.06 3.00 4.13 4.78 +0.021 +0.041 +0.060 +0.083 +0.096 A. lebbeck 1.00 2.40 3.62 4.90 6.00 +0.020 +0.048 +0.072 +0.098 +0.120 D. sissoo 1.28 2.35 3.00 4.51 5.33 +0.026 +0.047 +0.060 +0.090 +0.107 B. purpurea 1.73 3.00 4.03 5.07 6.33 +0.035 +0.060 +0.081 +0.101 +0.127 M. peguensis 1.32 2.69 3.58 4.60 6.10 +0.026 +0.054 +0.072 +0.092 +0.122
Two way ANOVA Source of Variation SS Df MS F P-value Significance Species 18.98643 14 1.356174 17.67969 1.2 x 10 -15 *** Wastewater concentrations 146.8009 4 36.70023 478.4407 1.4 x 10 -42 *** Error 4.295648 56 0.076708 Total 170.083 74 Significant result, F (17.67) > F critical (1.87), P-value (1.2 x 10 -15 ) < α (0.05)
(Supplementary graphs are given in appendix VI, Fig VI.62 - VI.66).
85 4.6. Metal Bioaccumulation Studies
4.6.1. Effect on heavy metal uptake rate
The data for metal bio-accumulation is presented in Table 4.11. In presence of domestic
wastewater the maximum uptake was observed in Bauhinia purpurea (134.54 mgd -1), while the least uptake was observed in Millettia peguensis (4.76 mgd -1). In case on
hospital wastewater, the Mn uptake range from 0.69 to 8.2 mgd -1. Again Bauhinia purpurea showed the maximum uptake. The highest uptake rate was observed in industrial wastewater by Bauhinia purpurea which reached up to 163 mgd -1 for Pb. The
uptake rate of Cr is quite slow and ranged from 0.25 to 1.4 mgd -1.
Table 4.11. Heavy Metals uptake rate of selected tree species in different wastewater concentrations Wastewater Name of Heavy metal uptake rate (mg plant -1 d -1) Species Pb Mn Cu Cr Domestic D. sissoo 72.432 ------A. lebbeck 62.324 ------B. purpurea 134.542 ------P. pinnata 16.543 ------M. peguensis 4.762 ------Hospital D. sissoo --- 6.912 0.523 1.603 A. lebbeck --- 4.210 0.409 0.934 B. purpurea --- 8.219 1.089 2.225 P. pinnata --- 2.525 0.263 0.473 M. peguensis --- 0.695 0.092 0.152 Industrial D. sissoo 107.061 5.957 0.598 1.491 A. lebbeck 84.710 4.758 0.528 1.142 B. purpurea 163.801 5.314 0.621 1.166 P. pinnata 27.764 1.837 0.179 0.434 M. peguensis 12.066 1.036 0.116 0.252
86 4.6.2. Effect on Metal accumulation
The data for metal accumulation is presented in figure 4.43 – 4.50 for all species and all wastewaters. The results showed that in IWW the Cr accumulated more in leaf and less in roots. The order of accumulation is as follows:
Cr leaf > root > stem
Cu leaf > root > stem
Pb stem > root > leaf
Mn leaf > root > stem
Figure 4.43 revealed that the bio-accumulation of Cr in Dalbergia sissoo , Albizia lebbeck and Millettia peguensis is almost the same and do not differ significantly. Whereas,
Bauhinia purpurea and Pongamia pinnata shows the same pattern. According to the
Figure 4.45 all the five selected species behave significantly different from one another
for Mn uptake and accumulation. The maximum Mn accumulation is reported in
Millettia peguensis leaf (29 µgg -1) and the lowest accumulation is reported in Bauhinia purpurea root and stem. In presence of hospital wastewater the maximum Mn was reported in Dalbergia sissoo root (25 µgg -1). Accumulation of Mn in Pongamia pinnata root was least (10 µgg -1).
87 8 root 7 leaf stem 6
5
4
3
Cr Cr concentration (ug/g) 2
1
0 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.43: Chromium bioaccumulation in selected five species in IWW
3.500 root 3.000 leaf stem 2.500
2.000
1.500
Cu concentrationCu (ug/g) 1.000
0.500
0.000 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.44: Copper bioaccumulation in selected five species in IWW
88
35 root 30 leaf stem 25
20
15
10 Mn concentrationMn (ug/g)
5
0 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.45: Manganese bioaccumulation in selected five species in IWW
800 root 700 leaf stem 600
500
400
300
Pb Pb concentration (ug/g) 200
100
0 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.46: Lead bioaccumulation in five selected species in IWW
89
7.000 root 6.000 leaf stem 5.000
4.000
3.000
Crconcentration (ug/g) 2.000
1.000
0.000 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.47: Chromium bioaccumulation in selected five species in HWW
3.500 root 3.000 leaf stem 2.500
2.000
1.500
Cu concentration (ug/g) 1.000
0.500
0.000 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.48: Copper bioaccumulation in selected five species in HWW
90
30 root leaf 25 stem
20
15
10 Mn concentrationMn (ug/g)
5
0 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.49: Manganese bioaccumulation in selected five species in HWW
160 root leaf 140 stem
120
100
80
60
Pb Pb concentration (ug/g) 40
20
0 D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure 4.50: Lead bioaccumulation in selected five species in DWW
91 4.6.3. Effect on translocation factor
Translocation factor of all the species in all the wastewater is presented in table 4.12. The maximum to minimum order for Pb translocation in presence of DWW is as follows:
Dalbergia sissoo (2.1) > Millettia peguensis (1.2) > Albizia lebbeck (1.15) > Bauhinia purpurea (1.12) > Pongamia pinnata (0.9)
In presence of HWW Albizia lebbeck showes the maximum TF of 3.03 for Cr and 4.46
TF for Mn. Where as, in IWW the Bauhinia purpurea shows high TF for Cr, Cu and Mn.
Table 4.12. Heavy Metal Translocation factor of selected tree species in different wastewater concentrations Wastewater Species Translocation Factor Cr Cu Mn Pb Domestic D. sissoo ------2.132 A. lebbeck ------1.153 B. purpurea ------1.123 P. pinnata ------0.933 M. peguensis ------1.232 Hospital D. sissoo 2.524 2.125 1.520 -- A. lebbeck 3.032 1.667 2.469 -- B. purpurea 1.982 3.150 2.389 -- P. pinnata 2.520 2.846 3.182 -- M. peguensis 2.917 2.222 2.818 -- Industrial D. sissoo 2.400 2.500 2.526 3.376 A. lebbeck 2.400 1.667 2.333 1.730 B. purpurea 2.667 2.000 2.500 2.108 P. pinnata 1.800 2.000 1.636 2.190 M. peguensis 1.833 1.667 1.760 1.945
4.6.4. Effect on stem diameter
All the tree species stem diameter increased with the increase in WW concentration. The data is presented in Table 4.13 and Figure 4.51, 4.52 and 4.53.
92 Table 4.13. Changes in Stem diameter (cm) of selected tree species in different
wastewater concentrations
Type of wastewaters Name of species Wastewater concentrations 0% 25% 50% 75% 100% Domestic D. sissoo 1.20 1.33 1.50 1.56 1.42 +0.036 +0.040 +0.030 +0.031 +0.028 A. lebbeck 2.30 2.52 2.61 2.62 2.37 +0.041 +0.043 +0.055 +0.055 +0.033 B. purpurea 1.70 1.85 1.93 1.79 1.68 +0.051 +0.056 +0.039 +0.041 +0.035 P. pinnata 2.00 2.20 2.31 2.33 2.08 +0.080 +0.132 +0.069 +0.070 +0.063 M. peguensis 0.70 0.81 0.82 0.79 0.70 +0.011 +0.013 +0.016 +0.013 +0.015 Hospital D. sissoo 1.20 1.27 1.39 1.34 1.18 +0.028 +0.027 +0.035 +0.043 +0.065 A. lebbeck 2.30 2.39 2.46 2.48 2.25 +0.048 +0.033 +0.025 +0.040 +0.045 B. purpurea 1.70 1.76 1.81 1.66 1.59 +0.034 +0.035 +0.036 +0.043 +0.032 P. pinnata 2.00 2.11 2.18 2.10 1.96 +0.080 +0.063 +0.131 +0.105 +0.078 M. peguensis 0.70 0.77 0.77 0.67 0.62 +0.014 +0.023 +0.019 +0.014 +0.015 Industrial D. sissoo 1.20 1.23 1.27 1.18 1.12 +0.029 +0.049 +0.042 +0.032 +0.026 A. lebbeck 2.30 2.34 2.36 2.29 2.09 +0.053 +0.051 +0.050 +0.041 +0.033 B. purpurea 1.70 1.71 1.71 1.61 1.54 +0.048 +0.055 +0.036 +0.039 +0.049 P. pinnata 2.00 2.07 2.07 2.02 1.88 +0.080 +0.124 +0.083 +0.061 +0.075 M. peguensis 0.70 0.73 0.72 0.64 0.58 +0.017 +0.015 +0.012 +0.015 +0.012
93 35 D. sissoo A. lebbeck 30 B. purpurea P. pinnata 25 M. peguensis
20
15
10
DifferencevsControl (%) 5
0 25% 50% 75% 100% -5 Wastewater concentration
Figure 4.51: Changes in stem diameter of five selected species in DWW
20
15
10
5
0 25% 50% 75% 100%
DifferencevsControl (%) -5 D. sissoo A. lebbeck B. purpurea -10 P. pinnata M. peguensis
-15 Wastewater concentration
Figure 4.52: Changes in stem diameter of five selected species in HWW
94 7
2
25% 50% 75% 100% -3
-8
DifferencevsControl (%) D. sissoo A. lebbeck -13 B. purpurea P. pinnata M. peguensis
-18 Wastewater concentration
Figure 4.53: Changes in stem diameter of five selected species in IWW
95 5. Discussion
In developing countries the wastewater management is a serious problem and among
different treatment technologies the eco-friendly and nature based technologies are
gaining popularity. Phytoremediation is one of the leading eco-friendly technologies. As
compared to NEQS (National Environmental Quality Standards), all parameters of all the
three types of wastewaters (i.e. IWW, HWW and DWW) EC, pH, BOD and COD are
found significantly above NEQS (Table 4.1). Nitrogen, potassium and phosphorous are
little close to the permissible limit.
In present study three types of WW were used to find out the germination potential and
growth of the five selected species. Soaking time is important in seed germination
studies, generally seeds with long soaking time period are not feasible for germination
(Jaleel et al., 2007; Chen et al., 2015; Agnello et al., 2016). Soaking helps the seeds in
three ways, firstly it makes the seed coat soft so the emergence of plumule and radicle is
facilitated. Secondly, it provides the aqueous medium to metabolites for enzymatic
actions (Pena et al ., 2014) and thirdly soaking helps in hydrolysis of complex
carbohydrates for energy provision (Mosse et al., 2010). In the present study, soaking
time for all the five selected species varied significantly with three types of wastewater.
The minimum soaking time for seed germination was observed in D. sissoo . The order of
germination percentages in different WWs was as follows: DWW > HWW > IWW
The maximum percentage germination was observed in D. sissoo (74.2) and minimum
was observed in M. peguensis (41.6) in non-diluted DWW (Table 4.2). Similar trends of toxicity have been reported in other studies (Adam and Duncan, 2002; Stutte et al., 2006;
Mosse et al., 2010; Khaleel et al., 2013). In low WW concentration the toxicity of seed
germination was low and it increased gradually with the increase in WW concentration.
At high concentration the toxic effect was more than its nutritive effect (Prabhakar et al.,
96 2004; Hussain et al., 2010). Mean time to germination (MTG) is effective indicator to get an idea about seed potential to withstand WW irrigation. In this study the MTG difference in IWW was as follows: M. peguensis (115 hrs) > P. pinnata (106 hrs) > B. purpurea (97 hrs) > A. lebbeck (95 hrs) > D. sissoo (86 hrs)
Variation in MTG was probably due to seed coat permeability, thickness, seed size, amount/nature of toxins, uptake rate, etc. (Mekki et al ., 2007; Jaleel et al ., 2007). Studies have reported that phenolics and salts impart negative impact on MTG by delaying germination (Mosse et al., 2010; Rekik et al ., 2017). The seedling length showed a parabolic trend as it increased first in more diluted WWs and decreased with less diluted.
All the five species showed the same trend for MTG. Similar trends and results have been reported by other studies (Barbera et al ., 2013; Ma et al ., 2016). Seedling FW and
DW also showed same pattern at high concentrations. There is no clear evidence that which component of WW was responsible for toxicity but researchers have suggested the role of sodium, phosphorous, ethanol, benzene and polyphenols in toxicology (Stutte et al., 2006; Mosse et al., 2010).
Many studies have concluded that DWW can be the alternative of fertilizer as it contains high nutrients (Hussain et al., 2010; Manu et al., 2012; Han et al., 2014; Pena et al.,
2014). Organic matter (plant, animal and human origin) present in WW rapidly converts into non-toxic and stable compounds, in soil most commonly found are fulvic and humic acid. These metabolites support soil fertility and physio-chemical properties (Han et al.,
2014). Soils have the potential to reduce high BOD and COD load under controlled/limited irrigation of WW (Pena et al., 2014). For example, Mansell et al.
(2004) has reported the reduction of BOD upto zero after few centimeters of percolations. Similarly COD reduced up to 1 to 5 mgL -1 by Khaleel et al. (2013). In case of removal of inorganic ions, removal of K+ depends on the amount of WW applied and
97 the nitrogen content of WW (Jelusic et al ., 2013). Generally it is reported that the alternate periods of drying and flooding if applied, can reduce the nitrogen content up to
75%. These alternate periods promote the denitrification and nitrification process (Singh and Singh, 2006; Chang et al., 2015; Minhas et al., 2015). The case of phosphorous is somewhat complex, in WW it reacts with different metal ions and forms oxides, which are insoluble, but alternation of dry and flood periods reduces the formation of insoluble oxides (Miao et al., 2012; Barbera et al ., 2013). The present study shows similar results as the three types of WW applied did not exert any negative effects on plants.
Different studies have reported high tolerance index (T.I) and high vigor index (V.I) as a result of wastewater use. Plants with high T.I and V.I are considered more suitable parameters to select species for phytoremediation and phytoextrection. In this study the
D. sissoo showed the maximum V.I (1050 in IWW) (Fig 4.13) and M. peguensis reported least V.I (350 in IWW). As compared to control the V.I dropped vary sharply in HWW, whereas it increase was gradual in DWW (Fig 4.13, 4.15), the maximum T.I (120) was observed in B. purpurea (Fig 4.18). High value of T.I and V.I indicated that the high pollutant load in WW do not effect the translocation in plants (Jelusic et al., 2013) and do not create any osmotic imbalance in root cells (Ali et al., 2011; Pena et al., 2014). In growth studies the results were very significant. The height of all the five species increased with low wastewater concentrations and decreased with less diluted wastewater. For example, P. pinnata showed 98% increase in height at 75% of DWW.
Increase in height was also recorded in HWW (upto 75%). Industrial WW showed more growth retarding impact at 50% concentration. In growth studies the response of the five selected species was in the following order: P. pinnata > A. lebbeck > D. sissoo > B. purpurea > M. peguensis
98 Other studies have also reported increase in plant height with the use of WW (Brahim et
al., 2016; Tekaya et al., 2016; Christou et al., 2016). The similar trend of increase in FW and DW was observed in all the selected five plant species and were in accordance with other researchers (Vallejos et al ., 2014; Minhas et al., 2015). The negative effects on the selected species were observed by the decrease in photosynthetic rate, stomatal conductance and increase in transpiration rate. In HWW only B. purpurea showed 22% increase in stomatal conductance. Rest of the 4 species showed decrease in stomatal conductance. Pongamia pinnata showed 13% increase in stomatal conductance in IWW.
Auda et al. (2016) reported similar physiological trend in crops like, carrot, onion, potato and cucumber. Many researchers also reported that the physiological parameters decreased with the increase in metal concentration (Salemaa and Monni, 2003; Borghi et al ., 2007; Disante et al., 2010; Salam et al., 2016).
The mechanism of metal uptake and its translocation has been investigated by number of researchers (Subhashini et al., 2013; Terebova et al ., 2014). This information is very useful in optimizing the tree’s performance for metal removal form soil. Authors have reported two types of plants, “excluders” and “accumulators”. The accumulators store metals in their organs, where as, excluders survive in presence of metal presence but do not accumulate metals in their biomass (Stanislawska et al ., 2011). Plants have evolved highly efficient and specific mechanism to uptake micro and macro nutrients, even at very low concentration in soil/water. The uptake of any nutrient first needs its solubilization which is facilitated by chelating (produced by plants), redox reactions and pH changes (induced by plants). A vide range of specialized proteins are known, which are embedded in plasma membrane and are responsible for the uptake. These transporters include, proton pumps, co-transporters and channel proteins (Rascio et al., 2011). Each transport mechanism is specific but the problem arises when different ions interact with
99 each other. Mechanism of translocation from root to shoot or other aerial parts is not
very clear. One widely accepted mechanism is the evapo-transpiration, which exerts
pulling force to move nutrients from below ground parts to above ground parts. In
phytoremediation, root zone is of special interest. Our results highlight that the
translocation factor (TF) was high in IWW and low in DWW. The order of translocation
of Pb in IWW is as follow (Table 4.11): D. sissoo (3.37) > P. pinnata (2.19) > B.
purpurea (2.11) > M. peguensis (1.94) > A. lebbeck (1.73). Sun et al. (2011) reported the
TF of 1.09 for Tagetes patula.
In the present study the metal uptake was maximum by B. purpurea for Pb and least
uptake rate was of M. peguensis . The organ of metal storage behaved differently for all
the five selected species as D. sissoo , M. peguensis and A. lebbeck stored maximum
amount of metal in their leaves, whereas in P. pinnata root stored more metal than
leaves. These variations in heavy metal types, their concentrations and site of
accumulation have also been reported in number of studies (Zhivotovsky et al ., 2011; Ji
et al ., 2011; Garba et al., 2012; Yang et al., 2014). To safeguard the metabolism from
HM toxicity, plants have different defensive mechanism, one of them is proline content.
In the present study, the proline content was high in IWW and low in DWW. The proline
content increases with the increase in wastewater concentration. For example, in D.
sissoo the proline content increased from 1.28 (µgg -1 FW, in control) to 5.33 (µgg -1 FW, in 100% IWW). Least increase in proline was estimate in P. pinnata , which increased from 1.04 to 4.78 (µgg -1 FW, in 100% IWW). The increase in proline content in response
to increased metal concentration was also reported by Ma et al. (2016) and Chen et al.
(2015).
There are several factors that affect the efficiency of phytoremediation. Firstly, the selection of plant species is very important and researchers prefer those species which
100 have high biomass, easy to cultivate and are tolerant (Evangelou et al., 2012). Secondly, properties of growth media are also important, as presence of chelators and fertilizers change the pattern of HM uptake. Thirdly, root zone is of especial interest, like root diameter, root biomass and root morphological adaptations (Xu et al., 2010). Fourthly, bioavailability of HM is dependent on solubilility, retention, and interaction with other metals. Fifthly, addition of chelating agents; Andrades-Moreno et al . (2013)
recommended the use of EDTA and other chelators to detach HM from soil and other
interferences. However the trend to use organic and natural chelating agents is increasing
compared to the use of synthetic and inorganic one. Excessive use of chelating agents
causes HM leaching and their addition in ground water (Miretzky et al., 2010; Pandey et al., 2015). Sixthly, plant root exudates and lignads affect the biouptake of HMs through the formation of metal-ligand complexes and change the potential to leach metals below the root zone (Verma et al., 2014; Fuentes et al., 2016). In the present study, the five selected species showed successful uptake of HMs, translocated them and stored in different organs, with out the addition of any chelating agent or any organic amendment.
Many authors were of the view that chelatins are necessary for HM uptake (Doumett et al ., 2008; January et al ., 2008; Garba et al., 2012; Nevel et al., 2013; Tariq and Ashraf
2013). Another positive aspect of this study is that all the selected trees are indigenous specie and are very adaptive to local climatic conditions/factors.
101 6. Conclusion
This study concludes that the maximum percentage germination was observed in D.
sissoo (74.2) and minimum was observed in M. peguensis (41.6) in non-diluted DWW.
In this study the MTG difference in IWW was as follows:
M. peguensis (115 hrs) > P. pinnata (106 hrs) > B. purpurea (97 hrs) > A. lebbeck (95
hrs) > D. sissoo (86 hrs).
The three types of WW applied did not exert any negative effects on plants. D. sissoo
showed the maximum VI (1050 in IWW) and M. peguensis reported least V.I (350 in
IWW). The maximum TI (120) was exhibited by B. purpurea . P. pinnata showed 98%
increase in height at 75% of DWW. Increase in height was also recorded in HWW (upto
75%). In growth studies the response of the five selected species was in the following
order:
P. pinnata > A. lebbeck > D. sissoo > B. purpurea > M. peguensis
In HWW only B. purpurea showed 22% increase in stomatal conductance. P. pinnata
showed 13% increase in stomatal conductance in IWW. Our results highlight that the
translocation factor (TF) was high in IWW and low in DWW. The order of translocation
of Pb in IWW is as follow; D. sissoo (3.37) > P. pinnata (2.19) > B. purpurea (2.11) >
M. peguensis (1.94) > A. lebbeck (1.73). In the present study the metal uptake was
maximum by B. purpurea for Pb and least uptake rate was of M. peguensis . The organ of
metal storage behaved differently for all the five selected species as D. sissoo , M.
peguensis and A. lebbeck stored maximum amount of metal in their leaves, whereas in P.
pinnata root stored more metal than leaves. These variations in heavy metal types, their
concentrations and site of accumulation have also been reported in number of studies. D.
sissoo the proline content increased from 1.28 (µgg -1 FW, in control) to 5.33 (µgg -1 FW, in 100% IWW). Least increase in proline was estimate in P. pinnata , which increased
102 from 1.04 to 4.78 (µgg -1 FW, in 100% IWW). In the present study, the five selected species showed successful uptake of HMs, translocated them and stored in different organs, with out the addition of any chelating agent or any organic amendment.
This study concludes that:
• The five selected trees species can tolerate WW irrigation
• It may provide cost effective phytoremediation of WW
• It may be eco-friendly solution for WW management
• It provides the option to restrict the movement of heavy metals and prevent them to
percolate downward and entering into water table
• It can help to save the fresh water for future use
103 7. Recommendation
The results of this study support the idea that the said investigated five species can be the potential candidates for phytoremediation and can used effectively for the management of domestic, industrial and hospital WW in urban forestry. These species are good candidate for urban forestry. Wastewaters can be used as resource for the irrigation of tree species.
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118 Appendix I
Plate 1: Collection of DWW
Plate 2: Collection site of DWW at River Ravi
Appendix I
Plate 3: Collection of HWW
Plate 4: Collection of HWW
Appendix I
Plate 5: Collection of IWW
Plate 6: Collection of IWW
Appendix I
Plate 7: Response of Albizia lebbeck in HWW
Plate 8: Response of Albizia lebbeck in IWW
Appendix I
Plate 9: Response of Albizia lebbeck in DWW
Plate 10: Response of Millettia peguensis in IWW
Appendix I
Plate 11: Response of Millettia peguensis in DWW
Plate 12: Response of Millettia peguensis in HWW
Appendix I
Plate 13: Response of Bauhinia purpurea in HWW
Plate 14: Response of Bauhinia purpurea in IWW
Appendix I
Plate 15: Response of Bauhinia purpurea in DWW
Plate 16: Response of Dalbergia sissoo in HWW
Appendix I
Plate 17: Response of Dalbergia sissoo in IWW
Plate 18: Response of Dalbergia sissoo in DWW
Appendix I
Plate 19: Response of Pongamia pinnata in IWW
Plate 20: Response of Pongamia pinnata in HWW
Appendix I
Plate 21: Response of Pongamia pinnata in DWW
Pak. J. Bot., 47(SI): 275-280, 2015. Appendix II
EXPLORING GERMINATING POTENTIAL OF TREE SPECIES IN DOMESTIC WASTEWATER FOR USE IN URBAN FORESTRY
AMINA KANWAL1*, SAFDAR ALI MIRZA1 AND MUHAMMAD FARHAN2,3
1Department of Botany, Government College University, Lahore, Pakistan 2Biological Sciences Department, Forman Christian College (A Chartered University), Lahore, Pakistan 3Sustainable Development Study Center, Government College University, Lahore, Pakistan *Corresponding author’s e-mail: [email protected]
Abstract
Domestic wastewater is an important source of water and nutrients for irrigation in developing countries, particularly to arid, semi-arid and water scarce areas. The use of wastewater is widespread and represents around 10 percent of the total irrigation. It imparts both positive and negative effects on ecosystem. As wastewater reuse is currently necessary (due to water shortage), it is important to use it wisely. The best feasible management practice is to use wastewater for forest irrigation to maximize benefits and minimize damage. Species which have higher tolerance index can be used in urban forestry. In the present study, germination studies of 5 tree species were investigated, irrigated with domestic wastewater (in different concentrations). Statistical analysis revealed that germination %, seedling length/weight increase with increase in DWW concentration. But concentration beyond 50% starts imparting negative effects. Study shows that only Millettia peguensis Ali, Pongamia pinnata (L.) Pierre, Albizia lebbeck (L.) Benth, Bauhinia purpurea L. and Dalbergia sissoo L. can withstand toxicity of domestic wastewater and thus can be the potential candidate for urban forestry. These species show significantly high vigor index, germination index and tolerance index. Result supports the use of 50% diluted DWW for forest irrigation. This study highlights the possible solution (DWW use for urban forest irrigation) to multiple problems like, wastewater management/treatment, biodiversity loss, lack of urban green spaces and low forest cover.
Key Words: Domestic wastewater, germination, urban forestry, Fabaceae,
Introduction and flowers) are sold in markets (Ensink et al., 2004b). Use of wastewater for irrigation has both advantages In developed countries, reuse of wastewater (WW) and disadvantages. Advantages include higher yields, is part of tactic to protect natural water bodies and to round the year availability, round the year production, limit management expenses. On the other hand, in availability in arid and semi-arid areas, recycles developing countries water scarcity and fertilizing organic matter/nutrients, reduces fertilizers amount / properties are the main factor for its reuse (Jiménez & cost, low-cost wastewater disposal, avoids polluting Garduño 2001; Anon., 2003a). Irrigation with domestic surface water bodies, increases the economic wastewater is in use of urban and peri-urban areas of efficiency, conserves freshwater sources and recharges arid or semiarid countries. It depends on wastewater aquifers through infiltration (Khaleel et al., 2013). availability, demand of fresh food, poverty and lack of Whereas, disadvantages/limitations include need of alternatives. Mostly, small farmers use wastewater to careful planning, storage capacity, pathogens related fulfill their domestic need of vegetables and fodder. problems, presence of toxic materials which may Very small quantities of generated products (vegetables contaminate ground water (Pena et al., 2014).
Fig. 1. Area under wastewater irrigation 276 AMINA KANWAL ET AppendixAL., II
There is no complete global inventory on the extent to d = incubation time which wastewater is used to irrigate trees (Fig. 1), however N = total number of germinated seeds global figure commonly cited is at least 20 million hectares in 50 countries (Anon., 2003b). Estimates suggest that nearly Statistical analysis: Data was analyzed for ANOVA and 1/10 of world’s population use WW irrigated crops (Smit & Duncan’s Multiple Range test by Co-stat. Nasr, 1992). For instance, in Hanoi (Vietnam) nearly 80% vegetables are grown using wastewater (Ensink et al., Results and Discussion 2004a). Keeping in view the benefits and limitations of Number of problems is prevailing due to population wastewater irrigation, researchers have started to use it for explosion and lack of urban/industrial planning. These growing forests (not edible crops). If these forests are in problems include water pollution, water scarcity, lack of urban spaces then multiple benefits can be gained urban green spaces and low forest cover. The single (Mongkhonsin et al., 2011). Wastewater can be used to irrigate urban forests in many forms, either treated solution of these multiple problem is urban forests with (reclaimed water), non-treated (raw wastewater), directly or wastewater irrigation. indirectly after dilution with water from rivers or reservoirs (Han et al., 2014). In India number of experimental sites Waste water analysis: Compared to National was developed to investigate WW irrigation to trees. One Environmental Quality Standards (NEQS), domestic example is the CSSRI (Central Soil Salinity Research wastewater (DWW) pH, EC, COD, BOD were found Institute in Karnal, Haryana State) which evaluated the significantly above average (Table 1). N, K and P were practicability of using untreated sewage to irrigate forest. close to the acceptable limit, where as TDS and TSS were Eucalyptus tereticornis, Populus deltoides and Leucaena significantly lower then the acceptable values. Due to high leucocephala exhibit faster growth with no negative signs nutrient availability domestic wastewater can be the over the course of five years (Das & Kaul, 1992). alternative for fertilizer. Most organic compounds of human, The present study deals with the investigation of animal, or plant origin present in sewage are rapidly germination potential of 5 tree species, under domestic transformed in soils to stable, non-toxic organic compounds wastewater and their potential use in urban forestry. (humic and fulvic acids). Actually, soils can biodegrade a wider variety and a greater amount of organic compounds Materials and Methods than water bodies (Han et al., 2014). Water application under controlled conditions (limited irrigation rate and Plant and seed selection: Five tree species of family intermittent flooding) permits the biodegradation of hundreds of kilograms of biological oxygen demand per Fabaceae were used as test species; Millettia peguensis hectare per day (kg BOD/ha/d) with no impact on the Ali, Pongamia pinnata (L.) Pierre, Albizia lebbeck (L.) Benth, Bauhinia purpurea L., Dalbergia sissoo L. Seeds environment (Bouwer 1987). BOD levels are virtually were provided by Punjab Forest Department, Cooper reduced after a few meters of percolation through the soil, where total organic carbon (TOC) values of 1-5 mg/L can Road, Lahore. Seeds were physically screened and damaged/unhealthy were excluded. still be measured (Mansell et al., 2004; Khaleel et al., 2013). The amount of nitrogen remaining in wastewater after
irrigation depends on the nitrogen content and the amount Waste water collection and analysis: Domestic waste of water applied to crops (Ali et al., 2011; Jelusic et al., water was collected from sewage drain near River Ravi, 2013). Nitrogen removal is enhanced if flooding and drying Lahore. The collections and physicochemical analysis of periods are alternated, which promotes a waste waters were done according to the standard nitrification/denitrification process on soil that can remove protocols. Five dilutions of wastewater were prepared; about 75 percent of the nitrogen in sewage (Bouwer 1987). named T0 (distilled water), T1 (75% diluted), T2 (50% In sewage wastewater phosphate may react with calcium, diluted), T3 (25% diluted), T4 (0% diluted). iron and aluminum oxide, all the resultant forms are
insoluble. Immobilized phosphate gradually converts to Germination experiment: Whatmann filter paper was mobile phosphate (Barbera et al., 2013). put in petri dishes and seeds were placed over filter paper for 15 days. Petri dishes were arranged in complete Soaking time: Socking time is the critical factor for seed randomized block design over laboratory table in germination. It basically provides water to soften seed coat triplicate. At the start of experiment 3ml and subsequently for easy rupture and release of plumule and radicle. 2ml of respective WW dilution was added in respective Secondly, complex carbohydrates are broken down into petridish. Seeds were considered germinated with the monosaccharide and are able to provide energy (Mosse et emergence of radicles. Parameters recorded were: % al., 2010). Thirdly, during germination water provides germination, plumule length (cm), root length (cm), shoot aqueous media without which metabolic reactions will not length (cm), seedling fresh weight (g), seedling dry proceed (Pena et al., 2014). Socking time varies with specie weight (g), seedling vigor index and tolerance indices. to specie. In the present study, B. Purpurea differed significantly from rest of the species in socking time. It Seedling vigor index = Germination (%) X seedling length needed 5 hour of socking time, whereas, P. Pinnata and A. Wastewater treatment Tolerance Indices = x 100 Lebbeck showed non-significant difference (4hrs). Control Similarly, D. Sissoo and M. Peguensis were non-significant ∑ n x d Mean time to germination (MTG) = among each other but significantly differ from other 3 N species. From practical prospective, species with low where: n = number of germinated seeds socking time duration are more preferred (Fig. 2). EXPLORING GERMINATING POTENTIAL OF TREE SPECIES IN DOMESTIC WASTEWATER Appendix277 II
Table 1. Physio-chemical characteristics of domestic 88.8 and 96 (hrs) for D. sissoo, A. lebbeck, B. purpurea, wastewater. P. pinnata and M. peguensis, respectively. Difference in Parameters Values MTG depends on seed size, seed coat thickness / pH 6.9 permeability, degree of difference in toxin/nutrient uptake EC (µs) 88 (Mekki et al., 2007). Studies have reported strong negative influence of salts and phenolics in delaying TDS (mgL-1) 0.0024 MTG (Mosse et al., 2010). TSS (mgL-1) 0.0018 -1 COD (mgL ) 372 Seedling length: Seeding length is affected by wastewater -1 BOD(mgL ) 234 but is depend on the nature and concentration of N (%) 1.76 wastewater. Data for root and shoot length is presented K (ppm) 679 (Fig. 5). D. sissoo represent most lengthy shoot and root at P (ppm) 422 75% of wastewater. Other species also exhibit better length Cl-1 (mgL-1) 340 at 75% of WW, which may be due to the more availability Mg+2(mgL-1) 71 of nutrients (Barbera et al., 2013). Statistical analysis Ca+2 (mgL-1) 156 revealed that seedling length is in the following order:
Moisture requirement: Figure 3 depicts the relationship D. sissoo > A. labbeck > B. purpurea > P. pinnata > M. between germination % and water quantity requirement. peguensis All species shows hyperbolic curve, which means that seeds need optimum water quantity. Increase or decrease Seeding fresh weight: Seedling fresh weight was from optimum value will decrease the germination measure in order to know the best treatment for irrigation. percentage. All 5 species respond differently at different Here again the trend was somewhat similar as was in water concentration. Optimum water requirement for B. germination percentage. With the increase in WW Purpurea, A. Lebbeck,, D. Sissoo and M. Peguensis is 12- concentration the fresh weight increases up to 75% but 15ml, whereas P. Pinnata showed optimum germination at further increase in concentration decrease the fresh weight 18-20ml. Statistical analysis showed significant difference due to the toxicity (Table 3). B. purpurea did not differ among 5 species. At low moisture, germination is effected significantly at 50-75% of DWW. M. peguensis show due to the lack of water and mostly metabolic processes are least difference from 25-75%. It is not conform which dependent on water (Ali et al., 2011). Whereas, at high component of DWW exhibit phyto-toxicity at higher water availability germination is reduced due to the poor concentration, however some evidences suggest the aeration, reduced oxygen, leaching of essential material involvement of phosphorous, sodium, ethanol and (enzymes, soluble food reserves, etc) from seed by polyphenols (Stutte et al., 2006). The variation in species exosmosis (Khaleel et al., 2013). may be due to the tolerance and differential nutrient requirements (Mosse et al., 2010). Percentage germination: Domestic waste water is rich in nutrient and also toxic materials like pharmaceutics, Tolerance index: Tolerance index is one of the important detergents and surfactants etc. Theoretically, it is expected parameter to get an idea of specie response. From the result that due to more nutrients wastewater irrigation will enhance it is clear that the A. labbeck is the most tolerant out of 5 germination. The same trend is shown in the Table 2. At low species (Fig. 6). Statistical analysis also revealed that the domestic wastewater concentration, germination is increased tolerance index decrease with the increase in wastewater as compared to the control and as the concentration of waste concentration. The maximum tolerance was shown by A. water is increased the germination percentage in decreased labbeck at 50% of DWW (133) and the least tolerance was (Prabhakar et al., 2004). However the 5 species differ reported by M. peguensis (117). All the rest differ significantly in their germination response. Better response significantly from one another. At high concentration of was shown by D. Sissoo and the least response was of B. wastewater the salts accumulation increases which interfere Purpurea. Statistically, M. Pegaensis and P. Pinnata do not with translocation and photosynthesis (Jelusic et al., 2013). differ significantly at 25% domestic wastewater. Similarly, Salts accumulation also disturbs the osmotic balance D. Sissoo and A. lebbeck respond same at highest between soil and roots which creates problems in water concentration. This difference in germination response is due absorption. Those species which are more tolerant are to the variable needs of difference species, some need more useful in agro-forestry (Pena et al., 2014). nutrients and other need less nutrients (Hussain et al., 2010).
At high concentration, the toxicity of wastewater was more Vigor index: When different dilutions of wastewater apparent than its effectiveness. This parameter is useful in were compared for vigor index (VI) it gives very optimizing the wastewater quantity in urban forestry (Manu promising results. As a rule of thumb, the VI increase et al., 2012). with the increase in WW concentration but after certain
point it start decreasing (Fig. 7). Probably due to the fact Mean time to germination: Domestic wastewater that in dilute solution the toxic materials are less and as significantly reduces the mean time to germination (Adam the concentration increases the amount of toxic material & Duncan, 2002). All the 5 species differ significantly in also increases (Ali et al., 2011). Statistical analysis mean time to germination (MTG). The minimum time showed that the concentrations and species differ from was exhibited by D. sissoo and maximum was reported by one another. The maximum VI was shown by D. sissoo in M. peguensis (Fig. 4). The MTG values are 72, 79.2, 81.6, 25-75% wastewater 278 AMINA KANWAL ET AppendixAL., II
Fig. 2. Socking time requirement of different plants. Fig. 5. Influence of domestic wastewater on root and shoot length
Fig. 3. Moisture requirement of different species Fig. 6. Tolerance response in domestic wastewater
Fig. 4. Impact of domestic wastewater on germination time Fig. 7. Effect of domestic wastewater on vigor index EXPLORING GERMINATING POTENTIAL OF TREE SPECIES IN DOMESTIC WASTEWATER Appendix279 II
Table 2. Relationship between germination % and domestic water concentration. Concentration of domestic wastewater
25% 50% 75% 100% D. sissoo 97.6±1.95 a 95.2±2.86 a 88.8 ±2.58 a 70.2±2.37 a A. labbeck 94.9±2.85 b 90.8±2.54 b 81.3±1.63 b 69.1±2.15 a B. purpurea 92.2±3.04 c 82.3±2.63 c 68.4±2.05 c 55.5±1.17 b P. pinnata 84.8±3.51 d 74.2±1.34 d 55.5±1.83 d 47.7±1.05 c M. peguensis 83.4±2.34 d 69.8±2.16 e 52.8±1.48 e 41.6±1.50 d Treatment means followed by different letters in each column are significantly different at p=0.05 according to Duncan’s Multiple Range Test
Table 3. Impact of DWW on seedling fresh weight (gm). Concentration of domestic wastewater
0% 25% 25% 25% 25% D. sissoo 0.496±0.0099 a 0.55±0.0110 a 0.592±0.0184 a 0.62±0.0167 a 0.58±0.0110 a A. labbeer 0.414±.0091 b 0.43±0.0129 b 0.49±0.0127 b 0.52±0.0156 b 0.488±0.0102 b B. purpurea 0.241±0.0072 c 0.352±0.0123 c 0.401±0.0120 c 0.4±0.0100 c 0.35±0.0095 c P. pinnata 0.203±0.0043 d 0.269±0.0062 d 0.323±0.0081 d 0.32±0.0058 d 0.296±0.0080 d M. peguensis 0.173±0.0035 e 0.215±0.0039 e 0.214±0.0043 e 0.208±0.0052 e 0.2±0.0056 e Treatment means followed by different letters in each column are significantly different at p=0.05 according to Duncan’s Multiple Range Test.
Conclusion Das, D.C. and R. N. Kaul. 1992. Sewage water: utilization through forestry. Karnal, India, Central Soil Salinity This study is successful in solving local problem of Research Institute. Greening wastelands through waste wastewater pollution with indigenous and eco-system water. New Delhi, National Wastelands Development Board. based or natural solution. Instead of artificial and man- Ensink, J., J. Simmons and W. Van der Hoek. 2004a. made water purification system we must opt nature based Wastewater use in Pakistan: The cases of Haroonabad and systems as they are more reliable, eco-friendly and Faisalabad. In Wastewater use in irrigated agriculture, C. sustainable. It also give multiple benefits like increase in Scott, N. Faruqui, and L. Raschid-Sally, Wallingford: CAB forest cover, increase in urban green spaces, reduction in International. pp. 91-102. air pollution, serves are heat sink. Ensink, J., T. Mahmood, W. Van der Hoek, L. Raschid-Sally and F. Amerasinghe. 2004b. A nationwide assessment of References wastewater use in Pakistan: An obscure activity or a vitally important one? Water Policy. 6: 197-206. Adam, G. and H. Duncan. 2002. Influence of diesel fuel on seed Han, P., P. Kumar and O. Bee-Lian. 2014. Remediation of germination. Environ. Pollut., 120: 363-370. nutrient-rich waters using the terrestrial plant, Pandanus Ali, H.M., E.M. EL-Mahrouk, F.A. Hassan and M.A. EL- amaryllifolius Roxb. J. Environ. Sci., 26(2): 404-414. Hussain, F., S.A. Malik, M. Athar, N. Bashir, U. Younis, M.U. Tarawy. 2011. Usage of sewage effluent in irrigation of Hassan and S. Mahmood. 2010. Effect of tannery effluents some woody tree seedlings. Part 3: Swietenia mahagoni on seed germination and growth of two sunflower cultivars. (L.) Jacq. Saudi J. Biol. Sci., 18: 201-207. Afr. J. Biotech., 9(32): 5113-5120. Anonymous. 2003a. IWMI (International Water Management Jelusic, M., H. Grcman, D. Vodnik, M. Suhadolc and D. Lestan. Institute). Confronting the realities of wastewater use in 2013. Functioning of metal contaminated garden soil after agriculture. Water policy briefing 9. Colombo: IWMI remediation. Environmental Pollution, 174: 63-70. Anonymous. 2003b. Water for people, water for life. The United Jiménez, B. and H. Garduño. 2001. Social, political and Nations world water development report. Barcelona: scientific dilemmas for massive wastewater reuse in the UNESCO world. In Navigating rough waters: Ethical issues in the Barbera, A.C., C. Maucieri, A. Ioppolo, M. Milani and V. water industry. C. Davis and R. McGin. London: American Cavallaro. 2013. Effects of olive mill wastewater physico- Water Works Association (AWWA) Khaleel, R.I., N. Ismail and M.H. Ibrahim. 2013. The impact of chemical treatments on polyphenol abatement and Italian waste water treatments on seed germination and ryegrass (Lolium multiflorum L) germinability. Water biochemical parameter of Abelmoschus esculentus L. research, 52(1): 275-281. Procedia - Social and Behavioral Sciences, 91: 453-460. Bouwer, H. 1987. Soil-aquifer treatment of sewage. Rome: Land Mansell, J., J. Drewes and T. Rauch. 2004. Removal mechanisms of and Water Development Division, Food and Agriculture endocrine disrupting compounds (steroids) during soil aquifer Organization of the United Nations (FAO). treatment. Water Sci. & Technol., 50(2): 229-237. 280 AMINA KANWAL ET AppendixAL., II
Manu, K.J., M. Kumar and V.S. Mohana. 2012. Effect of dairy Pena, A., M.D. Mingorance, I. Guzmán, L. Sánchez, A.J.F. effluent (treated and untreated) on seed germination, Espinosa, B. Valdés and S.R. Oliva. 2014. Protecting effect seedling growth and biochemical parameters of maize (Zea of recycled urban wastes (sewage sludge and wastewater) mays L.). Int. J. Res. Chem. Environ., 2(1): 62-69. on ryegrass against the toxicity of pesticides at high . J. Mekki, A., A. Dhouib and S. Sayadi. 2007. Polyphenols Environ. Manag., 142: 23-29. dynamics and phytotoxicity in a soil amended by olive mill Prabhakar P.S., M. Mall and J. Singh. 2004. Impact of fertilizer wastewaters. J. Environ. Manage, 84: 134-140. factory effluent on Seed Germination, Seedling growth and Mongkhonsin, B., W. Nakbanpote, I. Nakai, A. Hokura and N. Chlorophyll content of Gram (Cicer aeritenum). J. Environ. Jearanaikoon. 2011. Distribution and speciation of Biol., 27(1): 153-156. chromium accumulated in Gynura pseudochina (L.) DC. Smit, J. and J. Nasr. 1992. Urban agriculture for sustainable Environ. Exp. Bot., 74: 56-64. cities: Using wastes and idle land and water bodies as Mosse, K.P.M., A.F. Patti, E.W. Christen and T.R. Cavagnaro. resources. Environment and Urbanization, 4(2): 141-152. 2010. Winery wastewater inhibits seed germination and Stutte G.W., I. Eraso, S. Anderson and R.D. Hickey. 2006. vegetative growth of common crop species. J. Hazard. Bioactivity of volatile alcohols on the germination and Mat., 180: 63-70. growth of radish seedlings. Hort. Sci., 41: 108-112.
(Received for publication 26 August 2014)
Int. J. Biosci. 2017Appendix III
International Journal of Biosciences | IJB | ISSN: 2220-6655 (Print), 2222-5234 (Online) http://www.innspub.net Vol. 10, No. 1, p. 81-90, 2017
RESEARCH PAPER OPEN ACCESS
Germination response of five tree species on hospital wastewater
Amina Kanwal*, Safdar Ali
Department of Botany, Government College University, Lahore, Pakistan
Key words:Germination, Hospital Wastewater, Tolerance Index. http://dx.doi.org/10.12692/ijb/10.1.81-90 Article published on January15, 2017
Abstract
World is facing water scarcity and wastewater may be important source of water and nutrients for irrigation. Estimates reveal that about 10% of agri-land is irrigated usingwastewater with both positive and negative effects on ecosystem. Since wastewater reuse is currently necessary (due to water shortage). The best feasible management practice is to use wastewater for forest irrigation in and around cities. Species with higher tolerance index can be used in urban forestry. In the present study, germination studies of five tree species were investigated, using hospital wastewater (HWW). Germination experiment was conducted in Petri dishes in completely randomized design, each containing four seeds on filter paper moistened with different concentrations of HWW. Petri dishes in triplicate were placed under 16 hrs photoperiod. Statistical analysis revealed that germination %, seedling length andweight increased with increase in HWW concentration but concentration beyond 50% imparted negative effects. Study showed that only Millettia peguensis Ali, Pongamia pinnata L. Pierre, Albizia lebbeck L. Benth, Bauhinia purpurea L. and Dalbergia sissoo L. can withstand toxicity of HWW and thus can be the potential candidate for urban forestry. These species showed significantly high vigor index and tolerance index. Results support the use of HWW with 50% dilution for forest irrigation. This study suggests the possible use of HWW for forest irrigation and highlights the multiple benefits of HWW use in irrigation such as to improve forest cover and to reduce; pollutant migration in environment and water scarcity. * Corresponding Author: Amina Kanwal [email protected]
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Introduction Wastewater may be applied to forest in many ways Water scarcity is the growing problem at world level. like, without treatment (raw wastewater), with In developing countries the use of wastewater is dilution and with treatment (reclaimed water) (Han increasing due to two main factors. Firstly due to et al., 2014). One of the pioneer experiments for the unavailability of fresh water, secondly, wastewater use of wastewater in forest irrigation was conducted has fertilizing properties (Miscellaneous, 2003). at CSSRI (Central Soil Salinity Research Institute), Developing countries do not have segregated system Karnal Haryana India. This experiment estimated the for hospital and sewage wastewater as a result of practicability of using raw wastewater (untreated) to which the hospital wastewater getsmixed with sewage irrigate trees like, Leucaena leucocephala, Populus wastewater. Small farmers in peri-urban areas are deltoids and Eucalyptus tereticornis. The experiment fulfilling their irrigation water requirements with lasted for 5 year and the selected tree species did not wastewater to grow fresh vegetables and fodder showed any negative growth sign (Das and Kaul, (Ensink et al. 2004b). Irrigation with wastewater has 1992). The present study is designed to investigate both advantages and disadvantages. Some of the germination potential of five tree species under common advantages are; high yield, whole year hospital wastewater irrigation for their potential use availability, whole year production, availability in arid in urban forestry. and semi arid zones, reduction in fertilizer amount, cost effective, low cost water disposal, fresh water Materials and methods conservation, ground water recharge (Khaleel et al., Plant and seed selection 2013), whereas, limitations or disadvantages of Based on the literature survey and in collaboration wastewater include; presence of pathogens, presence with Punjab Forest Department, following tree of toxic components, contamination of ground water, species of Fabaceae were selected for research; require sustainable planning (Pena et al., 2014). Dalbergia sissoo L., Pongamia pinnata (L.) Pierre, Millettia peguensis Ali, Bauhinia purpurea L., According to United Nations estimates, about 20 Albizia lebbeck (L.) Benth,. Seeds of all species were million hectares of land in 50 countries is under collected from Punjab Forest Department, Lahore. wastewater irrigation (United Nations, 2003); Physical screening was conducted and unhealthy and however no concrete information is available (Figure damaged seeds were discarded. 1). Another estimate advocates that about one tenth of world’s population is using products (mostly Waste water collection and analysis vegetables) growing on wastewater (Smit and Nasr, Hospital wastewater was collected as per standard 1992). As in Hanoi (Vietnam) about 80% vegetables protocols from outlets of Combined Military Hospital, are irrigated with wastewater (Ensink et al., 2004a). Services Hospital and Mayo Hospital, Lahore. Physiochemical analysis was conducted in Botany Due to growing concern over the extensive use of Department Government College University, Lahore. wastewater for irrigation. Number of studies has Different dilutions were prepared, as follow; recommended the use of wastewater for tree T0 = 100% tap water irrigation, as trees are non-edible. Another benefit is T1 = 25% Hospital Wastewater that the metals and toxic pollutants will remain T2 = 50% Hospital Wastewater bonded in tree wood and will not spread in food T3 = 75% Hospital Wastewater chain/food web. Researchers are planning to plant T4 = 100% Hospital Wastewater forests within cities (as urban forests) using wastewater irrigation. It will offer multiple benefits Germination experiment like; wastewater use, immobilization of toxic metals, Seed germination experiment was conducted in provide urban green belts, carbon sinks and heat Petridishes. In Petri dishes, filter paper was placed as sinks (Mongkhonsin et al., 2011). base and 4 seeds were arranged in each petridish.
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Petri dishes were placed in triplicates over lab table in Statistical analysis complete randomized block design. Initially seed Germination data was statistically analyzed using Co- were irrigated with 3 ml HWW (respective dilution) stat. Tests applied was ANOVA and Duncan’s and later 2ml HWW was used daily, under aseptic Multiple Range. conditions. Emergence of radical was considered as the sign of germination. Germination parameters Results and discussion noted were; mean time for germination, germination Wastewater analysis %, roots and shoots length, seedling length, fresh Hospital wastewater analysis revealed that all the weight, tolerance index and vigor index. Different parameters like COD, BOD, EC, pH, TS, TSS, TDS, equations used are as follow; etc. (Table 1) were above the National Environmental
Quality Standards (NEQS). Nutrients like potassium, sodium and nitrogen were close to acceptable limit. The TDS and TSS were quite low compared to NEQS, probably due to dilution factor or due to settlement of suspended particles. Hospital wastewater is the
Where: n = number of germinated seeds combination of lot of drugs, metabolites, chemicals d = incubation time and sewage waste. N = total number of germinated seeds
Table 1. Physio-chemical characteristics of hospital wastewater. Parameters Values pH 7.9 EC (µs) 94 TDS (mgL-1) 0.0043 TSS (mgL-1) 0.0021 COD (mgL-1) 654 BOD(mgL-1) 335 N (%) 2.16 K (ppm) 732 P (ppm) 487 Cl-1 (mgL-1) 367 Mg+2(mgL-1) 98 Ca+2 (mgL-1) 201
All the values are the mean of 3 replicates.
This complex nature of HWW makes it both a With controlled irrigation the BOD or TOC drops ‘resource’ and ‘problem’. Presence of sewage waste in rapidly within a few meter wastewater HWW makes it a resource, as it consists of percolations(Mansell et al., 2004; Khaleel et al., biodegradable organic waste, whereas, presence of 2013). Nitrogen removal from WW during irrigation toxic chemicals and metabolites makes it a problem. depends on 2 main factors. Firstly the nitrogen Sewage sludge degrades into non-toxic fulvic and content and secondly the WW quantity. Studies humic acid. Generally, biodegradation of organic recommend the rotation of flooding and drying compounds is more facilitated in soil compared to periods to enhance nitrogen removal. water bodies (Han et al., 2014).
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Table 2. Relationship between soaking time and seed germination. Time (hrs) 3 4 5 6 D. sissoo + - - - A. labbeck + + - - B. purpurea + - - - P. pinnata + + + - M. peguensis + + + +
Table 3. Relationship between seed germination and moisture requirement. Moisture requirement (ml) 5 10 15 20 D. sissoo + ++ +++ + A. labbeck + ++ +++ + B. purpurea + ++ +++ + P. pinnata + ++ +++ +++ M. peguensis + ++ ++ +++
This rotation facilitates nitrification/denitrification Soaking time process and may lead to 75% (up to) nitrogen removal Research studies have revealed that the seed (Ali et al., 2011; Jelusic et al., 2013). One drawback in germination is dependent on optimum soaking time SW irrigation is that the potassium ions binds with (Mosse et al., 2010; Khaleelet al., 2013). Its optimum iron, aluminum or calcium and is converted into value is critical, too short or too long soaking time is insoluble form. With the passage of time these detrimental for germination. Soaking basically serves immobilized phosphate may become soluble (Barbera three important functions, firstly it provides aqueous et al., 2013). environment which is essential for activating enzymes.
Table 4. Relationship between seed germination % and HWW. Concentration of HWW 25% 50% 75% 100% D. sissoo 95.8 ± 90.0 ± 82.0 ± 70.2 ± 1.64 a 1.56 a 2.35 a 1.37 a A. labbeck 92.4 ± 84.9 ± 73.1 ± 63.1 ± 2.54 b 2.43 b 1.43 b 2.02 b B. purpurea 88.5 ± 76.8 ± 61.6 ± 51.3 ± 2.04 c 2.11 c 1.55 c 2.07 c P. pinnata 83.2 ± 67.8 ± 48.8 ± 37.6 ± 2.50 d 1.45 d 1.32 d 1.54 d M. peguensis 76.5 ± 61.6 ± 43.7 ± 33.6 ± 2.54 e 2.23 e 2.08 e 1.54 e Treatment means followed by different letters in each column are significantly different at p=0.05 according to Duncan’s Multiple Range Test.
Secondly, it dissolves monosaccharides and Duncan Multiple range test revealed that the D. sissoo oligosaccharides and also helps in the hydrolysis of and B. Purpurea does not differ significantly between polysaccharides. Thirdly, water softens the seed coat them. Similarly, P. pinnata and A. lebbeck show the and makes it possible for radical and plumule same socking time of 4.5 hrs without any statistical emergence(Pena et al., 2014). Statistical analysis difference (Kanwal et al., 2015). Generally species revealed that the maximum socking time of 5.8 hrs is with less socking time requirement have more required by the M. peguensis and the least socking practical applications (Barbera et al., 2013). time of 3 hrs is of D. sissoo (Table 2).
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Table 5. Impact of HWW on seedling fresh weight (g). Concentration of HWW 0% 25% 50% 75% 100% D. sissoo 0.278 ± 0.308 ± 0.332 ± 0.347 ± 0.325 ± 0.0083a 0.0092a 0.0099a 0.0104a 0.0097a A. labbeck 0.232 ± 0.241 ± 0.274 ± 0.291 ± 0.273 ± 0.0070b 0.0072b 0.0082b 0.0087b 0.0082b B. purpurea 0.135 ± 0.197 ± 0.225 ± 0.224 ± 0.196 ± 0.0040c 0.0059c 0.0067c 0.0067c 0.0059c P. pinnata 0.114 ± 0.151 ± 0.181 ± 0.179 ± 0.166 ± 0.0034d 0.0045d 0.0054d 0.0054d 0.0050d M. peguensis 0.097 ± 0.120 ± 0.120 ± 0.116 ± 0.112 ± 0.0029e 0.0036e 0.0036e 0.0035e 0.0034e
Treatment means followed by different letters in each column are significantly different at p=0.05 according to Duncan’s Multiple Range Test.
Moisture requirement germination at 18 to 20 ml (Table 3). Statistical Moisture requirement is one of the prerequisites for analysis showed significant difference among 5 seed germination.All species show hyperbolic trend, species (Kanwal et al., 2015). At low moisture, which means that seeds need optimum water germination is effected due to the lack of moisture quantity. Increase or decrease from optimum value and mostly metabolic processes are dependent on will decrease the germination percentage. All 5 water (Ali et al., 2011), whereas, at high moisture species respond differently at different water content germination was reduced due to the poor concentration. Optimum water requirement for B. aeration, reduced oxygen, leaching of essential Purpurea, A. Lebbeck, D. Sissoo and M. Peguensis is molecules (enzymes, soluble food reserves, etc.) from 12 to15 ml, whereas P. Pinnata showed optimum seed by ex-osmosis (Khaleel et al., 2013).
Fig. 1. Area under wastewater irrigation at international level.
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Percentage germination percentage was decreased (Prabhakar et al., 2004), Hospital wastewater is rich in nutrientsalongwith however, the 5 experimental species differed toxic materials like pharmaceutics, detergents and significantly in their germination response. Better surfactants etc. Theoretically, it is expected that due response was shown by D. Sissoo and the lesser to more nutrients wastewater irrigation will enhance response was of B. Purpurea. Statistically, M. germination. The same trend is visible in the Table 4. Pegaensis and P. Pinnata do not differ significantly at At low HWW concentration, germination is increased 25% hospital wastewater. Similarly, D. Sissoo and A. as compared to the control and as the concentration lebbeck responded in same manner at highest of waste water wasincreased the germination concentration.
Fig. 2. Impact of HWW on germination time.
Fig. 3. Influence of HWW on root and shoot length.
This difference in germination response may be due At high concentration, the toxicity of wastewater was to the variable needs of difference species, some need more apparent than its effectiveness. This parameter more nutrients and others need lesser nutrients was useful in optimizing the wastewater quantity in (Hussain et al., 2010). urban forestry (Manu et al., 2012). 86 Kanwal and Ali
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Mean time for germination The MTG values are 112, 124, 127, 137 and 150 (hrs) Hospital wastewater significantly reduced mean time for D. sissoo, A. lebbeck, B. purpurea, P. pinnata and for germination (Adam and Duncan, 2002). All the M. peguensis, respectively. Difference in MTG depends on seed size, seed coat five species differed significantly in mean time for thickness/permeability, degree of difference in germination (MTG). The minimum time was toxin/nutrient uptake (Mekki et al., 2007). Studies exhibited by D. sissoo and maximum was reported by have reported strong negative influence of salts and M. peguensis (Fig. 2). phenolics in delaying MTG (Mosse et al., 2010).
Fig. 4. Tolerance response in HWW.
Seedling length B. purpurea did not differ significantly at 50-75% of Seeding length was affected by wastewater but was HWW. Millettia peguensis showed least difference from dependent on the nature and concentration of 25-75%. It is not clear that which component of HWW wastewater. Data for root and shoot length showed exhibited phyto-toxicity at higher concentration, (Fig. 3) that D. sissoo represented the longestshoots however, some evidences suggest the involvement of and roots at 75% of wastewater. Other species also phosphorous, sodium, ethanol and polyphenols (Stutte exhibited considerably better length at 75% of HWW, et al., 2006). The variation in species may be due to the which may be due to availability of the more nutrients tolerance and differential nutrient requirements (Mosse (Barbera et al.,2013). Statistical analysis revealed the et al., 2010). seedling length in the following order: D. sissoo > A. labbeck >B. purpurea >P. pinnata > M. Tolerance index peguensis Tolerance index is another important parameter to get specie response. From the results it is clear that the D. Seeding fresh weight sissoo is the most tolerant out of the five species (Fig. 4). Seedling fresh weight was measured in order to Statistical analysis (one way ANOVA and Duncan’s optimize the treatment for irrigation. Again the trend Multiple Range test) also revealed that the tolerance was somewhat similar as was in germination index decreased with the increase in wastewater percentage. With the increase in HWW concentration concentration. The maximum tolerance was shown by D. the fresh weight increased up to 75% but further sissoo at 75% of HWW (TI-99) and the least tolerance increase in concentration decrease the fresh weight was exhibited by M. peguensis (TI-86). All the rest due to the toxicity (Table 5). species differedsignificantly from one another.
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At high concentration of WW the salt accumulation Vigor index increased which interfered with translocation and When different dilutions of wastewater were photosynthesis (Jelusic et al., 2013). Salt compared for vigor index (VI), very promising results accumulation also disturbs the osmotic balance were exhibited. Statistical analysis showed that the between soil and roots which creates problems in concentrations of HWW and the species differ from water absorption. Those species which are more one another. The maximum VI was shown by D. tolerant are useful in agro-forestry (Pena et al., 2014). sissoo in 25-75% HWW.
Fig. 5. Effect of HWW on vigor index.
The VI increased with the increase in HWW Ali HM, EL-Mahrouk EM, Hassan FA, EL- concentration but after certain concentration it was Tarawy MA. 2011. Usage of sewage effluent in decreased (Fig. 5), probably due to the fact that in irrigation of some woody tree seedlings. Part 3: dilute solution the toxic molecules are less and as the Swietenia mahagoni (L.) Jacq. Saudi Journal of concentration increases the amount of toxic Biological Sciences 18, 201-207. molecules also increases (Ali et al., 2011). http://dx.doi.org/10.1016/j.sjbs.2010.08.001
Conclusion Barbera AC, Maucieri C, Ioppolo A, Milani M, This study suggests solution to reduce pollution of HWW with indigenous species. Instead of artificial Cavallaro V. 2013. Effects of olive mill wastewater and man-made water purification systems we may physico-chemical treatments on polyphenol opt nature-based system with some modifications, as abatement and Italian ryegrass (Lolium multiflorum they are more reliable, eco-friendly and sustainable. It L) germinability. Water research 52(1), 275-281. may provide multiple benefits like reduction in air http://dx.doi.org/10.1016/j.watres.2013.11.004 pollution; increase in forest cover, urban green spots and also to serve as heat sink. Das DC, Kaul RN. 1992. Sewage water: utilization
through forestry. Karnal, India, Central Soil Salinity References Research Institute. Greening wastelands through Adam G, and Duncan H. 2002. Influence of diesel waste water. New Delhi, National Wastelands fuel on seed germination. Environmental Pollution 120, 363-370. Development Board. https://www.ncbi.nlm.nih.gov/pubmed/12395850 www.fao.org/3/a-w0312e/w0312e09.htm
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Ensink J, Mahmood T, VanderHoek W, Manu KJ, Kumar M, Mohana VS. 2012. Effect of Raschid-Sally L, Amerasinghe F. 2004. A Dairy Effluent (treated and untreated) on Seed nationwide assessment of wastewater use in Pakistan: Germination, Seedling Growth and Biochemical An obscure activity or a vitally important one? Water Parameters of Maize (Zea mays L.). International Policy 6, 197-206. Journal of Research, Chemistry and Environment http://wp.iwaponline.com/content/6/3/197 2(1), 62-69.
Han P, Kumar P, Bee-Lian O. 2014. Remediation http://journals.indexcopernicus.com/abstract.php?ic of nutrient-rich waters using the terrestrial id=1060467 plant, Pandanus amaryllifolius Roxb. Journal of Environmental Science 26(2),404-414. Mekki A, Dhouib A, Sayadi S. 2007. Polyphenols https://www.ncbi.nlm.nih.gov/pubmed/25076532 dynamics and phytotoxicity in a soil amended by olive mill wastewaters.Journal of Environmental Hussain F, Malik SA, Athar M, Bashir N, Management 84, 134-140. Younis U, Hassan MU, Mahmood S. 2010. Effect http://dx.doi.org/10.1016/j.jenvman.2006.05.015 of tannery effluents on seed germination and growth of two sunflower cultivars. African Journal of Mongkhonsin B, Nakbanpote W, Nakai I, Biotechnology 9(32), 5113-5120. Hokura A, Jearanaikoon N. 2011. Distribution www.ajol.info/index.php/ajb/article/viewFile/92138 /81572 and speciation of chromium accumulated in Gynura pseudochina (L.) DC. Environmental and Miscellaneous, IWMI (International Water Experimental Botany74, 56-64. Management Institute). 2003. Confronting the http://dx.doi.org/10.1016/j.envexpbot.2011.04.018 realities of wastewater use in agriculture. Water policy briefing 9. Colombo: Mosse KPM, Patti AF, Christen EW, Cavagnaro IWMI.http://www.iwmi.cgiar.org/publications/briefs TR. 2010. Winery wastewater inhibits seed /water-policy-briefs germination and vegetative growth of common crop
Jelusic M, Grcman H, Vodnik D, Suhadolc M, species. Journal of Hazardous Material 180, 63-70. Lestan D. 2013. Functioning of metal contaminated http://www.sciencedirect.com/science/article/pii/S0 garden soil after remediation. Environmental 304389410002839 Pollution 174, 63-70. https://www.ncbi.nlm.nih.gov/pubmed/23246748 Pena A, Mingorance MD, Guzmán I, Sánchez L, Espinosa AJ, Valdés B, Rossini-Oliva S. Khaleel RI, Ismail N, Ibrahim MH. 2013. The 2014. Protecting effect of recycled urban wastes Impact of Waste Water Treatments on Seed (sewage sludge and wastewater) on ryegrass against Germination and Biochemical Parameter of the toxicity of pesticides at high. Journal of Abelmoschus Esculentus L. Procedia - Social and Environmental Managment142,23-29. Behavioral Science 91, 453-460. http://www.sciencedirect.com/science/article/pii/S1 https://www.ncbi.nlm.nih.gov/pubmed/24797639 877042813025743 Prabhakar PS, Mall M, Singh J. 2004. Impact of Mansell J, Drewes J, Rauch T. 2004. Removal fertilizer factory effluent on Seed Germination, mechanisms of endocrine disrupting compounds Seedling growth and Chlorophyll content of Gram (steroids) during soil aquifer treatment. Water (Ciceraeritenum). Journal of Environmental Biology Science and Technology 50(2), 229–237. 27(1), 153-156. http://citeseerx.ist.psu.edu/viewdoc/download?doi= https://www.ncbi.nlm.nih.gov/pubmed/16850894 10.1.1.483.3265&rep=rep1&type=pdf.
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Smit J, Nasr J. 1992. Urban agriculture for germination and growth of radish seedlings. sustainable cities: Using wastes and idle land and Hortriculture Science 41, 108-112. water bodies as resources. Environment and Urbanization 4(2), 141-152. United Nations. 2003. Water for people, water for http://www.klamathsustainablecommunities.org/arti life. The United Nations world water development cles/urbanAg/urbanAgForSustCities.pdf. report. Barcelona: UNESCO.
Stutte GW, Eraso I, Anderson S, Hickey RD. 2006. Bioactivity of volatile alcohols on the
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Journal of Biodiversity and Environmental Sciences (JBES) ISSN: 2220-6663 (Print) 2222-3045 (Online) Vol. 10, No. 6, p. 83-91, 2017 http://www.innspub.net
RESEARCH PAPER OPEN ACCESS
Natural plant based solution for industrial wastewater
Amina Kanwal1, Safdar Ali1, Muhammad Farhan*2
1Department of Botany, Government College University, Lahore, Pakistan 2Sustainable Development Study Center, Government College University, Lahore, Pakistan
Article published on June 11, 2017
Key words: Industrial wastewater, Germination, Urban forestry, Eco-friendly, Fabaceae
Abstract In developing countries like Pakistan, industries are increasing rapidly and are reluctant to manage industrial wastes and wastewaters. This industrial wastewater (IWW) containing number of toxic chemicals, which join natural water streams to disturb the whole ecosystem. Among physical and chemical methods to treat IWW, nature based systems are gaining popularity being more eco-friendly, less laboriously and economical. One way is to irrigate forests with IWW where toxic chemicals/metals can be taken up by plants and is stored for longer time. We conducted seed germination studies on 5 tree species of family fabaceae. Healthy seeds of each species were surface sterilized and placed as 10 per Petri plate on 1 g cotton bed moistened with 15 ml of IWW diluted to 4 concentrations along with control, the Petri plates were placed in growth room for 15 days. Only 4 species responded well in the following sequence; Dalbergia sissoo L. > Albizia lebbeck (L.) Benth > Bauhinia purpurea L. > Pongamia pinnata (L.) Pierre. Seed germination percentage, germination time, seedling length and seedling fresh weight showed positive correlation with concentration of IWW. Heavy metal concentrations found in IWW were 0.006(Cu), 0.0097(Mn), 0.0014(Cr) and 0.0017(Pb) mgL-1. At higher concentration of IWW the germination response was reduced to nil, may be due to the increased toxicity level. Dalbergia sissoo showed 65% germination in 100% IWW. The maximum mean time to germination (115 hrs) was observed in Millettia peguensis and the maximum tolerance index (122) was exhibited by Dalbergia sissoo. Based on germination index, mean time to germination, tolerance index and vigor index these species can be potential candidates to be used in forestry with diluted IWW irrigation. This study highlighted the use of IWW for forest irrigation benefits like, IWW management, IWW treatment, irrigation water scarcity and low forest cover. *Corresponding Author: Muhammad Farhan [email protected]
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Introduction Materials and methods Heavy metal values above threshold level affect long- Seed collection term fertility of soils and ecosystem health (Baebera Seeds of 5 tree species (Dalbergia sissoo L., Albizia et al., 2013). Use of industrial effluents for irrigation lebbeck L. Benth, Bauhinia purpurea L., Pongamia (Prabhakar et al., 2004) and sludge used as manure pinnata L. and Millettia peguensis) of family are the major sources of heavy metal contamination Fabaceae were collected from Punjab Forest (Hussain et al., 2010). In many developing countries Department, Cooper Road, Lahore. Healthier seeds due to non-avability of irrigation water, farmers are were selected stored in paper bags and used for irrigating their crops with industrial effluents having germination experiments. high level of toxic metals like Cu, Pb, Cr, Ni, Mn, Fe, Zn and Cd (Ensink et al., 2004). Surface sterilization of seeds Healthy seeds of each species were surface sterilized These heavy metals through food chain affect all the by washing in distilled water, soaking in 10% bleach components of ecosystem. Bio-accumulation of these for 2 min, 0.5% HgCl2 for 5 minutes, each solution metals lead to chronic diseases in humans (Mansell et added with 2 drops of Tween-20 and thorough al., 2004). Removal of toxic metals from environment rinsing with sterilized distilled water after each is essentially needed to render the animals including treatment. Seeds were then rinsed three times with human beings lead healthy life. distilled water.
Phytoremediation is the plant use for the purpose of Wastewater collection and analysis heavy metal elimination/lessening from soil Industrial wastewater (IWW) was collected from (Mongkhonsin et al., 2011; Naser et al., 2012). Some Quaid-e-Azam industrial state, Kot Lakpat, Lahore tree species like popular, pine and spruce have the and analyzed for heavy metals according to standard capability to respond against toxic levels of heavy protocols. Five treatments of industrial wastewater metals by root exudation of organic acids in soil that were prepared by making dilutions including 0% avoid metal uptake (Khaleel et al., 2013). Hyper- dilution as control (Table 2). accumulation of heavy metal ions is a striking phenomenon exhibited by approximately < 0.2% of Seed Germination angiosperms (Rascio and Navari-Izzo, 2011). Table 1 Bed of one gram cotton was used in Petri plates show some species which have been investigated as soaked with 15 ml of IWW (respective treatment). metal hyper-accumulators. The best known These Petri plates were sterilized in autoclave under angiosperm hyper-accumulator of metals is Thlaspi 121oC, 15 lb/inch2 pressure for 15 minutes. Ten (now: Noccaea) caerulescens (pennycress), which can surface sterilized seeds were place in each Petri plate accumulate large amounts of Zn i.e. 39,600 mg/kg and were covered properly. Petri plates containing (Zhang et al., 2002). seeds were placed in growth room under darkness.
Each treatment had 3 replicates and all were placed in Fabaceae or leguminoseae, is a large and completely randomized block design for 15 days. economically important flowering plant family, members of which are found to grow in many Germination parameters different climates and environments around the Following parameters were recorded from world (Stevens, 2001). The present study was germination setup, percentage germination, mean designed to investigate germination response of five time to germination (MTG), seedling length, seedling tree species (family Fabaceae) to evaluate their use in fresh weight and tolerance index. natural plant based IWW treatment and urban forestry.
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Mean time to germination (MTG) = ∑ n x d N Results and discussion Where; n = number of germinated seeds Industrial wastewater analysis d = time period to incubated Industrial wastewater drained into natural streams N = total number of seeds carries heavy metals (Table 3) which cause serious threats to ecosystem. These metal ions disturb soil
fertility and are carcinogenic for animals (Ensink et Seedling vigor index = Seedling length x germination al., 2004). Trend of using wastewater for irrigation is % increasing day by day due to number of factors including irrigation water scarcity (Jelusic et al., Statistical analysis 2013). ANOVA and Duncan’s multiple range tests was conducted using SPSS (version 18).
Table 1. Important plant species which have been reported as metal hyper-accumulators. Metal Number of hyper-accumulator species reported Plant species that accumulate particular metal specifically Ni 320 Berkheya coddii Phidiasia lindavii Cu 34 Commelina communis Crassula helmsii Co 34 Crotalaria cobalticola Haumaniastrum robertii Zn 18 Thlaspi caerulescens Arabis gemmifera Pb 14 Sesbania drummondii Hemidesmus indicus Cd 4 Thlaspi caerulescens Arabidopsis halleri Cr (VI) Not available Salsola kali Leersia hexandra Gynura (Naser et al., 2012). pseudochina
Table 2. Different treatments of IWW. Treatments T0 T1 T2 T3 T4 Concentration of industrial 0% 25% 50% 75% 100% wastewater control
Percentage germination (Fig.1). It was noted that the increase in IWW lead to Germination is an important parameter in urban the decrease in germination percentage. The most forestry or agro-forestry study, species which show drastic effect was observed with undiluted IWW. better germination are considered potential Among the 5 species the D. sissoo exhibited candidates for phyto-remediation. The results of the maximum germination percentage, i.e. 90% at 25% present study reveled that all the species differed IWW, the minimum germination was shown by M. significantly from one another in all treatments peguensis which was 68% with 25% of IWW.
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Table 3. Heavy metal concentration in IWW. Metal Values (mg/L) Cu 0.001–0.006 Mn 0.0013–0.0097 Cr 0.0003–0.0014 Pb 0.0004–0.0017
It was observed that at lower IWW concentration the the other (Hussain et al., 2010). At high difference in germination among 5 species was minor, concentration, the toxicity of wastewater was more may be at high concentration germination difference apparent than effectiveness (Naser et al., 2012). This was well pronounced. This difference in germination parameter was useful in optimizing the wastewater response may be due to the variable needs of different quantity for urban forestry (Manu et al., 2012). species, some species requiring more nutrients than
Fig. 1. Effect of IWW on germination.
Fig. 2. Effect of IWW on mean time to germination.
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Mean time to germination due to variation in seed size, seed coat permeability, Statistically all the five species differed significantly in differential uptake of nutrients, indigenous toxins and mean time to germination (MTG). The MTG values metabolites (Jelusic et al., 2013). were 87, 94, 97, 107 and 115 hr for D. sissoo, A. lebbeck, B. purpurea, P. pinnata and M. peguensis, Difference in MTG depends on seed size, seed coat respectively (Fig. 2). thickness/permeability, degree of difference in toxin/nutrient uptake (Mekki et al., 2007). Studies Generally the species having less MTG are preferred have reported strong negative impact of salts and over those who have high MTG. Dalbergia sissoo and phenolics on MTG (Mosse et al., 2010). M. peguensis showed sharp difference among the species, however, A. lebbeck and B. purpurea Delay in germination has been reported in studies of exhibited less sharp difference. The delay in olive mill wastewater (Mekki et al., 2007) and diesel germination differed between species and might be oil (Adam and Duncan, 2002).
Fig. 3. Effect of IWW on seedling fresh weight.
Fig. 4. Effect of IWW on seedling length.
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Seedling fresh weight D. sissoo > A. lebbeck > B. purpurea > P. pinnata > Seedling fresh weight represents the health and M. peguensis tolerance of species, in this study five species differed Concentrations of IWW between 25-75% usually significantly from one another, whereas same specie contribute better results. In an applied sense, it is also differ significantly at different concentrations of important to know the effects of wastewater IWW with reference to seedling fresh weight. Among application on growth at different growth stages, to species, D. sissoo exhibited maximum seedling fresh optimize IWW application. In seeds moistened with weight and M. peguensis showed lowest fresh weight IWW, the time of emergence was likely to be affected, (Fig. 3). but the percentage of emergence was unlikely to be The order of fresh weight was: impacted (Mongkhonsin et al., 2011).
Fig. 5. Effect of IWW on tolerance index.
Industrial wastewater is complex in chemical Uptake of metal ions by roots is influenced by many properties (Manu et al., 2012). At low concentrations factors like, bioavailability in rhizosphere, metal the availability of nutrients are limited which concentration and binding affinity with other soil decrease the seedling fresh weight, where as at high particles (Ali et al., 2011). concentration, the abundance of nutrient make them During uptake, first hindrance is created by cell wall, toxic which hinder the physiochemical processes, but has low selectivity (Stutte et al., 2006). Plasma leading to the decrease in seedling weight (Pena et membrane is more selective in metal ion uptake and al., 2014). it has secondary transporters, H+ coupled carrier and channel proteins (Barbera et al., 2013). Translocation Seedling length through shoot is primarily controlled by root pressure Seedling length was influenced softly by IWW and transpiration pull (Jelusic et al., 2013). irrigation. In D. sissoo and A. lebbeck the 75% concentration of IWW showed better results as Tolerance index Tolerance index is effective tool to identify the compared to the 50%, however, B. purpurea, P. tolerance level of species against different metal pinnata and M. peguensis did not show significant concentrations along with determination of the extent difference at 50% and 75% IWW. Among the five of IWW use for irrigation. In present study, D. sissoo species root length showed less variation at different showed high tolerance at 75% IWW, the other four concentrations, whereas shoot length exhibited species showed better tolerance at 50% IWW (Fig. 5). considerable variation (Fig. 4).
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This indicates that D. sissoo is more tolerant to higher they may not hinder cyto-chemical processes (Mosse metal concentration which makes it suitable et al., 2010). Second is the binding of metal ions with candidate for phytoextraction and IWW irrigation. ligands/chelatins like proteins, peptides and organic Statistical analysis reveled that all the species differed acids (Prabrakar et al., 2004), however detailed significantly from one another and for IWW evidences and mechanisms of ligands/chelatins are concentration. Generally it is observed that high still not very clear (Manu et al., 2012). Metal ions are concentration is more toxic for plants. Plant has converted into less toxic oxidation state to further several mechanisms to minimize the effect of metal reduce toxicity, this typically include reduction of Cr6+ toxicity. One is to store metal ions in vacuoles so that to Cr2+ (Han et al., 2014).
Fig. 6. Vigor index of selected species in IWW.
Vigor index Conclusion Promising results were obtained when different This study indicates that, Dalbergia sissoo L., Albizia dilutions of IWW were compared for vigor index (VI). lebbeck (L.) Benth, Bauhinia purpurea L., Pongamia pinnata (L.) Pierre and Millettia peguensis Ali are The order of VI was: D. sissoo > A. lebbeck > B. considerably tolerant in IWW and can be successfully purpurea > P. pinnata > M. peguensis (fig 6). used for phytoextraction processes. Dalbergia sissoo stood more vigorous in terms of health and it showed positive signs of growth up to The tolerance index was as follows: Dalbergia sissoo 75% of IWW, whereas A. lebbeck and B. purpurea > Albizia lebbeck Benth > Bauhinia purpurea > seemed to show negative trend with 50% dilution of Pongamia pinnata > Millettia peguensis. This idea to IWW and above. Millettia peguensis had least VI for plant urban forests with above mentioned species and only up to 25% of IWW and further increase in IWW irrigating them with IWW (in diluted form), can concentration caused decrease in VI. Statistical reduce multiple and serious problems like, analysis reveled that all the 5 species were wastewater toxicity, lack of urban green areas, air significantly different from each other for VI. Other pollution and serve as heat sinks. This study provides studies also reported somewhat similar results (Ali et eco-friendly and sustainable solution for multiple al., 2011; Naser et al., 2012). problems.
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Acknowledgment Jelusic M, Grcman H, Vodnik D, Suhadolc M, The authors are grateful to GC University, Lahore for Lestan D. 2013. Functioning of metal contaminated providing funding and laboratory infrastructure. garden soil after remediation. Environmental Thanks are also due to Punjab Forest Department for Pollution 174, 63-70. helping in field work. Special thanks to PINSTAC http://dx.doi.org/10.1016/j.envpol.2012.10.027 Islamabad for lab assistance. Khaleel RI, Ismail N, Ibrahim MH. 2013. The References Impact of Waste Water Treatments on Seed Adam G, and Duncan H. 2002. Influence of diesel Germination and Biochemical Parameter of fuel on seed germination. Environmental Pollution Abelmoschus Esculentus L. Procedia - Social and 120, 363-370. Behavioral Sciences 91, 453-460. www.agriculturejournals.cz/publicFiles/153034.pdf. http://dx.doi.org/10.1002/jsfa.5923
Ali HM, EL-Mahrouk EM, Hassan FA, EL- Mansell J, Drewes J, Rauch T. 2004. Removal Tarawy MA. 2011. Usage of sewage effluent in mechanisms of endocrine disrupting compounds irrigation of some woody tree seedlings. Part 3: (Steroids) during soil aquifer treatment. Water Swietenia mahagoni (L.) Jacq. Saudi Journal of Science and Technology 50(2), 229–237 Biological Sciences 18, 201-207 www.geol.lsu.edu/blanford/NATORBF/.pdf http://dx.doi.org/10.1016/j.sjbs.2010.08.001 Manu KJ, Kumar M, Mohana VS. 2012. Effect of Barbera AC, Maucieri C, Ioppolo A, Milani M, Dairy Effluent (treated and untreated) on Seed Cavallaro V. 2013. Effects of olive mill wastewater Germination, Seedling Growth and Biochemical physico-chemical treatments on polyphenol Parameters of Maize (Zea mays L.). International abatement and Italian ryegrass (Lolium multiflorum Journal of Research and Chemical Environment 2(1), L) germinability. Water research 52(1), 275-281. 62-69. www.ncbi.nlm.nih.gov/pubmed/24289894 www.journals.indexcopernicus.com/issue.php?id=80 0&id_issue=864388 Ensink J, Simmons J, Van der Hoek W. 2004. Wastewater use in Pakistan: The cases of Haroonabad Mekki A, Dhouib A, Sayadi S. 2007. Polyphenols and Faisalabad. In Wastewater use in irrigated dynamics and phytotoxicity in a soil amended by olive agriculture, C. Scott, N. Faruqui, and L. Raschid-Sally, mill wastewaters. Journal of Environmental Wallingford: CAB International, 91–102. Management 84, 134-140. https://books.google.com.pk/books?isbn=1848261837 http://dx.doi.org/10.1016/j.jenvman.2006.05.015
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91 | Kanwal et al. Abstract of Submitted paper Appendix V
Exploring sustainability of Heavy Metal Phytoextraction by Indigenous Tree Species of Family Fabaceae
Amina Kanwal 1, Safdar Ali 1, Muhammad Farhan 2
1Department of Botany, Government College University, Lahore, Pakistan 2Sustainable Development Study Center, Government College University, Lahore, Pakistan
Abstract The present study highlights the possibility of using industrial wastewater for forest irrigation. Five tree species selected for the study were, Dalbergia sissoo , Albizia lebbeck , Pongamia pinnata , Bauhinia purpurea and Millettia peguensis . In pot experiment, the decrease in photosynthetic rate was as follows; Pongamia pinnata (- 80%), Albizia lebbeck (-60%), Dalbergia sissoo (-45%), Millettia peguensis (-45%) and Bauhinia purpurea (-58%). The proline content in all treatments was measured as a sign of oxidative stress. Maximum proline was observed in Bauhinia purpurea (6.33), where as the least quantity of proline was observed in Pongamia pinnata (3.89). The metal uptake and translocation results are also very promising. Maximum uptake was observed for Pb in IWW by Dalbergia sissoo (107.06 mg/day). Uptake of Cr and Cu uptake was slow in all species. Translocation factor of Albizia lebbeck was maximum i.e. 3.03. Untreated IWW seems to create number of problems in ecosystem by disturbing both biotic and abiotic (soil properties, soil osmotic potential) components. This study seems to be successful in combating wastewater problem. This study indicates that, Dalbergia sissoo L., Albizia lebbeck (L.) Benth, Bauhinia purpurea L., Pongamia pinnata (L.) Pierre and Millettia peguensis Ali are much tolerant in IWW and can be successfully used for phytoextraction processes. The tolerance index is as follows: Dalbergia sissoo > Albizia lebbeck > Bauhinia purpurea > Pongamia pinnata > Millettia peguensis The idea is to utilize IWW to generate urban forests with the said five species. This idea can reduce multiple and serious problems like, IWW toxicity, WW treatment, and air pollution through urban forestry. The most prominent benefit is that this urban forest is eco-friendly and sustainable solution for those multiple problems.
Supplementary graphs Appendix VI
0 25 50 75 100 -5
-10
-15
-20
Control -25 Domestic Hospital -30 Industerial
% Germinationvs differnece -35
-40 Wastewater concentration (%)
Figure VI.1: Germination response of D. sissoo in different WWs
0 -5 25 50 75 100 -10 -15 -20 -25
control -30 Domestic -35 Hospital -40 Industerial
% Germinationvs difference -45 -50 Wastewater concentration (%)
Figure VI.2: Germination response of A. lebbeck in different WWs
0 25 50 75 100 -10
-20
-30 Control -40 Domestic
-50 Hospital
% Germinationvs difference Industerial -60 Wastewater concentration (%)
Figure VI.3: Germination response of B. purpurea in different WWs Supplementary graphs Appendix VI
0 25 50 75 100 -10
-20
-30
-40
Control -50 Domestic -60 Hospital
% Germinationvs difference -70 Industerial -80 Wastewater concentration (%)
Figure VI.4: Germination response of P. pinnata in different WWs
0 25 50 75 100 -10 -20 -30
-40 -50 Control -60 Domestic -70 Hospital
% vs Germination difference -80 Industerial -90 Wastewater concentration (%)
Figure VI.5: Germination response of M. peguensis in different WWs
160 a 150 a 140 a 130 a 120 a b b 110 b c 100 b b c 90 c c 80 c 70 60 Meantime to germination(hrs) Hospital Hospital Hospital Hospital Hospital Domestic Domestic Domestic Domestic Domestic Industerial Industerial Industerial Industerial Industerial D. sissoo A. lebbeck B. purpurea P. pinnata M. peguensis Species
Figure VI.6: Mean Time to Germination of 5 species in different WWs Supplementary graphs Appendix VI
0.70 D. sissoo 0.65 0.60 0.55 0.50 0.45 0.40 0.35 0.30 0.25 Seedling weight (g) fresh 0.20 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.7: Seedling fresh weight of D. sissoo in different WWs
0.55 A. lebbeck
0.50 0.45
0.40
0.35
0.30 0.25 Seedling (g) weight fresh 0.20 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.8: Seedling fresh weight of A. lebbeck in different WWs
0.45 B. purpurea
0.40
0.35
0.30
0.25
0.20 Seedling fresh weight Seedling weight (g) fresh 0.15 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.9: Seedling fresh weight of B. purpurea in different WWs Supplementary graphs Appendix VI
0.35 P. pinnata 0.30
0.25 0.20
0.15
0.10 0.05 Seedling weight (g) fresh 0.00 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.10: Seedling fresh weight of P. pinnata in different WWs
0.23 M. peguensis
0.18
0.13
0.08
0.03 Seedling weight (g) fresh -0.02 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.11: Seedling fresh weight of M. peguensis in different WWs
14 Root length Shoot length 12 10 8 6 4
Seedling length (cm) 2 0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Hospital Industerial Wastewater concentration
Figure VI.12: Seedling length of D. sissoo in different WWs
Supplementary graphs Appendix VI
12 Root length Shoot length
10
8
6
4
Seedling length (cm) length Seedling 2
0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Hospital Industerial Wastewater concentration Figure VI.13: Seedling length of A. lebbeck in different WWs
10 Root length Shoot length 9 8 7 6 5 4 3 2 Seedling length(cm) 1 0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Hospital Industerial Wastewater concentration
Figure VI.14: Seedling length of B. purpurea in different WWs
9 Root length Shoot length 8 7 6 5 4 3 2 Seedling length (cm) length Seedling 1 0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Hospital Industerial Wastewater concentration Figure VI.15: Seedling length of P. pinnata in different WWs
Supplementary graphs Appendix VI
6 Root length Shoot length
5
4
3
2
Seedlinglength(cm) 1
0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Hospital Industerial Wastewater concentration
Figure VI.16: Seedling length of M. peguensis in different WWs
1400 D. sissoo 1200
1000
800
600
400
200 Germination Vigor Index Germination 0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.17: Vigor Index of D. sissoo in different WWs
1200 A. Lebbeck
1000
800
600
400
200 Germination Vigor Index Vigor Germination 0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.18: Vigor Index of A. lebbeck different WWs Supplementary graphs Appendix VI
900 B. purpurea 800 700 600 500 400 300 200
Germination Vigor Index Vigor Germination 100 0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.19: Vigor Index of B. purpurea in different WWs
700 P. pinnata 600
500
400
300
200
100 Germination Vigor Index Vigor Germination 0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.20: Vigor Index of P. pinnata in different WWs
450 M. peguensis 400 350 300 250 200 150 100
Germination Vigor Index Vigor Germination 50 0 0% 0% 0% 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.21: Vigor Index of M. peguensis in different WWs
Supplementary graphs Appendix VI
140 D. sissoo 120
100
80
60
40 Tolerance Index 20
0 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.22: Tolerance Index of D. sissoo in different WWs
130 A. lebbeck 120 110 100 90 80 70
ToleranceIndex 60 50 40 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.23: Tolerance Index of A. lebbeck in different WWs
200 B. purpurea
180
160
140
120 Tolerance Index 100
80 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.24: Tolerance Index of B. purpurea in different WWs Supplementary graphs Appendix VI
200 P. pinnata
180
160
140
120 ToleranceIndex 100
80 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.25: Tolerance Index of P. pinnata in different WWs
210 M. peguensis 190
170
150
130
110 ToleranceIndex 90
70 25% 50% 75% 25% 50% 75% 25% 50% 75% 100% 100% 100% Domestic Industerial Hospital Wastewater concentration
Figure VI.26: Tolerance Index of M. peguensis in different WWs
60 D. sissoo 50 Domestic 40 Hospital 30 Industerial 20 10 0 -10 25% 50% 75% 100%
% Difference vs Control vs Difference % -20 -30 -40 Wastewater concentration
Figure VI.27: Height response of D. sissoo in different WWs Supplementary graphs Appendix VI
100 A. lebbeck 80 Domestic Hospital 60 Industerial 40
20
0 25% 50% 75% 100% -20 % Difference vs Control vs %Difference -40
-60 Wastewater concentration
Figure VI.28: Height response of A. lebbeck in different WWs
30 B. purpurea 20 10 0 25% 50% 75% 100% -10 -20
-30 Domestic -40 Hospital % Difference Control vs Industerial -50 -60 Wastewater concentration
Figure VI.29: Height response of B. purpurea in different WWs
110 P. pinnata 90 70 50 30 10
-10 25% 50% 75% 100% -30
% Difference vs Control vs %Difference Domestic -50 Hospital Industerial -70 Wastewater concentration
Figure VI.30: Height response of P. pinnata in different WWs Supplementary graphs Appendix VI
30 M. peguensis 20
10
0 25% 50% 75% 100% -10
-20
-30 Domestic Hospital -40 % Difference vs Control Difference% Industerial -50
-60 Wastewater concentration
Figure VI.31: Height response of M. peguensis in different WWs
50 D. sissoo 40
30
20
10
0 25% 50% 75% 100% -10 % Difference vs Control vs % Difference Domestic -20 Hospital Industerial -30 Wastewater concentration
Figure VI.32: Fresh weight response of D. sissoo in different WWs
40 A. lebbeck
30
20
10
0 25%Domestic 50% 75% 100% -10 Hospital % Difference vs Control vs % Difference Industerial -20
-30 Wastewater concentration
Figure VI.33: Fresh weight response of A. lebbeck in different WWs Supplementary graphs Appendix VI
50 B. purpurea 40
30
20
10
0 25% 50% 75% 100% -10 Domestic -20 % Difference vs Control vs % Difference Hospital -30 Industerial -40 Wastewater concentration
Figure VI.34: Fresh weight response of B. purpurea in different WWs
P. pinnata 70
50
30
10
-10 25% 50% 75% 100%
% Difference vs Control vs % Difference Domestic -30 Hospital Industerial -50 Wastewater concentration
Figure VI.35: Fresh weight response of P. pinnata in different WWs
55 M. peguensis 45 Domestic 35 Hospital 25 Industerial 15 5
-5 25% 50% 75% 100% -15 % Difference vs Control vs % Difference -25
-35 Wastewater concentration
Figure VI.36: Fresh weight response of M. peguensis in different WWs
Supplementary graphs Appendix VI
55 D. sissoo 45
35
25
15
5
-5 25% 50% 75% 100% % Difference vs vs Control % Difference Domestic -15 Hospital Industerial -25 Wastewater concentration
Figure VI.37: Dry weight response of D. sissoo in different WWs
45 A. lebbeck
35
25
15
5
-5 25% 50% 75% 100%
% Difference vs Control vs % Difference Domestic -15 Hospital Industerial -25 Wastewater concentration
Figure VI.38: Dry weight response of A. lebbeck in different WWs
50 B. purpurea
40
30
20
10
0 25% 50% 75% 100% -10
% Difference vs Control vs % Difference Domestic -20 Hospital Industerial -30 Wastewater concentration
Figure VI.39: Dry weight response of B. purpurea in different WWs
Supplementary graphs Appendix VI
75 P. pinnata
55
35
15
-5 25% 50% 75% 100%
% Difference vs Control vs % Difference Domestic -25 Hospital Industerial -45 Wastewater concentration
Figure VI.40: Dry weight response of P. pinnata in different WWs
60 M. peguensis 50 Domestic 40 Hospital 30 Industerial
20
10
0 25% 50% 75% 100% -10 % Difference vs vs Control % Difference
-20
-30 Wastewater concentration
Figure VI.41: Dry weight response of M. peguensis in different WWs
Wastewater concentration 0 25% 50% 75% 100% -5 -10 Domestic
-15 Hospital Industrial -20
-25 -30
-35
% Difference with control % Difference -40
-45 -50 D. sissoo
Figure VI.42: Changes in photosynthetic rate of D. sissoo under different WWs Supplementary graphs Appendix VI
Wastewater concentration 0 25% 50% 75% 100% -10
-20
-30
-40
-50 Domestic
% Difference with control % Difference Hospital -60 Industrial
-70 A. lebbeck
Figure VI.43: Changes in photosynthetic rate of A. lebbeck under different WWs
Wastewater concentration 0 25% 50% 75% 100% -10
-20
-30
Domestic -40 Hospital
% Difference with control % Difference Industrial -50
B. purpurea -60 Figure VI.44: Changes in photosynthetic rate of B. purpurea under different WWs
10 Wastewater concentration 0 25% 50% 75% 100% -10 -20 -30
-40 -50 -60 Domestic Hospital % Difference with control % Difference -70 Industrial -80 -90 P. pinnata
Figure VI.45: change in photosynthetic rate of P. pinnata under different WWs Supplementary graphs Appendix VI
Wastewater concentration 5 0 -5 25% 50% 75% 100% -10 -15 -20
-25 Domestic -30 Hospital Industrial
% Difference with control % Difference -35 -40 M. peguensis -45 Figure VI.46: Changes in photosynthetic rate of M. peguensis under different WWs
Wastewater concentration 0 25% 50% 75% 100% -10
-20
-30
-40 Domestic % Difference with control % Difference -50 Hospital Indistrial -60 D. sissoo
Figure VI.47: Changes in stomatal conductance of D. sissoo under different WWs
Wastewater concentration -20 -25 25% 50% 75% 100% -30 -35 -40
-45 -50 -55 Domestic
% Difference with control % Difference -60 Hospital -65 Indistrial A. lebbeck -70 Figure VI.48: Changes in stomatal conductance of A. lebbeck under different WWs Supplementary graphs Appendix VI
30 B. purpurea 20
10 0 25% 50% 75% 100% -10
-20 -30 Domestic -40 Hospital
% Difference with control % Difference -50 Indistrial -60 Wastewater concentration -70 Figure VI.49: Changes in stomatal conductance of B. purpurea under different WWs
30 P. pinnata
10
-10 25% 50% 75% 100% Wastewater concentration
-30
-50 Domestic Hospital % Difference with control % Difference -70 Indistrial
-90
Figure VI.50: Change in stomatal conductance of P. pinnata under different WWs
20 M. peguensis
10
0 25% 50% 75% 100% -10
-20
-30 Domestic -40 Hospital -50 Industrial % Difference with control % Difference
-60
Wastewater concentration -70 Figure VI.51: Changes in stomatal conductance of M. peguensis under different WWs
Supplementary graphs Appendix VI
20 D. sissoo 10 0 25% 50% 75% 100% -10 -20 -30 -40 -50 Domestic % Difference with control -60 Hospital -70 Industrial Wastewater concentration -80 Figure VI.52: Changes in Transpiration rate of D. sissoo under different WWs
A. lebbeck 45
25
5
25% 50% 75% 100% -15
Domestic % Difference with control % Difference -35 Hospital Industrial
-55 Wastewater concentration
Figure VI.53: Changes in Transpiration rate of A. lebbeck under different WWs
40 B. purpurea 30 20 10 0 -10 25% 50% 75% 100% -20
-30 Domestic -40 Hospital
% Difference with control % Difference -50 Industrial -60 Wastewater concentration -70 Figure VI.54: Changes in Transpiration rate of B. purpurea under different WWs Supplementary graphs Appendix VI
50 P. pinnata Domestic 40 Hospital Industrial 30
20
10
0 25% 50% 75% 100%
%Difference with control -10
-20
Wastewater concentration -30 Figure VI.55: change in Transpiration rate of P. pinnata under different WWs
20 M. peguensis
10
0 25% 50% 75% 100% -10
-20
-30
-40 Domestic
% Difference with control % Difference -50 Hospital -60 Industrial
-70 Wastewater concentration
Figure VI.56: Changes in Transpiration rate of M. peguensis under different WWs
35 Domestic D. sissoo 30 Hospital Industerial 25
20
15
10 Difference vs control (%) 5
0 25% 50% 75% 100% Wastewater concentration
Figure VI.57: Changes in MDA of D. sissoo under different WWs
Supplementary graphs Appendix VI
60 A. lebbeck Domestic 50 Hospital Industerial 40
30
20
Difference vs control(%) 10
0 25% 50% 75% 100% Wastewater concentration
Figure VI.58: Changes in MDA of A. lebbeck under different WWs
25 Domestic B. purpurea Hospital 20 Industerial
15
10
Difference vs control (%) 5
0 25% 50% 75% 100% Wastewater concentration
Figure VI.59: Changes in MDA of B. purpurea under different WWs
80 P. pinnata Domestic 70 Hospital 60 Industerial
50
40
30
20 Difference vs control(%) 10
0 25% 50% 75% 100% Wastewater concentration
Figure VI.60: change in MDA of P. pinnata under different WWs Supplementary graphs Appendix VI
25 Domestic M. peguensis Hospital 20 Industerial
15
10
Difference vs control vs Difference (%) 5
0 25% 50% 75% 100% Wastewater concentration Figure VI.61: Changes in MDA of M. peguensis under different WWs
350 D. sissoo
300 Domestic Hospital 250 Industerial
200
150
100 Difference vsDifferencecontrol (%) 50
0 25% 50% 75% 100% Wastewater concentration
Figure VI.62: Changes in proline of D. sissoo under different WWs
600 A. lebbeck Domestic 500 Hospital 400 Industerial
300
200
Difference vscontrol Difference (%) 100
0 25% 50% 75% 100% Wastewater concentration Figure VI.63: Changes in proline of A. lebbeck under different WWs Supplementary graphs Appendix VI
300 B. purpurea Domestic 250 Hospital 200 Industerial
150
100
Differencecontrolvs (%) 50
0 25% 50% 75% 100% Wastewater concentration Figure VI.64: Changes in proline of B. purpurea under different WWs
400 P. pinnata 350 Domestic Hospital 300 Industerial 250
200
150
100 Differencevs control (%) 50
0 25% 50% 75% 100% Wastewater concentration Figure VI.65: change in proline of P. pinnata under different WWs
400 M. peguensis 350 Domestic Hospital 300 Industerial 250
200
150
100 Differencevs control (%) 50
0 25% 50% 75% 100% Wastewater concentration Figure VI.66: Changes in proline of M. peguensis under different WWs Appendix VII
Morphological description of selected tree species The plants were selected with the help of available literature i.e., Flora of Pakistan.
1. Dalbergia sissoo Roxb. (Syn: Amerimnon sissoo ) Vern: Shisham, Sissu, Tali English name: Indian rose wood Family: Papilionaceae Species description: Tree with rough bark and mainly longitudinal furrows, young branch pubescent. Leaf imparipinnate, rachis 3.7-7.5 cm long; leaflets 3-5, 3.5-6.5 cm long, broadly ovate or suborbicular, acuminate, glabrescent, petiolule. 5-8mm long; stipules 5 mm long. Inflorescence an axillary panicle, composed of several short spikes with sessile to subsessile flowers. Bract small, pubescent, caducous. Calyx 5 mm long, teeth ciliate, unequal, shorter than the tube. Corolla yellowish white. Stamens 9, monadelphous, tube slit on the upper side only, anthers uniform. Ovary pubescent, 2-4- ovulate, style glabrous, stigma capitate. Fruit 3.7-10 cm long, 7.0-13 mm broad, strap- shaped, glabrous, 1-4-seeded. Seed flattened. (Ali, 1977). Fl. Per: March - May Distribution: Pakistan; India; Sikkim; Afghanistan; Persia; Iraq Economic importance: It is commonly used for furniture, carts, boats, wheels etc
2. Albizia lebbeck (L.) Benth. (Syn: Acacia lebbeck, Mimosa lebbeck, Mimosa sirissa .) Vern: Siris English name: lebbeck, lebbek tree, flea tree, frywood, koko and woman's tongue tree Family: Mimosaceae Species description: A large deciduous tree with dark grey bark, usually cracked, young parts usually hairy. Leaves bipinnate, rachis 7.5-15 cm long, glabrous or tomentose, with a large gland 1.2-3.7 cm from the base; stipules 3-4 mm long, linear, caducous, tomentose. Pinnae 1-4 pairs, 5-20 cm long, often with glands between the upper pairs of leaflets or between all the pairs. Leaflets 3-9 pairs, petiolule 1 mm long, the lateral leaflets oblong, terminal obovate, obtuse or retuse, glabrous or hairy. Inflorescence pedunculate heads, solitary or fasciculated; peduncle 3.5-10 cm long. Flowers whitish, Appendix VII very fragrant, pedicel hairy 2-3 mm long, bracteate; bract 5 mm long, linear, caducous. Calyx campanulate 3-4 mm long, hairy, short toothed, teeth deltoid-acute. Corolla 7-8 mm long, funnel shaped, lobes 2 mm long, ovate, acute, hairy externally. Stamens 2.5- 3.8 cm long, staminal tube slightly shorter than corolla tube, anthers minute. Pod 15-30 cm long, 2.5-5.0 cm broad, thin, pale straw coloured. Seeds 6-12 compressed, pale brown, faveolate on both the faces (Ali, 1973a). Fl. Per: April - May Distribution: Pakistan, widely cultivated; Tropical Asia; N. Australia and Tropical Africa Economic importance: excellent for furniture, picture frames, house building, canoes etc. It is also used for cane crushers, oil mills and wheels
3. Bauhinia purpurea L. (Syn: Phanera purpurea, Bauhinia rosea, Bauhinia triandra) Vern: Kachnar, Koiral, Khairwal, Koliar English name: Orchid tree, Hong Kong orchid tree, purple bauhinia, camel's foot, butterfly tree. Family: Ceasalpiniaceae Species description: A medium sized tree with ashy to dark brown bark, young parts pubescent. Leaves petiolate, petiole 2.5-5 cm long, lamina 7.0-18 cm long, rather longer than broad, 9-11 nerved, cleft about halfway down into 2 acute or rounded lobes, minutely pubescent below when young. Inflorescence few flowered panicles at the ends of the branches. Flowers pedicellate, pedicel 5-13 mm long; tomentose, bract 3 mm long, bracteole 2 mm long. Hypanthium 7-10 mm long. Calyx 2.5-3.0 cm long, usually splitting into two reflexed segments, one emarginate the other 3 toothed. Petals 3.7-5 cm long, oblanceolate, long clawed, spreading, veined. Stamens usually 3 fertile, others reduced to antherless filaments. Ovary downy, long stalked; style long, stigma oblique. Pod 15-25 cm long, 1.5-2 cm broad; stalk 2 cm long. Seeds 12- 15, almost round, 1.2-1.3 cm in diameter, brown, smooth (Ali, 1973b). Fl. Per: September - November Distribution: Pakistan (KPK, Punjab); India (Punjab, Uttar Pradesh, Central India, Bombay, Madras, Bengal, Assam) Sikkim; Burma; South East Asia; China Appendix VII
Economic importance: It is often planted as an ornamental roadside and garden plant. The leaves are used as fodder. The leaves, flower buds, flowers and young pods are eaten as vegetable and the flower buds are often pickled. The plant yields gum and the bark is good as tanning material and for fibre. The wood is used for making agri¬cultural implements and for fuel. The bark, root and flowers are also reputed to have medicinal properties
4. Pongamia pinnata (L.) Pierre (Syn: Milletia pinnata ) Vern: Sukh Chain, pungai (in Tamil), karach (in Bengali), English name: Indian Beech Tree, Honge Tree, Pongam Tree, Family: Papilionaceae Species description: Tree, branches spreading, twigs glabrous. Leaf imparipinnate, rachis 5-15 cm long, leaflets 5-9, 5-10 cm long, elliptic or ovate-oblong, acute- acuminate, glabrous; petiolule 5-8.0 mm long; stipels absent; stipules small, caducous. Raceme shorter than the leaf. Pedicel 7-10 mm long. Bract 2.5 mm long. Calyx 3.5-4.0 mm long, pubescent, obscurely toothed. Corolla white tinged with violet or pinkish. Vexillum 1.2-1.3 cm long. Fruit 3.5-5.0 cm long, 1.7-2.5 cm long, obliquely oblong, woody, indehiscent, usually 1-seeded. (Ali, 1977). Fl. Per: April-May Distribution: Widely cultivated in Punjab and Sind; distributed in India; Ceylon; Burma; Malaya; N. Australia; Economic importance: It is often used for landscaping purposes as a windbreak or for shade due to the large canopy and showy fragrant flowers. The bark can be used to make twine or rope and it also yields a black gum that has historically been used to treat wounds caused by poisonous fish. The wood is said to be beautifully grained but splits easily when sawn thus relegating it to firewood, posts, and tool handles. Oil made from the seeds, known as pongam oil, is an important asset of this tree and has been used as lamp oil, in soap making, and as a lubricant for thousands of years.
5. Millettia peguensis Ali (Syn: Millettia ovalifolia, Pongamia ovalifolia ) Appendix VII
Vern: Tuma (in Bengali) English name: Moulmein rosewood Family: Papilionaceae Species description: A small deciduous tree. Leaf imparipinnately compound, 15-20 cm long; leaflets 5-7, 3-7 cm long, elliptical, obtuse, acute to acuminate, petiolule c. 4-6 mm long; stipels absent. Inflorescence a raceme, 5-20 cm long, flowers solitary or fascicled. Bract absent. Bracteoles 1 mm long. Pedicel 4-7 mm long. Calyx 1-2 mm long, glabrous except the margin, teeth inconspicuous. Vexillum 7-8 mm long, glabrous, auriculate. Disc absent. Ovary pubescent, ovules many. Fruit linear, 6.5- 9 cm long, 1.5 cm broad, glabrous to subglabrous (Ali, 1977). Fl. Per: February – April. Distribution: This species is native to Lower Burma and Siam but it is cultivated in Burma, India and Pakistan. In Pakistan, it is grown in the gardens at Karachi and Lahore Economic importance: The plant is a food source for the Jamides bochus caterpillar and as ornamental plants.