Final Master's Exam Presentation 071615

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Predicting Metal(loid) Phytoaccumulation/Phytoavailability from Soil Property and Chemical Extraction MethodZhenfei Liang, M.S.Advisor: Nick BastaEnvironmental Science Graduate ProgramPredicting Metal(loid) Phytoaccumulation from Soil Property and Chemical Extraction Good afternoon everyone. My name is Zhenfei Liang. I am a graduate student in the Environmental Science Graduate Program and working with my advisor Dr. Basta in the School of Environment and Natural Resources.The topic I will talk about today is Predicting metal(loid) phytoaccumulation from soil property and chemical extraction.1ContentsINTRODUCTIONTRANSFER FROM SOIL TO PLANTMETAL(LOID) BIOAVAILABILITYMETHODS FOR PREDICTING PHYTOACCUMULATIONSOIL PROPERTY METHODCHEMICAL EXTRACTION METHODConclusionPerspectivesHere are the contents of my presentation.2IntroductionConcern over metal contaminated soilIntroduction of metals into the food chainLoss of vegetation cover induces through phytotoxicityCycling of metals to surface soil horizons by tolerant plants to induce toxic effects on plants(McLaughlin, 2001)WHY BOTHER?First and foremost, lets look at the importance of this study. So why should we care the prediction of phytoaccumulation?As a matter of fact, there has always been concern over metal(loid) contaminanted soils. For instance,The metal(loid) contaminated soils can introduce metals into the food chain.And the vegetation cover grown on the soil may lose as a result of phytotoxicity.Lastly, the cycling of metals to surface soil horizons can induce toxic effects on plants.3IntroductionPredicting plant uptake in contaminated soil important, with regard to plant nutrition, crop contamination, environmental qualityMeasuring total metal content in soil may not predict phytoaccumulationTherefore, predicting plant uptake in metal(loid) contaminated soils is important, especially with regard to plant nutrition, crop contamination, and environmental quality.Analysis of total content may provide information on the accumulation of contaminants. However, measuring total content may not predict phytoaccumulation, since not all the forms of contaminants present are available to plants. Actually, there is consensus in literature that the determination of only total content does not provide enough information in contaminant environmental behavior, risk assessment practices and site-specific remediation. 4Transfer FROM soil TO plantControlling factors: geochemical, climatic, biological, anthropogenicPhytoaccumulation depends upon abundance, speciation and binding characteristics on soil surfaces, governed by sorption, complexation and redox processes(Marschner, 1995; McBride, 1995; Sauv et al., 2000; Kabata-Pendias, 2004; Patra et al., 2004; Moreno et al., 2005; Sterckeman et al., 2005; Rieuwerts et al., 2006; Kalis et al., 2007; Anawar et al., 2008; Rmkens et al., 2009a; Rodrigues et al., 2010)So why is that? Lets look at the transfer process of metal(loid)s from soil to plant:The transfer of metal(loid)s from soil to plant is an element flow from abiotic to biotic compartments of the biosphere, controlled by geochemical, climatic, biological and anthropogenic factors. Phytoaccumulation of contaminants depends upon their abundance, chemical forms and binding characteristics on soil surfaces, which is governed by soil chemical processes including sorption, complexation and redox. As shown in the right picture, metal uptake and accumulation in plants can be divided into five steps:First: A metal fraction is sorbed at root surface;Second: Bioavailable metal moves across cellular membrane into root cells;Third: A fraction of the metal absorbed into roots is immobilized in the vacuole;Fourth: Intracellular mobile metal crosses cellular membranes into root vascular tissue (xylem);Fifth: Metal is translocated from the root to aerial tissues (stems and leaves).5Metal(loid) BioavailabilityAvailable fraction fraction of total amount of contaminant present in a specific environmental compartment, within a given time span, either available or can be made available for uptake by organisms from either direct surrounding of the organism or by ingestion of foodBioavailability contaminant absorbed into the organism and may cause an adverse or beneficial effect in the exposed organismIn contrast to total content, the bioavailability concept is more widely used.Before moving forward, lets first look at availability. The available fraction is the fraction of total amount of contaminant present in a specific environmental compartment, within a given time span, either available or can be made available for uptake by organisms from either direct surrounding of the organism or by ingestion of food.While bioavailability is the amount of contaminant absorbed into the organism and cause an adverse or beneficial effect in the exposed organism.6Metal(loid) BioavailabilityDifferent researchers try to explain the bioavailability process involved in the soil-plant system from different perspectives. For instance, Dr. McBride at Cornell University, Drs. Wang and Han at Chinese Academy of Sciences, Dr. Kabata-Pendias at the Institute of Soil Science and Plant Cultivation in Pulawy, Poland. Noteworthily, my advisor Dr. Basta in his excellent review paper Trace element chemistry in residual-treated soil: Key concepts and metal bioavailability, assumes that the bioavailability process is a complex process affected by a variety of abiotic and biotic processes, including adsorption onto and desorption from mineral surfaces, precipitation, release through the dissolution of minerals, and interactions with soil, plants, and microbes. 7Metal(loid) BioavailabilityBioavailability reduces uncertainty in exposure estimates and improves risk assessment from contaminated plantsAccurate prediction of bioavailability improve risk assessment in terrestrial ecosystems(Peijnenburg et al., 1997; Sauv et al., 1998; McLaughlin et al., 2000a; McLaughlin et al., 2000b; Peijnenburg et al., 2000; Weng et al., 2004; Dayton et al., 2006; Menzies et al., 2007; USEPA, 2007; Zhang et al., 2010)Bioavailability could reduce uncertainty in exposure estimates and improve risk assessment from contaminated plants.And accurate prediction of bioavailability improves risk assessment in terrestrial ecosystems.Here we are talking about the bioavailability of metal(loid)s to plants, also called phytoavailability or phytoaccumulation.8Methods For Predicting PhytoaccumulationPlant bioassay takes a long timePrediction is hot topic, great progress, but still difficult, no single one reliable method existsMechanistic models & empirical models Soil contaminant measurement methods: Single Chemical Extraction Chemical Speciation (sequential extraction or spectroscopy) Diffusive Gradients in Thin Films (DGT) (Zhang and Davison, 1995) Pore Water (PW) (McBride et al., 1997) Windermere Humic Aqueous Model (WHAM) (Tipping, 1998) Free Ion Activity Model (FIAM) (Sauv et al., 1998) Donnan Membrane Technique (DMT) (Temminghoff et al., 2000) terrestrial Biotic Ligand Model (tBLM) (Di Toro et al., 2001) HOW TO MEASURE?So how can we measure phytoaccumulation? Direct plant bioassy usually takes a long time, which is not a desirable way.The prediction of phytoaccumulation has been a hot topic for years in both agricultural and environmental studies. There has been a great progress made. However, prediction is still very difficult and no single one reliable method exists.The current existing prediction methods can be classified into two groups: methanistically based and empirically based. Mechanistic models, describing such rhizosphere-plant interactions, are rather difficult to develop due to the complexity of processes involved both at the soil-root interface as well as those regulating the internal translocation of contaminants to aboveground tissues. As an alternative, empirical models are used to link the chemical availability of contaminants in soil to internal levels in plants correcting for common soil properties.The current existing soil contaminant measurement methods include:Single Chemical ExtractionChemical Speciation (sequential extraction or spectroscopy)Diffusive Gradients in Thin Films (DGT)Pore Water (PW)Windermere Humic Aqueous Model (WHAM)Free Ion Activity Model (FIAM)Donnan Membrane Technique (DMT)terrestrial Biotic Ligand Model (tBLM)9Soil Property MethodModifying effect of soil property on correlation and multiple-regression techniques routinely used to examine the relationship between and among soil properties and biological endpointsDominant soil properties to affect phytoaccumulation: pH, OC, CEC, clay content, and reactive Fe, Al, Mn oxides(Basta et al., 2005; Fairbrother et al., 2007)This study will focus on soil property and chemical extraction methods. First, lets look at the soil property method.The modifying effects of soil property on correlation and multiple-regression techniques have been routinely used to examine the relationship between and among soil properties and biological endpoints. Dominant soil chemical/physical properties known to affect the phytoaccumulation of contaminants are soil pH, organic carbon (OC), cation exchange capacity (CEC), clay content, and reactive Fe, Al, and Mn oxides.10Here is a list of relevant key literatures using soil property method to predict phytoaccumulation/phytoavailability. These are the correlation results, to the left of the equation is plant concentration of contaminants, to the right of the equation are correlated soil properties.11Continued.12Soil Property MethodSoil samples: natural source (naturally uncontaminated or contaminated), anthropogenic source (artificially spiked)Studied metal(loid)s: As, Cd, Ce, Cr, Cu, La, Nd, Ni, Pb, Pr, ZnNumber of soils or study sites: 3 to 215pH, OC, total content the most significant factors for prediction, pH and OC negatively correlated with plant uptake, total content positively correlatedEmpirical methodology, overlooking other abiotic or biotic factors besides soil property Soil properties inherently intercorrelated, necessitating techniques to quantify the marginal contribution of each mitigating propertyCollectively, the soil samples used in above literature include natural source (naturally uncontaminated or contaminated) and anthropogenic source (artificially spiked).The studied metal(loid)s include As, Cd, Ce[srim], Cr, Cu, La[lnnm], Nd[ni:odmim], Ni, Pb, Pr[preziodmim], Zn.The number of soils or study sites ranges from 3 to 215.pH, OC, total content are found to be the most significant factors for prediction, with pH and OC negatively correlated, and total content positively correlated.However, there are problems involved with the soil property method, since it is empirical methodology, which overlooks other abiotic or biotic factors besides soil property.Furthermore, some soil properties are inherently intercorrelated, which necessitates techniques to quantify the marginal contribution of each mitigating property.13Chemical Extraction MethodMechanistically based, only extract very small proportion of potential available (bioaccessible) poolExtraction methods: Single extraction procedure Sequential extraction procedures Enhancement with microscopic and spectroscopic techniques(Peijnenburg et al., 1999; Basta and Gradwohl 2000; Peijnenburg et al., 2007)In parallel with the soil property methodology, other researchers try to reach the prediction of phytoaccumulation from another direction, based on chemical extraction. The extraction methodology is methanistically based, and it only extracts a very small proportion of a potential available (bioaccessible) pool contaminants. And their utility lies not in the magnitude of the amount of chemical extracted, but in the relationship between the amount of chemical extracted and the biological response. The current existing extraction methods include:Single extraction procedureSequential extraction proceduresEnhancement with microscopic and spectroscopic techniquesXANES (near-edge portions of the spectra)EXAFS (extended fine-structure portions of the spectra)14Here is a list of relevant key studies using chemical extraction method to predict phytoaccumulation/phytoavailability.15Continued.16 * p < 0.05, ** p < 0.01, *** p < 0.001. Aboveground Leersia hexandra 0.688*, underground Juncus effuses 0.512*.For the specific metal Cd, the correlation results are shown here, with the significant correlations highlighted in each cell.17For the specific metal Zn, the correlation results are shown here, with the significant correlations highlighted in each cell.18For the specific metal Pb, the correlation results are shown here, with the significant correlations highlighted in each cell.19For the specific metalloid As, the correlation results are shown here, with the significant correlations highlighted in each cell.20Soil samples: 2 naturally uncontaminated, 7 naturally contaminated, 3 natural soils (plus naturally uncontaminated or contaminated), 1 combination of naturally contaminated and artificially spikedStudied metal(loid)s: As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Se, ZnNumber of soils or study sites: 1 to 53Extraction tests: H2O; Neutral salt solutions: 0.01 M CaCl2, 0.05 M CaCl2, 0.01 M Ca(NO3)2, 0.05 M Ca(NO3)2, 0.1 M LiNO3, 0.1 M NaNO3, 0.01 M Sr(NO3)2, 1 M NH4NO3, 1 M NH4Ac, 0.1 M (NH4)2SO4, 1 M NH4Cl, 1 M MgCl2, 0.5 M NaHCO3, 1.0 M NaAc, 0.5 M KH2PO4; Chelating agents: 0.01 M EDTA, 0.04 M EDTA, 0.05 M EDTA, 0.02 M AAAC-EDTA, 0.05 M AAAc-EDTA, 0.1 M Na2EDTA, 0.05 M NH4-EDTA, Mehlich 3, AEM-EDTA, EDTA-NH4Ac, 0.005 M DTPA, AEM- DTPA, 0.005 M DTPA-TEA, AB-DTPA, CaCl2-TEA-DTPA, DTPA-TEA-CaCl2; Weak acids: 0.11 M HAc, 0.43 M HAc, 0.2 M C6H8O7; Strong acids: HClc, 0.1 M HCl, 1 M HCl, 0.43 M HNO3, 0.5 M HNO3, HNO3/HClO4, HCl/HClO4, HCl/HNO3, Mehlich 1; Others: EPA 3050, TCLP, BCR, and rhizoChemical Extraction MethodCollectively, the soil samples used in above literature include naturally uncontaminated, naturally contaminated, natural soils, and combination of naturally contaminated and artificially spiked. The studied metal(loid)s include As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Se, and Zn.The number of soils or study sites ranges from 1 to 53.The extraction tests can be classified into H2O; neutral salt solutions; chelating agents; weak acids; strong acids; and others.21CaCl2 significantly correlated in 6 studies NH4OAc suitable in 3 studies NH4Cl effective in 2 studiesCd: 0.01 M CaCl2, 1 M NH4OAc, 1 M NH4NO3, 0.005 M DTPA-TEA Zn: 0.01 M CaCl2, 1 M NH4OAc, 0.005 M DTPA-TEA, 1 M NaNO3 Pb: 0.01 M CaCl2, 1 M NH4OAc, 0.005 M DTPA-TEA, Mehlich 3 As: 0.01 M CaCl2, 1 M NaNO3, 0.1 M (NH4)2SO4, H2OChemical Extraction Method(Gray et al., 1999; Krishnamurti et al., 2000; Song et al, 2004; Meers et al, 2005; Zhang et al, 2006; Meers et al.,2007; Vzquz et al., 2008; Zhang et al., 2010) The suitability of neutral salt solutions for prediction of phytoaccumuiton is in accordance with general knowledge. CaCl2 is significantly correlated in 6 studies; NH4OAc is suitable in 3 studies; NH4Cl is effective in 2 studies.Best extractants for Cd are in the order of 0.01 M CaCl2, 1 M NH4OAc, 1 M NH4NO3, and 0.005 M DTPA-TEA; best extractants for Zn are in the order of 0.01 M CaCl2, 1 M NH4OAc,0.005 M DTPA-TEA, and 1 M NaNO3; best extractants for Pb are in the order of 0.01 M CaCl2, 1 M NH4OAc, 0.005 M DTPA-TEA, and Mehlich 3; and best extractants for As are in the order of 0.01 M CaCl2, 1 M NaNO3, 0.1 M (NH4)2SO4, and H2O. 22ConclusionpH, OC, total content are the most significant factors for predictionNeutral salt extractants provide the most useful indicationNo single one prediction method is recognized universallyIn conclusion, As for the soil property method, pH, OC, total content are the most significant factors for prediction; As for chemical extraction mthod, neutral salt extractants provide the most useful indication; Overrall, no single one prediction method is recognized universally.23PerspectivesSoil property method based on spiked soils, most chemical extraction method based on natural soils, metal(loid) availability greater in spiked soils than naturally contaminated The ability of regression equations from spiked soils, to predict phytoaccumulation from naturally contaminated soils, or vice versaPrediction ability for other sources, such as inorganic fertilizer, organic sewage sludge, manure byproducts(Bolan et al., 2003; Bolan et al., 2004; Basta et al., 2005) Noteworthily, some of the soil property method are based on spiked soils, while most chemical extraction method are based on natural soils, since metal(loid) availability is greater in spiked soils than naturally contaminated;There is research need to test the prediction ability of regression equations generated from spiked soils, to predict phytoaccumulation from naturally contaminated soils, or vice versa;There is also research need to test the prediction ability for other contamination sources, such as inorganic fertilizer, organic sewage sludge, and manure byproducts.24OK. A portrait of mine working on Waterman Farm.25AcknowledgementsM.S. Committee Dr. Nick Basta Dr. Roman Lanno Dr. Jiyoung LeeColleagues Shane Whitacre John Obrycki Brooke StevensOSU ESGPESGPI would like to sincerely thank my M.S. committee, my colleagues, the staff in the environmental soil chemistry lab, my Chinese friends and American friends, and my roommates for their support during the past two years.I would also appreciate for Ohio State and ESGP for the funding support. 26Thank you for your attentionQuestions and Comments?Thank you. Do you have any questions or comments?27Table 1. Selected relevant key literature using soil property method to predict phytoaccumulation/phytoavailabilityElements Soil SamplesContamination SourceNumberof SoilsComparative MethodCorrelation ResultsReferencesCdSubsamples collected from Ap horizons in 7 sites in AustriaNone7Quality winter wheat, spring durum, and non-quality winter wheat grain concentrationY = -0.0381+ cultivar + 0.3750Cd r2 = 0.688Y = 0.0324 + cultivar + 0.3177Cd - 0.0097pH r2 = 0.714Y = 0.0117 + cultivar + 0.2359Cd + pH - 0.0401OC r2 = 0.814Y = -0.0958 + cultivar + 0.2771Cd + 0.0194pH - 0.0218OC + 0.0004Cl- - 11.40Ca2+ r2 = 0.904(Wenzel et al., 1996)Cd3 topsoil samples typical in New ZealandNone3Above ground parts of wheat (Triticum aestivum L. 'Monad'.), white clover (Trifolium repens L. 'Huia'.), lettuce (Lactuca sativa L. 'Buttercrunch'.), carrot (Daucus carota L. 'Space Saver'.), and ryegrass (Lolium perenne L. 'Nui'.), and carrot roots Cd contentlog [Cd]s = 7.28 - 0.89 pH + 1.21 log CdT - 1.04 log OM r2 = 0.763, se = 0.273, p < 0.001(Gray et al., 1999)CdPaired soil and crop samples collected across the main cereal-growing areas in BritainNaturally uncontaminated or contaminated162 paired soil and wheat samples and 215 paired soil and barley samplesWheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) grain concentrationWheat:log grain Cd = 0.28 + 0.44 log soil Cd - 0.18 pH; n = 162, radj2 = 0.49, se = 0.23, p < 0.001Winter barley:log grain Cd = 0.04 + 0.21 log soil Cd - 0.23 pH; n = 90, radj2 = 0.22, se = 0.28, p < 0.05(Adams et al., 2004)Cr, Ni, Zn, Cu, Cd, Pb, La, Ce, Pr, Nd14 surface soil samples collected in northern ChinaNaturally uncontaminated or contaminated14Root and leave concentration of Chinese cabbage [Brassica compestris L. ssp. pekinensis (lour) Olsson], spinach (Spinacia oleracea L.), celery (Apium graveolens) and cole [Brassica cumpestris L. ssp. chinensis (L.) Makino, var. communis Tsenetlee]log [Mroot] = a + blog[Msoil] + cOM + dpH + eCEC + flog[Mextra] 0.741 < r2 < 0.954, p < 0.05(Wang et al., 2004)Ni3 different soils from various experimental fields in the NetherlandsArtificially spiked3Dry shoot weight of Oats (Avena sativa L.) pH (4.7-7.0) is the most important factor to explain difference of Ni bioavailability in the soils. The remaining variation is caused by other differences in soil type. Soil organic matter binds Ni much stronger than clay silicates and iron (hydr)-oxides within the acidic pH range(Weng et al., 2004)PbSurface and subsurface soil samples collected from typical tea gardens in Zhejiang, ChinaNone17Tea leave concentrationBioavailable Pb = 0.2345 (10-pH) + 0.5722 OM r = 0.78, p < 0.001PBP = 0.1012 (10-pH) + 0.5696 OM r = 0.67, p < 0.001(Jin et al., 2005)Pb21 temperate soils from uncontaminated sites in the USArtificially spiked21Dry matter growth and tissue concentration of lettuce (Lactuca sativa var. Paris Island Cos)log tissue Pb = -0.07 pH - 0.36 OC - 0.06FEAL - 0.44 CEC r2 = 0.67, p < 0.001(Dayton et al., 2006)As, Cd, Pb, Zn5 soils in the USArtificially spiked5Tissue contaminant concentration of Alfalfa (Medicago sativa L.), perennial ryegrass (Lolium perenne L.), and Japanese millet (Echinochloa crusgalliL.)As TC = 1.71 - 0.496 logFeOX n = 14, radj2 = 0.469Cd TC = 4.14 - 1.17 logOC - 0.787 logClay 0.357pH n = 13, radj2 = 0.705Pb TC = 0.702 - 0.241 log CEC n = 13, radj2 = 0.717Zn TC = 4.74 - 1.64 logOC - 0.908 logClay- 0.403pH n = 14, radj2 = 0.677(Anderson & Basta, 2009) Naturally uncontaminatedCr, Ni, Zn, Cu, Cd, Pb, La, Ce, Pr, Nd14 surface soil samples collected in northern ChinaNaturally uncontaminated or contaminated14Root and leave concentration of Chinese cabbage [Brassica compestris L. ssp. pekinensis (lour) Olsson], spinach (Spinacia oleracea L.), celery (Apium graveolens) and cole [Brassica cumpestris L. ssp. chinensis (L.) Makino, var. communis Tsenetlee]log [Mroot] = a + blog[Msoil] + cOM + dpH + eCEC + flog[Mextra] 0.741 < r2 < 0.954, p < 0.05(Wang et al., 2004)Ni3 different soils from various experimental fields in the NetherlandsArtificially spiked3Dry shoot weight of Oats (Avena sativa L.) pH (4.7-7.0) is the most important factor to explain difference of Ni bioavailability in the soils. The remaining variation is caused by other differences in soil type. Soil organic matter binds Ni much stronger than clay silicates and iron (hydr)-oxides within the acidic pH range(Weng et al., 2004)PbSurface and subsurface soil samples collected from typical tea gardens in Zhejiang, ChinaNone17Tea leave concentrationBioavailable Pb = 0.2345 (10-pH) + 0.5722 OM r = 0.78, p < 0.001PBP = 0.1012 (10-pH) + 0.5696 OM r = 0.67, p < 0.001(Jin et al., 2005)Pb21 temperate soils from uncontaminated sites in the USArtificially spiked21Dry matter growth and tissue concentration of lettuce (Lactuca sativa var. Paris Island Cos)log tissue Pb = -0.07 pH - 0.36 OC - 0.06FEAL - 0.44 CEC r2 = 0.67, p < 0.001(Dayton et al., 2006)As, Cd, Pb, Zn5 soils in the USArtificially spiked5Tissue contaminant concentration of Alfalfa (Medicago sativa L.), perennial ryegrass (Lolium perenne L.), and Japanese millet (Echinochloa crusgalliL.)As TC = 1.71 - 0.496 logFeOX n = 14, radj2 = 0.469Cd TC = 4.14 - 1.17 logOC - 0.787 logClay 0.357pH n = 13, radj2 = 0.705Pb TC = 0.702 - 0.241 log CEC n = 13, radj2 = 0.717Zn TC = 4.74 - 1.64 logOC - 0.908 logClay- 0.403pH n = 14, radj2 = 0.677(Anderson & Basta, 2009) Naturally uncontaminatedTable 2. Selected relevant key literature using chemical extraction method to predict phytoaccumulation/phytoavailability.ElementsSoil SamplesContamination SourceNumber of Soils or Study SitesExtraction MethodComparative MethodReferencesCd3 topsoil samples typical in New ZealandNone 30.05 M Ca(NO3)2, 1 M NH4NO3, 0.01 M CaCl2, 0.05 M CaCl2, 1 M NH4OAc, 1 M NH4Cl, 0.04 M EDTA, and 0.05 M AAAc-EDTAAbove ground parts of wheat (Triticum aestivum L. Monad.), white clover (Trifolium repens L. Huia.), lettuce (Lactuca sativa L. Buttercrunch.), carrot (Daucus carota L. Space Saver.), and ryegrass (Lolium perenne L. Nui.), and carrot roots Cd content(Gray et al., 1999)Cd11 selected typical soil cereal growing in South AustraliaNone110.01 M CaCl2, 0.05 M CaCl2,0.1 M Na2EDTA, 0.005 M DTPA-TEA, 1 M NH4NO3, 0.02 M AAAc-EDTA, and 1 M NH4ClMeasuring Cd concentration in the stem and leaves of durum wheat (Triticum aestivum L. var. Excalibur)(Krishnamurti et al., 2000)Cu, Zn12 urban surface soils within the city of Montreal and 1 forest soil from the Morgan Aroretum in CanadaNaturally contaminated130.1 M HCl, 0.01 M EDTA, 1.0 M NaAc, 0.005 M DTPA, H2O, HNO3/HClO4, AEM-DTPA, AEM-EDTA, electrochemical analysis, dilute salt extraction Measuring metal concentrations in lettuce (Lactuca sativa) leaves(Tambasco et al., 2000)Pb, AsA mixed apple orchard from historical use of leadarsenate insecticide in WA, USNaturally contaminated1HClc, EPA 3050, Mehlich 3,0.5 M NaHCO3,TCLPAssessing tree (Malus domestica Borkh.) growth, measuring leave and fruit concentration(Peryea, 2002)Pb, Zn, Cu, Cd3 top soil/sediment from metal-contaminated wetlands close to mine sites in ChinaNaturally contaminated 3HCl/HClO4, 0.005 M DTPA, 0.1 M TEAMeasuring abovegroundand underground tissue concentrations of 12 emergent-rooted wetland plants(Deng et al., 2004)Cu30 soils were collected from diverse contaminatedsites in the UK, Chile and ChinaNaturally contaminated and artificially spiked301 M NH4NO3, 0.05 M EDTA, free Cu2+ activity, DGTMeasuring shoot and root concentration of Elsholtzia splendens and Silene vulgaris(Song et al, 2004)Cd, Cr, Cu, Ni, Pb, and Zn7 topsoil sampling from dredged sediment disposal sites in BelgiumNaturally contaminated7H2O, 0.01 M CaCl2, 1 M NH4OAc, NH4OAc-EDTA, CaCl2-TEA-DTPA Measuring bark, leaves, roots, and wood concentration of Salix viminalis Orm(Meers et al, 2005)Cu, Cd, Pb, ZnSurface acid soils from different tea plantations in Southeastern ChinaNatural soil320.01 M CaCl2, Mehlich 1, DTPA-TEA, 1 M NH4OAc, Mehlich 3Measuring the contents of metals in tea plant (Camellia sinensis) leaves (Zhang et al., 2006)Cd, Cu, Ni, Pb, ZnDredged sediment, agricultural, polluted industrial, commercial clay quarry in BelgiumNaturally uncontaminated or contaminated210.01 M CaCl2, 0.1 M NaNO3, 1 M NH4NO3, 1 M NH4OAc, 1 M MgCl2, 0.11 M HAc, 0.5 M HNO3, 0.1 M HCl, DTPA-TEA-CaCl2, EDTA-NH4OAc and aqua regiaShoot accumulation of metals by the test plant Phaseolus vulgaris(Meers et al., 2007)Fe, Mn, Cu, Zn, AsAcidified contaminated soils from the Aznalcollar spill-affected area in SpainNaturally uncontaminated or contaminated9AB-DTPA, 0.01 M CaCl2, 0.1 M NaNO3, BCR, 0.1 M (NH4)2SO4 and rhizoMeasuring the uptake by white lupin (Lupinus albus L.)(Vzquz et al., 2008)Cd, Pb, Cu, ZnPaddy soils contaminated with Pb-Zn mine tailings in Southeastern ChinaNaturally contaminated530.01 M CaCl2, Mehlich 1, DTPA-TEA, 1 M NH4OAc, Mehlich 3, EDTAMeasuring metal concentrations in the grain and stalk of rice plants (Oryza sativa L.)(Zhang et al., 2010)Ni, Cu, Cd, Pb, As, Se, CoSurface medium-textured mineral soil near three smelters in CanadaNaturally elevated contamination60.01M Sr(NO3)2, H2O, 0.01 M CaCl2, 0.1 M NaNO3, 1.0 M NH4NO3, 0.1 M LiNO3, 1.0 M MgCl2, 0.11 M HAc, 1.0 M NH4OAc, 0.05 M NH4-EDTA, pore waterMeasuring shoot concentration of indigenous grass Deschampsia L.(Abedin et al., 2012)AsSurface paddy soil in abandoned mines in KoreaNaturally contaminated30H2O, 0.01 M Ca(NO3)2, 0.1 M HCl, 0.2 M C6H8O7,0.43 M HNO3, 0.43 M HAc, 0.5 M KH2PO4, 1 M HCl, and 1 M NH4NO3Determining As contents in polished rice(Go et al., 2014) Naturally uncontaminatedCd, Cr, Cu, Ni, Pb, and Zn7 topsoil sampling from dredged sediment disposal sites in BelgiumNaturally contaminated7H2O, 0.01 M CaCl2, 1 M NH4OAc, NH4OAc-EDTA, CaCl2-TEA-DTPA Measuring bark, leaves, roots, and wood concentration of Salix viminalis Orm(Meers et al, 2005)Cu, Cd, Pb, ZnSurface acid soils from different tea plantations in Southeastern ChinaNatural soil320.01 M CaCl2, Mehlich 1, DTPA-TEA, 1 M NH4OAc, Mehlich 3Measuring the contents of metals in tea plant (Camellia sinensis) leaves (Zhang et al., 2006)Cd, Cu, Ni, Pb, ZnDredged sediment, agricultural, polluted industrial, commercial clay quarry in BelgiumNaturally uncontaminated or contaminated210.01 M CaCl2, 0.1 M NaNO3, 1 M NH4NO3, 1 M NH4OAc, 1 M MgCl2, 0.11 M HAc, 0.5 M HNO3, 0.1 M HCl, DTPA-TEA-CaCl2, EDTA-NH4OAc and aqua regiaShoot accumulation of metals by the test plant Phaseolus vulgaris(Meers et al., 2007)Fe, Mn, Cu, Zn, AsAcidified contaminated soils from the Aznalcollar spill-affected area in SpainNaturally uncontaminated or contaminated9AB-DTPA, 0.01 M CaCl2, 0.1 M NaNO3, BCR, 0.1 M (NH4)2SO4 and rhizoMeasuring the uptake by white lupin (Lupinus albus L.)(Vzquz et al., 2008)Cd, Pb, Cu, ZnPaddy soils contaminated with Pb-Zn mine tailings in Southeastern ChinaNaturally contaminated530.01 M CaCl2, Mehlich 1, DTPA-TEA, 1 M NH4OAc, Mehlich 3, EDTAMeasuring metal concentrations in the grain and stalk of rice plants (Oryza sativa L.)(Zhang et al., 2010)Ni, Cu, Cd, Pb, As, Se, CoSurface medium-textured mineral soil near three smelters in CanadaNaturally elevated contamination60.01M Sr(NO3)2, H2O, 0.01 M CaCl2, 0.1 M NaNO3, 1.0 M NH4NO3, 0.1 M LiNO3, 1.0 M MgCl2, 0.11 M HAc, 1.0 M NH4OAc, 0.05 M NH4-EDTA, pore waterMeasuring shoot concentration of indigenous grass Deschampsia L.(Abedin et al., 2012)AsSurface paddy soil in abandoned mines in KoreaNaturally contaminated30H2O, 0.01 M Ca(NO3)2, 0.1 M HCl, 0.2 M C6H8O7,0.43 M HNO3, 0.43 M HAc, 0.5 M KH2PO4, 1 M HCl, and 1 M NH4NO3Determining As contents in polished rice(Go et al., 2014) Naturally uncontaminatedTable 3. Correlation results of Cd for using chemical extraction method to predict phytoaccumulation/phytoavailability from studies listed in Table 2.Cd0.05 M Ca(NO3)21 M NH4NO30.01 M CaCl20.05 M CaCl21 M NH4Ac1 M NH4Cl0.04 M EDTA0.05 M AAAc-EDTA0.1 M Na2EDTA0.005 M DTPA-TEA0.02 M AAAC-EDTA,0.005 M DTPAH2ONH4Ac-EDTACaCl2-TEA-DTPAMehlich 1Mehlich 30.1 M NaNO31 M MgCl20.11 M HAc0.5 M HNO30.1 M HCl(Gray et al., 1999)Wheat r0.43 ns0.58 ns0.48 ns0.53 ns0.49 ns0.44 ns0.02 ns-0.25 ns--------------Clover r0.54 ns0.41 ns0.41 ns0.43 ns0.55 ns0.46 ns0.75*0.66 nsLettuce r0.68 *0.52 ns0.49 ns0.69*0.79*0.72*0.75*0.57 nsCarrot r*0.52 ns0.46 ns0.65 ns0.76*0.70*0.83**0.65 nsRyegrass r0.77*0.660.560.73*0.80**0.69*0.63 ns0.40 ns(Krishnamurti et al., 2000) r2-0.706***0.0510.581**-0.862***--0.433*0.640**0.08-----------(Deng et al., 2004)-----------a----------(Meers et al, 2005)Bark r2----0.530.58--------0.310.51--------Leaf r2(Zhang et al., 2006) Old leaf r--0.912***0.956***-0.885***0.914***----0.876***0.936***-----0.058-0.0080.489**0.423*-----Mature leaf r(Meers et al., 2007)Primary leaves-0.83**0.84**0.73**0.85**-0.350.35--------0.140.09---0.82**0.82**0.210.200.460.380.130.080.220.12Total shoot(Zhang et al., 2010)Grain r--0.832**0.806**-0.848**0.935**-0.363**0.426**--0.618**0.586**-----0.376**0.396**0.428**0.406**-----Stalk r(Abedin et al., 2012) r-0.38**0.08-0.17-------0.50***0.13---0.34*0.050.13--