In vitro and in vivo approaches for the measurement of oral bioavailability of lead (Pb) in contaminated soils: A review (original) (raw)

Lead bioavailability as influenced by its sources, speciation and soil properties

2019

Lead has been of particular concern as a neurotoxin since the 1970s due to its permanent adverse effects on human health. People can be exposed to Pb by ingestion (either through accidental oral ingestion or through food or drinking), inhalation (e.g. fine Pb particles in dust) and dermal uptake. Ingestion of Pb contaminated soils poses a significant risk to humans, especially children and babies due to their behaviors including crawling and hand-to-mouth activities, fast metabolic rates and rapidly developing neuronal systems. Thus, determining the bioavailability of Pb (Pb-BA) in soils is critical in human health risk assessment. However, it remains a serious challenge due to measurement uncertainties and the lack of information on the influences of sources of Pb contamination, Pb speciation and soil properties to Pb-BA. Consequently, this thesis focuses on the following issues: 1) validation of a reliable model to measure Pb bioaccessibility (Pb-BAc) and minimization of associate...

The effects of lead sources on oral bioaccessibility in soil and implications for contaminated land risk management

Environmental pollution (Barking, Essex : 1987), 2015

Lead (Pb) is a non-threshold toxin capable of inducing toxic effects at any blood level but availability of soil screening criteria for assessing potential health risks is limited. The oral bioaccessibility of Pb in 163 soil samples was attributed to sources through solubility estimation and domain identification. Samples were extracted following the Unified BARGE Method. Urban, mineralisation, peat and granite domains accounted for elevated Pb concentrations compared to rural samples. High Pb solubility explained moderate-high gastric (G) bioaccessible fractions throughout the study area. Higher maximum G concentrations were measured in urban (97.6 mg kg(-1)) and mineralisation (199.8 mg kg(-1)) domains. Higher average G concentrations occurred in mineralisation (36.4 mg kg(-1)) and granite (36.0 mg kg(-1)) domains. Findings suggest diffuse anthropogenic and widespread geogenic contamination could be capable of presenting health risks, having implications for land management decisi...

Using soil properties to predict in vivo bioavailability of lead in soils

RB of Pb in swine dosed with Pb spiked soils ranged from 30 ± 9% to 83 ± 7%. K d of Pb in soils ranged from 21 to 234 L/kg showing widely different binding. A strongly significant (R 2 = 0.94) exponential relationship exists between RB and K d. This model can help predict potentially bioavailable Pb in contaminated soils. a b s t r a c t Soil plays a significant role in controlling the potential bioavailability of contaminants in the environment. In this study, eleven soils were used to investigate the relationship between soil properties and relative bioavailability (RB) of lead (Pb). To minimise the effect of source of Pb on in vivo bioavailability, uncontaminated study soils were spiked with 1500 mg Pb/kg soil and aged for 10–12 months prior to investigating the relationships between soil properties and in vivo RB of Pb using swine model. The biological responses to oral administration of Pb in aqueous phase or as spiked soils were compared by applying a two-compartment pharmacokinetic model to blood Pb concentration. The study revealed that RB of Pb from aged soils ranged from 30 ± 9% to 83 ± 7%. The very different RB of Pb in these soils was attributed to variations in the soils' physico-chemical properties. This was established using sorption studies showing: firstly, Freundlich partition coefficients that ranged from 21 to 234; and secondly, a strongly significant (R 2 = 0.94, P < 0.001) exponential relationship between RB and Freundlich partition coefficient (K d). This simple exponential model can be used to predict relative bioavailability of Pb in contaminated soils. To the best of our knowledge, this is the first such model derived using sorption partition coefficient to predict the relative bioavailability of Pb.