Biosorption of heavy metals: Transferability between batch and column studies.

The design of an industrial water treatment system using sorption is based on laboratory column tests. To verify the applicability of a column sorption system at industrial scale, it is necessary to determine the system's breakthrough time (BT) in a laboratory setting. In a laboratory column set-up, BT is referred to as the time taken by the adsorbate to appear at column outlet for the first time. This is when the mass transfer zone (MTZ), where the equilibrium sorption occurs, reaches the end of the sorbent bed. However, such laboratory set-up requires significant resources including laboratory space, time and multiple trials, which is the opposite to the batch experimental approach that is commonly used to assess efficiency of sorbents. This study identified batch sorption parameters that can be used to determine BT for a column sorption setting for three toxic heavy metals commonly found in industrial wastewater, namely, Pb2+, Cd2+ and Cu2+. The study conducted a comprehensive evaluation of the relationships between column BT and its key influential factors, namely, equilibrium sorption capacity (qe), pseudo second-order kinetic rate constant (k2) and initial sorption rate (h). The results revealed that BT can be better estimated using h compared to qe and k2. As such, a batch experiment which is more resource efficient could be undertaken for an initial estimation of the experimental BT of a column system. Moreover, a simulation model developed to replicate column sorption could demonstrate the behaviour of the breakthrough curve, which is a key to the selection and assessment of the performance of a sorbent in an adsorbent column. The estimation errors in qe and k2 were found to influence the simulation outcomes. Hence, it is necessary to further investigate the other factors that can potentially influence sorption behaviour.

Mathematical modelling of the influence of physico-chemical properties on heavy metal adsorption by biosorbents.

Adsorption rate is a critical parameter in the design of effective biosorbent treatment systems for heavy metals removal. Though numerous studies have identified the physico-chemical properties of biosorbents that exert influence on the adsorption rate, such influence has not been mathematically defined, limiting the effective design of adsorption systems. This study quantifies the influence of biosorbent physico-chemical properties including, specific surface area, surface functional groups, pore size, pore volume and zeta potential on the adsorption rate in relation to three divalent metal cations. Mathematical equations were developed to predict the influence of physico-chemical properties on pseudo second order kinetic constant and thereby predict the adsorption rate. Tea factory waste and coconut shell biochar were mixed in different weight percentages to vary the physico-chemical properties under consideration. Four different initial metal ion concentrations were used. Relationship between pseudo second order kinetic constant at each concentration with physico-chemical properties was quantified using regression analysis. The experimental analysis revealed that among the physico-chemical properties, acidic surface functional groups had the most profound influence on sorption mechanisms. Reliability and accuracy of the predictive models were significantly improved when separate models were developed for two ranges of initial metal ion concentrations. The outcomes of this study will contribute to the effective design and optimization of biosorbent mixtures with the capacity to remove Pb2+, Cu2+ and Cd2+ in wastewater.

Quantifying the influence of surface physico-chemical properties of biosorbents on heavy metal adsorption.

Heavy metals present in industrial wastewater contribute to human and ecosystem health risk when discharged without proper treatment. Low-cost biosorbents with high metal-binding capacity are increasingly being utilized for the removal of heavy metals. Inherent physico-chemical properties of biosorbents significantly influence their adsorption capacity. Studies quantifying the influence exerted by these properties on adsorption capacity are scarce. This study quantifies the influence and relative importance of selected physico-chemical properties on the adsorption capacity of three divalent heavy metals; Cu2+, Cd2+ and Pb2+ using multivariate analysis. Twenty one biosorbent mixtures were created, systematically varying their physico-chemical properties using tea factory waste and coconut shell biochar. Their adsorption capacities were measured using batch sorption studies. The influence of physico-chemical properties on the adsorption capacity is comparable for all three metal cations. Regression models were developed to quantify the influence of physico-chemical parameters on the adsorption capacity based on regression coefficients. All models were found to have high reliability with R2 values above 0.98. Acidic surface functional groups were found to act as the key property that governs the adsorption capacity of Pb2+, Cu2+ and Cd2+. Carboxylic groups played a major role in the adsorption of Cu2+ and Pb2+, while lactonic groups were more important in providing binding sites to Cd2+. SSA failed to demonstrate a significant impact on the adsorption capacity of these three metals on its own when the biosorbent had a low surface functional group density.

Health risk assessment of heavy metals in atmospheric deposition in a congested city environment in a developing country: Kandy City, Sri Lanka.

This research study which was undertaken in a congested city environment in a developing country provides a robust approach for the assessment and management of human health risk associated with atmospheric heavy metals. The case study area was Kandy City, which is the second largest city in Sri Lanka and bears the characteristics of a typical city in the developing world such as the urban footprint, high population density and traffic congestion. Atmospheric deposition samples were collected on a weekly basis and analyzed for nine heavy metals common to urban environments, namely, Al, Cr, Mn, Fe, Ni, Cu, Zn, Cd and Pb. Health risk was assessed using hazard quotient (HQ) and hazard index (HI), while the cancer risk was evaluated based on life time daily cancer risk. Al and Fe were found to be in relatively high concentrations due to the influence of both, natural and anthropogenic sources. High Zn loads were attributed to vehicular emissions and the wide use of Zn coated building materials. Contamination factor and geo-accumulation index showed that currently, Al and Fe are at uncontaminated levels and other metals are in the range of uncontaminated to contaminated levels, but with the potential to exacerbate in the long-term. The health risk assessment showed that the influence of the three exposure pathways were in the order of ingestion > dermal contact > inhalation. The HQ and HI values for children for the nine heavy metals were higher than that for adults, indicating that children may be subjected to potentially higher health risk than adults. The study methodology and outcomes provide fundamental knowledge to regulatory authorities to determine appropriate mitigation measures in relation to HM pollution in city environments in the developing world, where to-date only very limited research has been undertaken.

Microorganisms and heavy metals associated with atmospheric deposition in a congested urban environment of a developing country: Sri Lanka.

The presence of bacteria and heavy metals in atmospheric deposition were investigated in Kandy, Sri Lanka, which is a typical city in the developing world with significant traffic congestion. Atmospheric deposition samples were analyzed for Al, Cr, Mn, Fe, Ni, Cu, Zn, Cd and Pb which are heavy metals common to urban environments. Al and Fe were found in high concentrations due to the presence of natural sources, but may also be re-suspended by vehicular traffic. Relatively high concentrations of toxic metals such as Cr and Pb in dissolved form were also found. High Zn loads can be attributed to vehicular emissions and the wide use of Zn coated roofing materials. The metal loads in wet deposition showed higher concentrations compared to dry deposition. The metal concentrations among the different sampling sites significantly differ from each other depending on the traffic conditions. Industrial activities are not significant in Kandy City. Consequently, the traffic exerts high influence on heavy metal loadings. As part of the bacterial investigations, nine species of culturable bacteria, namely; Sphingomonas sp., Pseudomonas aeruginosa, Pseudomonas monteilii, Klebsiella pneumonia, Ochrobactrum intermedium, Leclercia adecarboxylata, Exiguobacterium sp., Bacillus pumilus and Kocuria kristinae, which are opportunistic pathogens, were identified. This is the first time Pseudomonas monteilii and Ochrobactrum intermedium has been reported from a country in Asia. The culturable fraction constituted ~0.01 to 10%. Pigmented bacteria and endospore forming bacteria were copious in the atmospheric depositions due to their capability to withstand harsh environmental conditions. The presence of pathogenic bacteria and heavy metals creates potential human and ecosystem health risk.

Build-up of toxic metals on the impervious surfaces of a commercial seaport.

In the context of increasing threats to the sensitive marine ecosystem by toxic metals, this study investigated the metal build-up on impervious surfaces specific to commercial seaports. The knowledge generated from this study will contribute to managing toxic metal pollution of the marine ecosystem. The study found that inter-modal operations and main access roadway had the highest loads followed by container storage and vehicle marshalling sites, while the quay line and short term storage areas had the lowest. Additionally, it was found that Cr, Al, Pb, Cu and Zn were predominantly attached to solids, while significant amount of Cu, Pb and Zn were found as nutrient complexes. As such, treatment options based on solids retention can be effective for some metal species, while ineffective for other species. Furthermore, Cu and Zn are more likely to become bioavailable in seawater due to their strong association with nutrients. Mathematical models to replicate the metal build-up process were also developed using experimental design approach and partial least squares regression. The models for Cr and Pb were found to be reliable, while those for Al, Zn and Cu were relatively less reliable, but could be employed for preliminary investigations.

Bioaccumulation and associated dietary risks of Pb, Cd, and Zn in amaranth (Amaranthus cruentus) and jute mallow (Corchorus olitorius) grown on soil irrigated using polluted water from Asa River, Nigeria.

Dietary uptake of heavy metals through the consumption of vegetables grown on polluted soil can have serious human health implications. Thus, the study presented in this paper investigated the bioaccumulation and associated dietary risks of Pb, Zn, and Cd present in vegetables widely consumed in Nigeria, namely amaranth and jute mallow, grown on soil irrigated with polluted water from Asa River. The study found that the soil was polluted with Zn, Pb, and Cd with Pb and Cd being contributed by polluted river, while Zn was from geogenic sources. The metal concentration in amaranth and jute mallow varied in the order of Zn > Pb > Cd and Zn > Pb ≈ Cd, respectively. Jute mallow acts as an excluder plant for Pb, Cd, and Zn. Consequently, the metal concentrations in jute mallow were below the toxic threshold levels. Furthermore, non-cancer human health risk of consuming jute mallow from the study site was not significant. In contrast, the concentrations of Pb and Cd in amaranth were found to be above the recommended safe levels and to be posing human health risks. Therefore, further investigation was undertaken to identify the pathways of heavy metals to amaranth. The study found that the primary uptake pathway of Pb and Cd by amaranth is foliar route, while root uptake is the predominant pathway of Zn in amaranth.

Mathematical relationships for metal build-up on urban road surfaces based on traffic and land use characteristics.

The study investigated the influence of traffic and land use parameters on metal build-up on urban road surfaces. Mathematical relationships were developed to predict metals originating from fuel combustion and vehicle wear. The analysis undertaken found that nickel and chromium originate from exhaust emissions, lead, copper and zinc from vehicle wear, cadmium from both exhaust and wear and manganese from geogenic sources. Land use does not demonstrate a clear pattern in relation to the metal build-up process, though its inherent characteristics such as traffic activities exert influence. The equation derived for fuel related metal load has high cross-validated coefficient of determination (Q(2)) and low Standard Error of Cross-Validation (SECV) values which indicates that the model is reliable, while the equation derived for wear-related metal load has low Q(2) and high SECV values suggesting its use only in preliminary investigations. Relative Prediction Error values for both equations are considered to be well within the error limits for a complex system such as an urban road surface. These equations will be beneficial for developing reliable stormwater treatment strategies in urban areas which specifically focus on mitigation of metal pollution.

Characterisation of atmospheric deposited particles during a dust storm in urban areas of Eastern Australia.

The characteristics of dust particles deposited during the 2009 dust storm in the Gold Coast and Brisbane regions of Australia are discussed in this paper. The study outcomes provide important knowledge in relation to the potential impacts of dust storm related pollution on ecosystem health in the context that the frequency of dust storms is predicted to increase due to anthropogenic desert surface modifications and climate change impacts. The investigated dust storm contributed a large fraction of fine particles to the environment with an increased amount of total suspended solids, compared to dry deposition under ambient conditions. Although the dust storm passed over forested areas, the organic carbon content in the dust was relatively low. The primary metals present in the dust storm deposition were aluminium, iron and manganese, which are common soil minerals in Australia. The dust storm deposition did not contain significant loads of nickel, cadmium, copper and lead, which are commonly present in the urban environment. Furthermore, the comparison between the ambient and dust storm chromium and zinc loads suggested that these metals were contributed to the dust storm by local anthropogenic sources. The potential ecosystem health impacts of the 2009 dust storm include, increased fine solids deposition on ground surfaces resulting in an enhanced capacity to adsorb toxic pollutants as well as increased aluminium, iron and manganese loads. In contrast, the ecosystem health impacts related to organic carbon and other metals from dust storm atmospheric deposition are not considered to be significant.

Characterising metal build-up on urban road surfaces.

Reliable approaches for predicting pollutant build-up are essential for accurate urban stormwater quality modelling. Based on the in-depth investigation of metal build-up on residential road surfaces, this paper presents empirical models for predicting metal loads on these surfaces. The study investigated metals commonly present in the urban environment. Analysis undertaken found that the build-up process for metals primarily originating from anthropogenic (copper and zinc) and geogenic (aluminium, calcium, iron and manganese) sources were different. Chromium and nickel were below detection limits. Lead was primarily associated with geogenic sources, but also exhibited a significant relationship with anthropogenic sources. The empirical prediction models developed were validated using an independent data set and found to have relative prediction errors of 12-50%, which is generally acceptable for complex systems such as urban road surfaces. Also, the predicted values were very close to the observed values and well within 95% prediction interval.