Leaching characteristics of metals from recycled concrete aggregates (RCA) and reclaimed asphalt pavements (RAP).

Recycled concrete aggregates (RCA) and reclaimed asphalt pavements (RAP) are two construction waste products that are commonly used in the road construction industry. Besides many advantages, pollutants leaching from RCA and RAP are highlighted as the most concerning environmental issue. This study investigated metals leaching characteristics from RCA and RAP due to the variations in key influential factors of pH, dissolved organic carbon (DOC), compaction and liquid to solid ratio (L/S). The leaching tests for RCA and RAP were carried out separately and additionally, the standard leaching test was conducted as the benchmark for leaching investigations. Study outcomes revealed that the combined influences of factors are variable for RCA and RAP, while influences are also variable for individual metals. L/S ratios considerably affect the release of metals from RCA under saturated conditions, facilitating high metal concentrations in the leachate. On the other hand, acidic solutions are more favourable for leaching of metals from RAP. The influence of DOC in solution was minimal on the metal leachability. Interestingly, the increased degree of compaction with a higher density of materials presented the highest negative influence on metal leachability, suggesting that the metal leachability can significantly reduce, in particular when the RCA and RAP are used for the sub-base layers of road structure with a higher degree of compaction. However, the use of these recycled materials under field conditions should be further studied as there is an increasing concern of metal leaching from RCA and RAP with respect to recreational and drinking water thresholds.

Pattern-based assessment of the influence of rainfall characteristics on urban stormwater quality.

Urbanisation increases pollutant generation within catchments and their transport to receiving waters. Changes to rainfall patterns, particularly in the age of climate change, make pollution mitigation a challenging task. Understanding how rainfall characteristics could influence the changes to stormwater pollutant runoff is important for designing effective mitigation strategies. This study employed a pattern-based assessment of relationships between rainfall characteristics and stormwater quality in urban catchments to develop this understanding. The research outcomes showed that rainfall events could be distinctly clustered based on intensity and duration, and each cluster of events would produce different stormwater quality responses. The high-intensity bursts occurring in the latter part of long-duration events were found to produce uniform and low concentrations of suspended solids. One the contrary, high intensity bursts occurring in the initial part of short-duration events triggered the first-flush effect, thus producing high concentrations of suspended solids. Furthermore, the first-flush effect was likely to present when the high intensity bursts occurred in the mid portion of rainfall events and produced variable concentrations of suspended solids. It was also found that the average rainfall intensity plays a key role in mobilising and transporting pollutants accumulated on urban surfaces.

Inherent and external factors influencing the distribution of PAHs, hydroxy-PAHs, carbonyl-PAHs and nitro-PAHs in urban road dust.

The distribution and fate of hazardous polycyclic aromatic hydrocarbons (PAHs) and their associated transformed PAHs products (TPPs) notably carbonyl-PAHs (CPAHs), hydroxy-PAHs (HoPAHs), and nitro-PAHs (NPAHs) on urban road surfaces are influenced by diverse factors to varying extent. The pollutants are eventually transported to urban receiving waters via stormwater runoff posing risks to human and ecosystem health. In order to formulate an effective mitigation strategy, it is essential to comprehensively examine the role of both inherent and external factors in the distribution and fate of these hazardous pollutants, and thus, the need for this study. The research study showed that commercial land use has the highest cumulative concentration of PAHs and TPPs. Antecedent dry days (ADDs) has an inverse influence on the distribution of the total concentrations of low-molecular weight PAHs (LMW-PAHs), PAHs, and (PAHs + TPPs) irrespective of the type of land use, whilst there was no major influence on the total concentrations of high molecular weight PAHs (HMW-PAHs), and TPPs. The high volatility of LMW-PAHs compared to HMW-PAHs is considered to account for the decreasing concentration of LMW-PAH with increasing ADD. Particle size range has significant inverse influence on the cumulative concentration of pollutants across all land uses, since smaller particles are characteristically associated with larger surface area leading to the higher sorption of pollutants. Multivariate analysis of the influential factors indicated that two particle size ranges (0.45-150 µm and 150-425 µm) constitute the major influential factors on the distribution and fate of PAHs and TPPs in urban road dust. Greater quantum of pollutants are sorbed to the 0.45-150 µm particles due to the relatively higher specific surface area (SSA), concentration of total organic carbon (TOC) and total suspended solids (TSS) concentration. Therefore, it is critical to effectively remove finer particles from road surfaces in order to reduce exposure to hazardous pollutants.

Automatic model calibration of combined hydrologic, hydraulic and stormwater quality models using approximate Bayesian computation.

A range of automatic model calibration techniques are used in water engineering practice. However, use of these techniques can be problematic due to the requirement of evaluating the likelihood function. This paper presents an innovative approach for overcoming this issue using a calibration framework developed based on Approximate Bayesian Computation (ABC) technique. Use of ABC in automatic model calibration was undertaken for a combined urban hydrologic, hydraulic and stormwater quality model. The simulated runoff hydrograph and total suspended solid (TSS) pollutograph were compared with observed data for multiple events from three different catchments, and found to be within 95% confidence intervals of the simulated results. The R programmed model was validated by comparing simulated flow with similar commercially available modeling software, MIKE URBAN output determined using mean value of parameters obtained from the calibration exercise, and performed well by satisfying statistical criteria's such as coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME). The developed framework is useful for automatic calibration and uncertainty estimation using ABC approach in complex hydrologic, hydraulic and stormwater quality models with multi-input-output systems.

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.

Adsorption-desorption behavior of heavy metals in aquatic environments: Influence of sediment, water and metal ionic properties.

Limited knowledge of the combined effects of water and sediment properties and metal ionic characteristics on the solid-liquid partitioning of heavy metals constrains the effective management of urban waterways. This study investigated the synergistic influence of key water, sediment and ionic properties on the adsorption-desorption behavior of weakly-bound heavy metals. Field study results indicated that clay minerals are unlikely to adsorb heavy metals in the weakly-bound fraction of sediments (e.g., r = -0.37, kaolinite vs. Cd), whilst dissociation of metal-phosphates can increase metal solubility (e.g., r = 0.61, dissolved phosphorus vs. Zn). High salinity favors solubility of weakly-bound metals due to cation exchange (e.g., r = 0.60, conductivity vs. Cr). Dissolved organic matter does not favor metal solubility (e.g., r = -0.002, DOC vs. Pb) due to salt-induced flocculation. Laboratory study revealed that water pH and salinity dictate metal partitioning due to ionic properties of Ca2+ and H+. Selectivity for particulate phase increased in the order Cu>Pb>Ni>Zn, generally following the softness (2.89, 3.58, 2.82, 2.34, respectively) of the metal ions. Desorption followed the order Ni>Zn>Pb>Cu, which was attributed to decreased hydrolysis constant (pK1 = 9.4, 9.6, 7.8, 7.5, respectively). The study outcomes provide fundamental knowledge for understanding the mobility and potential ecotoxicological impacts of heavy metals in aquatic ecosystems.

Influence of land use class and configuration on water-sediment partitioning of heavy metals.

Influence of land use and population characteristics on solid-liquid partitioning of heavy metals in aquatic ecosystems is little understood. This study hypothesised that the partitioning of heavy metals (Cd, Cr, Cu, Ni, Pb and Zn) between water and sediments is influenced by different land use classes, their configuration patterns including patch density, Shannon's diversity index, largest patch index, and splitting index and population density. Relationships between variables were investigated from different distances to the stream network (sub-catchment and riparian scales) and considering land use patterns within individual land use classes and individual sub-catchments as a whole (class and landscape levels, respectively). The study outcomes confirmed that the influence of land use and configuration on metals partitioning is scale independent. However, population density increases metal bioavailability at the riparian scale compared to the sub-catchment scale. Agricultural lands discharge the highest fractions of dissolved metals at both spatial scales (eigenvectors = 0.409 - sub-catchment, and -0.533 - riparian, whilst metals have opposite loadings). Positive relationships between splitting index and metal partitioning confirmed that the division of anthropogenic land uses into smaller patches reduces water pollution. However, high fragmentation of forested areas increases the fraction of soluble metals. Further, high patch density and patch diversity are beneficial for controlling the solubility of some metals. Configuration metrics at the landscape level fundamentally reproduce the patterns of the largest land use type and are not effective for assessing metal partitioning. Therefore, analyses at the class level are preferred. This research investigation contributes essential knowledge to improve land use management strategies and, thereby, help safeguard urban waterways.

Water-sediment interactions and mobility of heavy metals in aquatic environments.

The adsorption-desorption behaviour of heavy metals in aquatic environments is complex and the processes are regulated by the continuous interactions between water and sediments. This study provides a quantitative understanding of the effects of nutrients and key water and sediment properties on the adsorption-desorption behaviour of heavy metals in riverine and estuarine environments. The influence levels of the environmental factors were determined as conditional regression coefficients. The research outcomes indicate that the mineralogical composition of sediments, which influence other sediment properties, such as specific surface area and cation exchange capacity, play the most important role in the adsorption and desorption of heavy metals. It was found that particulate organic matter is the most influential nutrient in heavy metals adsorption in the riverine environment, while particulate phosphorus is more important under estuarine conditions. Dissolved nutrients do not exert a significant positive effect on the release of heavy metals in the riverine area, whilst dissolved phosphorus increases the transfer of specific metals from sediments to the overlying water under estuarine conditions. Furthermore, the positive interdependencies between marine-related ions and the release of most heavy metals in the riverine and estuarine environments indicate an increase in the mobility of heavy metals as a result of cation exchange reactions.

A Bayesian approach to model the trends and variability in urban stormwater quality associated with catchment and hydrologic parameters.

Stormwater runoff pollution has become a key environmental issue in urban areas. Reliable estimation of stormwater pollutant discharge is important for implementing robust water quality management strategies. Even though significant attempts have been undertaken to develop water quality models, deterministic approaches have proven inappropriate as they do not address the variability in stormwater quality. Due to the random nature of rainfall characteristics and the differences in catchment characteristics, it is difficult to generate the runoff pollutographs to a desired level of certainty. Bayesian hierarchical modelling is an effective tool for developing complex models with a large number of sources of variability. A Bayesian model does not look for a single value of the model parameters, but rather determines a distribution of the model parameters from which all inference is drawn. This study introduces a Bayesian hierarchical linear regression model to describe a catchment specific runoff pollutograph incorporating the associated uncertainties in the model parameters. The model incorporates catchment and rainfall characteristics including the effective impervious area, time of concentration, rain duration, average rainfall intensity and the antecedent dry period as the contributors to random effects.

Dispersal and transport of microplastics in river sediments.

Rivers are viewed as major pathways of microplastic transport from terrestrial areas to marine ecosystems. However, there is paucity of knowledge on the dispersal pattern and transport of microplastics in river sediments. In this study, a three dimensional hydrodynamic and particle transport modelling framework was created to investigate the dispersal and transport processes of microplastic particles commonly present in the environment, namely, polyethylene (PE), polypropylene (PP), polyamide (PA), and polyethylene terephthalate (PET) in river sediments. The study outcomes confirmed that sedimental microplastics with lower density would have higher mobility. PE and PP are likely to be transported for a relatively longer distance, while PA and PET would likely accumulate close to source points. High water flow would transport more microplastics from source points, and high flow velocity in bottom water layer are suggested to facilitate the transport of sedimental microplastics. Considering the limited dispersal and transport, the study outcomes indicated that river sediments would act as a sink for microplastic pollutants instead of being a transport pathway. The patchiness associated with the hotspots of different plastic types is expected to provide valuable information for microplastic source tracking.

Physico-chemical properties of sediments governing the bioavailability of heavy metals in urban waterways.

Bioavailability is a critical facet of metal toxicity. Although past studies have investigated the individual role of sediment physico-chemical properties in relation to the bioavailability of heavy metals, their collective effects are little-known. Further, limited knowledge exists on the contribution of nutrients to metal bioavailability. In this study, the influence of physico-chemical properties of sediments, including total organic carbon (TOC), total phosphorus (TP), total nitrogen (TN), cation exchange capacity (CEC), specific surface area (SSA), and mineralogical composition to metal bioavailability is reported. The weak-acid extraction method was used to measure Cd, Cr, Cu, Ni, Pb and Zn as the potentially bioavailable fraction in sediments in an urban creek. The results confirmed that Cu has strong selectivity for organic matter (r = 0.814, p < 0.01). Cr bioavailability was influenced by either sediment mineralogy, nutrients, CEC or SSA. Zn, Ni and Pb showed strong affinity to mineral oxides, though their preferred binding positions were with nutrients, particularly organic matter (r = 0.794, 0.809, and 0.753, p < 0.01, respectively). The adsorption of Cd was strongly influenced by the competition with other metals and its bioavailability was weakly influenced by ion exchange (CEC: r = 0.424, p < 0.01). The study results indicate that nitrogen and phosphorus compounds can elevate metal bioavailability due to complexation reactions. Generally, the estuarine area was more favourable for the adsorption of weakly-bound metals. This is concerning as estuaries generate high biogeochemical activity and are economically important.

Source quantification and risk assessment as a foundation for risk management of metals in urban road deposited solids.

Urban road build-up solids contain toxic metals posing potential risks to human health. Management of human health risks arising from these metals is critical in urban areas. This study collected solids build-up data from 16 study sites with various land use and traffic characteristics. Source quantification was conducted using PCA/APCS receptor model. It was found that soil and asphalt wear are the largest contributors (69.43%) to risk and mainly contribute Al, Cr, Mn, Fe, Ni, Zn and Pb to build-up solids. Brake wear is the second largest contributor accounting for 17.20% and contributes Cd and Cu. Tyre wear is the third major contributor (11.38%) and it primarily contributes Ni, Zn and Cr. Mathematical equations were fitted to estimate the risk against daily traffic volume and land use fractions, and the uncertainty analysis highlighted that risk assessment should account for the variability in metal concentrations rather than a point value of concentrations at a given time and space. Based on source quantification and risk assessment, an integrated risk management model was developed to manage human health risks from toxic metals in build-up solids. This risk model provides guidance for urban planning and land use development to mitigate risk arising from urban road deposited solids.

New conceptualisation of first flush phenomena in urban catchments.

First flush is an important phenomenon commonlyused in stormwater treatment system design where only the highly concentrated initial part of the runoff hydrograph is subject to treatment. Despite the existing methods for estimating the first flush, a robust quantitative definition is difficult to find. This paper discusses a novel approach, where a new parameter is introduced to analyse the variability in the discharge of pollutants at different times throughout a runoff event and thereby enable the identification of first flush. It was found that due to variability in rainfall, the first flush runoff volume varies from event to event. Therefore, a static estimate of the first flush is not applicable for a runoff event. The Monte Carlo simulation undertaken strengthened the analysis by providing credible limits to the outcomes. Accordingly, an interval estimation was obtained in which the first flush runoff can vary, and it was found that most commonly, the first flush can exist through the initial 30%-50% of the runoff. Therefore, in order to treat the stormwater runoff with minimum risk of discharging high loads of pollutants to the receiving water environment, at least the initial 30% of the runoff should be subject to treatment. This understanding provides a fundamental basis for the design of robust stormwater treatment systems.

Influence of photolysis on source characterization and health risk of polycyclic aromatic hydrocarbons (PAHs), and carbonyl-, nitro-, hydroxy- PAHs in urban road dust.

In this study, PAHs and their transformed PAH products (TPPs) in road dust were subjected to UV driven photolysis, and then extracted using simultaneous pressurized fluid extraction, and analysed using Shimadzu Triple Quadrupole GC/MS. The results of the analysis were used to investigate the robustness and reliability of 14 existing diagnostic ratios (DRs) and two newly proposed molecular DRs that are relevant for characterizing the sources of PAHs and TPPs. The influence of photolysis on the carcinogenic health risk posed to humans by these hazardous pollutants was then assessed. The findings indicated that the DRs segregated into stable, moderately stable and non-stable classes of source characteristics under the influence of photolysis. Only two of the existing DRs, namely, benzo(a)pyrene/benzo(ghi)perylene (BaP/BghiP) and total index exhibited consistent stability to photolysis, whilst fluoranthene/(fluoranthene + pyrene) (FRT/(FRT+PYR)) showed moderate stability. The two newly proposed DRs, naphthalene/1-nitronaphthalene (NAP/NNAP) and pyrene/(1-nitropyrene + 1-hydroxypyrene) (PYR/(1NPY+HPY)) were found to be highly reliable in post-emission source characterization. The cross-plots of the most stable DRs showed that traffic emissions is the primary source of PAHs, whilst post-emission photolysis is the secondary source of nitro-PAH (NPAH) TPPs. The percent resonance energy thermodynamic stability of the PAH pollutants does not exert any direct influence on the source characteristics of the DRs. Adults are more vulnerable to potential carcinogenic risks as a result of PAH and TPPs photolysis whereas negligible risk exist for children. This study contributes to a more reliable diagnosis of PAH and TPP sources and thus, to the regulatory mitigation of these hazardous pollutants thereby, promoting enhanced protection of human health and the environment.

Catchment based estimation of pollutant event mean concentration (EMC) and implications for first flush assessment.

The Event Mean Concentration (EMC) is considered as a key analytical parameter for assessing the quality of stormwater. The conventional estimation methods to determine EMC do not necessarily address the variability associated with the hydrologic characteristics. Accordingly, this study was conducted to identify the potential hydrologic variables that can influence EMC and thereby to create a mathematical model to determine EMC using the hydrologic variables while incorporating the catchment as an influential factor. This paper introduces an innovative approach to estimate EMC of a runoff event using a stepwise multiple linear regression model. The model incorporates hydrologic variables together with their two-way interaction terms. The catchment was included in the model as a dummy variable. This allows identifying the variability of EMC between catchments. Model can reasonably predict the EMC with an overall prediction error of 0.811. The regression coefficients of the model specify that, maximum rainfall intensity is the most influential variable having a coefficient of 1.008, followed by the average intensity with a coefficient -0.586. The interaction term of rainfall depth and the antecedent dry period indicates that for a relatively small rainfall event (<5 mm), an optimum value of antecedent dry period exists that maximises the EMC. Subsequently, EMC was employed to define the first flush runoff as an alternative approach to the conventional approaches for determining the first flush. The dynamic mean concentration (DMCt), was introduced as a parameter for estimating the first flush using EMC. The maximum accumulated runoff volume such that, DMCt≥EMC was defined as the first flush runoff. It was found that residential catchments generate more intense first flush compared to catchments with totally impervious surface areas and thereby a significant pollutant load is transported within a small initial fraction of the runoff.f.

Optimized simultaneous pressurized fluid extraction and in-cell clean-up, and analysis of polycyclic aromatic hydrocarbons (PAHs), and nitro-, carbonyl-, hydroxy -PAHs in solid particles.

The development, modification and optimization of analytical methods capable of simultaneous extraction and in-cell clean-up of extracts for subsequent determination of parent PAHs and their associated transformed nitro-PAHs (NPAH), carbonyl-PAHs (CPAH) and hydroxy-PAHs (HO-PAH) products (TPPs) is essential for reducing the time and cost of analysis. The aim of this study was to modify and optimize the pressurized fluid extraction (PFE) technique capable of simultaneous extraction and in-cell clean-up of PAHs and TPPs in urban dust standard reference material and road dust for GC-MS analyses. In this study, multivariate data analysis such as factor analysis (FA), and preference ranking organisation method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive aid (GAIA) were used to assess the performance of the methods. As the key outcome of the study, an optimized selective reaction monitoring (SRM) Triple Quadrupole (TQ) electron ionization (EI)-GC/MS for measuring PAHs and TPPs without derivatization of polar HO-PAHs was developed. The limits of detection (LOD) for parent PAHs, CPAHs, NPAHs and HO-PAHs using Shimadzu TQ were 1.0-5.0 pg, 1.0-5.0 pg, 1.0-50.0 pg, and 1.0-25.0 pg, respectively. The PROMETHEE-GAIA analysis of the results showed that a combination of 3% deactivated silica gel and activated alumina (2:1) as in-cell clean-up material, and sequential PFE extraction (200 °C ASE temperature, 9 min preheat time and 3 times extraction cycle) using 100% hexane followed by hexane/DCM (1:1) is the best condition for analytes extraction from road dust. An optimized, fast and reliable GC/MS method operated solely in electron ionization (EI) mode was developed for measuring all analytes. The outcomes of this study will contribute significantly to future research on PAHs and TPPs, thereby promoting a safe and sustainable environment.

Influential factors on microplastics occurrence in river sediments.

Rivers are regarded as sinks and pathways of plastic pollutants from terrestrial environments to various other aquatic systems such as lakes and oceans. Although extensive research has been conducted in recent years on microplastic pollution in river sediments, knowledge on the relationships between potential influential factors such as catchment characteristics and sediment properties, and microplastics occurrence in river sediments, is still considered an under-researched area. This study evaluated the influence of land use, population, and sediment particle size on the presence of microplastics abundance and types. Based on a Bayesian Network modelling approach to characterise the correlations between influencing factors and microplastics occurrence, it was evident that microplastics type had a positive correlation with different land use types and population. Catchment characteristics were found to play a more important role in influencing microplastics type than microplastics concentration. A statistically significant positive relationship was observed between microplastics concentration and clay particles which suggested that the occurrence of microplastics in sediments can be impacted by the presence of clay particles.

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.

Application of multivariate data techniques in photochemical study of polycyclic aromatic hydrocarbons (PAHs) and transformed PAH products in road dust.

Road dust is a key repository for PAHs and transformed PAH products (TPPs) generated from natural and anthropogenic sources in the urban environment. Eventhough PAHs and TPPs are prone to post-emission photochemical processes, very limited studies exist on the subject for road dust. This knowledge gap is of particular concern since some of the resultant TPPs are notably more carcinogenic than their precursor PAHs. This study evaluated the role of 254 nm ultraviolet (UV) photons on the photochemistry of PAHs and TPPs in road dust. The findings show that UV irradiation had varying effects on the fate of analytes, particularly naphthalene (NAP), phenanthrene (PHE), 7, 12-dimethylbenz(a)anthracene (DMBA), 1-hydroxypyrene (HPY), 1-nitropyrene (1NPY), pyrene (PYR) and 5-nitroacenaphthene (5NAC). Photochemical relationship was identified between PYR, 1NPY and HPY, and DMBA and benzo(a)anthracene. Unlike carbonyl-PAHs, parent PAHs, nitro-PAHs and hydroxy-PAHs can originate from photolysis. Photon irradiation durations of 3, 6 and 7.5 h had the most intense influence on the photolytic process with 7.5 h as optimum. The photochemical rate at optimum irradiation duration shows an increasing trend of NAP < PHE < 1NPY < DMBA < 5NAC < HPY with respective estimates of 0.08, 0.11, 0.21, 0.22, 0.43, and 0.59 mg kg-1 hr-1. Physicochemical properties of analytes such as index of refraction and vapour pressure (in logarithmic form) had an inverse effect on photolysis. The knowledge generated is significant for the in-depth understanding of the fate of PAHs and TPPs on urban road surfaces and contributes to the greater protection of human health and the environment.

Application of quantitative structure-activity relationship (QSAR) model in comprehensive human health risk assessment of PAHs, and alkyl-, nitro-, carbonyl-, and hydroxyl-PAHs laden in urban road dust.

The carcinogenic human health risks (CHHR) posed by the exposure to PAHs and transformed PAH products (TPPs) are currently inconclusive due to the lack of toxicity equivalency factors (TEFs) for most TPPs although some of these pollutants are more potent carcinogens. The applicability of quantitative structure-activity relationship (QSAR) model in predicting TEF of PAHs and TPPs to holistically evaluate the CHHR posed by the exposure to these pollutants in road dust from Gold Coast, Australia was examined. Statistical evaluation via ten metrics shows that partial least-squares regression (PLSR1) model has more statistical power in predicting TEF than multiple linear regression (MLR) within relevant applicability domain. For instance, the predicted residual sum of squares (PRESS) and standard deviation of error of prediction (SDEP) for PLSR is closer to zero than that of MLR. The total cancer risk estimated using the QSAR model derived TEFs and original TEFs for outliers gives a more holistic incremental lifetime cancer risk in relation to children and adults. Potential cancer risk exists for adults with this approach whereas reliance on only the originally available TEFs lead to a negligible risk diagnosis. The application of QSAR model in assessing CHHR due to PAHs and TPPs exposures is very viable.