Heavy metals deposited on urban road surfaces can be washed-off by stormwater runoff, undermining stormwater reuse safety due to their high toxicity to ecological and human health. Heavy metals on urban road surfaces come from diverse sources and tracking these sources is essential to effectively manage stormwater and hence its reuse safety. This research study developed an innovative approach to tracking sources of heavy metals using data collected in Shenzhen, China. This approach developed was based on a "flag element ratio" theory, where each source generally corresponds to a specific ratio of targeted pollutants to the flag element. It is noted that Cr, Cu, Pb, Ni, and Zn on urban roads were 19.05 mg/kg to 152.01 mg/kg, 25.66 mg/kg to 310.75 mg/kg, 15.61 mg/kg to 220.35 mg/kg, 10.65 mg/kg to 100.28 mg/kg, and 138.14 mg/kg to 1047.05 mg/kg, respectively. Gasoline emission was the main source for Cr, Ni and Pb, while braking wear and tyre wear were the major sources of Cu and Zn, respectively. Furthermore, the rankings of sources of each heavy metal in terms of their contributions were obtained by using this approach. Vehicle exhaust was found as the main contributor for all the heavy metals on urban road surfaces. This highlighted that vehicle exhaust should be seriously considered in terms of controlling heavy metal pollution on urban road surfaces and hence resulting urban road stormwater runoff.
Biosurfactant producers are crucial for incremental oil production in microbial enhanced oil recovery (MEOR) processes. The isolation of biosurfactant-producing bacteria from oil reservoirs is important because they are considered suitable for the extreme conditions of the reservoir. In this work, a novel biosurfactant-producing strain Acinetobacter junii BD was isolated from a reservoir to reduce surface tension and emulsify crude oil. The biosurfactants produced by the strain were purified and then identified via electrospray ionization-Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR-MS). The biosurfactants generated by the strain were concluded to be rhamnolipids, the dominant rhamnolipids were C26H48O9, C28H52O9, and C32H58O13. The optimal carbon source and nitrogen source for biomass and biosurfactant production were NaNO3 and soybean oil. The results showed that the content of acid components increased with the progress of crude oil biodegradation. A glass micromodel test demonstrated that the strain significantly increased oil recovery through interfacial tension reduction, wettability alteration and the mobility of microorganisms. In summary, the findings of this study indicate that the newly developed BD strain and its metabolites have great potential in MEOR.
The research is designed to explore the SEM-AVS concept as a tool to assess bioavailability and toxicity of heavy metals in heavily polluted river sediments. The value of AVS and SEM is in a high level and only a few benthic invertebrate are found. Abundance of benthic invertebrate has significant correlation with SEM/AVS (r= -0.913, p<0.01) and SEM-AVS (r= -0.725, p<0.05). The analytical results of MDS (Non-matric Multi-dimensional Scaling) analysis indicate the benthic community structures of seven among nine stations where the SigmaSEM(5)-AVS<0 are similar. The two facts indicate the SEM-AVS concept also is useful to heavily polluted river sediments.
Heavy metal pollution of urban stormwater poses potential risks to human and ecosystem health. The design of reliable pollution mitigation strategies requires reliable stormwater modelling approaches. Current modelling practices do not consider the influence of urbanisation characteristics on stormwater quality. This could undermine the accuracy of stormwater quality modelling results. This research study used a database consisting of over 1000 datasets to compare the characteristics of heavy metal build-up (one of the most important stormwater pollutant processes) on urban surfaces under the influence of anthropogenic and natural factors specific to different urban regions from China (Shenzhen) and Australia (Gold Coast), using Bayesian Networks. The outcomes show that the differences in heavy metals build-up loads between the two regions (mean value for Shenzhen - mean value for Gold Coast)/mean value for Shenzhen) were 0.45 (Al), 0.88 (Cr), 0.99 (Mn), 0.68 (Fe), 0.98 (Ni), 0.24 (Cu), 0.47 (Zn) and 0.13 (Pb), respectively. The research outcomes also confirmed that the influence of traffic on the build-up of different sized particles varies between Shenzhen and Gold Coast, and traffic plays distinct roles as a source and as a factor that drives heavy metal re-distribution. The road surface roughness was also found to influence build-up process differently between the two regions. More importantly, the assessment of inherent process uncertainty revealed that heavy metal build-up between different road sites in Shenzhen varies over a wider range than in Gold Coast. The study highlighted a clear distinction in the influence of sources and key anthropogenic factors on the variability of particle-bound heavy metals build-up between geographically different urban regions. The study outcomes provide new knowledge to enhance the accuracy of urban stormwater quality modelling.
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