Remediation of heavy metal contaminated soils remains a global challenge. Here, low-molecular-weight organic acids were used to extract Cu and Zn from polluted soils, and the extracted heavy metals were subsequently adsorbed by activated carbon electrodes. The electrochemical adsorption mechanism as well as the influence of pH, organic acid type and voltage were investigated, and the soil remediation effect was further evaluated by the cultivation of rape. After extraction by citrate at initial pH 8.3 and electrochemical adsorption at 0.9 V for 7 d, the concentrations of total and bioavailable Cu in soils decreased from 1090 to 281 to 391 and 52 mg kg⁻¹, and those of Zn decreased from 262 to 39 to 208 and 30 mg kg⁻¹, respectively. Cu and Zn ions were mainly electrochemically adsorbed on the carbon cathode and anode, respectively, resulting in decreases of their concentrations to below 1 mg L⁻¹ in the leachate. The presence of organic acids improved the remediation performance in the order of citrate > oxalate > acetate. The decrease in the initial pH of citrate solution enhanced the removal rate of Zn, while seemed to have no effect on that of Cu. The removal capacity for heavy metals decreased with decreasing cell voltage from 0.9 to 0.3 V. In the rape cultivation experiment, the Cu and Zn contents in shoot and root were decreased by more than 50%, validating the soil remediation effect. The present work proposes a facile method for heavy metal removal from contaminated soils.

Exposure to particulate matters (PM) is recognized as an important risk factor for cardiovascular disease. A change in cardiac autonomic function is one postulated mechanism leading to PM related cardiovascular events. This study therefore evaluated the associations of short-term exposure to PM and heart rate variability (HRV) parameters, which can reflect the cardiac autonomic function.Four electronic databases were searched for controlled studies of rodents published prior to December 2018. A systematic review and meta-analysis was conducted. Effect sizes were calculated for five main HRV parameters, including standard deviation of normal-to-normal intervals (SDNN), square root of mean squared differences between successive normal-to-normal intervals (rMSSD), low frequency (LF), high frequency (HF), and the ratio of LF and HF (LF/HF).The review included 23 studies with 401 animals. Short-term exposure to PM by instillation yielded statistically significant effects on SDNN (Standardized Mean Difference [SMD] = −1.11, 95% Confidence Intervals [CI] = −2.22 to −0.01, P = 0.05), LF (SMD = −1.19, 95% CI = −1.99 to −0.40, P = 0.003) and LF/HF (SMD = −1.05, 95% CI = −2.03 to −0.07, P = 0.04). Short-term exposure to PM by inhalation only yielded statistically significant effect on LF/HF (SMD = −0.83, 95% CI = −1.39 to −0.27, P = 0.004). There was no evidence that animal model and exposure frequency influenced the relationship of PM and HRV.Short-term exposure to PM can decrease HRV of rodents, affecting cardiac autonomic function. Exposure methods can influence the relationships of PM and HRV parameters. Further studies should focus on the effects of long-term PM exposure, on human beings, and potential influential factors of PM-HRV associations.

Due to the increase of the human population and the rapid industrial growth in the past few decades, air quality monitoring is essential to assess the pollutant levels of an area. However, monitoring air quality in a high-density area like Sunway City, Selangor, Malaysia is challenging due to the limitation of the local monitoring network. To establish a comprehensive data for air pollution in Sunway City, a mobile monitoring campaign was employed around the city area with a duration of approximately 6 months, from September 2018 to March 2019. Measurements of air pollutants such as carbon dioxide (CO₂) and nitrogen dioxide (NO₂) were performed by using mobile air pollution sensors facilitated with a GPS device. In order to acquire a more in-depth understanding on traffic-related air pollution, the measurement period was divided into two different time blocks, which were morning hours (8 a.m.–12 p.m.) and afternoon hours (3 p.m.–7 p.m.). The data set was analysed by splitting Sunway City into different zones and routes to differentiate the conditions of each region. Meteorological variables such as ambient temperature, relative humidity, and wind speed were studied in line with the pollutant concentrations. The air quality in Sunway City was then compared with various air quality standards such as Malaysian Air Quality Standards and World Health Organisation (WHO) guidelines to understand the risk of exposure to air pollution by the residence in Sunway City.

To improve catalytic performance and stability of Ag nanoparticles (Ag NPs), a facile ultrasonication-assisted chemical reduction method was developed to fabricate reduced graphene oxide (rGO) aerogels loaded with 1–3 nm Ag NPs under the normal temperature and pressure. The ultrasonication facilitated the dispersion of Ag(I) in the form of silver ammonia and anchored onto GO nanosheets. Ag(I) and GO were simultaneously reduced to Ag(0) immobilizing onto 3D rGO hydrogels within the heterogeneous liquid phase, and ultimately formed 3D rGO-Ag NPs aerogels. The 3D rGO-Ag NPs aerogels displayed superb catalytic performance for the reduction of nitrobenzene (NB), 1,3-dinitrobenzene (DNB) and 4-nitrophenol (NP) into aniline, 1,3-diaminobenzene and 4-aminophenol, respectively. The individual reduction rate Kobs for NB, DNB and NP were 0.168 h−1, 0.109 h−1 and 0.092 h−1, which were much higher than those of other Ag NPs-based materials. Moreover, the immobilization of 1–3 nm Ag NPs in 3D rGO-Ag NPs was stable during the whole reduction reaction without aggregation and leaching. The high stability of Ag NPs in 3D rGO-Ag NPs and superb performance on catalytic reduction of nitroaromatic compounds (NACs) could be concluded into ultrasonication influence in the preparation procedure and synergistic effect of Ag NPs and 3D rGO in the catalytic reduction process. The simple ultrasonication-assisted chemical reduction approach provided a scaled-up application prospect in catalytic reduction of NACs by metal nanoparticle catalysts.

Global concern exists regarding human exposure to organic pollutants derived from public open spaces and indoor dust. This study has evaluated the occurrence of 18 polycyclic aromatic hydrocarbons (PAHs), 11 organophosphorus flame retardants (OPFRs) and bisphenol A (BPA). To achieve this, a new simple, efficient and fast multi-residue analytical method based on a fully automated pressurised liquid extraction (PLE) and subsequent quantification by gas chromatography coupled to electron ionization-mass spectrometry (GC-EI-MS) in selected ion monitoring (SIM) mode was developed. The developed method was applied to indoor dust (12 sampling households) and soil derived from two public open spaces (POSs). Among all compounds studied, PAHs were the most ubiquitous contaminants detected in POS soils and indoor dust although some OPFRs and BPA were detected in lower concentrations. An assessment of the incremental lifetime cancer risk (ILCR) was done and indicated a high potential cancer risk from the POS sites and some of the indoor dust sampled sites. However, key variables, such as the actual exposure duration, frequency of contact and indoor cleaning protocols will significantly reduce the potential risk. Finally, the ingestion of soils and indoor dust contaminated with OPFRs and BPA was investigated and noted in almost all cases to be below the USEPA reference doses.

The seasonal variation and distribution among different matrices of endocrine-disrupting chemicals (EDCs) were investigated in the eutrophic water ecosystem of the Pearl River Delta, Guangdong, China. The chlorophyll a (Chl a) levels were generally higher in summer than in spring; however, the concentrations of 4-tert-octylphenol (OP), 4-nonylphenol (NP), and bisphenol A (BPA) in surface water were generally higher in spring (oligotrophic) than in summer (eutrophic). The levels of EDCs in SPM were lower in spring than in summer, a pattern seen in the seasonal variation of Chl a and particulate organic carbon (POC). The seasonal variations of EDCs in water bodies with different levels of eutrophication were analyzed in several dimensions including sediment, POC, algae and fish bile. The log Kₒc for SPM/water was higher in summer than in spring. The log Kₒc values for NP, OP, and BPA exhibited the following trends between matrices: colloid/water > sediment/water > SPM/water > algae/water, colloid/water > sediment/water > algae/water > SPM/water, and colloid/water > algae/water > sediment/water > SPM/water. The EDCs levels were different in fish tissues with the order bile > liver > muscle, with the concentrations being an order of magnitude higher in bile than in liver and an order of magnitude higher in liver than in muscle. The sequence of the bioconcentration factor (log BCF) for bile/water and liver/water was NP < OP < BPA in eutrophic conditions, but NP > OP > BPA in oligotrophic conditions. The order in eutrophic conditions was the same as the log BCF and log Kₒc for algae/water, indicating that the accumulation of EDCs in water bodies could be affected by algae, which could be one of the reasons of the seasonal variation of EDCs in water.

Particulate matter (PM) emission is one of the leading environmental pollution issues associated with the coal mining industry. Before any control techniques can be employed, however, an accurate prediction of PM concentration is desired. Towards this end, this work aimed to provide an accurate estimation of PM concentration using a hybrid machine-learning technique. The proposed predictive model was based on the hybridazation of random forest (RF) model particle swarm optimization (PSO) for estimating PM concentration. The main objective of hybridazing the PSO was to tune the hyper-parameters of the RF model. The hybrid method was applied to PM data collected from an open-cut coal mine in northern China, the Haerwusu Coal Mine. The inputs selected were wind direction, wind speed, temperature, humidity, noise level and PM concentration at 5 min before. The outputs selected were the current concentration of PM₂.₅ (particles with an aerodynamic diameter smaller than 2.5 μm), PM₁₀ (particles with an aerodynamic diameter smaller than 10 μm) and total suspended particulate (TSP). A detailed procedure for the implementation of the RF_PSO was presented and the predictive performance was analyzed. The results show that the RF_PSO could estimate PM concentration with a high degree of accuracy. The Pearson correlation coefficients among the average estimated and measured PM data were 0.91, 0.84 and 0.86 for the PM₂.₅, PM₁₀ and TSP datasets, respectively. The relative importance analysis shows that the current PM concentration was mainly influenced by PM concentration at 5 min before, followed by humidity > temperature ≈ noise level > wind speed > wind direction. This study presents an efficient and accurate way to estimate PM concentration, which is fundamental to the assessment of the atmospheric quality risks emanating from open-cut mining and the design of dust removal techniques.

Rapid accumulation of aerosol nitrate (NO3−) contributes to haze pollution; however, studies quantifying NO3− formation mechanisms remain scarce. To explore aerosol nitrate formation pathways, total suspended particulate (TSP) samples were collected in Beijing during the spring of 2013, and the concentration of NO3− and δ¹⁸O- NO3− value were analyzed. The NO3− concentrations on polluted days (PD) were higher than those on non-polluted days (NPD). Furthermore, higher δ¹⁸O- NO3− values were observed on PD (86.8 ± 8.1‰) as compared with NPD (73.7 ± 11.0‰) suggest that more nitrate was produced by pathways with relative high δ¹⁸O–HNO₃ values during PD. Based on the calculated δ¹⁸O–HNO₃ values from different formation pathways and the observed δ¹⁸O- NO3− values, the possible fractional contributions of HNO₃ formed via various pathways to TSP NO3− were estimated using the Bayesian isotope mixing model. The δ¹⁸O- NO3− constrained calculations suggest that the pathways of N₂O₅ + H₂O/Cl⁻, NO₃ + VOCs, and ClNO₃ + H₂O possibly contributed 53%–89% to nitrate production during PD. During NPD, the NO₂ + OH pathway produced 37%–69% of the NO3−. Using the δ¹⁸O- NO3− value combined with the isotope mixing model is a promising approach for exploring NO3− formation pathways.

Invasive plants readily invade metal-contaminated areas. The hyperaccumulation of toxic heavy metals is not an uncommon feature among plant species. Although several hypotheses were proposed to explain this phenomenon, it is currently unclear how hyperaccumulation may benefit plants. The invasive Crofton weed (Ageratina adenophora) is a known hyperaccumulator of chromium and lead. We previously found that the species can also hyperaccumulate cadmium. The role of phytoaccumulation in defense to pathogen attack is unclear. We inoculated A. adenophora plants with a common generalist pathogen (Rhizoctonia solani) to test its resistance under cadmium treatment. We found evidence that cadmium hyperaccumulation reduced pathogen infection in A. adenophora. Our findings indicate elemental defense is highly cost efficient for hyperaccumulators inhabiting metal-contaminated sites, where plants were only modestly affected by cadmium. The reduction in pathogen damage conferred by cadmium was relatively high, particularly under lower cadmium levels. However, the benefits at higher levels may be capped. Elemental defense may be a key mechanism for plant invasion into polluted sites, especially in regions with widespread industrial activity. Our study highlights the importance of testing different metal concentrations when testing plant resistance and the importance of considering enemy attack when selecting plants for phytoremediation.

High levels of air pollutants in Vietnam, especially particulate matters including PM₂.₅, can be important risk factors for respiratory diseases among children of the country. However, few studies on the effects of ambient air pollution on human health have been conducted in Vietnam so far. The aim of this study is to examine the association between PM₂.₅ and hospital admission due to acute lower respiratory infection (ALRI) among children aged < 5 years old in Ho Chi Minh city, the largest city of Vietnam. Data relating PM₂.₅ and hospital admission were collected from February 2016–December 2017 and a time series regression analysis was performed to examine the relationship between PM₂.₅ and hospital admission including the delayed effect up to three days prior to the admission. We found that each 10 μg/m³ increase in PM₂.₅ was associated with an increase of 3.51 (95%CI: 0.96–6.12) risk of ALRI admission among children. According to the analysis, male children are more sensitive to exposure to PM₂.₅ than females, while children exposed to PM₂.₅ are more likely to be infected with acute bronchiolitis than with pneumonia. The study demonstrated that young children in HCMC are at increased risk of ALRI admissions due to the high level of PM₂.₅ concentration in the city's ambient air.