In school environments, children are constantly exposed to mixtures of airborne substances, derived from a variety of sources, both in the classroom and in the school surroundings. It is important to evaluate the hazardous properties of these mixtures, in order to conduct risk assessments of their impact on children’s health. Within this context, through the application of a maximum cumulative ratio approach, this study aimed to explore whether health risks due to indoor air mixtures are driven by a single substance or are due to cumulative exposure to various substances. This methodology requires knowledge of the concentration of substances in the air mixture, together with a health-related weighting factor (i.e. reference concentration or lowest concentration of interest), which is necessary to calculate the hazard index. Maximum cumulative ratio and hazard index values were then used to categorise the mixtures into four groups, based on their hazard potential and therefore appropriate risk management strategies. Air samples were collected from classrooms in 25 primary schools in Brisbane, Australia. Analysis was conducted based on the measured concentration of these substances in about 300 air samples. The results showed that in 92 % of the schools, indoor air mixtures belonged to the ‘low concern’ group, and therefore, they did not require any further assessment. In the remaining schools, toxicity was mainly governed by a single substance, with a very small number of schools having a multiple substance mix which required a combined risk assessment. The proposed approach enables the identification of such schools and thus aids in the efficient health risk management of pollution emissions and air quality in the school environment.

Anthyllis vulneraria was highlighted here as a Zn-hyperaccumulator for the development of a pilot phytoextraction process in the mine site of Les Avinières in the district of Saint-Laurent-Le-Minier. A. vulneraria appeared to hyperaccumulate the highest concentration of Zn in shoots with a better metal selectivity relative to Cd and Pb than the reference Zn-hyperaccumulator Noccea caerulescens. A bigger biomass production associated to a higher Zn concentration conducted A. vulneraria to the highest total zinc gain per hectare per year. As a legume, A. vulneraria was infected by rhizobia symbionts. Inoculation of A. vulneraria seeds showed a positive impact on Zn hyperaccumulation. A large-scale culture process of symbiotic rhizobia of A. vulneraria was investigated and optimized to allow large-scale inoculation process. Contaminated shoots of A. vulneraria were not considered as wastes and were recovered as Eco-Zn catalyst in particular, examples of organic synthesis, electrophilic aromatic substitution. Eco-Zn catalyst was much more efficient than conventional catalysts and allowed greener chemical processes.

Heavy metal levels (Pb and Cu) on adult mud crabs (Scylla spp.) from the East Bataan Coast were determined. Muscle tissue from each crab was processed through nitric acid digestion and analyzed using atomic absorption spectroscopy. The average concentrations in the samples were 3.37 × 10⁻³and 1.01 mg/L—both within WHO acceptable limits. These were contrasted with the levels found in sediments from catch and grow-out sites (17.9, 14.5, 37.8, and 31.3 mg/L) and were found to be significantly lower in concentration. It takes 3–8 months before adult mud crabs can be harvested from grow-out ponds, and the data suggests that the organisms, even when constantly exposed to high levels of Pb and Cu, do not bio-accumulate toxic levels of these heavy metals. Mud crabs constitute a major economic natural resource in the Philippines and in the province of Bataan. Commanding high prices due to the quality of its meat, it is also a preferred culture product due to its impressive size, rapid growth rate, and high flesh content. Mud crab culture in Bataan is primarily driven by grow-out of captured juveniles in pen or pond cultures sourced from nearby bodies of water—making them vulnerable to prolonged exposure to pollutants. The East Bataan Coast shares its waters with the polluted Manila Bay, giving rise to the concern of the quality of seafood acquired from the area.

Links between environmental chemicals and human health have emerged, but the effects on cognition were less studied. Therefore, it was aimed to study the relationships of different sets of environmental chemicals and the remembering condition in a national and population-based study in recent years. Data was retrieved from the US National Health and Nutrition Examination Surveys, 2011–2012, including demographics, blood pressure readings, serum measurements, lifestyle factors, self-reported remembering condition and urinary environmental chemical concentrations. Analyses included Chi-square test, t test and survey-weighted logistic and multi-nominal regression models. Among the elderly aged 60–80 (n = 1791), 320 (17.9 %) had difficulties in thinking or remembering. People who had difficulties in thinking or remembering had higher levels of urinary heavy metals, phthalates, pesticides and hydrocarbon concentrations but lower levels of urinary arsenic and polyfluorinated compound concentrations. During the recent past week, 146 people (8.2 %) had trouble remembering for more than three times while 619 people (35.2 %) had that for one to three times. These people had higher levels of urinary heavy metals, phthalates, pesticides and hydrocarbon concentrations but lower levels of urinary polyfluorinated compound concentrations. There were no associations with urinary bisphenols, parabens, perchlorate, nitrate or thiocyanate concentrations. This is the first time observing statistically significant risk associations of urinary heavy metals, phthalates, pesticides and hydrocarbon concentrations and the remembering condition specifically in the elderly, although the causality cannot be established. Elimination of such environmental chemicals in humans might need to be considered in future health policy and intervention programs.

Accurate measurements of PM₂.₅ concentration over time and space are especially critical for reducing adverse health outcomes. However, sparsely stationary monitoring sites considerably hinder the ability to effectively characterize observed concentrations. Utilizing data on meteorological and land-related factors, this study introduces a radial basis function (RBF) neural network method for estimating PM₂.₅ concentrations based on sparse observed inputs. The state of Texas in the USA was selected as the study area. Performance of the RBF models was evaluated by statistic indices including mean square error, mean absolute error, mean relative deviation, and the correlation coefficient. Results show that the annual PM₂.₅ concentrations estimated by the RBF models with meteorological factors and/or land-related factors were markedly closer to the observed concentrations. RBF models with combined meteorological and land-related factors achieved best performance relative to ones with either type of these factors only. It can be concluded that meteorological factors and land-related factors are useful for articulating the variation of PM₂.₅ concentration in a given study area. With these covariate factors, the RBF neural network can effectively estimate PM₂.₅ concentrations with acceptable accuracy under the condition of sparse monitoring stations. The improved accuracy of air concentration estimation would greatly benefit epidemiological and environmental studies in characterizing local air pollution and in helping reduce population exposures for areas with limited availability of air quality data.

In order to evaluate heavy metal contamination in surface waters in the Jiaozhou Bay (JZB), a typical semi-enclosed bay in the north of China, and to identify the response of heavy metal distribution to terrigenous sources and tides, the land-based discharge flux of dissolved Cu, Pb, Zn and Cd and their particulates, as well as their concentrations, were synchronously surveyed in JZB in flood season and normal season respectively. The survey results showed that the amount of dissolved Cu clearly increased from the estuaries to the offshore waters during the flood season, especially from the Dagu estuary to the mouth of JZB. The same trend was observed for Pb. The isopleths of dissolved Zn during the flood season presented a different pattern in which a clear decrease was observed from the Lianwan, Moshui and Dagu estuaries to the offshore waters. However, the particulate Cu isopleths during the flood season, which had the same pattern as those of particulate Pb, Zn and Cd, showed a clear decrease from the Dagu estuary to the mouth of JZB. The isopleths for dissolved and particulate Cu during the normal season showed a clear decrease from the northeast to the entrance of JZB, and the same trend was observed for Pb, Zn and Cd. Observations based on synchronous investigations of the fluvial fluxes of the selected metals and their average concentrations in JZB showed that these patterns were controlled by the strong external fluvial inputs, especially from the Dagu River. The diurnal change in the Cu, Pb, Zn and Cd concentrations showed a periodicity with a cycle length of approximately 12 h in JZB, which indicates the noticeable impact of the semi-diurnal tide. The weighed average concentration from freshwater inputs calculated for dissolved Cu, Pb, Zn and Cd were higher than their average concentrations in JZB. This indicated that JZB had been contaminated with these metals, whose concentrations were also higher than those found in uncontaminated waters.

Nickel pollution imposes deleterious effects on soil ecosystem. The responses of soil microorganisms to long-term nickel pollution under field conditions remain largely unknown. Here, we used high-throughput sequencing to elucidate the impacts of long-term nickel pollution on soil bacterial communities in two contrasting agricultural soils. Our results found that the soil microbial biomass carbon consistently decreased along the nickel gradients in both soils. Nickel pollution selectively favored or impeded the prevalence of several dominant bacterial guilds, in particular, Actinobacteria showed tolerance, while Acidobacteria and Planctomycetes displayed sensitivity. Despite the apparent shifts in the bacterial community composition, no clear tendency in the bacterial diversity and abundance was identified along the nickel gradients in either soil. Collectively, we provide evidence that long-term nickel pollution shifted the soil bacterial communities, resulting in the decrease of microbial biomass although the bacterial diversity was not significantly changed.

A dispersion-advection model was used to simulate the Elk river chemical spill 2014. The numerical and analytical solutions were used to predict the concentrations of 4-methylcyclohexane methanol (MCHM) at the water treatment plants located along the Elk and Kanawha rivers. The results are of similar magnitude as measured concentrations although a time-lag was found between modeled and measured plume arrival likely due to accumulation of systematic errors. Considering MCHM guidelines for drinking water, the spill represented a serious health threat through the water up taken by the treatment plant located on the Elk river and it also constituted a risk of contamination for the drinking water produced by treatment plants located on the Kanawha river.

In this study, Cu-doped ZnO nanoparticles were investigated as an efficient synthesized catalyst for photodegradation of humic substances in aqueous solution under natural sunlight irradiation. Cu-doped ZnO nanocatalyst was prepared through mild hydrothermal method and was characterized using FT-IR, powder XRD and SEM techniques. The effect of operating parameters such as doping ratio, initial pH, catalyst dosage, initial concentrations of humic substances and sunlight illuminance were studied on humic substances degradation efficiency. The results of characterization analyses of samples confirmed the proper synthesis of Cu-doped ZnO nanocatalyst. The experimental results indicated the highest degradation efficiency of HS (99.2 %) observed using 1.5 % Cu-doped ZnO nanoparticles at reaction time of 120 min. Photocatalytic degradation efficiency of HS in a neutral and acidic pH was much higher than that at alkaline pH. Photocatalytic degradation of HS was enhanced with increasing the catalyst dosage and sunlight illuminance, while increasing the initial HS concentration led to decrease in the degradation efficiency of HS. Conclusively, Cu-doped ZnO nanoparticles can be used as a promising and efficient catalyst for degradation of HS under natural sunlight irradiation.

The environmental pollution and health impacts caused by the primitive and crude recycling of e-waste have become urgent global issues. Guiyu, China is a major hotspot of e-waste recycling. In this study, the levels and distribution of polycyclic aromatic hydrocarbons in soil in Guiyu were determined to investigate the effect of e-waste activities on the environment and to identify possible sources of these pollutants. Sediment samples from a local duck pond, water gullies, a river tributary, and combusted residue from e-waste burning sites were also investigated. The general trend found in soil (Σ16 PAHs) was acid leaching site > duck pond > rice field > printer roller dump site > reservoir (control site) and ranged from 95.2 ± 54.2 to 5,210 ± 89.6 ng/g (dry wt). The highest average total PAH concentrations were found in combusted residues of wires, cables, and other computer electrical components located at two e-waste open burning sites (18,600 and 10,800 ± 3,940 ng/g). These were 195- and 113-fold higher than the PAH concentrations of soil at the control site. Sediment PAH concentrations ranged from 37.2 ± 6 to 534 ± 271 ng/g. Results of this study provide further evidence of significant input of PAHs to the environment attributed to crude e-waste recycling.