The impacts of COVID-19 lockdown restrictions have provided a valuable global experiment into the extent of improvements in air quality possible with reductions in vehicle movements. Mexico City, London and Delhi all share the problem of air quality failing WHO guideline limits, each with unique situations and influencing factors. We determine, discuss and compare the air quality changes across these cities during the COVID-19, to understand how the findings may support future improvements in their air quality and associated health of citizens. We analysed ground-level PM₁₀, PM₂.₅, NO₂, O₃ and CO changes in each city for the period 1st January to August 31, 2020 under different phases of lockdown, with respect to daily average concentrations over the same period for 2017 to 2019. We found major reductions in PM₁₀, PM₂.₅, NO₂ and CO across the three cities for the lockdown phases and increases in O₃ in London and Mexico City but not Delhi. The differences were due to the O₃ production criteria across the cities, for Delhi production depends on the VOC-limited photochemical regime. Levels of reductions were commensurate with the degree of lockdown. In Mexico City, the greatest reduction in measured concentration was in CO in the initial lockdown phase (40%), in London the greatest decrease was for NO₂ in the later part of the lockdown (49%), and in Delhi the greatest decrease was in PM₁₀, and PM₂.₅ in the initial lockdown phase (61% and 50%, respectively). Reduction in pollutant concentrations agreed with reductions in vehicle movements. In the initial lockdown phase vehicle movements reduced by up to 59% in Mexico City and 63% in London. The cities demonstrated a range of air quality changes in their differing geographical areas and land use types. Local meteorology and pollution events, such as forest fires, also impacted the results.

Microplastics represent an emerging environmental issue and have been found almost everywhere including seafood, raising a great concern about the ecological and human health risks they pose. This study addressed the common technical challenges in the assessment of microplastics in seafood by developing an improved protocol based on Raman spectroscopy and using the green-lipped mussel Perna viridis and the Japanese jack mackerel Trachurus japonicus as the test models. Our findings identified a type of stainless-steel filter membranes with minimal Raman interference, and a combination of chemicals that achieved 99–100% digestion efficiency for both organic and inorganic biomass. This combined chemical treatment reached 90–100% recovery rates for seven types of microplastics, on which the surface modification was considered negligible and did not affect the accuracy of polymer identification based on Raman spectra, which showed 94–99% similarity to corresponding untreated microplastics. The developed extraction method for microplastics was further combined with an automated Raman mapping approach, from which our results confirmed the presence of microplastics in P. viridis and T. japonicus collected from Hong Kong waters. Identified microplastics included polypropylene, polyethylene, polystyrene and poly(ethylene terephthalate), mainly in the form of fragments and fibres. Our protocol is applicable to other biological samples, and provides an improved alternative to streamline the workflow of microplastic analysis for routine monitoring purposes.

A complex relationship exists between copper stress and the accumulation and release of domoic acid (DA) in toxin-producing Pseudo-nitzschia cells. To clarify the changes and role of DA in this process, we exposed the toxin-producing P. multiseries and the non-toxin-producing P. pungens to copper stress (5 and 9 μM) for 96 h. Results showed that P. multiseries grew better than P. pungens under the two aforementioned copper concentrations. DA content in the cells of P. multiseries increased with increased copper stress, and the dissolved DA in the medium under the 9 μM copper treatment increased. DA addition at a 9 μM copper concentration reduced the copper content in P. multiseries cells and cell walls, but did not change the free copper ion content in culture medium. Adding DA to the medium reduced the malondialdehyde (MDA) content in the cells of P. multiseries under copper stress, DA addition also reduced the activities of catalase (CAT) and superoxide dismutase (SOD) at 5 μM Cu, and the activity of peroxidase (POD) at 9 μM Cu. This suggests that DA may not alleviate copper stress by improving the antioxidant defense system of algal cells, nor can it be complexed with copper ions in the medium to alleviate copper stress. Furthermore, the reactive oxygen species (ROS) scavenger N-tert-butyl-α-phenylnitrone (BPN) was used to study the DA accumulated in cells. The BPN addition significantly reduced the accumulation of DA in the cells under copper stress, suggesting that DA content in cells was closely related to ROS. Moreover, further experiments demonstrated that DA addition can improve the growth of P. multiseries under hydrogen peroxide stress. Our results indicate that DA alleviates P. multiseries oxidative damage when expose to copper stress.

The assessment of trace metal pollution in aquatic environments remains a challenge. Chemical methods are insufficient and bioindicators seem to be the most promising alternative. Finding an adequate species is important to ensure accurate data. The combined use of several bioindicators may help to overcome the limitations of species’ spatial distribution and specific reactions. The aims of the present study were to compare the contents and bioaccumulation capability of 11 trace elements in Ceratophyllum demersum and different organs of Hydrocharis morsus-ranae and to validate H. morsus-ranae as a bioindicator of pollution in aquatic reservoirs using C. demersum, an established bioindicator, as a reference species. The application of several statistical techniques allowed us to identify similarities in accumulation patterns and concentration gradients between the two species. The results showed that concentrations of Cd, Co, Cr, Cu, Mn, Ni, Pb, Rb, Zn, V in C. demersum and roots of H. morsus-ranae were similar and mostly higher than in the leaves and stems of H. morsus-ranae. The contents of Cd, Co, Cr, Li, Mn, Ni, Rb, V, Zn were positively correlated. The inner transport of metals in H. morsus-ranae was limited (TF < 1). Both species are accumulators (BF > 10³) of Ni and Zn, and H. morsus-ranae also of Cu and Pb. Frog-bit roots were chosen to be most promising in bioindication. Major axis regression analysis showed that the uptake of Cd, Cr, Co, Li and Pb was similar in the two species. Neural networks demonstrated substantial uniformity in responses of C. demersum and roots of H. morsus-ranae to the type of anthropogenic activity and land use and similar spatial distributions of Cd, Cr, Co, Li and Pb. When Nemerow Pollution Index was applied, both species showed congruent gradients of contamination. Thus, H. morsus-ranae was validated as a reliable bioindicator of trace metal pollution in freshwater.

A large number of toxicity studies report abnormalities in early life-stage (ELS) fish that are described here as a sublethal toxicity syndrome (TxSnFELS) and generally include a reduced heart rate, edemas (yolk sac and cardiac), and a variety of morphological abnormalities. The TxSnFELS is very common and not diagnostic for any chemical or class of chemicals. This sublethal toxicity syndrome is mostly observed at high exposure concentrations and appears to be a baseline, non-specific toxicity response; however, it can also occur at low doses by specific action. Toxicity metrics for this syndrome generally occur at concentrations just below those causing mortality and have been reported for a large number of diverse chemicals. Predictions based on tissue concentrations or quantitative-structure activity relationship (QSAR) models support the designation of baseline toxicity for many of the tested chemicals, which is confirmed by observed values. Given the sheer number of disparate chemicals causing the TxSnFELS and correlation with QSAR derived partitioning; the only logical conclusion for these high-dose responses is baseline toxicity by nonspecific action and not a lock and key type receptor response. It is important to recognize that many chemicals can act both as baseline toxicants and specific acting toxicants likely via receptor interaction and it is not possible to predict those threshold doses from baseline toxicity. We should search out these specific low-dose responses for ecological risk assessment and not rely on high-concentration toxicity responses to guide environmental protection. The goal for toxicity assessment should not be to characterize toxic responses at baseline toxicity concentrations, but to evaluate chemicals for their most toxic potential. Additional aspects of this review evaluated the fish ELS teratogenic responses in relation to mammalian oral LD50s and explored potential key events responsible for baseline toxicity.

The incidence of thyroid cancer (TC) has increased rapidly worldwide in recent years. Exposure to endocrine disruptors can affect thyroid hormones and is probably carcinogenic to humans. The effects of polybrominated diphenyl ethers (PBDEs), some heavy metals (Cd, Pb, As and Hg) on risk of TC have been rarely reported. Hence, we aimed to examine the associations of TC risk with exposure to PBDEs and four heavy metals. This case-control study involved 308 TC cases and 308 age- and sex-matched controls. Plasma PBDEs concentrations were determined by gas chromatograph-mass spectrometry. Concentrations of heavy metals concentrations in urine specimens were detected by graphite furnace atomic absorption spectrometry or inductively coupled plasma optical emission spectrometry. Conditional logistic regression models were used to explore associations of PBDEs and 4 heavy metals exposures with TC risk. A joint-effect interaction term was inserted into the logistic regression models to assess the multiplicative interaction effects of PBDEs-heavy metals on TC risk. Some PBDE congeners (BDE-028, -047, −099, −183, −209) were positively correlated with TC risk. As and Hg were also associated with the increased TC risk. Compared with low exposure levels, participants with high exposure levels of As and Hg were 5.35 and 2.98 times more likely to have TC, respectively. Co-exposure to BDE-209 and Pb had a negative interaction effect on TC risk. Some PBDE congeners (e.g. BDE-028, -047, −209) and Hg had a significant positive interaction effect on the risk of TC. The joint exposure of BDE-183 and Hg showed a negative interaction effect on TC risk, but the corresponding OR value was still statistically significant. Exposure to PBDEs, As and Hg may be associated with TC development. Joint exposure to PBDEs and Pb or Hg has interaction effects on TC risk. Further prospective research with large sample is required to confirm these findings.

It is highly desirable but remains extremely challenging to develop a facile strategy to prepare adsorbent for dealing with heavy metal pollution in water. Here, we report a facile approach for preparing sulfydryl-functionalized graphene oxide (S-GO) by cross-linking method with an unprecedented adsorption capacity and ultrahigh selectivity for efficient Hg(II) removal. The adsorbents exhibit a prominent performance in capturing Hg(II) from wastewater with a record-high adsorption capacity of 3490 mg/g and rapid kinetics to reduce Hg(II) contaminants below the discharge standard of drinking water (2 ppb) within 60 min under a wide pH range even in the coexistent of other interfering metal ions. In addition, the adsorbents can be also easily recycled and reused multiple times with no apparent decline in removal efficiency. Considering the broad diversity, we developed also a magnetic Fe₃O₄/S-GO adsorbent by a simple chemical cross-linking reaction to achieve rapid separation of S-GO from their aqueous solution. In addition, the adsorbents were successfully applied in dealing with the practical industrial wastewater. The results indicate the potential of rationally designed sulfydryl-functionalized graphene oxide for high performance Hg(II) removal.

Private wells in Ireland and elsewhere have been shown to be prone to microbial contamination with the main suspected sources being practices associated with agriculture and domestic wastewater treatment systems (DWWTS). While the microbial quality of private well water is commonly assessed using faecal indicator bacteria, such as Escherichia coli, such organisms are not usually source-specific, and hence cannot definitively conclude the exact origin of the contamination. This research assessed a range of different chemical contamination fingerprinting techniques (ionic ratios, artificial sweeteners, caffeine, fluorescent whitening compounds, faecal sterol profiles and pharmaceuticals) as to their use to apportion contamination of private wells between human wastewater and animal husbandry wastes in rural areas of Ireland. A one-off sampling and analysis campaign of 212 private wells found that 15% were contaminated with E. coli. More extensive monitoring of 24 selected wells found 58% to be contaminated with E. coli on at least one occasion over a 14-month period. The application of fingerprinting techniques to these monitored wells found that the use of chloride/bromide and potassium/sodium ratios is a useful low-cost fingerprinting technique capable of identifying impacts from human wastewater and organic agricultural contamination, respectively. The artificial sweetener acesulfame was detected on several occasions in a number of monitored wells, indicating its conservative nature and potential use as a fingerprinting technique for human wastewater. However, neither fluorescent whitening compounds nor caffeine were detected in any wells, and faecal sterol profiles proved inconclusive, suggesting limited suitability for the conditions investigated.

Crude oil pollution is a global environmental concern since it persists in the environment longer than most conventional carbon sources. In December 2014, the hyper-arid Evrona Nature Reserve, Israel, experienced large-scale contamination when crude oil spilled. The overarching goal of the study was to investigate the possible changes, caused by an accidental crude oil spill, in the leaf reflectance and biochemical composition of four natural habitat desert shrubs. The specific objectives were (1) to monitor the biochemical properties of dominant shrub species in the polluted and control areas; (2) to study the long-term consequences of the contamination; (3) to provide information that will assist in planning rehabilitation actions; and (4) to explore the feasibility of vegetation indices (VIs), along with the machine learning (ML) technique, for detecting stressed shrubs based on the full spectral range. Four measurement campaigns were conducted in 2018 and 2019. Along with the various stress indicators, field spectral measurements were performed in the range of 350–2500 nm. A regression analysis to examine the relation of leaf reflectance to biochemical contents was carried out, to reveal the relevant wavelengths in which polluted and control plants differ. Vegetation indices applied in previous studies were found to be less sensitive for indirect detection of long-term oil contamination. A novel spectral index, based on indicative spectral bands, named the “normalized blue-green stress index” (NBGSI), was established. The NBGSI distinguished significantly between shrubs located in the polluted and in the control areas. The NBGSI showed a strong linear correlation with pheophytin a. Machine learning classification algorithms obtained high overall prediction accuracy in distinguishing between shrubs located in the oil-polluted and the control sites, indicating internal component differences. The findings of this study demonstrate the efficacy of indirect and non-destructive spectral tools for detecting and monitoring oil pollution stress in shrubs.

Shandong is the most populous and highly industrialized province in eastern China, and the resultant poor air quality is a cause for widespread concern. This study combines bottom–up and top–down approaches to develop a high-resolution anthropogenic emission inventory of air pollutants for 2017. The inventory was developed based on updated emission factors and detailed activity data. The emissions of sulfur dioxide (SO₂), nitrogen oxides (NOₓ), particulate matter with aerodynamic diameters smaller than 2.5 and 10 μm (PM₂.₅ and PM₁₀, respectively), carbon monoxide (CO), volatile organic compounds (VOCs), and ammonia (NH₃) were estimated to be 1387.8, 2488.6, 5281.7, 3193.0, 9250.7, 2254.7, and 1210.6 kt, respectively. Power plants were the largest contributors of SO₂ and NOₓ emissions accounting for 43.7% and 41.9% of the total emissions, respectively. CO emissions mainly originated from industrial processes (40.1%), mobile sources (24.8%), and fossil fuel burning (21.2%). The major sources of PM₁₀ and PM₂.₅ emissions were industrial processes and fugitive dust, contributing 83.0% and 86.9% of their total emissions, respectively. Industrial processes (60.0%) contributed the largest VOC emissions, followed by mobile sources (16.8%) and solvent use (14.5%). Livestock and N-fertilizers were major emitters of NH₃, accounting for 69.9% and 21.2% of the total emissions, respectively. Emissions were spatially allocated to grid cells with a resolution of 0.05 ° × 0.05 ° based on spatial surrogates, using Geographic Information System (GIS). Heavy pollutant emissions were mainly concentrated in the central and eastern areas of Shandong, while high NH₃–emissions occurred in the western region. Most pollutant emissions from industrial sectors occurred in June and July, while low emissions were recorded between January and February. Range uncertainties in emission inventory were quantified using Monte Carlo simulations. Our inventory provides effective information to understand local pollutant emission characteristics, perform air quality simulations, and formulate pollution control measures.