Polybrominated diphenyl ethers (PBDEs) are widely used as flame retardants for various products and have become ubiquitous pollutants in environmental media. However, little is known about PBDE levels in Shenzhen, a manufacturing center of electronic products. This study aimed to investigate spatiotemporal variability of PBDE concentration in atmospheric fine particles (PM2.5) and to estimate the daily inhalation exposure doses for local residents in Shenzhen, China. A total of 36 samples were collected and 8 PBDE compounds (BDE-28, 47, 99, 100, 153, 154, 183 and 209) were analyzed by isotope dilution high-resolution gas chromatograph/high-resolution mass spectrometer (HRGC/HRMS). Mean concentrations of Σ8PBDEs and BDE-209 in PM2.5 in Shenzhen were 33.47 pg/m3 and 24.75 pg/m3, respectively, which were lower than those for other reported cities from China. The mean concentration of Σ8PBDEs was higher in the winter + spring than that in summer + autumn, and both concentrations of BDE-28 and BDE-47 in PM2.5 were significantly higher in winter + spring than those in summer + autumn. Among the 8 congeners, BDE-209 was predominant, accounting for 73.9% of the Σ8PBDEs concentrations. Traffic area, industrial area, residential area and discharge of electronic industries had significant positive influences on PBDE concentrations in PM2.5. Both vegetation area and water area were significantly negatively correlated with PBDE levels in PM2.5. Significantly negative correlation was also found between PBDE concentrations in PM2.5 and the relative humidity. The ranking of estimated inhalation exposure doses of PBDEs via PM2.5 inhalation were toddlers (1.74 pg/kg b.w./day) > children (1.33 pg/kg b.w./day) > adults (1.26 pg/kg b.w./day) > teenagers (0.64 pg/kg b.w./day), and toddlers had a highest risk to expose to PBDEs by PM2.5. To our knowledge, the present study is the first to reveal the spatiotemporal variability of PBDEs in PM2.5 of Shenzhen, China.

The widespread occurrence of microplastics (MP) in the marine environment is cause of increasing concerns about the safety of the exposed ecosystems. Although the effects associated to the MP uptake have been studied in most marine taxa, the knowledge about their sub-lethal impacts on early life stages of marine species is still limited. Here, we investigated the uptake/retention of 3-μm polystyrene MP by early stages of the Mediterranean mussel Mytilus galloprovincialis, and the related effects on gut clearance, feeding efficiency, morphological and transcriptional parameters involved in embryo-larval development. Uptake measurements were performed on larvae at 48 h, 3, 6 and 9 days post fertilization (pf) after exposure to a range of 50–10,000 particles mL−1. At all tested pf periods, treatments resulted in a significant and linear increase of MP uptake with increasing concentrations, though levels measured at 48 h pf were significantly lower compared to 3–9 d pf. Ingested MP were retained up to 192 h in larvae's gut, suggesting a physical impact on digestive functions. No change was noted between the consumption of microalgae Nannochloropsis oculata by larvae when administered alone or in the presence of an identical concentration (2000 items mL−1) of MP. The exposure to 50–10,000 MP mL−1 did not alter the morphological development of mussel embryos; however, transcriptional alterations were observed at 50 and 500 MP mL−1, including the up-regulation of genes involved in shell biogenesis (extrapallial protein; carbonic anhydrase; chitin synthase) and immunomodulation (myticin C; mytilin B), and the inhibition of those coding for lysosomal enzymes (hexosaminidase; β-glucorinidase; catepsin-L). In conclusion, though not highlighting morphological or feeding abnormalities, data from this study revealed the onset of physical and transcriptional impairments induced by MP in mussel larvae, indicating sub-lethal impacts which could increase their vulnerability toward further environmental stressors.

Exposure to low frequency and radiofrequency electromagnetic fields at low intensities poses a significant health hazard that has not been adequately addressed by national and international organizations such as the World Health Organization. There is strong evidence that excessive exposure to mobile phone-frequencies over long periods of time increases the risk of brain cancer both in humans and animals. The mechanism(s) responsible include induction of reactive oxygen species, gene expression alteration and DNA damage through both epigenetic and genetic processes. In vivo and in vitro studies demonstrate adverse effects on male and female reproduction, almost certainly due to generation of reactive oxygen species. There is increasing evidence the exposures can result in neurobehavioral decrements and that some individuals develop a syndrome of “electro-hypersensitivity” or “microwave illness”, which is one of several syndromes commonly categorized as “idiopathic environmental intolerance”. While the symptoms are non-specific, new biochemical indicators and imaging techniques allow diagnosis that excludes the symptoms as being only psychosomatic. Unfortunately standards set by most national and international bodies are not protective of human health. This is a particular concern in children, given the rapid expansion of use of wireless technologies, the greater susceptibility of the developing nervous system, the hyperconductivity of their brain tissue, the greater penetration of radiofrequency radiation relative to head size and their potential for a longer lifetime exposure.

Bioindicators play an important role in understanding pollution levels, bioavailability and the ecological risks of contaminants. Several bioindicators have been suggested for understanding microplastic in the marine environment. A bioindicator for microplastics in the freshwater environment does not exist. In our previous studies, we found a high frequency of microplastic pollution in the Asian clam (Corbicula fluminea) in Taihu Lake, China. In the present study, we conducted a large-scale survey of microplastic pollution in Asian clams, water and sediment from 21 sites in the Middle-Lower Yangtze River Basin from August to October of 2016. The Asian clam was available in all sites, which included diverse freshwater systems such as lakes, rivers and estuaries. Microplastics were found at concentrations ranging from 0.3-4.9 items/g (or 0.4–5.0 items/individual) in clams, 0.5–3.1 items/L in water and 15–160 items/kg in sediment. Microfibers were the most dominant types of microplastics found, accounting for 60–100% in clams across all sampling sites. The size of microplastics ranged from 0.021-4.83 mm, and microplastics in the range of 0.25–1 mm were dominant. The abundance, size distribution and color patterns of microplastics in clams more closely resembled those in sediment than in water. Because microplastic pollution in the Asian clam reflected the variability of microplastic pollution in the freshwater environments, we demonstrated the Asian clam as an bioindicator of microplastic pollution in freshwater systems, particularly for sediments.

Aquatic animals live in an acoustic world, prone to pollution by globally increasing noise levels. Noisy human activities at sea have become widespread and continue day and night. The potential effects of this anthropogenic noise may be context-dependent and vary with the time of the day, depending on diel cycles in animal physiology and behaviour. Most studies to date have investigated behavioural changes within a single sound exposure session while the effects of, and habituation to, repeated exposures remain largely unknown. Here, we exposed groups of European seabass (Dicentrarchus labrax) in an outdoor pen to a series of eight repeated impulsive sound exposures over the course of two days at variable times of day/night. The baseline behaviour before sound exposure was different between day and night; with slower swimming and looser group cohesion observed at night. In response to sound exposures, groups increased their swimming speed, depth, and cohesion; with a greater effect during the night. Furthermore, groups also showed inter-trial habituation with respect to swimming depth. Our findings suggest that the impact of impulsive anthropogenic noise may be stronger at night than during the day for some fishes. Moreover, our results also suggest that habituation should be taken into account for sound impact assessments and potential mitigating measures.

Organic fertilizers, such as digestates and manure, are increasingly applied in agricultural systems because of the benefits they provide in terms of plant nutrients and soil quality. However, there are few investigations of N₂O emissions following digestate application to agricultural soils using process-based models. In this study, we modified the UK-DNDC model to include digestate applications to soils by adding digestate properties to the model and considering the effect of organic fertilizer pH. Using the modified model, N₂O emissions were simulated from two organic fertilizers (digested food waste and livestock slurry) applied to three farms in the United Kingdom: one growing winter wheat at Wensum (WE) and two grasslands at Pwllpeiran (PW) and North Wyke (NW). The annual cumulative gross (i.e. not excluding control emission) N₂O emissions were calculated using MATLAB trapezoidal numerical integration. The relative errors of the modeled annual cumulative emissions to the measured emissions ranged from −5.4% to 48%. Two-factor models, including linear, exponential and hyperbola responses, correlating total N loading and soil clay content to calculations of N₂O emissions and N₂O emission factors (EFs) were developed for calculations of emission fluxes and EFs. The squares of the correlation coefficients of the measured and two-factor linear modeled emissions were 0.998 and 0.999 for digestate and slurry, respectively, and the corresponding squares of correlation coefficients of the EFs were 0.998 and 0.938. The two-factor linear model also predicted that the EFs increased linearly with decreasing clay content and the maximum EFs for digestate and slurry were 0.95 and 0.76% of total N applied, respectively. This demonstrates that the modified UK_DNDC is a good tool to simulate N₂O emission from digestate and slurry and to calculate UK EFs using TIER 3 methodology..

How terrestrial ecosystem responds to global warming has received wide attention. Plant stoichiometry has the potential to reflect ecosystem responses to climate change, thus, investigating the variations in plant stoichiometry with temperature is important and necessary for revealing the responses of terrestrial ecosystem to global warming. Although many studies had explored the relationships between plant N, P stoichiometry and temperature, previous field investigations did not eliminate the interference of precipitation effect with these observed relationships. To minimize the effect of precipitation on leaf N, P stoichiometry, this investigation was conducted across a temperature gradient over broad geographical scale along the 400 mm isohyet, which extends about 6000 km in China. This study showed that leaf N did not vary, whereas leaf P decreased and leaf N:P ratio increased with increasing mean annual temperature (MAT). The responses of leaf N and P stoichiometry to MAT observed in this study might be general patterns; because they were almost ubiquitous across functional groups, genera and species examined, and moreover, they were independent of vegetation and soil type. It could be inferred from this study that global warming in future will have no effect on leaf N, but reduce leaf P and increase leaf N:P ratio. Stable leaf N and varied leaf P with changing MAT suggested that leaf N and P decoupled with changing temperature.

The relative impact of non-exhaust sources (i.e. road dust, tire wear, road wear and brake wear particles) on urban air quality is increasing. Among them, road dust resuspension has generally the highest impact on PM concentrations but its spatio-temporal variability has been rarely studied and modeled. Some recent studies attempted to observe and describe the time-variability but, as it is driven by traffic and meteorology, uncertainty remains on the seasonality of emissions. The knowledge gap on spatial variability is much wider, as several factors have been pointed out as responsible for road dust build-up: pavement characteristics, traffic intensity and speed, fleet composition, proximity to traffic lights, but also the presence of external sources. However, no parameterization is available as a function of these variables.We investigated mobile road dust smaller than 10 μm (MF10) in two cities with different climatic and traffic conditions (Barcelona and Turin), to explore MF10 seasonal variability and the relationship between MF10 and site characteristics (pavement macrotexture, traffic intensity and proximity to braking zone). Moreover, we provide the first estimates of emission factors in the Po Valley both in summer and winter conditions. Our results showed a good inverse relationship between MF10 and macro-texture, traffic intensity and distance from the nearest braking zone. We also found a clear seasonal effect of road dust emissions, with higher emission in summer, likely due to the lower pavement moisture. These results allowed building a simple empirical mode, predicting maximal dust loadings and, consequently, emission potential, based on the aforementioned data. This model will need to be scaled for meteorological effect, using methods accounting for weather and pavement moisture. This can significantly improve bottom-up emission inventory for spatial allocation of emissions and air quality management, to select those roads with higher emissions for mitigation measures.

Air pollution forecasting is significant for public health and controlling pollution, and statistical methods are important air pollution forecasting techniques. Nevertheless, the research of AQI (air quality index) forecasting is very rare. So an accurate and stable AQI forecasting model is very urgent and necessary. For the high complex, volatile and nonlinear AQI series, this research presents a novel optimal-combined model based on CEEMD (complementary ensemble empirical mode decomposition), PSOGSA (particle swarm optimization and gravitational search algorithm), PSO (particle swarm optimization) and combined forecasting method. The proposed model effectively solves the blind combined forecasting. AQI series forecasts of five cities in North China show that the proposed model has the highest correct rate of forecasting classifications compared with the candidates. Totally, the presented model has the following advantages compared with the candidates: more robust forecasting performance, smaller forecasting error and better generalization ability.

Outdoor air pollution is considered as the most serious environmental problem for human health, associated with some million deaths worldwide per year. Cities have to cope with the challenges due to poor air quality impacting human health and citizen well-being. According to an analysis in the framework of this study, the annual mean concentrations of tropospheric ozone (O₃) have been increasing by on average 0.16 ppb year⁻¹ in cities across the globe over the time period 1995–2014. Green urban infrastructure can improve air quality by removing O₃. To efficiently reduce O₃ in cities, it is important to define suitable urban forest management, including proper species selection, with focus on the removal ability of O₃ and other air pollutants, biogenic emission rates, allergenic effects and maintenance requirements. This study reanalyzes the literature to i) quantify O₃ removal by urban vegetation categorized into trees/shrubs and green roofs; ii) rank 95 urban plant species based on the ability to maximize air quality and minimize disservices, and iii) provide novel insights on the management of urban green spaces to maximize urban air quality. Trees showed higher O₃ removal capacity (3.4 g m⁻² year⁻¹ on average) than green roofs (2.9 g m⁻² year⁻¹ as average removal rate), with lower installation and maintenance costs (around 10 times). To overcome present gaps and uncertainties, a novel Species-specific Air Quality Index (S-AQI) of suitability to air quality improvement is proposed for tree/shrub species. We recommend city planners to select species with an S-AQI>8, i.e. with high O₃ removal capacity, O₃-tolerant, resistant to pests and diseases, tolerant to drought and non-allergenic (e.g. Acer sp., Carpinus sp., Larix decidua, Prunus sp.). Green roofs can be used to supplement urban trees in improving air quality in cities. Urban vegetation, as a cost-effective and nature-based approach, aids in meeting clean air standards and should be taken into account by policy-makers.