Fine particulate matter (PM₂.₅) is an essential risk factor of chronic obstructive pulmonary disease (COPD). Recent studies showed weak association between PM₂.₅ and COPD incidence, but smokers who exposed to higher PM₂.₅ concentration had more opportunity to gain COPD. Cigarette smoking is the most important risk factor of COPD. Thus, we hypothesized: the role of PM₂.₅ played on cigarette-inflamed airways was more significant than normal airways. The study firstly established an animal model of C57BL/6J mice with cigarette smoke exposure and PM₂.₅ orotracheal administration. After calculating pathological scores, mean linear intercept and mean alveolar area, we found PM₂.₅ aggravated pathological injury of cigarette-inflamed lungs, but the injury on normal lungs was not significant. Meanwhile, inflammatory factors as T-bet, IFN-γ and IL-1α were tested using qRT-PCR and ELISA. The results showed PM₂.₅ aggravated inflammation of cigarette-inflamed lungs, but the effect on normal lungs was not significant. The most important pathogenesis of COPD is abnormal apoptosis in airway epithelium, due to oxidative stress following long-term exposure to cigarette smoke. Then, apoptotic responses were detected in lungs. TUNEL analysis demonstrated that PM₂.₅ promoted DNA fragmentation of cigarette-inflamed lungs, but the effect on normal lungs was not significant. Western-blot and immunohistochemistry showed caspase activated significantly in PM₂.₅-cigarette smoke exposed lungs and activated caspase 3 located mainly on bronchial epithelium. Next, human bronchial epithelial cells were cultured treated with cigarette smoke solution (CSS) with or without PM₂.₅. Z-VAD-FMK, a pan-caspase inhibitor, was used to suppress the activation of caspases. After analyzing cell viability, DNA fragmentation, mitochondrial activities and caspase activities, the results clarified that PM₂.₅ aggravated apoptosis in cigarette-inflamed bronchial epithelial cells and the responses could be suppressed by Z-VAD-FMK. Our results gave a new idea about the mechanism of PM₂.₅ on COPD and inferred cigarette-inflamed airways were more vulnerable to PM₂.₅ than normal airways.

Anthropogenic activity-mediated nutrient pollution, especially nitrogen enrichment, poses one of the major threats to river ecosystems. However, it remains unclear how and to which extent it affects aquatic microbial communities, especially in heavily polluted rivers. In this study, a significant environmental gradient, particularly nitrogen gradient, was observed along a wastewater receiving river, the North Canal River (NCR). The pollution level was highest, moderate, and lowest in the up-, middle, and down-streams, respectively. The community composition of bacterioplankton transitioned from being Betaproteobacteria-dominated upstream to Gammaproteobacteria-dominated downstream. Copiotrophic groups, such as Polynucleobacter (Betaproteobacteria) and Hydrogenophaga (Betaproteobacteria), were dominant in the upstream. Multiple statistical analyses indicated that total nitrogen (TN) was the most important factor driving the adaptive shifts of community structure. Analyses of co-occurrence networks showed that the complexity of networks was disrupted in the up- and middle streams, while enhanced in the downstream. Our findings here suggested that microbial interactions were reduced in response to the aggravation of nutrient pollution. Similar to these changes, we observed significant dissimilarity of composition of functional groups, with highest abundance of nitrogen metabolism members under the highest level of nitrogen enrichment. Further analyses indicated that most of these functional groups belonged to Betaproteobacteria, suggesting the potential coupling of community composition and function diversity. In summary, adaptive shifts of bacterioplankton community composition, as well as species interactions, occurred in response to nutrient pollution in highly polluted water bodies.

Rivers are an important source of marine anthropogenic litter, but the particular origins of riverine litter itself have not been well established. Here we used a citizen science approach where schoolchildren examined litter at riversides and identified possible sources at over 250 sampling spots along large and small rivers in Germany, during autumn 2016 and spring 2017. Litter densities have an overall median of 0.14, interquartile range 0–0.57 items m−2 and an overall average (±standard deviation) of 0.54 ± 1.20 litter items m−2. Litter quantities differed only little by sampling year. The principal litter types found were plastics and cigarette butts (31% and 20%, respectively), followed by glass, paper, and metal items, indicating recreational visitors as the principal litter source. At many sites (85%), accumulations of litter, consisting principally of cigarettes and food packaging, have been found. At almost all sampling sites (89%), litter potentially hazardous to human health has been observed, including broken glass, sharp metal objects, used personal hygiene articles and items containing chemicals. In the search for litter sources, the schoolchildren identified mainly people who use the rivers as recreational areas (in contrast to residents living in the vicinity, illegal dumping, or the river itself depositing litter from upstream sources). These results indicate the urgent need for better education and policy measures in order to protect riparian environments and reduce input of riverine litter to the marine environment.

Microplastics (plastic particles <5 mm) are a contaminant of increasing ecotoxicological concern in aquatic environments, as well as for human health. Although microplastic pollution is widespread across the land, water, and air, these environments are commonly considered independently; however, in reality are closely linked. This study aims to review the scientific literature related microplastic research in different environmental compartments and to identify the research gaps for the assessment of future research priorities. Over 200 papers involving microplastic pollution, published between 2006 and 2018, are identified in the Web of Science database. The original research articles in ‘Environmental Sciences’, ‘Marine/Freshwater Biology’, ‘Toxicology’, ‘Multidisciplinary Sciences’, ‘Environmental Studies’, ‘Oceanography’, ‘Limnology’ and ‘Ecology’ categories of Web of Science are selected to investigate microplastic research in seas, estuaries, rivers, lakes, soil and atmosphere. The papers identified for seas, estuaries, rivers and lakes are further classified according to (i) occurrence and characterization (ii) uptake by and effects in organisms, and (iii) fate and transport issues. The results reveal that whilst marine microplastics have received substantial scientific research, the extent of microplastic pollution in continental environments, such as rivers, lakes, soil and air, and environmental interactions, remains poorly understood.

Integrated systems with appropriate bio-filters can be used to treat aquaculture effluents. However, the information on bio-filters that alters the ecological functions of the bacterioplankton community (BC) in biodegradation of the aquaculture effluents remains controversial. In this study, we implemented a comprehensive restoration technology combined with bio-filters [biofilm, clam (Tegillarca granosa), and macrophytes (Spartina anglica)] to investigate their influence on the stability of the BC and nutrient removal. We found that the diversity of BC was linked with biogeochemical factors in processing and upcycling nitrogen-rich effluents into high-value biomass. The BC exhibited significant distinct patterns in the bio-filter areas. Potential biomarkers for constrained harmfully algae-bacteria (Nitriliruptoraceae, Bacillales, and Rhodobacteraceae) and nutrient removal were significantly higher in the bio-filters areas. The bio-filters significantly promoted the restoration effects of N and P balance by reducing 82.34% of total nitrogen (TN) and 81.64% of total phosphorus (TP) loads at the water interface. The main mechanisms for TN and TP removal and nutrient transformation were achieved by assimilation and absorption by the emergent macrophytes (Spartina anglica). The bio-filters significantly influenced the biodegradability and resolvability of particulate organic matter through ammonification, nitrification, and denitrification of microbes, which meliorated the nutrient removal. Beside bio-filter effects, the BC was significantly controlled by abiotic factors [nitrate (NO₃⁻-N), dissolved oxygen (DO), total nitrogen (TN), and water temperature (WT)], and biotic factors (chlorophyll ɑ and green algae). Our study revealed that the co-existence system with bio-filters may greatly improve our understanding on the ecological functions of the BC in aquaculture systems. Overall, combined bio-filters provide an opportunity for the development of efficient and optimized aquaculture wastewater treatment technology.

Schwertmannite (SCH) has strong adsorption ability to As(III). However, there are few reports on the stability of SCH load with As(III) (SCH-As(III)). In this study, the effects of tartaric acid (TA), pH and coexisting ions including K+, Ca2+, Al3+ and CO32− on the photoreductive dissolution of SCH- As(III) and the release of the adsorbed As (III) were investigated. The results showed that under UV irradiation TA could greatly enhance the release of total Fe and total As from SCH-As(III). Nevertheless, the total Fe and total As in the solution decreased when TA was consumed up. Compared to SCH, the reductive dissolution of SCH-As(III) was obviously suppressed. In the dark, TA could slowly enhance the dissolution of SCH-As(III), but its effect on the release of adsorbed As(III) was weak. Low pH was conducive to the release of iron and arsenic. Ca2+, K+, and CO32− promoted the decrease of the dissolved total Fe in the later reaction. However, Al3+ inhibited the decrease of the dissolved total Fe and total As. The analyses of FTIR and XRD demonstrated that the mineralogical phase of SCH-As(III) after reaction changed. With light, the dissolved total Fe and total As existed mainly as Fe(II) and As(V), respectively. This is because Fe(II) was generated via ligand to metal charge transfer and As(III) was oxidized to As(V) by ·OH produced during the reaction. Thus, this study provides us with a comprehensive understanding of the stability of SCH-As(III) and the release of adsorbed As(III) in natural environments.

Changzhou, an industrial city in the Yangtze River Delta, has been experiencing serious haze pollution, particularly in winter. However, studies pertaining to the haze in Changzhou are very limited, which makes it difficult to understand the characteristics and formation of winter haze in this area, and develop effective control measures. In this study, we carried out continuous online observation of particulate matter, chemical components, and meteorology in Changzhou in February 2017. Our results showed that haze pollution occurred frequently in Changzhou winter and exhibited two patterns: dry haze with low relative humidity (RH) and wet haze with high RH. Water-soluble inorganic ions (SO₄²⁻, NO₃⁻, and NH₄⁺) accounted for ∼52.2% of the PM₂.₅ mass, of which sulfate was dominant in wet haze periods while nitrate was dominant in other periods. With the deterioration of haze pollution, the proportion of nitrate in PM₂.₅ increased, while sulfate proportion increased under wet haze and decreased under dry haze. Dry haze and wet haze appeared under slow north wind and south wind, respectively, and strong north wind or sea breeze scavenged pollution. We found that formation of nitrate occurred rapidly in daytime with high concentrations of odd oxygen (Oₓ = O₃ + NO₂), whereas formation of sulfate occurred rapidly during nighttime with high RH, indicating that photochemistry and heterogeneous reaction were the major formation mechanisms for nitrate and sulfate, respectively. Through the cluster analysis of 36-h backward trajectories, five sources of air masses from three directions were identified. High PM₂.₅ concentrations (84.1 μg m⁻³ on average) usually occurred under the influence of two clusters (46%) from the northwest, indicating that regional transport from northern China aggravated the winter haze pollution in Changzhou. Emission reduction, particularly the mobile sources, and regional joint prevention and control can help to mitigate the winter haze in Changzhou.

Epidemiologists use prediction models to downscale (i.e., interpolate) air pollution exposure where monitoring data is insufficient. This study compares machine learning prediction models for ground-level ozone during wildfires, evaluating the predictive accuracy of ten algorithms on the daily 8-hour maximum average ozone during a 2008 wildfire event in northern California. Models were evaluated using a leave-one-location-out cross-validation (LOLO CV) procedure to account for the spatial and temporal dependence of the data and produce more realistic estimates of prediction error. LOLO CV avoids both the well-known overly optimistic bias of k-fold cross-validation on dependent data and the conservative bias of evaluating prediction error over a coarser spatial resolution via leave-k-locations-out CV. Gradient boosting was the most accurate of the ten machine learning algorithms with the lowest LOLO CV estimated root mean square error (0.228) and the highest LOLO CV Rˆ2 (0.677). Random forest was the second best performing algorithm with an LOLO CV Rˆ2 of 0.661. The LOLO CV estimates of predictive accuracy were less optimistic than 10-fold CV estimates for all ten models. The difference in estimated accuracy between the 10-fold CV and LOLO CV was greater for more flexible models like gradient boosting and random forest. The order of estimated model accuracy depended on the choice of evaluation metric, indicating that 10-fold CV and LOLO CV may select different models or sets of covariates as optimal, which calls into question the reliability of 10-fold CV for model (or variable) selection. These prediction models are designed for interpolating ozone exposure, and are not suited to inferring the effect of wildfires on ozone or extrapolating to predict ozone in other spatial or temporal domains. This is demonstrated by the inability of the best performing models to accurately predict ozone during 2007 southern California wildfires.

In the past few decades, extensive epidemiological studies have focused on exploring the adverse effects of PM₂.₅ (particulate matters with aerodynamic diameters less than 2.5 μm) on public health. However, most of them failed to consider the dynamic changes of population distribution adequately and were limited by the accuracy of PM₂.₅ estimations. Therefore, in this study, location-based service (LBS) data from social media and satellite-derived high-quality PM₂.₅ concentrations were collected to perform highly spatiotemporal exposure assessments for thirteen cities in the Beijing-Tianjin-Hebei (BTH) region, China. The city-scale exposure levels and the corresponding health outcomes were first estimated. Then the uncertainties in exposure risk assessments were quantified based on in-situ PM₂.₅ observations and static population data. The results showed that approximately half of the population living in the BTH region were exposed to monthly mean PM₂.₅ concentration greater than 80 μg/m³ in 2015, and the highest risk was observed in December. In terms of all-cause, cardiovascular, and respiratory disease, the premature deaths attributed to PM₂.₅ were estimated to be 138,150, 80,945, and 18,752, respectively. A comparative analysis between five different exposure models further illustrated that the dynamic population distribution and accurate PM₂.₅ estimations showed great influence on environmental exposure and health assessments and need be carefully considered. Otherwise, the results would be considerably over- or under-estimated.

Little information is available about the occurrence of neonicotinoid insecticides in surface water and sediment of the metropolitan regions around the rivers in China. Here we investigate the residual level of neonicotinoids in the Guangzhou section of the Pearl River. At least one or two neonicotinoids was detected in each surface water and sediment, and the total amount of neonicotinoids (∑₅neonics) in surface water ranged from 92.6 to 321 ng/L with a geometric mean (GM) of 174 ng/L. Imidacloprid, thiamethoxam and acetamiprid were three frequently detected neonicotinoids (100%) from surface water. As for the sediment, total concentration was varied between 0.40 and 2.59 ng/g dw with a GM of 1.12 ng/g dw, and acetamiprid and thiacloprid were the common sediment neonicotinoids. Western and Front river-route of the Guangzhou section of the Pearl River suffered a higher neonicotinoids contamination than the Rear river-route, resulting from more effluents of WWTPs receiving, and intensive commercial and human activities. Level of residual neonicotinoids in surface water was significantly correlated with the water quality (p < 0.01), especially items of pH, DO and ORP, and nitrogen and phosphorus contaminants. Compared with reports about residual neonicotinoids in water and sediment previously, the metropolitan regions of the Guangzhou could be confronted with a moderate contamination and showed serious ecological threats (even heavier than the Pearl Rivers). Our results will provide valuable data for understanding of neonicotinoids contamination in the Pearl River Delta and be helpful for further assessing environmental risk of neonicotinoids.