China National Environmental Monitoring Center

Inadequate water quality can mean that water is unsuitable for a variety of human uses, thus exacerbating freshwater scarcity. Previous large-scale water scarcity assessments mostly focused on the availability of sufficient freshwater quantity for providing supplies, but neglected the quality constraints on water usability. Here we report a comprehensive nationwide water scarcity assessment in China, which explicitly includes quality requirements for human water uses. We highlight the necessity of incorporating water scarcity assessment at multiple temporal and geographic scales. Our results show that inadequate water quality exacerbates China's water scarcity, which is unevenly distributed across the country. North China often suffers water scarcity throughout the year, whereas South China, despite sufficient quantities, experiences seasonal water scarcity due to inadequate quality. Over half of the population are affected by water scarcity, pointing to an urgent need for improving freshwater quantity and quality management to cope with water scarcity.

Significance Atmospheric ammonia plays important roles in fine particle pollution, acid rain, and nitrogen deposition. China, known as the world’s top emitter of gaseous ammonia, plans to control ammonia emissions to mitigate the haze pollution that has recently emerged. However, the complex side effects are still unclear. By integrating a chemical transport model, nationwide measurements, and a sophisticated ammonia emission model, we find that ammonia emission control would significantly aggravate acid rain pollution, thereby offsetting the benefit from reduced fine particle pollution and nitrogen deposition. Our work suggests that region-specific ammonia-control strategies provide a more rational and effective way to achieve the dual benefits of protecting human and ecosystem health in China.

Abstract Although much attention has been paid to investigating and controlling air pollution in China, the trends of air-pollutant concentrations on a national scale have remained unclear. Here, we quantitatively investigated the variation of air pollutants in China using long-term comprehensive data sets from 2013 to 2017, during which Chinese government made major efforts to reduce anthropogenic emission in polluted regions. Our results show a significant decreasing trend in the PM2.5 concentration in heavily polluted regions of eastern China, with an annual decrease of ∼7% compared with measurements in 2013. The measured decreased concentrations of SO2, NO2 and CO (a proxy for anthropogenic volatile organic compounds) could explain a large fraction of the decreased PM2.5 concentrations in different regions. As a consequence, the heavily polluted days decreased significantly in corresponding regions. Concentrations of organic aerosol, nitrate, sulfate, ammonium and chloride measured in urban Beijing revealed a remarkable reduction from 2013 to 2017, connecting the decreases in aerosol precursors with corresponding chemical components closely. However, surface-ozone concentrations showed increasing trends in most urban stations from 2013 to 2017, which indicates stronger photochemical pollution. The boundary-layer height in capital cities of eastern China showed no significant trends over the Beijing–Tianjin–Hebei, Yangtze River Delta and Pearl River Delta regions from 2013 to 2017, which confirmed the reduction in anthropogenic emissions. Our results demonstrated that the Chinese government was successful in the reduction of particulate matter in urban areas from 2013 to 2017, although the ozone concentration has increased significantly, suggesting a more complex mechanism of improving Chinese air quality in the future.

Interest in the risks posed by trace concentrations of pharmaceuticals and personal care products (PPCPs) in surface waters is increasing, particularly with regard to potential effects of long-term, low-dose exposures of aquatic organisms. In most cases, the actual studies on PPCPs were risk assessments at screening-level, and accurate estimates were scarce. In this study, exposure and ecotoxicity data of 50 PPCPs were collected based on our previous studies, and a multiple-level environmental risk assessment was performed. The 50 selected PPCPs are likely to be frequently detected in surface waters of China, with concentrations ranging from the ng L−1 to the low-g L−1, and the risk quotients based on median concentrations ranged from 2046 for nonylphenol to 0 for phantolide. A semi-probabilistic approach screened 33 PPCPs that posed potential risks to aquatic organisms, among which 15 chemicals (nonylphenol, sulfamethoxazole, di (2-ethylhexyl) phthalate, 17β-ethynyl estradiol, caffeine, tetracycline, 17β-estradiol, estrone, dibutyl phthalate, ibuprofen, carbamazepine, tonalide, galaxolide, triclosan, and bisphenol A) were categorized as priority compounds according to an optimized risk assessment, and then the refined probabilistic risk assessment indicated 12 of them posed low to high risk to aquatic ecosystem, with the maximum risk products ranged from 1.54% to 17.38%. Based on these results, we propose that the optimized risk assessment was appropriate for screening priority contaminants at national scale, and when a more accurate estimation is required, the refined probability risk assessment is useful. The methodology and process might provide reference for other research of chemical evaluation and management for rivers, lakes, and sea waters.

Abstract The formation mechanism of aerosol sulfate during wintertime haze events in China is still largely unknown. As companions, SO 2 and transition metals are mainly emitted from coal combustion. Here, we argue that the transition metal-catalyzed oxidation of SO 2 on aerosol surfaces could be the dominant sulfate formation pathway and investigate this hypothesis by integrating chamber experiments, numerical simulations and in-field observations. Our analysis shows that the contribution of the manganese-catalyzed oxidation of SO 2 on aerosol surfaces is approximately one to two orders of magnitude larger than previously known routes, and contributes 69.2% ± 5.0% of the particulate sulfur production during haze events. This formation pathway could explain the missing source of sulfate and improve the understanding of atmospheric chemistry and climate change.

Synthetic aperture radar (SAR) image classification is a hot topic in the interpretation of SAR images. However, the absence of effective feature representation and the presence of speckle noise in SAR images make classification difficult to handle. In order to overcome these problems, a deep convolutional autoencoder (DCAE) is proposed to extract features and conduct classification automatically. The deep network is composed of eight layers: a convolutional layer to extract texture features, a scale transformation layer to aggregate neighbor information, four layers based on sparse autoencoders to optimize features and classify, and last two layers for postprocessing. Compared with hand-crafted features, the DCAE network provides an automatic method to learn discriminative features from the image. A series of filters is designed as convolutional units to comprise the gray-level cooccurrence matrix and Gabor features together. Scale transformation is conducted to reduce the influence of the noise, which integrates the correlated neighbor pixels. Sparse autoencoders seek better representation of features to match the classifier, since training labels are added to fine-tune the parameters of the networks. Morphological smoothing removes the isolated points of the classification map. The whole network is designed ingeniously, and each part has a contribution to the classification accuracy. The experiments of TerraSAR-X image demonstrate that the DCAE network can extract efficient features and perform better classification result compared with some related algorithms.

Knowledge of the hazards and associated risks from chemicals discharged to the environment has grown considerably over the past 40 years. This improving awareness stems from advances in our ability to measure chemicals at low environmental concentrations, recognition of a range of effects on organisms, and a worldwide growth in expertise. Environmental scientists and companies have learned from the experiences of the past; in theory, the next generation of chemicals will cause less acute toxicity and be less environmentally persistent and bioaccumulative. However, researchers still struggle to establish whether the nonlethal effects associated with some modern chemicals and substances will have serious consequences for wildlife. Obtaining the resources to address issues associated with chemicals in the environment remains a challenge.

Abstract. A 6-year-long high-resolution Chinese air quality reanalysis (CAQRA) dataset is presented in this study obtained from the assimilation of surface observations from the China National Environmental Monitoring Centre (CNEMC) using the ensemble Kalman filter (EnKF) and Nested Air Quality Prediction Modeling System (NAQPMS).This dataset contains surface fields of six conventional air pollutants in China (i.e. PM2.5, PM10, SO2, NO2, CO, and O3) for the period 2013–2018 at high spatial (15 km×15 km) and temporal (1 h) resolutions. This paper aims to document this dataset by providing detailed descriptions of the assimilation system and the first validation results for the above reanalysis dataset. The 5-fold cross-validation (CV) method is adopted to demonstrate the quality of the reanalysis. The CV results show that the CAQRA yields an excellent performance in reproducing the magnitude and variability of surface air pollutants in China from 2013 to 2018 (CV R2=0.52–0.81, CV root mean square error (RMSE) =0.54 mg/m3 for CO, and CV RMSE =16.4–39.3 µg/m3 for the other pollutants on an hourly scale). Through comparison to the Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) dataset produced by the European Centre for Medium-Range Weather Forecasts (ECWMF), we show that CAQRA attains a high accuracy in representing surface gaseous air pollutants in China due to the assimilation of surface observations. The fine horizontal resolution of CAQRA also makes it more suitable for air quality studies on a regional scale. The PM2.5 reanalysis dataset is further validated against the independent datasets from the US Department of State Air Quality Monitoring Program over China, which exhibits a good agreement with the independent observations (R2=0.74–0.86 and RMSE =16.8–33.6 µg/m3 in different cities). Furthermore, through the comparison to satellite-estimated PM2.5 concentrations, we show that the accuracy of the PM2.5 reanalysis is higher than that of most satellite estimates. The CAQRA is the first high-resolution air quality reanalysis dataset in China that simultaneously provides the surface concentrations of six conventional air pollutants, which is of great value for many studies, such as health impact assessment of air pollution, investigation of air quality changes in China, model evaluation and satellite calibration, optimization of monitoring sites, and provision of training data for statistical or artificial intelligence (AI)-based forecasting. All datasets are freely available at https://doi.org/10.11922/sciencedb.00053 (Tang et al., 2020a), and a prototype product containing the monthly and annual means of the CAQRA dataset has also been released at https://doi.org/10.11922/sciencedb.00092 (Tang et al., 2020b) to facilitate the evaluation of the CAQRA dataset by potential users.

To improve air quality, China has been implementing strict clean air policies since 2013. These policies not only substantially improved air quality but may also modify the spatial distribution of air pollution, since urban emission sources were under stricter control and some were moved to rural regions with lower air quality improvement targets and lacking of monitoring. Here, we predicted satellite-based monthly PM2.5 concentrations during 2000–2018 at a 1-km resolution with complete spatial-temporal coverage to analyze changes in the spatial pattern of PM2.5 pollution in China. We found that the PM2.5 concentration in urban regions was higher than that in rural regions of the same city by an average of 3.3 μg/m3 during 2000–2018. This urban-rural disparity in PM2.5 concentration significantly increased from 2.5 μg/m3 in 2000 and peaked in 2007 of 3.8 μg/m3, then it sharply declined by 49% during 2013–2018 with the implementation of clean air policies. This shrinkage in the urban-rural PM2.5 gap was partly due to the 1.3 μg/m3 greater average decrease in the PM2.5 level in the urban region than in the rural region of the same town during 2013–2018 on average. We also observed that cities that started monitoring earlier experienced greater decreases in the urban-rural PM2.5 difference, and regions surrounding monitor showed significantly greater PM2.5 decrease than regions far away from monitor during 2013–2018. Additionally, clean air policies modified the relationship between PM2.5 concentrations and per capita gross domestic product (GDP), leading to a lower PM2.5 level with the same per capita GDP after 2013. Emissions in rural and suburban regions should be considered to further improve air quality in China.

Increased human activity threatens inland water quality in China. Major efforts have been made to alleviate water pollution since 2001. Understanding how water quality responds to these forces can help to guide future efforts to maintain water security and sustainability. We here analyzed the nationwide variability of inland water quality across China from 2003 to 2017 and its responses to anthropogenic discharges. We show that water quality has been improved markedly or was maintained at favorable levels over the country because of reduced discharges in the industrial, rural, and urban residential sectors. However, growing discharges from the agricultural sector threaten these gains. Moreover, the present status of water pollution is relatively severe in north and northeast China. Our findings suggest that China's water quality would further benefit from more flexible strategies for mitigation measures, which respond to regional differences in the factors that influence water pollution levels in specific regions.

Cationic polymers, known for their highly positive charges, have historically dominated the materials used in bioengineering. However, the demand for intelligent systems with high efficiency, bio-mimetic and tunable features is increasing. Artificial composites that mimic biorecognition and periodic structures may propel the development of advanced materials with outstanding properties. Polyethyleneimines (PEIs) constitute a valuable class of polycations because they have repetitive structural units, a wide molecular weight range and flexible polymeric chains, which facilitate customization of functional composites. Specific advantageous features could be introduced by purposeful modification or functionalization, such as specificity and sensitivity, distinct geometry, biocompatibility, and long service life. Thus, PEIs have been rapidly used in a wide range of applications in the fields of biomedicine, biotechnology and biomaterials science. This article provides an overview of recent advancements in the fabrication of PEI-based materials and corresponding applications in gene and drug delivery, bio-inhibitors, bio-separation, bioimaging, cell culture, and production of antibacterial and self-healing materials. The effects of molecular weight, topological structure, positive charges and hydrophilic properties on the performance of PEIs have been illustrated in detail. Finally, current technological limitations, research challenges, and future aspects are also discussed.

China has made considerable efforts to mitigate the pollution of lakes over the past decade, but the success rate of these restoration actions at a national scale remains unclear. The present study compiled a 13-year (2005-2017) comprehensive dataset consisting of 24,319 records from China's 142 lakes and reservoirs. We developed a novel Water Quality Index (WQI-DET), customized to China's water quality classification scheme, to investigate the spatio-temporal pollution patterns. The likelihood of regime shifts during our study period is examined with a sequential algorithm. Our analysis suggests that China's lake water quality has improved and is also characterized by two WQI-DET abrupt shifts in 2007 and 2010. However, we also found that the eutrophication problems have not been eradicated and heavy metal (HM) pollution displayed an increasing trend. Our study suggests that the control of Cr, Cd and As should receive particular attention in an effort to alleviate the severity of HM pollution. Priority strategies to control HM pollution include the reduction of the contribution from mining activities and implementation of soil remediation in highly polluted areas. The mitigation efforts of lake eutrophication are more complicated due to the increasing importance of internal nutrient loading that can profoundly modulate the magnitude and timing of system response to external nutrient loading reduction strategies. We also contend that the development of a rigorous framework to quantify the socioeconomic benefits from well-functioning lake and reservoir ecosystems is critically important to gain leeway and keep the investments to the environment going, especially if the water quality improvements in many Chinese lakes and reservoirs are not realized in a timely manner.

Bacteria influence site-specific disease etiology and the host's ability to metabolize xenobiotics, such as polycyclic aromatic hydrocarbons (PAHs). Lung cancer in Xuanwei, China has been attributed to PAH-rich household air pollution from burning coal. This study seeks to explore the role of lung microbiota in lung cancer among never smoking Xuanwei women and how coal burning may influence these associations. DNA from sputum and buccal samples of never smoking lung cancer cases (n = 8, in duplicate) and controls (n = 8, in duplicate) in two Xuanwei villages was extracted using a multi-step enzymatic and physical lysis, followed by a standardized clean-up. V1-V2 regions of 16S rRNA genes were PCR-amplified. Purified amplicons were sequenced by 454 FLX Titanium pyrosequencing and high-quality sequences were evaluated for diversity and taxonomic membership. Bacterial diversity among cases and controls was similar in buccal samples (P = 0.46), but significantly different in sputum samples (P = 0.038). In sputum, Granulicatella (6.1 vs. 2.0%; P = 0.0016), Abiotrophia (1.5 vs. 0.085%; P = 0.0036), and Streptococcus (40.1 vs. 19.8%; P = 0.0142) were enriched in cases compared with controls. Sputum samples had on average 488.25 species-level OTUs in the flora of cases who used smoky coal (PAH-rich) compared with 352.5 OTUs among cases who used smokeless coal (PAH-poor; P = 0.047). These differences were explained by the Bacilli species (Streptococcus infantis and Streptococcus anginosus). Our small study suggests that never smoking lung cancer cases have differing sputum microbiota than controls. Further, bacteria found in sputum may be influenced by environmental exposures associated with the type of coal burned in the home.

Short chain chlorinated paraffins (SCCPs) are under the evaluation for inclusion into the Stockholm Convention on persistent organic pollutants. However, information on their bioconcentration and biomagnification in marine ecosystems is unavailable, limiting the evaluation of their ecological risks. In this study, seawater, sediment, zooplankton, invertebrates, and fishes collected from Liaodong Bay, Bohai Sea, North China were analyzed to investigate the residual level, congener group profile, bioaccumulation, and trophic transfer of SCCPs in a marine food web. The total concentrations of SCCPs ranged from 4.1 to 13.1 ng L(-1) in seawater, 65 to 541 ng g(-1) (dw) in sediment, and 86 to 4400 ng g(-1) (ww) in organisms. Correspondence analysis indicated the relative enrichment of C10Cl5 and C11Cl5 formula groups in most aquatic organisms. Both the logarithm bioaccumulation factors (log BAFs: 4.1-6.7) and biota-sediment accumulation factors (BSAFs: 0.1-7.3) of individual congeners implied the bioaccumulation of SCCPs. The trophic magnification factor (TMF) of ∑SCCPs was determined to be 2.38 in the zooplankton-shrimp-fish food web, indicating biomagnification potential of SCCPs in the marine ecosystem. The TMF values of individual congener groups significantly correlated with their log KOW values.

formed one or more days prior to arrival was twice that formed on the arrival day. This suggests that control measures would be more effective if they were implemented two days prior to haze episodes. In contrast to Beijing, haze in Tianjin was governed by transport from outside sources, whereas in cities located in Hebei province this episode resulted from local emissions.

oxidation generally occurred at the amino moiety on the molecule, whereas •OH reaction experienced multi-site hydroxylation. Both these reactions preserve the basic parent structure of the compounds and raise concerns that the routes of phototransformation give rise to intermediates with similar antimicrobial potency as the parent SAs. We therefore recommend that these phototransformation pathways are included in risk assessments concerning the presence and fate of SAs in waste and surface waters.

Abstract A total of 8218 pelagic microplastic samples from the world’s oceans were synthesized to create a dataset composed of raw, calibrated, processed, and gridded data which are made available to the public. The raw microplastic abundance data were obtained by different research projects using surface net tows or continuous seawater intake. Fibrous microplastics were removed from the calibrated dataset. Microplastic abundance which fluctuates due to vertical mixing under different oceanic conditions was standardized. An optimum interpolation method was used to create the gridded data; in total, there were 24.4 trillion pieces (8.2 × 10 4 ~ 57.8 × 10 4 tons) of microplastics in the world’s upper oceans.

Abstract. The chemical mechanisms responsible for rapid sulfate production, an important driver of winter haze formation in northern China, remain unclear. Here, we propose a potentially important heterogeneous hydroxymethanesulfonate (HMS) chemical mechanism. Through analyzing field measurements with aerosol mass spectrometry, we show evidence for a possible significant existence in haze aerosols of organosulfur primarily as HMS, misidentified as sulfate in previous observations. We estimate that HMS can account for up to about one-third of the sulfate concentrations unexplained by current air quality models. Heterogeneous production of HMS by SO2 and formaldehyde is favored under northern China winter haze conditions due to high aerosol water content, moderately acidic pH values, high gaseous precursor levels, and low temperature. These analyses identify an unappreciated importance of formaldehyde in secondary aerosol formation and call for more research on sources and on the chemistry of formaldehyde in northern China winter.

As many antibiotics are ionizable and may have different dissociation forms in the aquatic environment, we hypothesized that the different dissociation species have disparate photolytic pathways, products, and kinetics, and adopted ciprofloxacin (CIP) as a case to test this hypothesis. Simulated sunlight experiments and matrix calculations were performed to differentiate the photolytic reactivity for each dissociation species (H4CIP(3+), H3CIP(2+), H2CIP(+), HCIP(0), and CIP(-)). The results prove that the five dissociation species do have dissimilar photolytic kinetics and products. H4CIP(3+) mainly undergoes stepwise cleavage of the piperazine ring, while H2CIP(+) mainly undergoes defluorination. For H3CIP(2+), HCIP(0), and CIP(-), the major photolytic pathway is oxidation. By density functional theory calculation, we clarified the defluorination mechanisms for the five dissociation species at the excited triplet states: All the five species can defluorinate by reaction with hydroxide ions (OH(-)) to form hydroxylated products, and H2CIP(+) can also undergo C-F bond cleavage to produce F(-) and a carbon-centered radical. This study is a first attempt to differentiate the photolytic products and mechanisms for different dissociation species of ionizable compounds. The results imply that for accurate ecological risk assessment of ionizable emerging pollutants, it is necessary to investigate the environmental photochemical behavior of all dissociation species.

Humans are exposed to an ever-increasing number of environmental toxicants, some of which have gradually been elucidated to be important risk factors for metabolic diseases, such as diabetes and obesity. These metabolism-sensitive diseases typically occur when key metabolic and signaling pathways were disrupted, which can be influenced by the exposure to contaminants such as endocrine disrupting chemicals (EDCs), along with genetic and lifestyle factors. This promotes the concept and research on environmental metabolism disrupting chemicals (MDCs). In addition, identifying endogenous biochemical markers of effect linked to disease states is becoming an important tool to screen the biological targets following environmental contaminant exposure, as well as to provide an overview of toxicity risk assessment. As such, the current review aims to contribute to the further understanding of exposome and human health and disease by characterizing environmental exposure and effect metabolic biomarkers. We summarized MDC-associated metabolic biomarkers in laboratory animal and human cohort studies using high throughput targeted and nontargeted metabolomics techniques. Contaminants including heavy metals and organohalogen compounds, especially EDCs, have been repetitively associated with metabolic disorders, whereas emerging contaminants such as perfluoroalkyl substances and microplastics have also been found to disrupt metabolism. In addition, we found major limitations in the effective identification of metabolic biomarkers especially in human studies, toxicological research on the mixed effect of environmental exposure has also been insufficient compared to the research on single chemicals. Thus, it is timely to call for research efforts dedicated to the study of combined effect and metabolic alterations for the better assessment of exposomic toxicology and health risks. Moreover, advanced computational and prediction tools, further validation of metabolic biomarkers, as well as systematic and integrative investigations are also needed in order to reliably identify novel biomarkers and elucidate toxicity mechanisms, and to further utilize exposome and metabolome profiling in public health and safety management.