Modeling multi-source plastic pollution yield and transport driven by catchment hydrometeorological processes.

Plastic pollution has emerged as a global environmental concern, impacting both terrestrial and marine ecosystems. However, understanding of plastic sources and transport mechanism at the catchment scale remains limited. This study introduces a multi-source plastic yield and transport model, which integrates catchment economic activities, climate data, and hydrological processes. Model parameters were calibrated using a combination of field observations, existing literature, and statistical random sampling techniques. The model demonstrated robust performance in simulating both plastic yield and transport from 2010 to 2020 in the upper and middle Mulan River Catchment, located in southeast China. The annual average yield coefficients were found to closely align with existing estimations, and the riverine outflow exhibited a high correlation coefficient of 0.97, with biases ranging from -63.0 % to -21.4 % across all monitoring stations. The analysis reveals that, on average, 12.5 ± 2.5 % of the total plastic yield is transported to rivers annually, with solid waste identified as the primary source, accounting for 37.8 ± 20.7 % of the total load to rivers, followed by agricultural film (26.4 ± 9.8 %), impermeable surfaces (21.5 ± 10.3 %), urban and rural sewage (10.4 ± 5.0 % and 3.0 ± 1.5 %, respectively), and industrial wastewater (0.9 ± 0.7 %). The annual average outflow was estimated to between 9.3 and 43.0 ton/year (median: 23.1) at a 95 % confidence level. This study not only provides insights into the primary sources and transport pathways of plastic pollution at the catchment scale, but also offers a valuable tool for informing effective plastic pollution mitigation strategies.

Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds.

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO3-N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts.

Spatially resolved transcriptomic profiling of placental development in dairy cow.

The placenta plays a crucial role in successful mammalian reproduction. Ruminant animals possess a semi-invasive placenta characterized by a highly vascularized structure formed by maternal endometrial caruncles and fetal placental cotyledons, essential for full-term fetal development. The cow placenta harbors at least two trophoblast cell populations: uninucleate (UNC) and binucleate (BNC) cells. However, the limited capacity to elucidate the transcriptomic dynamics of the placental natural environment has resulted in a poor understanding of both the molecular and cellular interactions between trophoblast cells and niches, and the molecular mechanisms governing trophoblast differentiation and functionalization. To fill this knowledge gap, we employed Stereo-seq to map spatial gene expression patterns at near single-cell resolution in the cow placenta at 90 and 130 days of gestation, attaining high-resolution, spatially resolved gene expression profiles. Based on clustering and cell marker gene expression analyses, key transcription factors, including YBX1 and NPAS2, were shown to regulate the heterogeneity of trophoblast cell subpopulations. Cell communication and trajectory analysis provided a framework for understanding cell-cell interactions and the differentiation of trophoblasts into BNCs in the placental microenvironment. Differential analysis of cell trajectories identified a set of genes involved in regulation of trophoblast differentiation. Additionally, spatial modules and co-variant genes that help shape specific tissue structures were identified. Together, these findings provide foundational insights into important biological pathways critical to the placental development and function in cows.

New model for predicting the development of pancreatic pseudocyst secondary to acute pancreatitis.

Pancreatic pseudocyst (PPC) increases the risk of a poor prognosis in in patients with acute pancreatitis (AP). Currently, an efficient tool is not available for predicting the risk of PPC in patients with AP. Therefore, this research aimed to explore the risk factors associated with PPC secondary to AP and to develop a model based on clinical information for predicting PPC secondary to AP. This study included 400 patients with acute pancreatitis and pancreatic pseudocyst secondary to acute pancreatitis admitted to the emergency department and gastroenterology department of The First Affiliated Hospital of the University of Science and Technology of China from January 2019 to June 2022. Participants were divided into no PPCs (321 cases) and PPCs (79 cases). Independent factors of PPC secondary to AP were analyzed using univariate and multivariate logistic regression. The nomogram model was constructed based on multivariate logistic regression analyses, which included all risk factors, and evaluated using R. We enrolled 400 eligible patients and allocated 280 and 120 to the training and test sets, respectively. Clinical features, including severe pancreatitis history [odds ratio (OR) = 4.757; 95% confidence interval (CI): 1.758-12.871], diabetes mellitus (OR = 6.919; 95% CI: 2.084-22.967), history of biliary surgery (OR = 9.232; 95% CI: 3.022-28.203), hemoglobin (OR = 0.974; 95% CI: 0.955-0.994), albumin (OR = 0.888; 95% CI: 0.825-0.957), and body mass index (OR = 0.851; 95% CI: 0.753-0.962), were significantly associated with the incidence of PPC after AP in the training sets. Additionally, the individualized nomogram demonstrated good discrimination in the training and validation samples with good calibration, The area under the curve and 95% CI of the nomogram were 0.883 (0.839-0.927) in the training dataset and 0.839 (0.752-0.925) in the validation set. We developed a nomogram model of PPC secondary to AP using R Studio. This model has a good predictive value for PPC in patients with AP and can help improve clinical decision-making.

Analyzing factors driving of eutrophication of river-type urban landscape lakes.

The eutrophication of river-type urban landscape (RTUL) lakes is different from that of natural lakes. In this study, Xiaofu Lake, a typical RTUL lake with high anthropogenic interference, was used as the study area. Monitoring data from 2018 to 2020 were used to analyze the temporal and spatial distribution characteristics of chlorophyll a (Chl-a) concentrations with meteorological, hydrodynamic, and nutrient factors. Correlation and regression analyses were used to identify the relationship between the factors influencing eutrophication and the Chl-a. The MIKE21 model is used to simulate changes in water quality indicators. The study determined the relationship between river water quality and environmental factors and explored the causes of eutrophication in the water bodies of Xiaofu Lake. The results showed that from 2018 to 2020, the water quality showed seasonal variation and differences in spatial distribution. Except for total nitrogen, which remained at a high level (average 8.23 mg/L), other water qualities remained between classes II and IV. The proportions of mild, moderate, and severe eutrophication in the study area were 25%, 69%, and 6%, respectively. Indicators that were highly correlated with water eutrophication were turbidity, water temperature, total phosphorus, and permanganate index. The contribution of water temperature, ammonia nitrogen, and permanganate index to eutrophication was 30.5%, 22.6%, and 20.9%, respectively. The high proportion of sewage in the source of recharge water is one of the reasons for the deterioration of water quality. In addition, the change in water eutrophication was closely related to the gate operation in the region. PRACTITIONER POINTS: There are differences between river-type urban landscape (RTUL) lakes and natural lakes, and the conditions that cause eutrophication are different. RTUL are subject to strong human interference and rely on water transfer and gate scheduling to maintain water quantity. The high proportion of sewage treatment plant tailwater in upstream water is the main reason for the long-term pollution of RTUL. The indicators highly correlated with water eutrophication are turbidity, water temperature, total phosphorus, and permanganate index.

Spatio-Temporal Distribution Characteristics and Driving Factors of Main Grain Crop Water Productivity in the Yellow River Basin.

To reveal the relationship between agricultural water resource consumption and grain production in the Yellow River Basin, the irrigation water productivity (WPI), crop water productivity (WPC), total inflow water productivity (WPT), and eleven influencing factors were selected. The spatial and temporal distribution characteristics and driving factors of water productivity of the main crops in the Yellow River Basin were analyzed with the spatial autocorrelation analysis, grey correlation analysis, sensitivity analysis, and relative contribution rate. The results showed that the minimum mean values of WPI, WPC, and WPT were 0.22, 0.35, and 0.18 kg/m3 in Qinghai, respectively, the maximum mean value of WPI was 2.11 kg/m3 in Henan, and the maximum mean values of WPC and WPT were 0.71 and 0.61 kg/m3 in Shandong, respectively. The changing trends in WPI and WPT in Qinghai and in WPC in Shandong were insignificant, whereas the WPI, WPC, and WPT in other provinces showed a significant increasing trend. Water productivity displayed a certain spatial clustering feature in the Yellow River Basin in different years, such as a high-high (H-H) aggregation in Henan in 2005, and an H-H aggregation in Shanxi in 2015 for WPI. The water productivity had a significant positive correlation with the consumption of chemical fertilizer with a 100% effective component (CFCEC), effective irrigated area (EIA), plastic film used for agriculture (PFUA), and total power of agricultural machinery (AMTP), while it had a significant negative correlation with the persons engaged in rural areas (PERA). There was a large grey correlation degree between the water productivity and the average annual precipitation (AAP), CFCEC, PFUA, consumption of chemical pesticides (CFC), and AMTP in the Yellow River Basin, but their sensitivity was relatively small. The main driving factors were EIA (8.98%), agricultural water (AW, 15.55%), AMTP (12.64%), CFCEC (12.06%), and CPC (9.77%) for WPI; AMTP (16.46%), CFCEC (13.25%), average annual evaporation (AAE, 12.94%), EIA (10.49%), and PERA (10.19%) for WPC; and EIA (14.26%), AMTP (13.38%), AAP (12.30%), CFCEC (10.49%), and PFUA (9.69%) for WPT in the Yellow River Basin. The results can provide support for improving the utilization efficiency of agricultural water resources, optimizing the allocation of water resources, and implementing high-quality agricultural developments in the Yellow River Basin.

Spatiotemporal evolution of chlorophyll-a concentration from MODIS data inversion in the middle and lower reaches of the Hanjiang River, China.

Owing to limitations in monitoring technologies, monitoring the algae content index of water has lagged behind the conventional water quality index. As a result, sample monitoring in many rivers has been too sparse, and the monitoring data have been inconsistent; thus the evolution of water eutrophication has not been fully reflected. This study focused on the middle and lower reaches of the Hanjiang River, China, and correlated moderate-resolution imaging spectroradiometer (MODIS) remote sensing data with measured chlorophyll-a concentrations. Algorithm settings for chlorophyll-a inversion in the middle and lower reaches of the Hanjiang River were established via the trial and error method. The algorithm model for the middle and lower reaches of the Hanjiang River chlorophyll-a concentration inversion, and the results of the inversion analysis for the spatiotemporal evolution characteristics were subsequently used to determine the influence of various environmental factors on changes in the chlorophyll-a concentration. The results indicate that (1) the band combinations B7/(B6 + B5), B7/B5, B4-B2, and B4/(B3 + B2) are well-correlated with the chlorophyll-a concentration; (2) the back propagation (BP) neural network model inversion achieved a better fit and more accurate inversion results than the band ratio model; (3) temporally, algal outbreaks were mostly concentrated occurring in February and March, with higher chlorophyll-a concentrations in the water column during 2000, 2006, 2007, and 2008; (4) spatially, high chlorophyll-a concentrations were observed in the Zhongxiang, the Shayang, and upper Xiantao sections; and (5) increases in the water temperature and decreases in the water level and flow rate could lead to higher chlorophyll-a concentrations; similarly, nutrient salts were identified to be a major factor contributing to changes in the chlorophyll-a concentrations.

Settling velocity of irregularly shaped microplastics under steady and dynamic flow conditions.

The behavior of microplastics (MPs) in aquatic environments can vary significantly according to their composition, shape, and physical and chemical properties. To predict the settling trajectory of MPs in aquatic environments, this study investigates the settlement law of MPs under static and dynamic conditions. Four types of materials were analyzed, namely polystyrene, polyamide, polyethylene terephthalate, and polyvinyl chloride. Approximately 1270 MP particles with irregular shapes (near-sphere, polygonal ellipsoid, and fragment) were selected for the settling experiments. The experimental results show that the main factors affecting the settling velocity of MPs were shape irregularity, density, and particle size. The settling velocity of irregular MPs was significantly lower than that of perfectly spherical MPs. We proposed a model that predicts the correlation between the settling velocity of MPs and their shape, density, particle size, and water density.

Eutrophication model driven by light and nutrients condition change in sluice-controlled river reaches.

River eutrophication has become a challenging environmental problem worldwide because of the strong interference of anthropogenic activities and hydraulic structures. The driving mechanism of algae growth in sluice-controlled river reaches (SCRRs) is more complicated than that of natural rivers, because the operation mode of the sluices is an important influencing factor which changes the light and nutrient conditions of the water body. The main purpose of this study was to assess algal growth in SCRRs under external conditions and sluice regulation. In this study, a eutrophication model for SCRRs was developed based on the mechanism of river hydrodynamics and algae growth kinetics, considering the variation in underwater light intensity and nutrient condition. By choosing the light intensity, phosphorus concentration and sluice gate opening size as the influencing factors, 16 different combination conditions were proposed by orthogonal experimental design, and eutrophication of water bodies in the SCRRs was simulated using a eutrophication model. In the scenario design, four gate opening sizes were set, and the light intensity and nutrients were enlarged or reduced based on the original monitoring data. The results showed that both light intensity and nutrient concentration can promote the algal growth within a suitable range, and increasing the gate opening size can inhibit algal growth.

Effects of hydrological change on the risk of riverine algal blooms: case study in the mid-downstream of the Han River in China.

Algal blooms usually occur in semi-closed water bodies such as lakes or estuaries; however, it has occurred frequently in the mid-downstream of the Han River (MSHR) in China since the 1990s. We made a comparative analysis of the hydrological conditions and identified the hydrological condition thresholds that induce algal blooms. From the hydrodynamic point of view, the changes and characteristics of the hydrological conditions in the MSHR were analyzed. Furthermore, the influence on the risk of algal blooms under different design water transfer schemes for the middle route of the South-to-North Water Diversion Project (SNWDP) was studied. The results indicated that (1) the flow in the MSHR less than 900 m3/s and water level in the Yangtze River higher than 14 m provided a suitable hydrological environment for diatoms multiply. (2) The flow of the MSHR showed a downtrend, while the water level of the Yangtze River showed an uptrend. There were variations in hydrological processes. Through specific IHA index analysis, the fact of flow reduction in the MSHR was demonstrated, and further indicated that algal bloom outbreak was in low flow period. (3) The water transfer in the middle route of SNWDP affected the risk probability of algal blooms. The more the amount of water transfer, the greater the risk probability of algal blooms. It was the Water Diversion Project from Yangtze River to Han River (WDPYHR) that replenished flow of the MSHR and was conducive to the prevention and control of algal bloom risk.

New species and records of Chapsa (Graphidaceae) in China.

We studied the genus Chapsa in China based on morphological characteristics, chemical traits and molecular phylogenetic analysis. One species new to science (C.murioelongata M.Z. Dou & M. Li) and two records new to China were found (C.wolseleyana Weerakoon, Lumbsch & Lücking and C.niveocarpa Mangold). Chapsamurioelongata sp. nov. is characterised by its lobed thalline margin, orange discs with white pruina, clear hymenium, and submuriform and long ascospores. Chapsawolseleyana was recombined into Astrochapsa based on phenotypic traits. Sequences of this species are for the first time reported here and phylogenetic analyses of three loci (mtSSU, ITS and nuLSU) supported the position of this species within Chapsa. A key for the Chapsa species known in China is provided.

Fe3O4 accelerates tetracycline degradation during anaerobic digestion: Synergistic role of adsorption and microbial metabolism.

Antibiotics contaminants, for example, tetracycline (TC) in the environment have attracted extensive attention around the world, and appropriate treatments for such contaminants are urgently required. In this study, five groups of anaerobic reactors supplemented with different amounts of Fe3O4 were operated periodically to investigate their performance on TC removal. The results showed that Fe3O4 effectively promoted TC removal. Compared with the control reactor, the TC removal efficiency was increased by 7.3% when co-digested with glucose, and increased by 40.4% when mono TC was digested in reactors with 5.0 g/L Fe3O4. Further analysis indicated that the probable mechanism of Fe3O4 promoting TC removal was through TC being adsorbed from the liquid onto Fe3O4, making TC more available for microbes to be biodegraded. Microbial community analysis indicated that the bacteria (Klebsiella, Pseudomonas, and Escherichia) related to TC removal were enriched, which meant more pathways for TC removal were available following the addition of Fe3O4. In addition, in the Fe3O4-supplemented reactors, syntrophic metabolism (between Desulfovibrio and Methanobacterium, Azonexus and Methanobacterium) were possibly established, which played an important role in improving TC removal and CH4 production. The electron transport system data further confirmed these results. The functional gene classification for Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that the dominant functions enhanced by Fe3O4 supplementation was microbial metabolic activities.

Abundance and removal characteristics of microplastics at a wastewater treatment plant in Zhengzhou.

The widespread use of synthetic polymers has made microplastic (MP) a new type of contaminant that has attracted worldwide attention. Studies have shown that wastewater treatment plants (WWTPs) are an important source of MP collection in the natural environment. This study investigated the removal efficiency and migration characteristics of MPs by sampling the sewage from each treatment section of a WWTP in Zhengzhou, China. The results showed that the abundance of MPs in the influent water and primary, secondary, and tertiary treatment discharges was 16.0, 10.3, 4.5, and 2.9 MP/L, respectively, and the total removal rate of MPs from the influent to the final effluent reached 81.9%. The MPs in the WWTP were mainly small-sized (0.08-0.55 mm), followed by medium-sized (0.55-1.7 mm). Fibers were the dominant MP shape in both the water and sediment samples. Black (36%) and red (23%) were the dominant MP colors. Six different polymer types of MPs were detected, which were mainly polypropylene followed by polyethylene. In general, for the MPs in the WWTP, the removal rate of fragments can reach 97.08%, which is better than that of fibers (70.50%); the removal rate of small-sized can reach 95.86%, which is better than that of medium-sized (83.53%) and large-sized (70.00%). In this study, primary treatment has better effects in eliminating fragments and large-sized MPs; secondary treatment has better effects in eliminating fibers and small-sized MPs. Although WWTPs have a very good removal effect on MPs, 870 million MP/d are still discharged into nearby rivers from WWTPs with a treatment scale of 300,000 m3/day. Graphical Abstract.

Enhanced two-phase anaerobic digestion of waste-activated sludge by combining magnetite and zero-valent iron.

Previous studies have found that magnetite can promote the hydrolysis-acidification but inhibit the methanogenesis, while zero-valent iron (ZVI) only promoted the methanogenesis. Therefore, a new two-phase anaerobic digestion model, in which magnetite was added to the first phase, and ZVI was added to the second phase, was proposed to promote both hydrolysis-acidification and methanogenesis and avoid magnetite inhibition. The results showed that in the new model, methane production was improved by 10.2% and 18.1% and chemical oxygen demand (COD) removal was improved by 7.9% and 10.9% compared with reactors that included only magnetite and only ZVI, respectively. In the new model reactors, inhibition of methanogenesis by magnetite was avoided compared with that of the magnetite-only reactors, and hydrolysis efficiency was improved via dissimilatory iron reduction (DIR) compared with that of ZVI-only reactors. The data on volatile fatty acids (VFAs), coenzyme F420 and electron transfer system (ETS) further confirmed these conclusions.

An optimization model of sewage discharge in an urban wetland based on the multi-objective wolf pack algorithm.

The Longfeng Wetland of Daqing City in China was taken as the research object to determine a reasonable sewage reduction scheme and resolve the pollution of urban wetland ecosystems. First, the main pollutants, including dichromate oxidizability (CODCr), ammonia nitrogen (NH3-N), total phosphorus (TP), and petroleum, were selected as indices. A two-dimensional hydrodynamic and water quality coupling model was established using MIKE 21. An optimal regulation method to improve the water quality of the wetland was then proposed following the numerical simulation method, and a multi-objective optimization model is established. The model establishes two objective functions based on wetland pollutant and water quality requirements. The model's constraints include hydrodynamic conditions and water quality conditions, and it considers the control point of the sewage concentration, sewage outfall processing capacity, depth of treatment, and changes in the water cycle. The wolf pack algorithm is introduced to resolve the multi-objective problem of sewage outfall optimization, and an optimal sewage scheme is obtained. According to the results of the scheme, some measures are proposed to manage the pollutants in urban wetland waters.

Multi-factor identification and modelling analyses for managing large river algal blooms.

River algal blooms have become a newly emerging global environmental issue in recent decades. Compared with water eutrophication in lakes and reservoirs, algal blooms in large river systems can cause more severe consequences to watershed ecosystems at the watershed scale. However, reveal the causes of river algal blooms remains challenging in the interdisciplinary of hydrological-ecological-environmental research, due to its complex interaction mechanisms impacted by multiple factors. In addition, there were still considerable uncertainties on the characteristics, impacts, driving factors, as well as the applicable water system models for river algal blooms. In this paper, we reviewed existing literature to elaborate the definition and negative effects of river algal blooms. We analyzed sensitive factors including nutrient, hydrological and climatic elements. We also discussed the application of ecohydrological models under complicated hydrological conditions. Finally, we explored the essence of the river algal bloom by the interaction effects of physical and biogeochemical process impacted by of climate change and human activities. The model-data integration accounting for multi-factor effects was expected to provide scientific guidance for the prevent and control of algal blooms in large river systems.

Multi-phase transformation model of water quality in the sluice-controlled river reaches of Shayinghe River in China.

To better understand the complex transformation mechanisms of pollutants in different phases in sluice-controlled river reaches (SCRRs), a multi-phase transformation model of water quality is proposed. This model mainly describes the interactions of the water body, suspended matter, deposited sediments, and organisms. Mathematical expressions were first derived to describe the mass transportation processes in different phases of the river system. The multi-phase transformation model in SCRRs was then established with defined physical mechanisms. Monitored data from the operation of Huaidian sluice were used to identify and validate the parameters of the transformation model and to simulate the spatial and temporal changes of pollutants in different phases. Four findings were made from the results. Firstly, the concentration values of pollutants in each phase in the upper and lower river reaches of the sluice are affected by flow, mode of sluice operation, and algal growth and enrichment. Secondly, the reaction processes in the upper and lower river reaches of the sluice indicate different dominant mechanisms according to the change in sluice operation. Thirdly, sluice operation leads to stronger exchanges between the water body and external materials because of the increased water disturbance. Fourthly, in the early period of the experiment, changes in the alga concentrations were mainly affected by water movement. In the later period, changes in the alga concentrations were mainly affected by the obstruction of the sluice in the upstream section, while these were affected by flow velocity, flow volume, and changes in nutrient concentration in the downstream section.

Health risk assessment of cadmium pollution emergency for urban populations in Foshan City, China.

With rapid socioeconomic development, water pollution emergency has become increasingly common and could potentially harm the environment and human health, especially heavy metal pollution. In this paper, we investigate the Cd pollution emergency that occurred in the Pearl River network, China, in 2005, and we build a migration and transformation model for heavy metals to simulate the spatiotemporal distribution of Cd concentrations under various scenarios of Cd pollution emergency in Foshan City. Moreover, human health hazard and carcinogenic risk for local residents of Foshan City were evaluated. The primary conclusions were as follows: (1) the number of carcinogen-affected people per year under scenario 1 reached 254.41 when the frequency was 0.1 year/time; specifically, the number of people with cancer per year in the area of the Datang, Lubao, and Nanbian waterworks was 189.36 accounting for 74% of the total number per year; (2) at the frequency of 5 years/time, the Lubao waterwork is the only one in extremely high- or high-risk grade, while besides it, the risk grade in the Datang, Nanbian, Xinan, Shitang, and Jianlibao waterworks is in the extremely high or high grade when the frequency is 0.1 year/time; (3) when Cd pollution accidents with the same level occurs again, Cd concentration decreases to a low level in the water only if the migration distance of Cd is at least 40-50 km. Based on the health risk assessment of Cd pollution, this study gives the recommendation that the distance should keep above 50 km in tidal river network of the Pearl River Delta between those factories existing the possibility of heavy metal pollution and the drinking water source. Only then can the public protect themselves from hazardous effects of higher levels of heavy metal.

[Effects of micro-fertilizers foliar spray on the content of main effective components of Angelica dahurica]. / 叶面喷施微肥对川白芷主要有效成分含量的影响.

The zinc, boron and molybdenum were sprayed on the foliage of Angelica dahurica du-ring the vigorous growth period to explore the effects of the combination of zinc, boron and molybdenum fertilizers on the content of main effective components of A. dahurica, and to find out the optimum spraying amount. The results showed that the application of zinc, boron and molybdenum foliar spray was beneficial to increase the content of imperatorin and total cumarin, whereas had no effect on the content of the isoimperatorin. The effect of boron spray on the accumulation of imperatorin and total coumarin was the most significant, followed by the zinc and molybdenum. The interaction between boron and molybdenum had a negative cooperative effect on the content of imperatorin, while the interaction between zinc and molybdenum had a positivecooperative effect on the content of total coumarin. The contents of total coumarin reached over 0.7% respectively, with the complex fertilizer spray of zinc at 0.15-0.24 kg·hm-2, boron at 2.02-2.36 kg·hm-2 and molybdenum at 0.08-0.13 kg·hm-2. The contents of imperatorin reached over 0.2% respectively, with the complex fertilizer spray of zinc at 0.15-0.20 kg·hm-2, boron at 1.37-1.47 kg·hm-2 and molybdenum at 0.09-0.13 kg·hm-2. It was concluded that the application of zinc, boron and molybdenum foliar spray was beneficial to promote the quality of A. dahurica by enhancing its accumulation of coumarin.

Temporal and spatial characteristics of the water pollutant concentration in Huaihe River Basin from 2003 to 2012, China.

Based on the monitoring data of 78 monitoring stations from 2003 to 2012, five key water quality indexes (biochemical oxygen demand: BOD5, permanganate index: CODMn, dissolved oxygen: DO, ammonium nitrogen: NH3-N, and total phosphorus: TP) were selected to analyze their temporal and spatial characteristics in the highly disturbed Huaihe River Basin via Mann-Kendall trend analysis and boxplot analysis. The temporal and spatial variations of water pollutant concentrations in the Huaihe River Basin were investigated and analyzed to provide a scientific basis for water pollution control, water environment protection, and ecological restoration. The results indicated that the Yinghe River, Quanhe River, Honghe River, Guohe River, and Baohe River were the most seriously polluted rivers, followed by Hongze Lake, Luoma Lake, Yishuhe River, and Nansi Lake. BOD5, CODMn, and NH3-N were the major pollution indexes, for which the monitoring stations reported that more than 40 % of the water quality concentrations exceeded the class IV level. There were 21, 50, 36, and 21 monitoring stations that recorded significantly decreasing trends for BOD5, CODMn, NH3-N, and TP, respectively, and 39 monitoring stations showed a significantly increasing trend for DO. Moreover, the water quality concentrations had a certain concentricity and volatility according to boxplot analysis for the 20 monitoring stations. The majority of monitoring stations recorded a large fluctuation for the monitoring indexes in 2003 and 2004, which indicated that the water quality concentrations were unstable. According to the seasonal variations of the water quality concentrations in the mainstream of Huaihe River, the monthly variation trends of the BOD5, CODMn, DO, NH3-N, and TP concentrations were basically consistent among the seven monitoring stations. The BOD5, CODMn, NH3-N, and TP concentrations were affected by the change of the stream discharge; changes in DO and NH3-N concentrations were influenced by the regional environmental temperature, and the DO and NH3-N concentrations decreased when the water temperature increased.