Trends of perfluorochemicals in Greenland ringed seals and polar bears: Indications of shifts to decreasing trends

Time-series of perfluorinated alkylated substances (PFASs) in East Greenland polar bears and East and West Greenland ringed seals were updated in order to deduce whether a response to the major reduction in perfluoroalkyl production in the early 2000s had occurred. Previous studies had documented an exponential increase of perfluorooctane sulphonate (PFOS) in liver tissue from both species. In the present study, PFOS was still the far most dominant compound constituting 92% (West Greenland ringed seals), 88% (East Greenland ringed seals) and 85% (East Greenland polar bears). The PFOS concentrations increased up to 2006 with doubling times of approximately 6 years for the ringed seal populations and 14 years in case of polar bears. Since then a rapid decrease has occurred with clearing half-lives of approximately 1, 2 and 4 years, respectively. In polar bears perfluorohexane sulphonate (PFHxS) and perfluorooctane sulphonamide (PFOSA) also showed decreasing trends in recent years as do perfluorodecanoic acid (PFDA) and perfluoroundecanoic acid (PFUnA). For the West Greenland ringed seal population perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), PFDA and PFUnA peaked in the mid 2000s, whereas PFNA, PFDA and PFUnA in the East Greenland population have been stable or increasing in recent years. The peak of PFASs in Greenland ringed seals and polar bears occurred at a later time than in Canadian seals and polar bears and considerably later than observed in seal species from more southern latitudes. We suggest that this could be explained by the distance to emission hot-spots and differences in long-range transport to the Arctic.     

Multivariate Analysis of Interactions Between Phytoplankton Biomass and Environmental Variables in Taihu Lake, China

Phytoplankton variation in large shallow eutrophic lakes is characterized by high spatial and temporal heterogenity. Understanding the pattern of phytoplankton variation and the relationships between it and environmental variables can contribute to eutrophic lakes management. In this study Taihu Lake, one of the largest eutrophic fresh water lake in China, was taken as study area. The water body of Taihu Lake was divided into five regions viz. Wuli bay (WB), Meilian Bay (MB), West Taihu Lake (WTL), Main Body of Taihu Lake (MBTL) and East Taihu Lake (ETL). Concentrations of chlorophyll-a and the related environmental variables were determined in each region in the period 2000–2003. Factor analysis and multivariate analysis were applied to evaluate the interactions between phytoplankton variation and environmental variables. Results showed that the highest average concentrations of TN, TP and Chl-a were observed in WB, followed in a descending order by MB and WTL, and the lowest concentrations of TN, TP and Chl-a were observed in MBTL and ETL. Chl-a and TP concentrations in most regions (except ETL) declined during the study period. It suggested that to some extent the lake was recovering from eutrophication. However, persistent ascending of TN and NH₄–N in all five regions indicated the deteriorating of water quality in the study period. Results of multivariate showed that the relationships between phytoplankton biomass and environmental variables varied among regions. TP illustrated itself a controlling role on phytoplankton in WB, MB, WTL and MBTL according to the significant positive relations to phytoplankton biomass in these regions. Nitrogen could be identified as a limiting factor to phytoplankton biomass in ETL in view of the positive correlations between TN and phytoplankton and between NH₄–N and phytoplankton. Spatial variation of interactions between phytoplankton and environmental parameters suggested proper eutrophication control measures were needed to restore ecological system in each region of Taihu Lake.     

近17年鄱阳湖区生态系统健康时空变化研究

以遥感影像和社会统计数据为基础,构建基于压力-状态-响应(P-S-R)概念模型的鄱阳湖区生态系统健康评价指标体系,并建立湖区生态系统健康评价模型,通过对生态系统健康指数的计算与分析,揭示鄱阳湖区生态系统健康的时空变化特征.研究结果表明,在人类生产活动的影响下,近17年鄱阳湖区生态系统结构渐趋不合理,生态系统功能有所减弱,虽然湖区生态系统健康总体处于一般水平,但人类活动干扰的不断加强,导致湖区生态系统健康正逐步向着恶化方向发展.湖区生态系统健康在空间分布上呈现出南北分异的特点,南部工业化、城镇化水平较高的地区生态系统健康状况较差,经济发展水平较低的北部地区,生态系统健康状况则相对较好.     

连云港近岸海域2011~2016年环境变化研究

依据2011年2月~2016年1月在连云港近岸海域进行的19个季节航次海洋环境综合调查结果,分析探讨了该海域主要海水要素的季节变化趋势和相关性,结合历史资料阐述和评价了海域的营养状态水平、环境质量现状及变化趋势,对存在的环境问题进行了分析.结果表明：研究海域水质状况总体良好;水质评价结果显示无机氮（DIN）是海域内最主要的环境污染因子,且DIN含量近年来有逐渐增加的趋势,年均值已经超过二类海水水质标准;此外其他环境污染因子是活性磷酸盐（DIP）、化学需氧量（COD）和油类.调查期间研究海域处于富营养化状态,潜在富营养化分析显示氮磷比值（N/P）有逐渐增加的趋势;绝大多数季节的有机污染状况为轻度污染状态.研究结论对科学、系统的认识和评估连云港近海生态环境现状及预测未来生态环境变化趋势具有重要的参考价值,对连云港近海海洋生态环境的可持续发展具有十分重要的科学意义和实际应用价值     

太行山脉不同量级降雨侵蚀力时空变化特征

基于太行山脉及其周边地区76个气象监测站点1954-2016年逐日降雨数据,建立了基于不同量级侵蚀性年降雨量模拟年降雨侵蚀力的简易模型,并采用气候倾向率、小波周期分析、重心模型、Co-Kriging插值、Mann-kendall非参数趋势检验以及突变分析等方法,分析了不同量级降雨侵蚀力时空变化特征及其影响因素。结果表明：（1）太行山脉地区年降雨侵蚀力简易模型为y=0.182x₁^1.095+5.463x₂^0.982+9.401x₃^1.017+15.258x₄-26.753,且多年降雨侵蚀力呈小幅上升趋势,10年间上升了2.4 MJ·mm·hm^-2·h^-1·a^-1,同时存在约20年的主周期和6年的小周期变化,并在1996年发生显著突变;中雨和大雨侵蚀力63年间均呈上升趋势,而暴雨和特大降雨侵蚀力呈下降趋势;春秋两季主要受中雨和大雨侵蚀力的影响,而夏季则主要受特大降雨侵蚀力的影响。（2）太行山脉地区各量级降雨侵蚀力最大值主要分布于太行山脉东南部以及五台山地区,最小值主要分布于地区的东北部;运用重心模型发现各量级降雨侵蚀力重心在春夏季节整体向东部以及东北部地区进行迁移,而秋冬季节则向南部以及西南地区迁移,形成一个循环,且与冬夏季风的控制时间相符。（3）太行山脉地区不同量级降雨侵蚀力与侵蚀性降雨量均呈显著正相关（P<0.01）,大雨和特大降雨侵蚀力分别与纬度、海拔呈显著负相关（P<0.05）,这主要与副热带高压移动、地形、海拔以及自然地理环境等因素有关。     

鄱阳湖微囊藻毒素时空分布格局及其与理化和生物因子的关系

本文分别于2012年4月(春季)、8月(夏季)、10月(秋季)和2013年1月(冬季)在鄱阳湖进行了4次野外调查和样品采集,采用超高效液相色谱-串联质谱仪(UPLC-MS/MS)对鄱阳湖水柱中常见的3种微囊藻毒素(MC-RR、MC-YR和MCLR)的质量浓度进行定量分析,探寻了微囊藻毒素(microcystins,MCs)质量浓度的时空变化规律及其与湖泊环境理化因子和生物因子之间的关系.结果表明,MC-RR是鄱阳湖MCs的主要毒素种类.胞内微囊藻毒素(intracellular MCs,IMCs)与微囊藻生物量(r=0.47,P0.01)、颤藻生物量(r=0.68,P0.01)、蓝藻生物量(r=0.56,P0.01)、Chl-a(r=0.28,P0.01)之间均具有显著的正相关关系,但与鱼腥藻生物量之间没有明显的相关关系(P0.05),这说明微囊藻和颤藻是鄱阳湖微囊藻毒素的主要产毒藻类.IMCs与水温(r=0.51,P0.01)、透明度(r=0.69,P0.01)、Fe(r=0.43,P0.01)和Zn(r=0.43,P0.01)之间均呈现显著的正相关关系,与TN(r=-0.44,P0.01)、TP(r=-0.29,P0.01)、NO-2-N(r=-0.28,P0.05)、NH+4-N(r=-0.33,P0.05)、Ca(r=-0.34,P0.01)和Mg(r=-0.35,P0.05)均呈现显著的负相关关系,但与pH、PO3-4-P、NO-3-N、电导率、高锰酸盐指数、Cu离子之间的相关关系不显著(P0.05),这说明光照强度(透明度反映)、氮、磷、水温是控制鄱阳湖微囊藻毒素产生的重要因子,金属离子Ca、Mg、Fe、Zn在一定程度上能影响微囊藻毒素的产生.鄱阳湖IMCs和胞外微囊藻毒素(extracellular MCs,EMCs)呈现相似的季节变化趋势,即夏季最高,其次为秋季,冬季和春季较低.鄱阳湖IMCs的空间分布整体上呈现东部湖汊群、松门山周围以及蚌湖和蚌湖进入鄱阳湖的入湖口较高,其它区域较低的趋势,而EMCs的高值区位于松门山周围和蚌湖及其入湖口.     

长江流域径流模拟及其对极端降雨的响应

研究流域径流量变化可为水资源科学调配、利用开发、水旱灾害防治、水环境污染整治和国民经济可持续发展等提供重要依据.但近年来受全球变暖影响,极端气候事件,尤其是极端降雨的发生频率和强度出现了变化,直接或间接影响径流量变化.运用SWAT模型模拟1965~2019年间长江流域径流时空变化规律,分析了不同极端降雨条件下径流对降雨的响应.结果表明,1965~2019年间长江流域径流变化并不显著,流域总径流和中下游径流均经历了"枯-丰-枯-丰"4个阶段.极端降雨情景模拟发现,50 a一遇极端降雨下,长江上、中和下游代表性子流域日均径流变化率分别为6200%、21%和15%,月均径流变化率为355%、5%和1.3%,年均变化率为78%、1%和0.24%.而100 a一遇极端降雨下,3个子流域日均径流变化率分别为8000%、25%和17%,月均径流变化率为437%、7%和1.5%,年均变化率为96%、1.2%和0.28%.研究结果可为流域水资源管理和利用及洪涝灾害预测与防控等提供理论依据.     

A stochastic-advective transport model for NAPL dissolution and degradation in non-uniform flows in porous media

Remediation schemes for contaminated sites are often evaluated to assess their potential for source zone reduction of mass, or treatment of the contaminant between the source and a control plane (CP) to achieve regulatory limits. In this study, we utilize a stochastic stream tube model to explain the behavior of breakthrough curves (BTCs) across a CP. At the local scale, mass dissolution at the source is combined with an advection model with first-order decay for the dissolved plume. Field-scale averaging is then employed to account for spatial variation in mass within the source zone, and variation in the velocity field. Under the assumption of instantaneous mass transfer from the source to the moving liquid, semi-analytical expressions for the BTC and temporal moments are developed, followed by derivation of expressions for effective velocity, dispersion, and degradation coefficients using the method of moments. It is found that degradation strongly influences the behavior of moments and the effective parameters. While increased heterogeneity in the velocity field results in increased dispersion, degradation causes the center of mass of the plume to shift to earlier times, and reduces the dispersion of the BTC by lowering the concentrations in the tail. Modified definitions of effective parameters are presented for degrading solutes to account for the normalization constant (zeroth moment) that keeps changing with time or distance to the CP. It is shown that anomalous dispersion can result for high degradation rates combined with wide variation in velocity fluctuations. Implications of model results on estimating cleanup times and fulfillment of regulatory limits are discussed. Relating mass removal at the source to flux reductions past a control plane is confounded by many factors. Increased heterogeneity in velocity fields causes mass fluxes past a control plane to persist, however, aggressive remediation between the source and CP can reduce these fluxes.     

广东省“十二五”生态环境时空变化趋势及影响因素

基于2011—2015年Landsat7、Landsat8等卫星遥感影像,结合土壤侵蚀面积、水资源量、降雨量、污染物排放量等统计数据,按照《生态环境状况评价技术规范》(HJ 192—2015),研究评价广东省"十二五"期间生态环境状况及其时空变化趋势,并对其影响因素进行综合分析。结果表明,广东省的生态环境状况总体为优,各市生态环境状况均属优、良,粤北生态环境状况整体最好;广东省及各市生态环境状况稳中趋好,但呈现温和地波动变化;主要污染物排放量下降和水资源总量提高是促进生态环境状况改善的主要原因。     

Kernel-based home range method for data with irregular sampling intervals

Studies of habitat selection and movements often use radio-tracking data for defining animal home ranges. Home ranges (HR) can be approximated by a utilization density distribution (UD) that instead of assuming uniform use of areas within HR boundary provides a probabilistic measure of animal space use. In reality, radio-tracking data contain periods of frequent autocorrelated observations interspersed with temporally more independent observations. Using such temporally irregular data directly may result in biased UD estimates, because areas that have been sampled intensively receive too much weight. The problem of autocorrelation has been tackled by resampling data with an appropriate time interval. However, resampling may cause a large reduction in the data set size along with a loss of information. Evidently, biased UD estimates or reduction in data may prejudice the results on animal habitat selection and movement. We introduce a new method for estimating UDs with temporally irregular data. The proposed method, called the time kernel, accounts for temporal aggregation of observations and gives less weight to temporally autocorrelated observations. A further extension of the method accounts also for spatially aggregated observations with relatively low weights given to observations that are both temporally and spatially aggregated. We test the behaviour of the time kernel method and its spatiotemporal version using simulated data. In addition, the method is applied to a data set of brown bear locations.