Water quality characteristics and assessment of Yongding New River by improved comprehensive water quality identification index based on game theory

The Yongding New River is essential for the water supplies of Tianjin. To date, there is no comprehensive report that assesses the year-round water quality of the Yongding New River Main stream. Moreover, little attention has been given to determining a combined weight for improving the traditional comprehensive water quality identification index (ICWQII) by the game theory. Seven water quality parameters were investigated monthly along the main stream of the Yongding New River from May 2018 to April 2019. Organic contaminants and nitrogen pollution were mainly caused by point sources pollution, and the total phosphorus mainly by non-point source pollution. Dramatic spatio-temporal variations of water quality parameters were jointly caused by different pollutant sources and hydrometeorological factors. In terms of this study, an improved comprehensive water quality identification index (ICWQII) based on entropy weight or variation coefficient and traditional CWQII underestimated the water qualities, and an ICWQII based on the superstandard multiple method overvalued the assessments. By contrast, water qualities assessments done with an ICWQII based on the game theory matched perfectly with the practical situation. The ICWQII based on game theory proposed in this study takes into account not only the degree of disorder and variation of water quality data, but also the influence of standard-exceeded pollution indicators, whose results are relatively reasonable. All findings and the ICWQII based on game theory can provide scientific support for decisions related to the water environment management of the Yongding New River and other waters.     

基于Google Earth Engine分析黄土高原植被覆盖变化及原因

为探明黄土高原植被覆盖时空变化及其原因,基于Google Earth Engine（GEE）,采用Landsat Surface Reflectance data（陆地卫星地表反射率数据）分析了黄土高原1987~2015年间植被覆盖度的时空变化规律,并借助累积量斜率变化率方法对引起植被覆盖度变化的气候和人为因素进行了量化分析.结果表明：黄土高原年均植被覆盖度由1987年的41.78%增加到2015年的53.23%,增速为0.38%/a（P<0.05）.其中,1987~1999年年均植被覆盖度变化趋势不显著（P>0.05）;而退耕还林还草工程实施以来（2000~2015年）,年均植被覆盖度显著增加（P<0.05）,增速达到0.59%/a.由像元尺度分析,黄土高原72.93%的区域植被覆盖度呈增加趋势,其中38.31%的区域增加趋势显著（P<0.05）.植被覆盖度的变化受气候和人为因素的共同影响,以1987~1999年为基准期,气候变化和人类活动对黄土高原2000~2015年间植被覆盖度变化的相对贡献率分别为23.77%、76.23%,人类活动为引起黄土高原植被覆盖度变化的主要原因.退耕还林还草工程极大地改善了黄土高原的植被覆盖状况,但是城市的扩张使得部分地区的植被覆盖呈显著退化现象.     

北京城区不同组分PM2.5散射特性及来源分析

近年来北京城区PM_2.5浓度下降伴随其中二次离子占比升高,为探索不同组分PM_2.5散射特性及其来源,于2020年12月至2021年11月开展了小时分辨率的PM_2.5及其组分浓度和散射系数的连续在线监测,分析了PM_2.5组分及散射的特征和来源.结果表明,研究期间北京城区PM_2.5最主要组分为NO^-₃,PM_2.5中ω(NO^-₃)和ω(SNA)分别为24%和46%.根据浓度和组分占比将PM_2.5划分为6种类型：优型出现频率最高,为56%,四季分布均匀,PM_2.5中ω(SNA)、ω(OM)和ω(FS)相当,分别为32%、 32%和28%;沙尘(D)型和OM(O)型全年出现频率较低,分别以FS和OM为主要组分,PM_2.5中ω(FS)和ω(OM)分别为66%和46%,主要分布于春季和夏季;OM+SO₄     

2017~2020年长江流域水体污染物通量时空变化特征分析

基于2017~2020年长江流域重要水系节点各污染物监测数据,在时空尺度下开展对长江流域干、支流水系通量变化规律的研究,从断面水量和水质及通量等方面分析其空间变化响应、年际变化趋势和通量相关性关系分析,揭示长江流域上游、中游和下游污染物通量时空贡献特征.结果表明,4年来长江流域主要污染物浓度整体呈下降趋势,总磷(TN)和氨氮(NH⁺₄-N)浓度下降较为明显,干流总氮(TN)和总磷(TP)浓度均在空间分布上呈现自西向东逐渐增高趋势,上中下游高锰酸盐指数在2017~2020年分别下降18.5%、16.0%和14.0%,以上游下降幅度最高.径流量空间分布年均值从466亿m³显著增大到9923亿m³,支流河湖水系中两湖流域水量贡献最大,主要污染物中高锰酸盐指数、总磷(TP)和总氮(TN)通量年均呈现先增后减的趋势,岷沱江、嘉陵江和中游两湖地区污染物通量对入江贡献较大,不同区域水环境下通量存在差异性.相关性和层次聚类分析结果表明,高锰酸盐指数和总磷(TP)通量与水量呈极显著性相关,通量关系间生化需氧量(BOD₅)与总氮(TN)、总磷(TP)和化学需氧量(COD)有显著相关性,主要污染物在汛期和非汛期差异性较强,在7~9月汛期反应强烈.研究结果可为长江流域水环境统筹管理与精准化防治等方面提供科学依据与理论支持.     

近40年陕西省农田土壤有机质时空变化及其影响因素

了解农田土壤有机质的时空动态变化对促进农田生态系统绿色发展具有重大意义。本研究对陕西省耕地土壤有机质含量进行测定,以期探讨长期耕种下陕西省农田土壤有机质时空变化特征及其影响因素。于2017年采集耕层土样705份,采用重铬酸钾氧化—外加热法测定其有机质含量,并运用ArcGIS 10.5和GS+9.0软件进行了数据分析。结果表明：陕西省耕地土壤有机质平均含量为15.90 g·kg^?1,4级水平占比最大;不同行政区有机质含量排序为：汉中＞西安＞安康＞咸阳＞宝鸡＞商洛＞渭南＞铜川＞延安＞榆林;陕西省各市有机质含量较20世纪80年代均有不同程度的提升,其中汉中市提升幅度最大;陕西省农田土壤有机质具有强烈的空间自相关性,最优拟合模型为高斯模型,呈现南高北低的空间分布特征;结构性因素（坡度、海拔、经度、纬度）和随机性因素（施肥、耕作、秸秆还田等）共同作用导致了陕西省农田土壤有机质的空间分布差异,不同类型土壤有机质含量差异显著（P＜0.05）。本研究为指导陕西省低碳农业的发展及实现碳达峰与碳中和提供了一定的科学依据。     

Fine particulate matter (PM2.5/PM1.0) in Beijing, China: Variations and chemical compositions as well as sources

Particulate matter (i.e., PM_1.0 and PM_2.5), considered as the key atmospheric pollutants, exerts negative effects on visibility, global climate, and human health by associated chemical compositions. However, our understanding of PM and its chemical compositions in Beijing under the current atmospheric environment is still not complete after witnessing marked alleviation during 2013–2017. Continuous measurements can be crucial for further air quality improvement by better characterizing PM pollution and chemical compositions in Beijing. Here, we conducted simultaneous measurements on PM in Beijing during 2018–2019. Results indicate that annual mean PM_1.0 and PM_2.5 concentrations were 35.49 ± 18.61 µg/m³ and 66.58 ± 60.17 µg/m³, showing a positive response to emission controls. The contribution of sulfate, nitrate, and ammonium (SNA) played an enhanced role with elevated PM loading and acted as the main contributors to pollution episodes. Discrepancies observed among chemical species between PM_1.0 and PM_2.5 in spring suggest that sand particles trend to accumulate in the range of 1–2.5 µm. Pollution episodes occurred accompanied with southerly clusters and high formation of SNA by heterogeneous reactions in summer and winter, respectively. Results from positive matrix factorization (PMF) combined with potential source contribution function (PSCF) models showed that potential areas were seasonal dependent, secondary and vehicular sources became much more important compared with previous studies in Beijing. Our study presented a continuous investigation on PM and sources origins in Beijing, which provides a better understanding for further emission control as well as a reference for other cities in developing countries.     

Determining the drivers of population structure in a highly urbanized landscape to inform conservation planning

Understanding the environmental contributors to population structure is of paramount importance for conservation in urbanized environments. We used spatially explicit models to determine genetic population structure under current and future environmental conditions across a highly fragmented, human‐dominated environment in Southern California to assess the effects of natural ecological variation and urbanization. We focused on 7 common species with diverse habitat requirements, home‐range sizes, and dispersal abilities. We quantified the relative roles of potential barriers, including natural environmental characteristics and an anthropogenic barrier created by a major highway, in shaping genetic variation. The ability to predict genetic variation in our models differed among species: 11–81% of intraspecific genetic variation was explained by environmental variables. Although an anthropogenically induced barrier (a major highway) severely restricted gene flow and movement at broad scales for some species, genetic variation seemed to be primarily driven by natural environmental heterogeneity at a local level. Our results show how assessing environmentally associated variation for multiple species under current and future climate conditions can help identify priority regions for maximizing population persistence under environmental change in urbanized regions.     

1982~2010年洞庭湖流域植被指数的变化及其与气候因子的相关分析

基于GIMMS 3 g、PAL、LTDR V3、FASIR及MODIS 5种不同的遥感影像数据,及洞庭湖流域30个气象站点的气温、降水和日照时数月值数据,采用逐像元一元线性回归模型,对比分析了在不同数据集背景下的植被变化趋势,并基于时间序列长度以及数据精度的考虑,选择GIMMS 3 g作为研究洞庭湖流域植被覆盖变化的基础数据集,进而利用相关系数和多元线性回归分析模型探讨流域植被覆盖变化与降水、气温、日照时数的关系。结果表明:(1)过去29 a间,流域GIMMS 3 g NDVI在时空尺度上均以增加趋势为主,1998~2000年出现最大的降低,以植被覆盖较好的山区减少最快;(2)去除年际变化趋势和季节性影响的NDVI与同期降水量距平、累积3个月气温距平值及同期日照时数距平值相关性程度最高;(3)统计意义上,降水量、气温和日照时数解释洞庭湖流域植被月NDVI变化的37%,日照时数对该流域NDVI变化的影响最大,其次为降水和气温;(4)在时间和空间范畴,生长季NDVI可以作为反映洞庭湖流域森林覆盖率变化的指标。     

1985—2005年聊城市土壤有机质的时空变异分析

通过统计及地质统计学方法,研究了山东省聊城市1985—2005年土壤w(有机质)的时空变异性. 结果表明:近20年来聊城市表层土壤有机质共增加了34.31×104 t,但不同土壤类型的增幅不尽相同,本底值较低的土壤亚类有机质增加较多,本底值较高的则增加较少. 2005年w(有机质)插值结果表明,研究区w(有机质)分布存在四周高、中部低的趋势. 聊城市北部、临清县南部以及高唐与茌平县之间部分区域w(有机质)比1985年下降明显,而冠县以南及以北、茌平县东部及南部部分区域的w(有机质)增加明显. 影响土壤有机质时空变异的因素主要为土壤类型和区域内农业种植及生产管理方式的改变.      

南四湖及入出湖河流水环境质量变化趋势分析

南四湖作为南水北调东线工程重要的输水通道和调蓄湖泊,其水质状况一直受到人们的广泛关注. 根据南四湖流域主要入出湖河流14个监控断面及湖内5个监测站点的数据,从年际、年内、不同时间段和不同监测站点等进行了南四湖及河流水质变化趋势的综合分析. 结果表明,2007与2000年相比,南四湖入出湖河流监控断面的ρ（COD_Cr）总体下降率达到84.2%,ρ（NH₃-N）总体下降率达到79.7%. 南四湖及河流水质总体上出现了大幅度的改善,但距离稳定达到调水水质Ⅲ类标准的要求还有较大差距. 受水文情势、底泥释放和污染源以及各项污染控制措施等因素的影响,南四湖及入出湖河流监控断面水质改善存在一定的波动现象,水体富营养化形势严峻. 提出了科学合理地计算与分配南四湖养殖承载力和流域水环境承载力,重视非点源的控制与治理,大力推进“退耕还湿、退渔还湖”策略,是当务之急.