Detecting the effects of coal mining,acid rain,and natural gas extraction in Appalachian basin streams in Pennsylvania (USA) through analysis of barium and sulfate concentrations

To understand how extraction of different energy sources impacts water resources requires assessment of how water chemistry has changed in comparison with the background values of pristine streams. With such understanding, we can develop better water quality standards and ecological interpretations. However, determination of pristine background chemistry is difficult in areas with heavy human impact. To learn to do this, we compiled a master dataset of sulfate and barium concentrations ([SO₄], [Ba]) in Pennsylvania (PA, USA) streams from publically available sources. These elements were chosen because they can represent contamination related to oil/gas and coal, respectively. We applied changepoint analysis (i.e., likelihood ratio test) to identify pristine streams, which we defined as streams with a low variability in concentrations as measured over years. From these pristine streams, we estimated the baseline concentrations for major bedrock types in PA. Overall, we found that 48,471 data values are available for [SO₄] from 1904 to 2014 and 3243 data for [Ba] from 1963 to 2014. Statewide [SO₄] baseline was estimated to be 15.8 ± 9.6 mg/L, but values range from 12.4 to 26.7 mg/L for different bedrock types. The statewide [Ba] baseline is 27.7 ± 10.6 µg/L and values range from 25.8 to 38.7 µg/L. Results show that most increases in [SO₄] from the baseline occurred in areas with intensive coal mining activities, confirming previous studies. Sulfate inputs from acid rain were also documented. Slight increases in [Ba] since 2007 and higher [Ba] in areas with higher densities of gas wells when compared to other areas could document impacts from shale gas development, the prevalence of basin brines, or decreases in acid rain and its coupled effects on [Ba] related to barite solubility. The largest impacts on PA stream [Ba] and [SO₄] are related to releases from coal mining or burning rather than oil and gas development.

     

磁絮凝高效处理高浊度废水的性能及机理研究

自来水供水厂在运行过程会产生大量高浊度废水,其中富集了许多微生物、有机物及无机杂质,若直接排放会严重污染河流水体及周边土壤.采用磁絮凝工艺处理自来水厂供水过程中产生的高浊度废水,通过单因素和正交试验考察了聚合氯化铝(PAC)投加量、磁种(Fe3O4)投加量、废水初始pH值和沉降时间对废水中浊度、COD和UV254去除效...     

可见光响应GO/g-C3N4改性平板膜的制备条件及其表面性能

以氧化石墨烯(GO)与石墨相氮化碳(g-C_3N_4)为改性剂,采用界面聚合与超滤抽吸结合,对PVDF平板超滤膜(简称原膜)进行表面改性,得到可见光响应的纳米复合改性膜(简称:GO/g-C_3N_4改性膜),研究改性膜的制备条件及其表面性能.结果表明:(1)最佳制备条件为:g-C_3N_410 mg、g-C_3N_4/GO比值为80、苯胺(An)浓度0.5%、An浸泡时间4 h、过硫酸铵(APS)浓度0.8 g·L~(-1)、APS浸泡时间3 h;(2)GO/g-C_3N_4改性膜表面亲水性与抗污染性能显著提高,表面接触角下降55.1%,通量衰减率下降46.3%,经水力冲洗后膜通量恢复率增加51.5%;(3)改性膜的机械强度与拉伸强度增强,拉伸弹性模量增加;(4)GO/g-C_3N_4改性膜表面具有较强的可见光活性,最大吸收边带为495 nm,表面改性功能层的禁带宽度(Eg)值为2.5 e V.改性膜对罗丹明B(Rh B)的可见光催化降解去除率达到81.2%,而原膜对Rh B吸附去除率仅为42.2%.     

纳米SiO2在含阴离子表面活性剂低浊水处理中的应用

在含有阴离子表面活性剂-十二烷基硫酸钠(SDS)的6 NTU高岭土悬浊液中,改变SDS的浓度,投加纳米SiO2与聚合铝PAC进行动态混凝实验与静沉实验,借助图像分析技术与分形理论,探讨了纳米SiO2与PAC处理含SDS低浊水的作用机理、絮凝效果与形态学特征.结果表明:①纳米SiO2与SDS使高岭土粒子表面负电性增强.纳米SiO2的絮凝机理以吸附架桥为主.②纳米SiO2对SDS的去除效果优于PAC.SDS浓度越高,去除效果越显著.但纳米SiO2对无机高岭土粒子的处理能力不如PAC,PAC絮凝后的上清液浊度低.当SDS浓度增至10 mg/L时,纳米SiO2对SDS的去除率高,而PAC对SDS的絮凝能力弱,PAC对无机颗粒的去除效果也下降.③助凝剂纳米SiO2较强的吸附活性能加快PAC絮体成长为结构密实的RLCA构型,分维值高,絮凝效果好.     

Reliability and input-data induced uncertainty of the EPIC model to estimate climate change impact on sorghum yields in the U.S. Great Plains

Crop simulation models are frequently used to estimate the impact of climate change on crop production. However, few studies have evaluated the model performance in ways that most researchers practiced in climate impact studies. In this article, we examined the reliability of the EPIC model in simulating grain sorghum (Sorghum bicolor (L.) Moench) yields in the U.S. Great Plains under different climate scenarios, namely in years with normal or extreme temperature and precipitation. We also investigated model uncertainties introduced by input data that are not site-specific but commonly used or available for climate change studies. Historical field trial data of sorghum at the Mead Experimental Center, NE, were used for model evaluations. The results showed that overall model reliability was about 56%. The mean absolute relative error (absRE) was about 29%. The degree of accuracy and reliability varied with climate-classes and nitrogen (N)-treatments. The largest bias occurred in drought years (RE = ?25%) and the most unreliable results were found in N-0 treatment (reliability = 32%). There was more than 69% probability that input-data-induced uncertainties were limited to less than 20% of absRE. Our results support the application of the EPIC model to climate change impact studies in the U.S. Great Plains. However, efforts are needed to improve the accuracy in simulating crop responses to extreme water- and nitrogen-stressed conditions.     

纳米SiO2在含阴离子表面活性剂低浊水处理中的应用

在含有阴离子表面活性剂-十二烷基硫酸钠（SDS）的6NTU高岭土悬浊液中,改变SDS的浓度,投加纳米SiO2与聚合铝PAC进行动态混凝实验与静沉实验,借助图像分析技术与分形理论,探讨了纳米SiO2与PAC处理含SDS低浊水的作用机理、絮凝效果与形态学特征。结果表明：①纳米SiO2与SDS使高岭土粒子表面负电性增强。纳米SiO2的絮凝机理以吸附架桥为主。②纳米SiO2对SDS的去除效果优于PAC。SDS浓度越高,去除效果越显著。但纳米SiO2对无机高岭土粒子的处理能力不如PAC,PAC絮凝后的上清液浊度低。当SDS浓度增至10mg／L时,纳米SiO2对SDS的去除率高,而PAC对SDS的絮凝能力弱,PAC对无机颗粒的去除效果也下降。③助凝剂纳米SiO2较强的吸附活性能加快PAC絮体成长为结构密实的RLCA构型,分维值高,絮凝效果好。