高铁-光催化氧化协同去除藻毒素的研究

研究了高铁-光催化氧化体系去除水中藻毒素的效能.结果表明,通过投加10mg/L的高铁到光催化体系中,由于高铁的强氧化性及其还原产物可作为电子捕获剂的特点,可将光催化效率从63%提高到100%,实现快速完全去除藻毒素的目的.同时对照研究了高铁、光催化、Fe³⁺-光催化、高铁-光催化4种不同反应体系对藻毒素去除的效能.结果显示,单纯的高铁或光催化都可以降解一部分藻毒素,但去除率低,分别为54%和63%,且需大剂量的高铁投加或大大延长光照时间.而在Fe³⁺-光催化、高铁-光催化体系中,只需投加10mg/L的三价铁或高铁,就可以将藻毒素去除率提高到73%和100%,但采用高铁协同光催化体系比三价铁协同光催化体系更有效.也就是说在本体系中,高铁具有十分重要的作用,明显存在着高铁与TiO₂光催化的协同效应.     

交替好氧/缺氧短程硝化反硝化生物脱氮Ⅰ.方法实现与控制

采用实时控制策略和曝气 搅拌交替运行方式在 ( 2 6± 1 )℃下开发了一种新型短程硝化反硝化生物脱氮工艺 :实时控制交替好氧 缺氧短程硝化反硝化脱氮工艺 .并对其与实时控制传统SBR法短程硝化反硝化脱氮和预先设定时间控制交替好氧 缺氧短程硝化反硝化脱氮工艺进行了比较研究 .结果显示 ,实时控制交替好氧 缺氧短程硝化反硝化脱氮工艺无论从硝化速率、反硝化速率还是从硝化时间、反硝化时间上均优于实时控制传统SBR法短程硝化反硝化脱氮和预先设定时间控制交替好氧 缺氧短程硝化反硝化脱氮两种工艺 .其硝化速率和反硝化速率分别是预先设定时间控制交替好氧 缺氧短程硝化反硝化工艺的 1 3 8倍和 1 2 5倍 ,是实时控制传统SBR法短程硝化反硝化脱氮工艺的 1 82倍和 1 6 1倍 .因此 ,实时控制交替好氧 缺氧短程硝化反硝化脱氮工艺不但能够合理分配曝气和搅拌时间 ,而且还能提高硝化、反硝化速率 ,缩短反应时间 ,从而达到降低运行成本的目的     

长江输送颗粒态磷的生物可利用性及其环境地球化学意义

模拟不同采样时间长江输送悬浮态颗粒物实验,通过测定藻类增长潜力来讨论颗粒态磷的生物可利用性.结果表明,悬浮物中生物可利用磷(SSBAP)含量在不同采样时间(2001年2月、5月、12月和2002年8月)的平均值分别为(288 3±49 4),(228 2±38 2),(251 6±32 9)和(182 0±8 1)mg·kg-1.不同藻种的SSBAP BAP平均值为:铜绿微囊藻(Microcystisaerugilnosa)54 2%,斜生栅藻(Scendesmusobliquus)60 3%.在4次采样中,通过大通站的BAP浓度均大于水体富营养化的限制值(0 02mg·L-1),说明SSBAP对长江流域、河口及近海区营养盐的贡献是不容忽视的,颗粒态磷是长江河口及近海区富营养化的潜在污染源,它对河口及近海的生态环境造成很大影响.     

磷肥对砷污染土壤的植物修复效率的影响:田间实例研究

通过田间试验研究施用磷肥对砷超富集植物蜈蚣草(PterisvittataL.)生长和砷污染土壤修复效率的影响.结果表明,适量施用磷肥促进蜈蚣草的生长,显著提高其生物量,但过量施用磷肥对植物产量无贡献.随着磷肥施用量的增加,蜈蚣草地上部砷含量呈先增加后减少的趋势,理论上在施磷量为340kg·hm-2时,砷含量可达最高(1622mg·kg-1).磷的含量与施磷量呈极显著的正相关关系.施磷量为200kg·hm-2的砷累积量最高,是不施磷处理砷累积量的2 4倍及600kg·hm-2施磷量砷累积量的1 2倍.种植蜈蚣草7个月后,土壤总砷均有不同程度的下降,施磷量为200kg·hm-2的土壤中砷含量下降5 0mg·kg-1,土壤修复效率最高(7 84%).对照和600kg·hm-2施磷量处理的土壤修复效率分别为2 31%和6 63%.理论上达到最大土壤修复效率所需施磷量为369kg·hm-2.施用磷肥可以维持土壤有效态砷含量在蜈蚣草种植前后变化不大,保证蜈蚣草下个生育期对砷的吸收.这些结果说明施用磷肥是蜈蚣草等砷超富集植物在现场修复中的必要手段,优化施磷技术可大大提高砷污染土壤的修复效率.     

UV/H2O2降解水中2,4-二氯酚实验研究

研究溶液浊度、pH值及不同光源等因素对 2 ,4 二氯酚降解的影响 ,确定了UV/H2 O2 光氧化降解 2 ,4 二氯酚反应器的水质适用范围 (浊度小于 6NTU)。在 30W的紫外光照射下 ,2 0mg/L 2 ,4 二氯酚 ,H2 O2 的投加剂量为 1 .2 8mg/L时 ,90min内 2 ,4 二氯酚去除率可达到 95 % .实验证明UV/H2 O2 光氧化技术是低浊度水深度处理的一种有效方法 .     

长江中下游浅水湖泊沉积物中磷的形态及其与水相磷的关系

研究了长江中下游22个不同生态类型的浅水湖泊表层沉积物中磷的地球化学形态及水相磷含量等水质特征.对沉积物中磷形态的连续提取分析发现,自然粒度下,绝大部分湖泊的沉积物中90%以上的磷是以生物较难利用的形态存在的,活性磷所占比例很小.而在严重污染的城市湖泊中,活性磷含量则可以占到总磷的35%以上.沉积物中活性磷含量的高低与总磷含量并不一致.水草的存在对水相磷含量及沉积物中磷的活性都有显著的影响.水相磷的含量与沉积物中交换态磷的含量、沉积物铁磷比有显著的相关关系.研究表明,沉积物地球化学性质、水体营养盐含量及浅水湖泊生态类型之间存在复杂而密切的联系.     

长江中下游平原三个湖泊表层沉积物对磷的吸附特征

以长江中下游太湖、巢湖和龙感湖等3个湖泊表层沉积物(0～1cm)为对象,研究了不同沉积物对湖水中磷的吸附特性,并探讨了沉积物表面特性和化学组分等因素对磷的吸附行为的影响.结果表明:表层沉积物对磷的吸附作用主要发生在快吸附过程的前1～2h之内;湖泊表层沉积物对磷的吸附基本符合修正后的Langmuir型等温方程,不同采样点的表层沉积物中本底磷吸附量(QNAP)以及磷饱和吸附量(Qmax)差别显著,与采样点所处环境条件有很大关系.同时,沉积物的饱和吸附量与比表面积、活性铁、铝含量和有机质含量有较好的正相关性,相关系数分别为0 92,0 98,0 78和0 96;活性铁、铝含量与有机质含量之间也有较好的正相关性;颗粒物Zeta电位在一定程度上影响沉积物对磷的吸附能力.     

微生物菌剂对生活污水的除臭实验

利用微生物菌剂对生活污水进行除臭处理,结果表明:对于嗅阈值比较高的混合生活污水,利用XM液体菌剂和XM固体菌剂都可以消除生活污水的臭味,二者都取得较好的效果。但在实际的应用方面,固体菌剂更具有使用方面的优越性。应用XM固体菌剂对混合生活污水进行除臭处理时,添加0.2%的除臭效果为最好。     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

A pyrazine based metal-organic framework for selective removal of copper from strongly acidic solutions

● pz-UiO-66 was synthesized facilely by a solvothermal method. ● Efficient capture of copper from highly acidic solution was achieved by pz-UiO-66. ● pz-UiO-66 exhibited excellent selectivity and capacity for copper capture. ● Pyrazine-N in pz-UiO-66 was shown to be the dominant adsorption site. The selective capture of copper from strongly acidic solutions is of vital importance from the perspective of sustainable development and environmental protection. Metal organic frameworks (MOFs) have attracted the interest of many scholars for adsorption due to their fascinating physicochemical characteristics, including adjustable structure, strong stability and porosity. Herein, pz-UiO-66 containing a pyrazine structure is successfully synthesized for the efficient separation of copper from strongly acidic conditions. Selective copper removal at low pH values is accomplished by using this material that is not available in previously reported metal–organic frameworks. Furthermore, the material exhibits excellent adsorption capacity, with a theoretical maximum copper uptake of 247 mg/g. As proven by XPS and FT-IR analysis, the coordination of pyrazine nitrogen atoms with copper ions is the dominant adsorption mechanism of copper by pz-UiO-66. This work provides an opportunity for efficient and selective copper removal under strongly acidic conditions, and promises extensive application prospects for the removal of copper in the treatment for acid metallurgical wastewater.