广东省杨村华侨柑桔场土壤微量元素含量与分布的研究

采集并分析全场不同母质形成的有代表性的土壤样本142个.研究结果表明,各类土壤全B、Mo、Zn和Mn含量的平均值均低于全国平均值,全量Cu平均值高于全国平均值.有效B、Mo、Zn和Mn含量的平均值均低于临界值,有效Cu的平均值稍高于临界值;但66.7％的土样有效Cu含量低于临界值.硼、钼、锌和锰严重缺乏,铜多数缺乏.全场各类土壤的微量元素含量差异较大,各类土壤微量元素的垂直和水平分布特征不尽相同,尤其是垂直分布差异明显.从土壤微量元素的全量与母质的关系来看,以玄武岩、紫色砂页岩母质形成的土壤全量较高,砂砾岩母质形成的土壤全量中等,砂页岩和冲积物母质形成的土壤全量较低.     

南亚热带丘陵土壤水分循环及其有效性的研究──Ⅳ.丘陵土壤贮水量的增减规律

根据三年定位实测资料,阐述0～100cm土层贮水量的动态变化,分析土壤贮水增减与降雨、蒸发的关系．观测结果表明,在气候正常年,雨季土壤贮水为增量,旱季土壤贮水为减量,但在坡地不同坡段和梯地不同梯级,土壤贮水增减有差异。在旱月土壤贮水减至最低,仅相当子田间持水量的55％～80％．因此在土壤水分管理上．应当密切注意土壤贮水减量最大的时期,以采取有效措施减少土壤水分蒸发,提高土壤水分利用率。     

南亚热带丘陵土壤水分循环及其有效性的研究──Ⅷ.丘陵赤红壤水分循环与平衡数学模型

依据田间实测资料,在分析丘陵赤红壤水分性质的基础上,建立了土壤有效含水量与土壤物理粘粒含量之间的数学模型、土壤水分特征曲线数学模型、土壤月均贮水量与月降雨总量之间的数学模型和径流率与土壤表层初始含水量之间的数学模型,研究了土壤水分循环与平衡数学模型及各分量与参数的确定方法.     

广西不同地理区域森林土壤水文物理性质研究

对广西９个不同区域森林土壤（０－１００ｃｍ）水文物理性质进行测定,结果表明,不同林型的土壤容重为０．５４～１５５ｇ／ｃｍ３;总孔隙度３９％一９６．４％;最大持水量４１１．７～７５９．６ｍｍ;通气度３．２％～２７．６％;平均渗透速度０．７９～３８．５ｍｍ／ｍｉｎ。不同土类及林型的土壤容重的大小为;黄壤＜红壤和阔叶林或针阔叶混交林＜针叶林,而总孔隙度、持水量、通气度及渗透速度则相反。     

Na_2CO_3/H_2O_2“稳定”的CO_2的型体研究(Ⅱ)——“稳定性二氧化氯”溶液的UV吸收光谱、纸层析特性、微观结构和离子色谱分析

本文对以稳定剂H_2O_2和Na_2CO_3与ClO_2制备的所谓"稳定性二氧化氯"溶液的UV吸收光谱、纸层析特性、微观结构及离子色谱进行了分析,并与纯NaClO_2及ClO_2溶液做了对比.结果表明,“稳定性二氧化氯” 与NaClO_2在UV吸收光谱、层析比移值、微观结构、离子色谱这几方面都具有很好或极其相似的一致性 表明“稳定性二氧化氮’与NaClO_2溶液中氯氧化物存在型体的一致性.因此,认为“稳定性二氧化氯“溶液中ClO_2是以亚氯酸盐ClO_2~-的型体存在的.     

Enantioselective aquatic toxicity of current chiral pesticides

Chiral pesticides are ubiquitous in the aquatic environment, and their enantioselectivities in aquatic toxicity are known to be complicated. The difference in enantioselective effects between enantiomers may sometimes differ by approximately 100-fold or more, which makes it important to incorporate enantioselective effects into the risk assessment of chiral pesticides. In this paper, we reviewed relevant work on the aquatic toxicity of chiral pesticides with an emphasis on the enantioselective aquatic toxicity under both chronic and acute exposure conditions. We provided a personal account of the importance of studies on molecular mechanisms of developmental toxicity and specific endpoints such as vitellogenin, yolk sac edema and pericardial edema in future research. Given the widespread use of chiral pesticides, we suggest that a more comprehensive understanding of the significance of enantioselective aquatic toxicity will be very helpful in improving risk assessment and regulation of chiral pesticides.     

Characteristics of plankton Hg bioaccumulations based on a global data set and the implications for aquatic systems with aggravating nutrient imbalance

• Hg bioaccumulation by phytoplankton varies among aquatic ecosystems. • Active Hg uptake may exist for the phytoplankton in aquatic ecosystems. • Impacts of nutrient imbalance on food chain Hg transfer should be addressed. The bioaccumulation of mercury (Hg) in aquatic ecosystem poses a potential health risk to human being and aquatic organism. Bioaccumulations by plankton represent a crucial process of Hg transfer from water to aquatic food chain. However, the current understanding of major factors affecting Hg accumulation by plankton is inadequate. In this study, a data set of 89 aquatic ecosystems worldwide, including inland water, nearshore water and open sea, was established. Key factors influencing plankton Hg bioaccumulation (i.e., plankton species, cell sizes and biomasses) were discussed. The results indicated that total Hg (THg) and methylmercury (MeHg) concentrations in plankton in inland waters were significantly higher than those in nearshore waters and open seas. Bioaccumulation factors for the logarithm of THg and MeHg of phytoplankton were 2.4–6.0 and 2.6–6.7 L/kg, respectively, in all aquatic ecosystems. They could be further biomagnified by a factor of 2.1–15.1 and 5.3–28.2 from phytoplankton to zooplankton. Higher MeHg concentrations were observed with the increases of cell size for both phyto- and zooplankton. A contrasting trend was observed between the plankton biomasses and BAF_MeHg, with a positive relationship for zooplankton and a negative relationship for phytoplankton. Plankton physiologic traits impose constraints on the rates of nutrients and contaminants obtaining process from water. Nowadays, many aquatic ecosystems are facing rapid shifts in nutrient compositions. We suggested that these potential influences on the growth and composition of plankton should be incorporated in future aquatic Hg modeling and ecological risk assessments.     

A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

• A spectral machine learning approach is proposed for predicting mixed antibiotic. • Pretreatment is far simpler than traditional detection methods. • Performance of the model is compared in different influencing factors. • Spectral machine learning is promising in the detection of complex substances. Antibiotics are widely used in medicine and animal husbandry. However, due to the resistance of antibiotics to degradation, large amounts of antibiotics enter the environment, posing a potential risk to the ecosystem and public health. Therefore, the detection of antibiotics in the environment is necessary. Nevertheless, conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation, which impose considerable time and economic costs. In this paper, we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning. With the help of a modified spectrometer, a large number of characteristic images were generated to map antibiotic information. The relationship between characteristic images and antibiotic concentrations was established by machine learning model. The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model. The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment. The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies.     

Functional flax fiber with UV-induced switchable wettability for multipurpose oil-water separation

● A PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed. ● The property of flax fiber could be switched from hydrophobicity to hydrophilicity. ● The mechanism of the acquired UV-induced switchable wettability was discussed. ● The developed flax fiber was successfully used for multipurpose oil-water separation. The large number of oily wastewater discharges and oil spills are bringing about severe threats to environment and human health. Corresponding to this challenge, a functional PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed for efficient oil-water separation in this study. The developed flax fiber was obtained through PAA grafted polymerization and then ZnO-HDTMS nanocomposite immobilization. The as-prepared PAA-ZnO-HDTMS flax fiber was hydrophobic initially and could be switched to hydrophilic through UV irradiation. Its hydrophobicity could be easily recovered through being stored in dark environment for several days. To optimize the performance of the PAA-ZnO-HDTMS flax fiber, the effects of ZnO and HDTMS concentrations on its switchable wettability were investigated. The optimized PAA-ZnO-HDTMS flax fiber had a large water contact angle (~130°) in air and an extremely small oil contact angle (~0°) underwater initially. After UV treatment, the water contact angle was decreased to 30°, while the underwater oil contact angle was increased to more than 150°. Based on this UV-induced switchable wettability, the developed PAA-ZnO-HDTMS flax fiber was applied to remove oil from immiscible oil-water mixtures and oil-in-water emulsion with great reusability for multiple cycles. Thus, the developed flax fiber could be further fabricated into oil barrier or oil sorbent for oil-water separation, which could be an environmentally-friendly alternative in oil spill response and oily wastewater treatment.     

Improving protected area effectiveness through consideration of different human-pressure baselines

Previous assessments of the effectiveness of protected areas (PAs) focused primarily on changes in human pressure over time and did not consider the different human-pressure baselines of PAs, thereby potentially over- or underestimating PA effectiveness. We developed a framework that considers both human-pressure baseline and change in human pressure over time and assessed the effectiveness of 338 PAs in China from 2010 to 2020. The initial state of human pressure on PAs was taken as the baseline, and changes in human pressure index (HPI) were further analyzed under different baselines. We used the random forest models to identify the management measures that most improved effectiveness in resisting human pressure for the PAs with different baselines. Finally, the relationships between the changes in the HPI and the changes in natural ecosystems in PAs were analyzed with different baselines. Of PAs with low HPI baselines, medium HPI baselines, and high HPI baselines, 76.92% (n=150), 11.11% (n=12), and 22.86% (n=8) , respectively, showed positive effects in resisting human pressure. Overall, ignoring human-pressure baselines somewhat underestimated the positive effects of PAs, especially for those with low initial human pressure. For PAs with different initial human pressures, different management measures should be taken to improve effectiveness and reduce threats to natural ecosystems. We believe our framework is useful for assessing the effectiveness of PAs globally, and we recommend it be included in the Convention on Biological Diversity Post-2020 Strategy.