Land-use dynamics and landscape pattern change in a coastal gulf region,southeast China

This study quantitatively analyzed spatiotemporal changes in land use and landscape pattern in a coastal gulf region of southeast China by comparing classified satellite images from 1988, 2002, and 2007, using a geographic information system (GIS), remote sensing (RS), and landscape pattern metrics. The results show an increase in cropland, built-up area, and aquaculture area and a decrease in orchards, woodland, and beach area during 1988–2007. Over the study period, 64.3% of newly-expanded cropland was from woodland; newly-expanded built-up area of 34.8, 27.2, and 20.4% was converted from cropland, woodland, and beach areas, respectively; and newly-expanded aquaculture increased by 45.1 and 29.4% from beach and water body areas, respectively. Trend analysis of landscape pattern metrics demonstrates fragmentation of the landscape, with landscape pattern structure becoming more complex over the last two decades in the Louyuan Gulf region. Urbanization and policy developed to transfer beach/seawater areas into built-up area/aquaculture are the two main driving forces contributing to dynamic changes in land use and landscape pattern in the last two decades in Louyuan.     

土壤中稀土元素的生态毒性研究进展

为了解稀土元素对农田生态系统的影响,综述了近几十年来国内外有关土壤稀土元素生态毒性的研究进展,包括土壤稀土元素的主要来源途径,稀土元素对农田生态系统中植物、动物和微生物生长、发育、繁殖的影响。高浓度的稀土元素会破坏植物细胞膜的性质和结构,影响植物的抗氧化系统,扰乱植物对矿质营养元素的正常吸收和利用,诱使植物细胞发育不良、染色体畸变等现象发生。稀土元素可影响动物的消化、呼吸、生殖、神经、血液和免疫系统等。稀土元素对土壤微生物数量、种类、群落结构与功能多样性等均有影响。探讨了土壤稀土元素的生态毒性诊断方法,目前常见的植物毒性诊断法、蚯蚓毒性诊断法、土壤微生物诊断法、生物标记物诊断法和遗传毒性诊断法等可用来诊断土壤中稀土元素的生态毒性。提出了以后开展土壤稀土元素生态毒性研究应加强的方面:在群落、个体和细胞水平上研究稀土元素对土壤动物和微生物的影响,加强稀土元素生态毒性诊断新方法和新技术的探讨,进行稀土元素生物有效性与土壤因素关系的研究等。     

亚热带水库沉积物钻孔中有机质的历史记录及其环境意义

氢指数(HI)是重要的有机质评价参数,能够反映沉积有机质中脂肪大分子物质的相对含量,并用于反演水生生态系统的历史初级生产力,有助于研究藻类生产力对污染物的富集作用。为了探讨氢指数的环境指示作用,选择了亚热带的3座水库作为研究对象,采用Rock-Eval热解与生物标志物-中性糖方法相结合的研究技术,研究了沉积钻孔有机质的来源与特征;并结合210Pb和137Cs定年技术,综合运用氢指数和总糖含量对水库的初级生产力进行了重建。结果表明:中富营养的增塘和联安水库沉积有机质主要来源于浮游藻类,且受降解的程度较小,而贫营养的新丰江水库钻孔下层有机质主要是受降解作用或陆源高等植物等的影响。近年来,3个水库的HI值都有显著性的增加,且与其对应的总糖含量以及近50年来的滑动平均温度都高度的相关,说明这些水库都经历了气候变暖所引起的初级生产力增长。同时,升高的水库生产力扩大了沉积物剖面中重金属和多环芳烃的累积。     

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.     

PDMS半透膜采样装置的制作研究

水中痕量持久性有机污染物的监测是经典的分析化学难题,传统分析方法既费时又费材料,且只能测定某一时间点的浓度.三油酸甘油脂半透膜被动采样器虽能克服传统方法的一些缺点,但对膜的要求较高.通过在一个固定于不锈钢网上,扁平、密封的商品低密度聚乙烯(LDPE)膜袋夹层中均匀涂布聚二甲基硅氧烷(PDMS),制作出一种新的半透膜被动采样器.用此被动采样器在混合多氯联苯(PCBs)的过饱和水溶液中反复模拟采样,测得半透膜最佳富集时间、时间和富集量的关系曲线以及其它特性.使用气质联用仪测得的数据证明此装置可用于水体中多氯联苯等痕量持久性有机污染物的采集和定量分析,其线性富集时间可达 9 d,富集率大约为3×103 ~ 6×103倍,为今后的环境监测提供了一种制作简单、使用方便、富集率好、费用低廉的新方法.     

IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.