Fenton试剂加硫酸处理高浓度含酚废水的研究

研究了硫酸、Fenton试剂对酚的催化降解作用，证实了硫酸与Fenton试剂对酚的催化降解具有协同作用。H_2SO_4－Fenton试剂对高浓度含酚废水的处理结果说明，在Fenton试剂中加入硫酸可大大增加其对酚的降解能力。与单独的Fenton试剂法比较，当H_2O_2∶COD（重量比）＜0．8时，本法对COD≥14000mg／L含酚废水COD去除率可提高40％以上，对高浓度含酚废水具有很好的处理效果。     

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.     

Evidence for the involvement of Fe(IV) in water treatment by Fe(III)-activated sulfite

Water contamination by emerging organic pollutants is calling for advanced methods of remediation such as iron-activated sulfite-based advanced oxidation. Sulfate radical, SO₄^??, and hydroxyl radical, ^?OH, are the primary reactive intermediates formed in the Fe(III)/sulfite system, yet the possible involvement of Fe(IV) produced from Fe(II) and persulfates is unclear. Here we explored the role of Fe(IV) in the Fe(III)/sulfite system by methyl phenyl sulfoxide (PMSO) probe assay, electron paramagnetic resonance spectra analysis, alcohol scavenging experiment, and kinetic simulation. Results show that PMSO is partially transformed into methyl phenyl sulfone (PMSO₂), thus evidencing Fe(IV) formation. The remaining degradation of PMSO is due to SO₄^?? and ^?OH. The contribution of Fe(IV) versus free radicals is progressively promoted when the Fe(III)-sulfite reaction proceeds, with an upper limit of 80–90%. The contribution of Fe(IV) versus free radicals increases with Fe(III) and sulfite dosages, and decreases with increasing pH. Overall, our findings demonstrate the involvement of Fe(IV) in the Fe-catalyzed sulfite auto-oxidation process.

     

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.     

New insights into different surfactants’ impacts on sludge fermentation: Focusing on the particular metabolic processes and microbial genetic traits

• The promoting effects for VFA generation follow the order of APG>SDBS>HTAB. • Surfactants improve the WAS solubilization/hydrolysis and acidification processes. • The VFA promotion is associated with surfactants’ distinctive characteristics. • Surfactants induce the enrichment of functional bacteria for VFA biosynthesis. • The vital genes for substrates delivery, metabolism, and VFA yields are upregulated. Surfactants were expected to exhibit positive effects on the waste activated sludge (WAS) disposal. However, the systematic comparison of different categories of surfactants on the WAS fermentation and the functional mechanisms, especially microbial metabolic traits, have not yet been precisely explored. This study revealed the positive effects of different surfactants on the volatile fatty acid (VFA) production, which followed the order of alkyl polysaccharides (APG)>sodium dodecylbenzene sulfonate (SDBS)>hexadecyl trimethyl ammonium bromide (HTAB). Mechanistic exploration found that the presence of different surfactants improved solubilization and hydrolysis steps, and then contributed to the subsequent acidification with different efficiencies. The functional microorganisms associated with VFA generation were enriched in surfactant-conditioned reactors. Metagenomic analysis further indicated that the key genes involved in the particular process of VFA generation were over-expressed. The simultaneous bioavailable substrate improvement, functional bacterial enrichment, and metabolic activity upregulation induced by different surfactants jointly contributed to VFA promotion during WAS fermentation. This study could provide a comprehensive realization of surfactants’ impacts on the WAS fermentation process, and more importantly, it reminded the public to discern the distinct interplaying effects induced by different chemicals in regulating the WAS disposal and resource recovery.     

Coprinus comatus endophytic bacteria characteristics and mechanisms for the cadmium resistance

Environmental Science and Pollution Research - Characteristics and resistant mechanisms of macro-fungus endophytic bacteria to cadmium (Cd) have not been well defined. Strains L1 and L3 with...     

紫色土旱坡地油菜/玉米轮作下氮流失的年际变化特征

明确三峡库区紫色土旱坡地氮流失的年际变化特征,为库区的施肥管理措施和面源污染治理提供参考.依托中国科学院成都山地灾害与环境研究所三峡库区试验站,于2018～2020年连续3 a设置不施肥(CK)、常规施肥(F)、优化施肥(OF)、化肥减量配施生物炭(BF)和化肥减量配施秸秆覆盖(SF)5种处理,研究紫色土旱坡地在油菜-玉米轮作模式下氮流失的年际变化特征.结果表明：(1)三峡库区紫色土旱坡地地表径流主要发生在5月和8月,壤中流主要发生在6～10月. 2018～2020年降雨量逐年增加,各处理地表径流产流量逐年减少,壤中流产流量大致呈逐年增加的趋势,年尺度下,壤中流产流量和产流次数均高于地表径流.(2)2018～2020年每年各形态氮的最高流失浓度出现时间大概一致,地表径流全氮、铵态氮和硝态氮最高流失浓度分别出现在5、 8～10和7月,壤中流各形态氮最高流失浓度分别出现在10、 10和5～7月.(3)地表径流各形态氮流失通量呈逐年降低趋势,壤中流各形态氮流失通量大致逐年增加.(4)生物炭和秸秆还田第一年降低氮流失通量的效果较好,但后续两年还田反而加剧了氮素流失通量.因此,三峡库区紫色土旱坡...     

基于知识的AVHRR影像的水体自动识别方法与模型研究

根据水体光谱特性，通过分析水体在ＮＯＡＡ气象卫星的ＡＶＨＲＲ影像上的表象特征及与其它相关环境因子在光谱信息上的差异，认为水体在ＡＶＨＲＲ影像上具有光谱可分辨性，从而提出了基于水体光谱知识的水体自动提取识别的水体描述模型，并将该模型应用于太湖、淮河、渤海等地区，取得较好的效果。该模型方法同样可扩展应用于其它传感器获得的影像数据，从而实现遥感信息提取的自动化与智能化     

衡阳盆地紫色土丘陵坡地自然恢复灌丛阶段主要种群空间分布格局

运用植被生态学与恢复生态学的原理与方法,在衡阳盆地紫色土丘陵坡地以受干扰而退化,经封育后自然恢复至灌丛阶段的植物群落为研究对象,通过在其中设置400个5 m×5 m共计1 hm2的相邻网格样方,对其进行群落学调查.应用聚集指数、平均拥挤度、聚块性指数、格林指数、聚集强度、Cassie指标、方差均值比的t检验等方法,研究了衡阳盆地紫色土丘陵坡地自然恢复灌丛阶段群落主要种群的空间分布格局.结果表明:所有种群的空间分布呈显著的聚集分布,同时,各种群在不同的发育阶段也呈聚集分布,且随发育阶段的进展聚集程度逐渐减小.这主要与物种本身的生态学与生物学特性有关,以及与物种的竞争排斥作用有密切联系.聚集程度的大小在一定的程度上可用来表征植物群落的恢复程度,随着恢复过程的向前发展,种群聚集程度将下降.这将丰富该地区植被生态学与恢复生态学的内容.为衡阳盆地紫色土丘陵坡地生态系统的植被恢复与重建提供了一定的理论依据.     

毛毯印染废水处理技术研究

本文采用投菌水解(酸化)--接触氯化法处理毛毯印染废水.试验表明该工艺流程简单,处理效果好,出水水质稳定.当进水CODc在480～750mg/L范围变化时,出水CODDc稳定在100mg/L以下.其中,水解池对色度有较好的去除效果,同时可提高后续接触氧化池的处理效率;而CODc的去除则主要在接触氧化池进行.