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.     

Spatiotemporal changes and driving factors of vegetation in 14 different climatic regions in the global from 1981 to 2018

Environmental Science and Pollution Research - Climate change affects the change of vegetation, and the analysis of vegetation change and its drivers in different globe climate zones is important...     

Spatiotemporal dynamics of vegetation in China from 1981 to 2100 from the perspective of hydrothermal factor analysis

Environmental Science and Pollution Research - The increased growth of vegetation has the potential to slow global climate warming. Therefore, analyzing and predicting the response assessment of...     

Numerical simulation and experimental research of fractal suspended carrier based on nonlinear equation

Environmental Science and Pollution Research - The geometric structure of the suspended carrier is an important factor that directly affects the effluent quality of the moving bed biofilm reactor,...     

Drivers and barriers to engage enterprises in environmental management initiatives in Suzhou Industrial Park, China

Small- and medium-sized enterprises (SMEs) play an important role in sustainable development not only for their significant contribution to China’s economy, but also for their large share of total discharged pollutants. Therefore, this research takes the enterprises in Suzhou Industrial Park, China as the case study to investigate the environmental management practices of SMEs, and identify drivers and barriers to engaging businesses in environmental management initiatives. It is shown that, as in other countries, SMEs are less active in adopting environmental management initiatives than larger companies. Legislation remains the key driver to engage SMEs in environmental management initiatives. Based on the analysis, policy recommendations are also presented.     

污染土壤电动修复增强方法研究进展

污染土壤电动修复是一项新兴绿色原位修复技术。其原理是在土壤上施加直流电场 ,利用电迁移和电渗去除污染物 ,土壤pH、Zeta电位以及土壤化学性质等因素影响电动修复效果。为了提高修复效率和扩大电动修复应用范围 ,现在已经发展了针对不同类型土壤和污染物的增强修复技术。本文归纳总结了 1995年以来土壤电动修复中常用增强处理效果的 8种方法 ,即酸碱中和法、阳离子选择膜法、电渗析法、络合剂法、表面活性剂法、氧化 还原法、EK 生物联用和LasagnaTM法 ,且对每种方法的典型实验装置、增强原理、方法特点和适用范围等进行了分析和讨论 ,为以后的实验设计提供了有益的参考     

清洁过程环境影响评估模块的开发

在过程开发早期阶段考虑环境问题是实现污染预防的有效手段。将环境影响评估功能集成于过程模拟软件是一项重要的工作。以通用模拟软件ECSS—ChStar为平台,开发出环境影响评估模块。该模块可以对物质流、过程单元和总流程提供环境模拟分析,并计算过程方案的环境影响指数。     

净化SO2的生物膜填料塔中微生物类群分析

对净化废气中SO2的生物膜填料塔内的微生物进行了分离纯化并做鉴定,得到一株嗜酸性氧化硫硫杆菌（Acidithiobacillus thiooxidans IEL001）和一株分类地位非常接近链二孢属（Bispora sp.）的极端嗜酸真菌IEL002,生物膜填料塔内的极端酸性环境和有机营养的缺乏导致生物膜上的微生物种类较为单一,多样性程度不高。本研究还发现IEL002自身并不能氧化单质硫,但它能促进Acidithiobacillus thiooxidans IEL001对单质硫的氧化。     

用次磷酸钠废渣制备饲料级磷酸三钙

采用高温煅烧工艺,以工业生产次磷酸钠的废渣为原料,制备饲料级磷酸三钙,并对最佳工艺条件进行探讨。最佳工艺条件：煅烧温度600℃、煅烧时间20min。制得的饲料级磷酸三钙中磷的质量分数为16％～18％,符合Q／YHY01—2003《饲料级磷酸三钙》产品质量企业标准。     

Relationships among multiple trace elements in coastal Casuarina equisetifolia ecosystems on Hainan Island, South China

Forty-six trace elements in coastal Casuarina equisetifolia plant–soil systems at nine sampling sites on Hainan Island were analyzed using ICP-MS. The relationships among the trace elements of the same group or the same periodicity of the Periodic Table in the plants and soils were complex and no consistent patterns were found. More combinations of elements occurred with high positive correlation coefficients within the same periodicity than within the same group of the Periodic Table, and there were more high positive correlations in soils than in plants. However, there were many element combinations in Block d (transition elements) with high positive correlation coefficients in plants. Markedly high positive correlation coefficients between individual rare earth elements and Y and among Zr, Nb, Cd existed in both plants and soils. The dendrograms obtained by cluster analysis show that rare earth elements had very similar occurrence and distribution in both soils and plants. Thus, they behaved as a coherent group of elements both geochemically and biogeochemically. The transition elements were more coherent in plants than in soils.