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.     

高含水油泥调质脱稳用剂

高含水油泥主要来自于页岩气田、油气田和炼厂的污水处理场（站）,含水率一般高达90%以上,成分复杂、乳化严重,是性质稳定的多相体系。破胶脱稳是高含水油泥处理处置与利用的前提,也是减量化的瓶颈,其核心是调质脱稳用剂的优选。介绍了高含水油泥的性质及调质脱稳的原理和方法,阐述了高含水油泥调质脱稳用剂的研究及应用现状,总结了助滤剂、氧化剂、电解质、破乳剂、絮凝剂和微乳化剂等常用药剂的调质机理、适应范围、研究实例和优缺点,并提出了调质脱稳用剂未来的发展方向。     

生物肥料对香蕉枯萎病及土壤微生物的影响

香蕉枯萎病是真菌引起的一种土传病害,它的蔓延已经严重影响到香蕉产业的正常发展.将腐熟的有机肥与3种生防细菌(枯草芽胞杆菌、胶质芽胞杆菌和巨大芽胞杆菌)结合,组合成生物复混肥和生物有机肥,将它们施用在香蕉上,研究其对枯萎病病害防治效果.盆栽香蕉试验结果显示,2种肥料不仅能抑制香蕉枯萎病(防病效果分别为61.5%和53.8%),同时也引起土壤微生物群落发生变化,真菌数量明显下降,放线菌明显升高,细菌变化较小.通过相关分析发现,生物肥料中3种生防细菌总数与土壤中枯萎菌和普通真菌呈显著负相关,而与防病效果呈极显著正相关,有机肥中细菌与土壤细菌和放线菌含量也呈显著正相关.     

洛阳市大气污染特征与相关气象要素24小时变化分析

通过对洛阳市环境空气监测资料的统计,归纳出洛阳市区日内24小时环境空气污染变化特征,并结合同步气象观测资料综合分析,找出了二者之间的联系特征。引入气温日较差这一便于观测、预报的气象要素表征空气污染物垂直扩散特征,为今后进行污染预报提供了新的思路。     

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。