Suppr超能文献

通过减少LED可见光谱的部件来实现高度经济且精确的废水传感器。

Towards highly economical and accurate wastewater sensors by reduced parts of the LED-visible spectrum.

作者信息

Carreres-Prieto Daniel, García Juan T, Carrillo José M, Vigueras-Rodríguez Antonio

机构信息

Department of Mining and Civil Engineering, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain.

Department of Mining and Civil Engineering, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain.

出版信息

Sci Total Environ. 2023 May 1;871:162082. doi: 10.1016/j.scitotenv.2023.162082. Epub 2023 Feb 6.

Abstract

Interest is growing in simple, fast and inexpensive systems to analyze urban wastewater quality in real time. In this research project, a methodology is presented for the characterization of COD, BOD, TSS, TN, and TP of wastewater samples, without the need to alter the samples or use chemical reagents, from a few wavelengths, belonging to the different color groups that compose the visible spectrum in isolation: (380-700 nm): violet (380-427 nm), blue (427-476 nm), cyan (476-497 nm), green (497-570 nm), yellow (570-581 nm), orange (581-618 nm), and red (618-700 nm). In this study, about 650 raw and treated urban wastewater samples from over 43 WWTPs and a total of 36 estimation models based on genetic algorithms have been calculated. Seven models were calculated for each pollutant parameter; one model for each color group of the visible spectrum, except for TN, which includes an additional model combining the wavelengths of the violet and red region of the spectrum. All the calculated models showed high accuracy, with an R between 80 and 85 % for COD, BOD and TSS, and 66-74 % for TN and TP. The tests carried out have shown the accuracy of the models of the different color groups to be very close to each other. However, it is noted that the models making use of the wavelengths between 497 and 570 nm (green) were the ones that showed the best performance in all the parameters under study. This research work lays the foundations for the development of cheaper, faster, and simpler wastewater monitoring and characterization equipment.

摘要

人们对能够实时分析城市污水水质的简单、快速且廉价的系统的兴趣与日俱增。在本研究项目中,提出了一种方法,可在不改变样品或使用化学试剂的情况下,从属于构成可见光谱(380 - 700 nm)的不同颜色组(紫色(380 - 427 nm)、蓝色(427 - 476 nm)、青色(476 - 497 nm)、绿色(497 - 570 nm)、黄色(570 - 581 nm)、橙色(581 - 618 nm)和红色(618 - 700 nm))的少数几个波长来表征废水样品中的化学需氧量(COD)、生化需氧量(BOD)、总悬浮固体(TSS)、总氮(TN)和总磷(TP)。在本研究中,已计算了来自43个以上污水处理厂的约650个未经处理和已处理的城市污水样品,并基于遗传算法总共计算了36个估算模型。针对每个污染物参数计算了七个模型;除TN外,针对可见光谱的每个颜色组计算一个模型,TN包括一个结合光谱紫色和红色区域波长的附加模型。所有计算出的模型都显示出高精度,COD、BOD和TSS的R值在80%至85%之间,TN和TP的R值在66%至74%之间。所进行的测试表明,不同颜色组的模型准确性非常接近。然而,需要注意的是,利用497至570 nm(绿色)之间波长的模型在所有研究参数中表现最佳。这项研究工作为开发更便宜、更快、更简单的废水监测和表征设备奠定了基础。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验