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近年来,用于检测富营养化营养物质的传感方法取得了新进展,重点是针对环境应用的自动化。

Recent developments in sensing methods for eutrophying nutrients with a focus on automation for environmental applications.

机构信息

Water Institute, School of Chemical Sciences, Dublin City University, Dublin, Ireland.

出版信息

Analyst. 2017 Nov 20;142(23):4355-4372. doi: 10.1039/c7an00840f.

Abstract

The demand for autonomous sensors for unattended, continuous nutrient monitoring in water is rapidly growing with the increasing need for more frequent and widespread environmental pollution monitoring. Legislative bodies, local authorities and industries all require frequent water quality monitoring, however, this is time and labour intensive, and an expensive undertaking. Autonomous sensors allow for frequent, unattended data collection. While this solves the time and labour intensive aspects of water monitoring, sensors can be very expensive. Development of low-cost sensors is essential to realise the concept of Internet of Things (IoT). However there is much work yet to be done in this field. This article reviews current literature on the research and development efforts towards deployable autonomous sensors for phosphorus (in the form of phosphate) and nitrogen (in the form of nitrate), with a focus on analytical performance and cost considerations. Additionally, some recent sensing approaches that could be automated in the future are included, along with an overview of approaches to monitoring both nutrients. These approaches are compared with standard laboratory methods and also with commercially available sensors for both phosphate and nitrate. Application of nutrient sensors in agriculture is discussed as an example of how sensor networks can provide improvements in decision making.

摘要

随着对更频繁和更广泛的环境污染监测的需求不断增加,对用于无人值守、连续营养监测的自主传感器的需求迅速增长。立法机构、地方当局和行业都需要频繁的水质监测,但这既费时费力,又耗费昂贵。自主传感器可实现频繁、无人值守的数据采集。虽然这解决了水质监测中耗时耗力的问题,但传感器的成本可能非常高。开发低成本传感器对于实现物联网 (IoT) 的概念至关重要。然而,在这一领域还有很多工作要做。本文综述了目前关于可部署自主传感器用于磷(以磷酸盐形式)和氮(以硝酸盐形式)的研究和开发工作的文献,重点关注分析性能和成本考虑。此外,还包括一些未来可能实现自动化的传感方法,以及监测这两种营养物质的方法概述。这些方法与标准实验室方法进行了比较,也与商业上可用的磷酸盐和硝酸盐传感器进行了比较。还讨论了营养物传感器在农业中的应用,以此为例说明传感器网络如何能够改善决策制定。

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