McLamore Eric, Duckworth Owen, Boyer Treavor H, Marshall Anna-Maria, Call Douglas F, Bhadha Jehangir H, Guzmán Sandra
Science and Technologies for Phosphorus Sustainability (STEPS) Center, United States.
Agricultural Sciences, Clemson University, United States.
Water Res X. 2023 Jan 27;19:100168. doi: 10.1016/j.wroa.2023.100168. eCollection 2023 May 1.
Phosphorus (P) is a finite resource, and its environmental fate and transport is complex. With fertilizer prices expected to remain high for years and disruption to supply chains, there is a pressing need to recover and reuse P (primarily as fertilizer). Whether recovery is to occur from urban systems (e.g., human urine), agricultural soil (e.g., legacy P), or from contaminated surface waters, quantification of P in various forms is vital. Monitoring systems with embedded near real time decision support, so called cyber physical systems, are likely to play a major role in the management of P throughout agro-ecosystems. Data on P flow(s) connects the environmental, economic, and social pillars of the triple bottom line (TBL) sustainabilty framework. Emerging monitoring systems must account for complex interactions in the sample, and interface with a dynamic decision support system that considers adaptive dynamics to societal needs. It is known from decades of study that P is ubiquitous, yet without quantitative tools for studying the dynamic nature of P in the environment, the details may remain elusive. If new monitoring systems (including CPS and mobile sensors) are informed by sustainability frameworks, data-informed decision making may foster resource recovery and environmental stewardship from technology users to policymakers.
磷(P)是一种有限的资源,其在环境中的归宿和迁移十分复杂。鉴于肥料价格预计在未来数年仍将居高不下且供应链受到干扰,迫切需要回收和再利用磷(主要用作肥料)。无论回收是从城市系统(如人类尿液)、农业土壤(如残留磷)还是受污染的地表水中进行,对各种形态磷的量化都至关重要。具备嵌入式近实时决策支持的监测系统,即所谓的信息物理系统,很可能在整个农业生态系统的磷管理中发挥重要作用。磷流数据连接了三重底线(TBL)可持续性框架的环境、经济和社会支柱。新兴的监测系统必须考虑样本中的复杂相互作用,并与一个动态决策支持系统相衔接,该系统要考虑到对社会需求的适应性动态变化。数十年来的研究表明磷无处不在,但如果没有用于研究环境中磷动态性质的定量工具,细节可能仍难以捉摸。如果新的监测系统(包括信息物理系统和移动传感器)以可持续性框架为依据,基于数据的决策制定可能会促进从技术使用者到政策制定者的资源回收和环境管理。