From Slide Rule to Big Data: How Data Science is Changing Water Science and Engineering

Hering, Janet G.

doi:10.1061/(asce)ee.1943-7870.0001578

Cited by 12 publications

(8 citation statements)

References 60 publications

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“…Besides mechanism-driven models, empirical or data-driven models are also used to describe contaminant breakthrough curves. The terms "big data" and "data science" are becoming pervasive, affecting many aspects of environmental remediation research (Hering 2019;Newhart et al 2019). Large amounts of data are being used to develop optimization and process control strategies.…”

Section: Introductionmentioning

confidence: 99%

Fixed bed adsorption of water and air contaminants: analysis of breakthrough curves using probability distribution functions

Chu

Hashim

2022

Chemical Engineering Communications

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Simple fixed bed models such as the Bohart-Adams and Thomas equations are often used to describe the breakthrough characteristics of water and air contaminant adsorption in fixed bed adsorbers. However, these popular models are confined to correlating highly symmetric breakthrough curves. The present study investigates the feasibility of using two probability distributions (normal and log-normal) to track asymmetric breakthrough curves for water and air contaminant adsorption in fixed bed columns (ciprofloxacin, ammonium, hydrogen chloride, and hydrogen sulfide). The normal and log-normal probability distributions provided accurate fits to the slightly asymmetric ciprofloxacin breakthrough curve. They also provided a good representation of the overall shape of the ammonium breakthrough curve, but failed to describe the leakage of ammonium during the initial period of column operation. The log-normal distribution was able to match the asymmetric HCI and H2S breakthrough curves. The normal distribution, by comparison, failed to describe these two asymmetric breakthrough curves.Because the log-normal distribution has a floating inflection point, it was much more successful in describing the asymmetric HCI and H2S breakthrough curves that were sharp initially and 2 then broadened significantly as the column approached saturation. The ability of the normal distribution to track such asymmetric breakthrough data was impeded by its invariant inflection point.

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Section: Introductionmentioning

confidence: 99%

Fixed bed adsorption of water and air contaminants: analysis of breakthrough curves using probability distribution functions

Chu

Hashim

2022

Chemical Engineering Communications

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“…The first issue of Environmental Science & Technology in 1967 showcased manually collected datasets with hundreds of observations or fewer. , Today, the journal frequently features hydrology, water resources, water management, and water treatment research with 10 5 –10 6 observations. − The ease of collecting, analyzing, archiving, and sharing data is transforming environmental engineering by improving the representativeness, comprehensiveness, and spatiotemporal resolution of our insight into natural and engineered systems. − While several review papers have highlighted opportunities for data collection and use in environmental engineering, − there has been much less discussion about where and how data should be stored and shared to best serve our field.…”

Section: Introductionmentioning

confidence: 99%

Recommendations for Advancing FAIR and Open Data Standards in the Water Treatment Community

2021

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Water treatment researchers will maximize insights from data by implementing FAIR and Open (FAIR/O) principles for data storage and management. Progress toward domain-specific FAIR/O data infrastructure and practices advance data synthesizability, data extensibility, and stakeholder diversity. Embracing FAIR/O data principles in domain research would enable data-driven research breakthroughs that benefit a diverse array of water treatment research stakeholders. These breakthroughs arise from increased data density to improve research scope, better cross-mode data translation between experimental and modeling research outputs, and improved multiscale data integration to answer key questions across research scales. This paper addresses the gap between the current state of data sharing and the envisioned potential of FAIR/O data by offering practical steps toward building effective and sustainable water treatment data infrastructure, engaging key stakeholders, and motivating their participation. We clarify essential activities of a water treatment research data repository and suggest opportunities for communicating and growing its value.

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“…An alternative to mechanism-driven models is the so-called data-driven models. The terms "big data" and "data science" are becoming pervasive, affecting many aspects of water science and engineering (Hering 2019;Newhart et al 2019). Large amounts of data are being used to develop optimization and process control strategies.…”

Section: Introductionmentioning

confidence: 99%

Using Probability Distribution Functions to Correlate Breakthrough Curves of Water and air Contaminants

Chu

2021

Preprint

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This paper reports the use of five probability cumulative distribution functions (normal, log-normal, logistic, Gompertz, and Weibull) to correlate published breakthrough data of water and air contaminants (ciprofloxacin, ammonium, hydrogen chloride, and hydrogen sulfide). Because the shape of the ciprofloxacin breakthrough curve is fairly symmetric, it is well correlated by all five functions (R2 > 0.99). They also provide a good representation of the overall shape of the ammonium breakthrough curve (R2 > 0.99). However, none can describe the leakage of ammonium during the initial period of column operation. The log-normal and Weibull functions give an excellent representation of the tailing HCl data while the normal, logistic, and Gompertz functions are quite poor. This difference in performance can be explained by the different characteristics of their inflection points. The log-normal and Weibull functions have a floating inflection point, which gives them flexibility in tracing the shape of the tailing data. The invariant inflection points of the normal, logistic, and Gompertz curves restrict their data fitting ability. Only the log-normal function can provide a reasonable fit to the H2S data with strong tailing. It is shown that the invariant inflection point of a probability function can be converted to a floating one. A version of the Gompertz function so modified provides a good quantitative correlation of the tailing data of H2S (R2 = 0.99).

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From Slide Rule to Big Data: How Data Science is Changing Water Science and Engineering

Cited by 12 publications

References 60 publications

Fixed bed adsorption of water and air contaminants: analysis of breakthrough curves using probability distribution functions

Fixed bed adsorption of water and air contaminants: analysis of breakthrough curves using probability distribution functions

Recommendations for Advancing FAIR and Open Data Standards in the Water Treatment Community

Using Probability Distribution Functions to Correlate Breakthrough Curves of Water and air Contaminants

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