Complete optical absorption and fluorescence spectra were collected for a diverse suite of 0.2-μm-filtered marine, riverine, and estuarine waters, as well as for colored dissolved organic matter (CDOM) isolated from several of these waters by solid-phase C 18 extraction. Absorption and fluorescence parameters for these samples are reported. For surface waters, variations in the fluorescence quantum yields obtained with 355- and 337-nm excitation fell within a narrow window (< 2.5-fold variation about the mean values), demonstrating that fluorescence measurements can be used to determine absorption coefficients of CDOM in the ultraviolet region with reasonably good accuracy. Methods for predicting absorption coefficients and line shapes from the fluorescence data are introduced and tested. The absorption and fluorescence spectra of CDOM extracted from some seawaters differed significantly from those of the original waters, demonstrating that material isolated by hydrophobic adsorption is not necessarily representative of the suite of colored organic matter present in aquatic systems. These results clearly illustrate that great care must be taken when extracted material is used to infer the optical properties of natural waters

Optical absorption and fluorescence properties of chromophoric dissolved organic matter in natural waters

The pollution conveyed by urban runoff: A review of sources.

Facile fabrication of BUC-21/Bi24O31Br10 composites for enhanced photocatalytic Cr(VI) reduction under white light

Untreated urban stormwater runoff contributes to poor water quality in receiving waters. The ability to identify toxicants and other bioactive molecules responsible for observed adverse effects in a complex mixture of contaminants is critical to effective protection of ecosystem and human health, yet this is a challenging analytical task. The objective of this study was to develop analytical methods using liquid chromatography coupled to high-resolution quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) to detect organic contaminants in highway runoff and in runoff-exposed fish (adult coho salmon, Oncorhynchus kisutch). Processing of paired water and tissue samples facilitated contaminant prioritization and aided investigation of chemical bioavailability and uptake processes. Simple, minimal processing effort solid phase extraction (SPE) and elution procedures were optimized for water samples, and selective pressurized liquid extraction (SPLE) procedures were optimized for fish tissues. Extraction methods were compared by detection of non-target features and target compounds (e.g., quantity and peak area), while minimizing matrix interferences. Suspect screening techniques utilized in-house and commercial databases to prioritize high-risk detections for subsequent MS/MS characterization and identification efforts. Presumptive annotations were also screened with an in-house linear regression (log Kowvs. retention time) to exclude isobaric compounds. Examples of confirmed identifications (via reference standard comparison) in highway runoff include ethoprophos, prometon, DEET, caffeine, cotinine, 4(or 5)-methyl-1H-methylbenzotriazole, and acetanilide. Acetanilide was also detected in runoff-exposed fish gill and liver samples. Further characterization of highway runoff and fish tissues (14 and 19 compounds, respectively with tentative identification by MS/MS data) suggests that many novel or poorly characterized organic contaminants exist in urban stormwater runoff and exposed biota.

Development of suspect and non-target screening methods for detection of organic contaminants in highway runoff and fish tissue with high-resolution time-of-flight mass spectrometry.

Roxarsone binding to soil-derived dissolved organic matter: Insights from multi-spectroscopic techniques

In this work, DOM was extracted from urban stormwater runoff samples collected at three typical regions (business, residential and campus regions) in Beijing, China. A comparison between the chemical characteristics of DOM extracted from these three regions was performed using UV-visible spectrometry (UV-vis), excitation–emission matrix (EEM) fluorescence, proton nuclear magnetic resonance spectroscopy (1H NMR) and ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS). The UV-vis and EEM spectra revealed that the DOM in stormwater runoff samples mainly contained UV humic-like (peak A) compositions with higher molecular weights. 1H NMR analysis indicated that the DOM of the three regions contained a similar distribution of functional groups, which mainly consisted of aliphatic chains and aromatic components with carbonyl, hydroxyl or alkyl terminal groups. And the UHPLC-Q-TOF-MS demonstrated the identification and characterization of possible compounds existing in the DOM. Further studies should focus on the interactive relationship between DOM and the co-existing contaminants (heavy metals and some typical organic pollutants) in stormwater runoff.

Dissolved organic matter in urban stormwater runoff at three typical regions in Beijing: chemical composition, structural characterization and source identification

Abstract In this work, the atmospheric corrosion of carbon steels was monitored at six different sites (and hence, atmospheric conditions) using Fe/Cu-type atmospheric corrosion monitoring technology over a period of 12 months. After analyzing over 3 million data points, the sensor data were interpretable as the instantaneous corrosion rate, and the atmospheric “corrosivity” for each exposure environment showed highly dynamic changes from the C1 to CX level (according to the ISO 9223 standard). A random forest model was developed to predict the corrosion rate and investigate the impacts of ten “corrosive factors” in dynamic atmospheres. The results reveal rust layer, wind speed, rainfall rate, RH, and chloride concentration, played a significant role in the corrosion process. 

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Long-term corrosion monitoring of carbon steels and environmental correlation analysis via the random forest method

This paper provides a review of models commonly used over the years in the study of microscopic models of material corrosion mechanisms, data mining methods and the corrosion-resistant performance control of structural steels. The virtual process of material corrosion is combined with experimental data to reflect the microscopic mechanism of material corrosion from a nano-scale to macro-scale, respectively. Data mining methods focus on predicting and modeling the corrosion rate and corrosion life of materials. Data-driven control of the corrosion resistance of structural steels is achieved through micro-alloying and organization structure control technology. Corrosion modeling has been used to assess the effects of alloying elements, grain size and organization purity on corrosion resistance, and to determine the contents of alloying elements.

Zi-Jian Pei

Papers

Dissolved organic matter in urban stormwater runoff at three typical regions in Beijing: chemical composition, structural characterization and source identification

Long-term corrosion monitoring of carbon steels and environmental correlation analysis via the random forest method

A Review of Trends in Corrosion-Resistant Structural Steels Research—From Theoretical Simulation to Data-Driven Directions