Improved Fluorescence Excitation‐Emission Matrix Regional Integration to Quantify Spectra for Fluorescent Dissolved Organic Matter

Abstract

The purpose of this short communication is to demonstrate the importance of numerical analysis and wavelength increment selection when characterizing fluorescent dissolved organic matter (FDOM) using fluorescence excitation-emission matrix (EEM) regional integration. A variety of water samples, representing a landscape gradient and different types of FDOM, were analyzed for their percentage distribution of five operationally defined FDOM fractions (aromatic protein I, aromatic protein II, fulvic acid-like, soluble microbial byproduct-like, and humic acid-like) using three numerical methods in integrating volume under the surface of the fluorescence EEMs: Riemann summation, composite trapezoidal rule, and composite Simpson's rule. The influence of wavelength increment was also examined for the precision of the percentage distribution of each fraction. Our results show that the FDOM fraction estimated by Riemann summation with a 10- or 5-nm excitation wavelength can cause >40% or >5% errors, respectively, when compared with the best estimated values obtained by averaging results from composite trapezoidal rule and composite Simpson's rule with 1-nm excitation wavelength at the same emission increment. Also, our experiments show that fluorescence matrix regional integration could underestimate the two aromatic protein fractions but could overestimate the soluble microbial byproduct-like and humic acid-like fractions if improper increment and integral methods are used. The error can be reduced if a smaller wavelength increment is used. The smallest increment in a spectrofluorometer and composite Simpson's rule should be used for scanning fluorescence EEMs and calculating the percentage distribution of each FDOM fraction. Alternatively, 5-nm wavelength increments with composite Simpson's rule could be cost effective, and the error of each FDOM fraction commonly falls within 5% compared with those estimated by 1-nm increments.

Controlled Burning of Forest Detritus Altering Spectroscopic Characteristics and Chlorine Reactivity of Dissolved Organic Matter: Effects of Temperature and Oxygen Availability

“…31 Specific UV absorbance at 254 nm (SUVA 254 ; in L mg C −1 m −1 ), a widely used indicator for DOM aromaticity, was calculated by dividing the UV absorbance at 254 nm by DOC concentration. 32 The E2/E3 ratio, an indicator of molecular weight of DOM, was calculated by dividing the absorbance at 254 nm by that at 365 nm.…”

Temporal variations of disinfection byproduct precursors in wildfire detritus

“…For all water extracts, we measured DOC and TDN using a Shimadzu TOC/TN analyzer, and ammonia/ammonium-N (NH 4 þ -N) and nitrate/nitrite-N (NO x À -N) using a Systea ® Easychem™ discrete analyzer . The UV-VIS absorption and fluorescence excitation-emission matrix (EEM) of the DOM was determined by a Shimadzu UV-1800 spectrophotometer (scan range: 200e700 nm) and Shimadzu spectrofluorometer RF5301 (emission, or Em: 200e550 nm; excitation, or Ex: 220e450 nm; slit width: 5 nm; Zhou et al, 2013). Based on the results, optical indices reflecting the DOM composition were calculated.…”

“…The E2/E3 ratio, an indicator of molecular size of DOM, was calculated as absorbance at 254 nm divided by absorbance at 365 nm (Peuravuori and Pihlaja, 1997). The raw EEM was corrected (Murphy et al, 2010) and the fluorescence regional integration based on Simpson's rule (Zhou et al, 2013) was used to divide the EEM into five operationally-defined regions: I, tyrosine-like; II, tryptophan-like; III, fulvic acid-like; IV, soluble microbial byproduct-like; and V, humic acid-like. The percent fluorescent response in each region i (P i,n ) was determined as the proportion of area-normalized volume in region i to the entire region.…”

Carbon mineralization from sewage sludge-amended mine dump by response surface methodology

“…Excitation(Ex)-emission(Em) revealed significant variations in common pools, the components of DOC (Zhou et al 2013) for the different treatments assayed (Fig. 5).…”