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Cited by 66Toxic Organic Pollutants ImpactAdvanced oxidation water treatmentPesticide and Herbicide Environmental Studies

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A Critical View of the Application of the APEX Software (Aqueous Photochemistry of Environmentally-Occurring Xenobiotics) to Predict Photoreaction Kinetics in Surface Freshwaters

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Vione, Davide·2019·Molecules
DOI 10.3390/molecules25010009PMC PMC7017383
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Abstract

The APEX (aqueous photochemistry of environmentally occurring xenobiotics) software computes the phototransformation kinetics of compounds that occur in sunlit surface waters. It is free software based on Octave, and was originally released in 2014. Since then, APEX has proven to be a remarkably flexible platform, allowing for the addressing of several environmental problems. However, considering APEX as a stand-alone software is not conducive to exploiting its full potentialities. Rather, it is part of a whole ecosystem that encompasses both the software and the laboratory protocols that allow for the measurement of substrate photoreactivity parameters. Coherently with this viewpoint, the present paper shows both how to use APEX, and how to experimentally derive or approximately assess the needed input data. Attention is also given to some issues that might provide obstacles to users, including the extension of APEX beyond the simple systems for which it was initially conceived. In particular, we show how to use APEX to deal with compounds that undergo acid–base equilibria, and with the photochemistry of systems such as stratified lakes, lakes undergoing evaporation, and rivers. Hopefully, this work will provide a reference for the smooth use of one of the most powerful instruments for the modeling of photochemical processes in freshwater environments. All authors have read and agreed to the published version of the manuscript.

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Figure 1 Top: Schematic of the input variables of the “aqueous photochemistry of environmentally occurring xenobiotics” APEX software, divided according to both the context they refer to (environment vs. molecule/substrate) and the wavelength dependence. Bottom: general block scheme that depicts how the APEX software works. The “substrate variables” can be neglected if one is only interested in the photochemical functioning of the environment. Note that Φ•OH^CDOM, Φ1O2^CDOM and Φ³CDOM*^CDOM are the formation quantum yields of, respectively, •OH, 1O2 and 3CDOM* from irradiated CDOM, while ηCO3^(•−)^CDOM describes the formation of CO3•− from 3CDOM*.
Figure 1 Top: Schematic of the input variables of the “aqueous photochemistry of environmentally occurring xenobiotics” APEX software, divided according to both the context they refer to (environment vs. molecule/substrate) and the wavelength dependence. Bottom: general block scheme that depicts how the APEX software works. The “substrate variables” can be neglected if one is only interested in the photochemical functioning of the environment. Note that Φ•OH^CDOM, Φ1O2^CDOM and Φ³CDOM*^CDOM are the formation quantum yields of, respectively, •OH, 1O2 and 3CDOM* from irradiated CDOM, while ηCO3^(•−)^CDOM describes the formation of CO3•− from 3CDOM*.CC BY · PubMed Central
Figure 2 This is the part of the apex.m file where the back-reduction process can be described. The default value of DOC1/2 is so high (100,000) that back-reduction is negligible in the as-provided file. If modeling of back-reduction is needed, a suitable DOC1/2 numerical value (in mgC·L−1 units) should replace the default 100,000. For instance, for the acid and basic forms of sulfadiazine it is DOC1/2 = 17 and 0.7 mgC·L−1, respectively [64]. It is advisable to restore the 100,000 value after use, to avoid inadvertent back-reduction modeling when it is not needed. Note that DOC and NPOC are synonyms.
Figure 2 This is the part of the apex.m file where the back-reduction process can be described. The default value of DOC1/2 is so high (100,000) that back-reduction is negligible in the as-provided file. If modeling of back-reduction is needed, a suitable DOC1/2 numerical value (in mgC·L−1 units) should replace the default 100,000. For instance, for the acid and basic forms of sulfadiazine it is DOC1/2 = 17 and 0.7 mgC·L−1, respectively [64]. It is advisable to restore the 100,000 value after use, to avoid inadvertent back-reduction modeling when it is not needed. Note that DOC and NPOC are synonyms.CC BY · PubMed Central
Figure 3 Modeling of the photodegradation kinetics of ibuprofen as a function of water DOC, carried out by using (a) the experimental photoreactivity data [19], and (b) the data obtained with the QSAR approaches described in the text. Other water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, 5 m water depth. Raw data were obtained with Savetable and further processed. The time unit is fair-weather days in mid-July, at 45°N latitude.
Figure 3 Modeling of the photodegradation kinetics of ibuprofen as a function of water DOC, carried out by using (a) the experimental photoreactivity data [19], and (b) the data obtained with the QSAR approaches described in the text. Other water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, 5 m water depth. Raw data were obtained with Savetable and further processed. The time unit is fair-weather days in mid-July, at 45°N latitude.CC BY · PubMed Central
Figure 4 Calculation procedure for the initial formation rates of the intermediates I1 and I2, produced upon S transformation, using the initial slope (graphical) technique. The initial formation rate of I1 is {R1 [mol L−1 s−1]} ≅ {[S]o [mol L−1]} (2.75 days × 3600 × 24)−1. The initial formation rate of I2 is {R2 [mol L−1 s−1]} ≅ 0.95 {[S]o [mol L−1]} (10 days × 3600 × 24)−1.
Figure 4 Calculation procedure for the initial formation rates of the intermediates I1 and I2, produced upon S transformation, using the initial slope (graphical) technique. The initial formation rate of I1 is {R1 [mol L−1 s−1]} ≅ {[S]o [mol L−1]} (2.75 days × 3600 × 24)−1. The initial formation rate of I2 is {R2 [mol L−1 s−1]} ≅ 0.95 {[S]o [mol L−1]} (10 days × 3600 × 24)−1.CC BY · PubMed Central
Figure 5 Modeled phototransformation kinetics of 2-hydroxy-4-methoxybenzophenone-5-sulfonic acid (BP4) (overall first-order rate constants, and role of the different photoreaction pathways), as a function of pH. Other water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, 3 mgC·L−1 DOC, 5 m water depth. Raw data were obtained with Savetable and further processed.
Figure 5 Modeled phototransformation kinetics of 2-hydroxy-4-methoxybenzophenone-5-sulfonic acid (BP4) (overall first-order rate constants, and role of the different photoreaction pathways), as a function of pH. Other water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, 3 mgC·L−1 DOC, 5 m water depth. Raw data were obtained with Savetable and further processed.CC BY · PubMed Central
Figure 6 (a) Schematic of a stratified lake. (b) Modeled time trends of ibuprofen in the hypolimnion, the epilimnion, and the overall lake during overturn. Water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, 2 mgC·L−1 DOC, dth = 10 m, dtot = 30 m. Raw data were obtained with Savetable and further processed.
Figure 6 (a) Schematic of a stratified lake. (b) Modeled time trends of ibuprofen in the hypolimnion, the epilimnion, and the overall lake during overturn. Water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, 2 mgC·L−1 DOC, dth = 10 m, dtot = 30 m. Raw data were obtained with Savetable and further processed.CC BY · PubMed Central
Figure 7 Modeled phototransformation kinetics of ibuprofen in river water, as a function of the flow rate Q (varied from 1 to 100 m3 s−1). Water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, 3 mgC·L−1 DOC, Qo = 100 m3 s−1, do = 4 m. Raw data were obtained with Savetable and further processed.
Figure 7 Modeled phototransformation kinetics of ibuprofen in river water, as a function of the flow rate Q (varied from 1 to 100 m3 s−1). Water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, 3 mgC·L−1 DOC, Qo = 100 m3 s−1, do = 4 m. Raw data were obtained with Savetable and further processed.CC BY · PubMed Central
Figure 8 Trends of the first-order degradation rate constant of ibuprofen (left Y axis) and of the corresponding half-life time (right Y axis), as a function of water loss due to evaporative concentration. The weights of the different photoreaction pathways are highlighted in different colors. Initial water conditions for do = 10 m: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, and 10−5 mol·L−1 CO32−. Raw data were obtained with Savetable and further processed.
Figure 8 Trends of the first-order degradation rate constant of ibuprofen (left Y axis) and of the corresponding half-life time (right Y axis), as a function of water loss due to evaporative concentration. The weights of the different photoreaction pathways are highlighted in different colors. Initial water conditions for do = 10 m: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, and 10−5 mol·L−1 CO32−. Raw data were obtained with Savetable and further processed.CC BY · PubMed Central
Figure 9 This figure reports the initial and final parts of apex.m (top) as well as a middle part of Savetable.m (bottom), showing the changes that should be made to apex.m in order to account for water evaporation (and how to undo such changes). The bottom panel reports the way Savetable.m should be set to run the evaporation scenario.
Figure 9 This figure reports the initial and final parts of apex.m (top) as well as a middle part of Savetable.m (bottom), showing the changes that should be made to apex.m in order to account for water evaporation (and how to undo such changes). The bottom panel reports the way Savetable.m should be set to run the evaporation scenario.CC BY · PubMed Central
Figure 10 (a) Modeled trend of the first-order degradation rate constant of ibuprofen (left Y axis) and of the corresponding half-life time (right Y axis), as a function of the water DOC. (b) Modeled DOC trend of the formation yield of IBAP from ibuprofen. In both cases, the weights of the different photoreaction pathways are highlighted in different colors. Other water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, and 2 m water depth. Raw data were obtained with Savetable and further processed.
Figure 10 (a) Modeled trend of the first-order degradation rate constant of ibuprofen (left Y axis) and of the corresponding half-life time (right Y axis), as a function of the water DOC. (b) Modeled DOC trend of the formation yield of IBAP from ibuprofen. In both cases, the weights of the different photoreaction pathways are highlighted in different colors. Other water conditions: 10−4 mol·L−1 NO3−, 10−6 mol·L−1 NO2−, 10−3 mol·L−1 HCO3−, 10−5 mol·L−1 CO32−, and 2 m water depth. Raw data were obtained with Savetable and further processed.CC BY · PubMed Central

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Metadata

Authors
Vione, D.
Affiliations
University of Turin (IT)
Corresponding author
Vione, Davide
ORCID
Vione, Davide
Venue
Molecules
Publisher
MDPI AG
Published
2019-12-18
Volume
25
Issue
1
Pages
9
ISSN
1420-3049 (ISSN-L)
DOI
10.3390/molecules25010009
PMC
PMC7017383
OpenAlex
W2994797139
Cited by
66
References
85
Citations by year
2026: 2 · 2025: 6 · 2024: 11 · 2023: 11 · 2022: 9 · 2021: 17 · 2020: 10
FWCI
0.87
Type
journal article
Language
en
Open access
Licence
Locations
  • Molecules (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Institutional Research Information System University of Turin (University of Turin) (submittedVersion, other-oa)
Topics
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Toxic Organic Pollutants Impact
  • Physical Sciences › Environmental Science › Water Science and Technology › Advanced oxidation water treatment
  • Physical Sciences › Environmental Science › Pollution › Pesticide and Herbicide Environmental Studies
Keywords
aqueous photochemistry, xenobiotics, acid-base balance, stratified lakes, lake evaporation, rivers, photochemical modeling
MeSH terms
Cheminformatics, Algorithms, Fresh Water, Models, Chemical, Photolysis, Software, Sunlight, Xenobiotics, Photochemical Processes

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