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An innovative approach for atrazine electrochemical oxidation modelling: Process parameter effect, intermediate formation and kinetic constant assessment

Water reuse for irrigation activities is becoming a crucial worldwide challenge due to the depletion of water sources. Anyway, agricultural drainage can potentially contain dangerous contaminants such as metals, pesticides, and herbicides, including atrazine. To address the need for agriculture wastewater purification, we investigated atrazine removal from simulated wastewater by electro-oxidation using platinum-coated titanium electrodes on a lab-scale experimental apparatus. The effects of electrolyte composition and concentration, i.e. ionic strength and applied current density on atrazine removal, were investigated. The results demonstrated that the electrochemical oxidation of the herbicide occurred through two routes, depending on the presence or absence of oxidizing chlorine species. The generation of intermediates during the treatment was monitored and quantified by evaluating the effect of an inert electrolyte (NaClO 4 ) versus an oxidizable chlorine species (NaCl). In both experimental conditions, five intermediates were identified, including desethyl-atrazine (DEA), hydroxyatrazine (ATZ-OH), desisopropyl-atrazine (DIA) and desethyl-desisopropyl-atrazine (DEDIA). A degradation mechanism and a model for describing hydroxyl radicals and active chlorine species contributions at ATZ oxidation were also proposed. Intermediate evolution profiles suggest that ATZ degradation can be considered as a series–parallel reaction system. Finally, the energy requirement assessment for ATZ removal was carried out. The highest ATZ removal (≅98%) was achieved with NaCl = 0.08 M, J = 60 A/m −2 , and E C = 5.83 kWh m −3 . Results highlight that atrazine removal was improved when an active chlorine species (NaCl) was present in the water solution. Moreover, the addition of chlorine species during electro-oxidation is an energy-saving strategy. Collectively, electro-oxidation technique can be efficiently applied to treat polluted water in order to meet the needs of recycling water quality and reduce resource consumption.

Electro-chemical oxidation↗

An integrated host-microbiome response to atrazine exposure mediates toxicity in Drosophila

Abstract The gut microbiome produces vitamins, nutrients, and neurotransmitters, and helps to modulate the host immune system—and also plays a major role in the metabolism of many exogenous compounds, including drugs and chemical toxicants. However, the extent to which specific microbial species or communities modulate hazard upon exposure to chemicals remains largely opaque. Focusing on the effects of collateral dietary exposure to the widely used herbicide atrazine, we applied integrated omics and phenotypic screening to assess the role of the gut microbiome in modulating host resilience in Drosophila melanogaster . Transcriptional and metabolic responses to these compounds are sex-specific and depend strongly on the presence of the commensal microbiome. Sequencing the genomes of all abundant microbes in the fly gut revealed an enzymatic pathway responsible for atrazine detoxification unique to Acetobacter tropicalis . We find that Acetobacter tropicalis alone, in gnotobiotic animals, is sufficient to rescue increased atrazine toxicity to wild-type, conventionally reared levels. This work points toward the derivation of biotic strategies to improve host resilience to environmental chemical exposures, and illustrates the power of integrative omics to identify pathways responsible for adverse health outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

Atrazine Degradation Using Immobilized Triazine Hydrolase from Arthrobacter aurescens TC1 in Mesoporous Silica Nanomaterials

Triazine hydrolase fromArthrobacter aurescens TC1 (TrzN) was successfully immobilized on mesoporous silica nanomaterials (MSNs) for the first time. For both nonfunctionalized MSNs and MSNs functionalized with Zn(II), three pore sizes were evaluated for their ability to immobilize wild-type TrzN: Mobile composition of matter no. 41 (small, 3 nm pores), mesoporous silica nanoparticle material with 10 nm pore diameter (MSN-10) (medium, 6-12 nm pores), and pore-expanded MSN-10 (large, 15-30 nm pores). Of these six TrzN:MSN biomaterials, it was shown that TrzN:MSN-10 was the most active (3.8 +/- 0.4 x 10 -5 U/mg) toward the hydrolysis of a 50 uM atrazine solution at 25 degrees C. The TrzN:MSN-10 biomaterial was then coated in chitosan (TrzN:MSN-10:Chit) as chitosan has been shown to increase stability in extreme conditions such as low/high pH, heat shock, and the presence of organic solvents. TrzN:MSN-10:Chit was shown to be a superior TrzN biomaterial to TrzN:MSN-10 as it exhibited higher activity under all storage conditions, in the presence of 20% MeOH, at low and high pH values, and at elevated temperatures up to 80 degrees C. Finally, the TrzN:MSN-10:Chit biomaterial was shown to be fully active in river water, which establishes it as a functional biomaterial under actual field conditions. A combination of these data indicate that the TrzN:MSN-10:Chit biomaterial exhibited the best overall catalytic profile making it a promising biocatalyst for the bioremediation of atrazine.

09 BIOMASS FUELS↗

Machine Learning Models for Mapping Groundwater Pollution Risk: Advancing Water Security and Sustainable Development Goals in Georgia, USA

The widespread use of pesticides, such as atrazine and malathion, in agricultural systems raises significant concerns regarding the contamination of groundwater, which serves as a critical resource for drinking water. This study applies machine learning techniques to predict the concentrations of atrazine and malathion in groundwater across Georgia, USA, using 2019 data. A Random Forest classifier was employed to integrate various environmental and demographic factors, including pesticide application rates, precipitation, lithology, and population density, to predict pesticide contamination in groundwater. The models demonstrated high training accuracies of 100% and moderate average testing accuracy of 55% for atrazine and 60% for malathion across five iterations. The low test accuracy of the model, ranging from 50% to 75%, is likely due to overfitting, which can be attributed to the small dataset size and the complex nature of pesticide-contamination patterns, making it challenging for the model to generalize to unseen data. Feature importance analysis revealed that average pesticide usage emerged as the most influential factor for atrazine, while aquifer lithology and precipitation played crucial roles in both models. These results provide valuable insights into the dynamics of pesticide contamination, highlighting areas at greater risk of contamination. The findings underscore the importance of integrating environmental, geological, and agricultural variables for more effective groundwater management and sustainable agricultural practices, contributing to the protection of water resources and public health.

54 ENVIRONMENTAL SCIENCES↗

Metribuzin resistance via enhanced metabolism in a multiple herbicide resistant Lolium rigidum population

Abstract BACKGROUND The photosystem II (PSII)‐inhibiting herbicides are important for Australian farmers to control Lolium rigidum Gaud. and other weed species in trazine tolerant (TT)‐canola fields. A L. rigidum population (R) collected from a TT‐canola field from Western Australia showed multiple resistance to PSII, acetyl‐coenzyme A carboxylase (ACCase) and acetolactate synthase (ALS) inhibitors. The mechanisms of multiple resistance in this R population were determined. RESULTS The R population showed a low‐level (about 3.0‐fold) resistance to the PSII‐inhibiting herbicides metribuzin and atrazine. Sequencing of the psbA gene revealed no differences between the R and susceptible (S) sequences. Furthermore, [ 14 C]‐metribuzin experiments found no significant difference in metribuzin foliar uptake and translocation between the R and S plants. However, [ 14 C]‐metribuzin metabolism in R plants was 2.3‐fold greater than in S plants. The cytochrome P450 monooxygenase inhibitor piperonyl butoxide (PBO) enhanced plant mortality response to metribuzin and atrazine in both R and S populations. In addition, multiple resistance to ALS and ACCase inhibitors are due to known resistance mutations in ALS and ACCase genes. CONCLUSION The results demonstrate that enhanced metribuzin metabolism likely involving cytochrome P450 monooxygenase contributes to metribuzin resistance in Lolium rigidum. This is the first report of metabolic resistance to the PSII‐inhibiting herbicide metribuzin in Australian Lolium rigidum . © 2020 Society of Chemical Industry

Ma, Hongju↗

Enzymatic Laser-Induced Graphene Biosensor for Electrochemical Sensing of the Herbicide Glyphosate

Glyphosate is a globally applied herbicide yet it has been relatively undetectable in-field samples outside of gold-standard techniques. Its presumed nontoxicity toward humans has been contested by the International Agency for Research on Cancer, while it has been detected in farmers’ urine, surface waters and crop residues. Rapid, on-site detection of glyphosate is hindered by lack of field-deployable and easy-to-use sensors that circumvent sample transportation to limited laboratories that possess the equipment needed for detection. Herein, the flavoenzyme, glycine oxidase, immobilized on platinum-decorated laser-induced graphene (LIG) is used for selective detection of glyphosate as it is a substrate for GlyOx. The LIG platform provides a scaffold for enzyme attachment while maintaining the electronic and surface properties of graphene. The sensor exhibits a linear range of 10–260 µm, detection limit of 3.03 µm, and sensitivity of 0.991 nA µm -1 . The sensor shows minimal interference from the commonly used herbicides and insecticides: atrazine, 2,4-dichlorophenoxyacetic acid, dicamba, parathion-methyl, paraoxon-methyl, malathion, chlorpyrifos, thiamethoxam, clothianidin, and imidacloprid. Sensor function is further tested in complex river water and crop residue fluids, which validate this platform as a scalable, direct-write, and selective method of glyphosate detection for herbicide mapping and food analysis.

47 OTHER INSTRUMENTATION↗

Landuse and land cover shape organic contaminants distribution in the Oconee River watershed in Georgia

Amid growing concerns over the persistence of organic contaminants, this study examines the influence of land-use patterns on their distribution in the Oconee River watershed, Georgia. Surface water samples from five sites across urban, recreational, and forested areas of Georgia’sOconee River watershed were analyzed for 22 organic contaminants, including pesticides and polycyclic aromatic hydrocarbons. Contaminant concentrations varied, with Acenaphthene (max: 19,462.04 ng/L), Chrysene (max: 984.10 ng/L), and Naphthalene (max: 2428.06 ng/L) being predominant. Atrazine (max: 171.04 ng/L) and Malathion (max: 114.99 ng/L)were the most detected pesticides. Land use and land cover significantly influence organic contaminant distribution, with higher levels in forested and urban areas. Risk Quotient (RQ) analysis confirmed no contaminants surpassed the critical threshold, though cumulative exposure may pose long-term risks. The study emphasizes the need for targeted monitoring and regulatory efforts to safeguard water quality in river systems influenced by diverse land-use practices.

54 ENVIRONMENTAL SCIENCES↗