Effect of Fe (III) on acid degradation of methylparathion
A study was undertaken to determine the transformation kinetic of methylparathion (O, O, -dimethyl O-4 nitrophenylphosphorotioate) in the presence of Fe(III) between pH 2 and 7. The Fe(III) was not electroactive under the conditions used in this study, and polarographic signals were exhibited by methylparathion and main degradation product only. Data suggest that hydrolysis of methylparathion in an acid medium is catalyzed by Fe(III) and the pesticide did not degrade in this medium without this cation. Methylparathion degradation was observed at all the pHs studied and was independent of the predominant chemical form of Fe(III) in the aqueous medium. The reaction was first-order with pH-dependent rate constant (k) values ranging from 3.3 × 10− 3 h− 1 to 7.0 × 10− 3 h− 1. The k values increased as pH decreased, suggesting that Fe(III) acted as an electrophile in the reaction mechanism.
Abiotic Behaviour of Organic Micropollutants in Soils and the Aquatic Environment. A Review: II. Transformations
The abiotic processes contributing to the transformation of pesticides in soils and natural waters are reviewed for pyrethroid, carbamate and organophosphorus (OP) insecticides; and the urea, chlorophenoxy and s-triazine herbicides. The review aims to highlight the known abiotic thermochemical and photochemical reactions that may contribute to the overall degradation of pesticides, and to identify the environmental factors influencing degradation pathways and rates of transformation. Studies indicate that transformation by hydrolysis is restricted to alkaline pH for pyrethroids, OPs, carbamates and benzoylphenylureas, and limited to acid pH for sulphonylureas. OPs are also susceptible to catalysed hydrolysis by certain cations and mineral-bound +III and +IV metal ions. Little or no hydrolysis of triazines occurs in the water column or groundwaters, although triazines may be subject to hydrolysis in certain soils at acid pH. Tests indicate that alkaline hydrolysis is the most significant abiotic process for mono-substituted carbamates, and that photosensitised degradation is the most important abiotic pathway many OPs. Certain pyrethroids, triazines and urea pesticides are susceptible to photodegradation. However, the potential for photosensitised transformation for the majority of pesticide classes is uncertain (e.g. ureas, carbamates, triazines and CPHs). Tests for sensitised photodegradation need to be extended and undertaken in mixtures of natural sensitisers because of the variable effects of dissolved organic matter (DOM). There appears to be insufficient information regarding the significance of hydrolysis, photochemical degradation, and metal/mineral-catalysed transformation in the environment for the majority of these extensively used pesticide classes.
Research on Fracture Recognition in Well Logging Images: Adversarial Learning with Attention
Semantic recognition of fractures in well logging images is vital for engineers to implement oil and gas exploration. An essential approach to accomplishing the object is to adopt deep learning based on convolutional neural networks. However, due to the lack of annotated labels in well logging images, it is scarcely available to directly train the semantic segmentation network. In this paper, we explore a domain shift model attempting to achieve domain adaptation from one annotated dataset to our target well logging images. This model's core is to utilize adversarial learning, including generator and discriminator, which can prompt the model to generate fracture segmentation similar to the source domain in the target domain. For enhancing the domain adaptive model further, an attention module is introduced, which can suppress redundant noise in semantic segmentation results. We demonstrate that our proposed model performs well by extensive tests and ablation experiments in the ultrasonic well logging images.