4.8 Article

Synthesizing Laboratory and Field Experiments to Quantify Dominant Transformation Mechanisms of 2,4-Dichlorophenoxyacetic Acid (2,4-D) in Aquatic Environments

期刊

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.est.2c03132

关键词

contaminant fate and transport; photodegradation; biodegradation; 2; 4-dichlorophenoxyacetic acid; herbicides

资金

  1. Onterra, LLC
  2. homeowners of Pike Lake Chain of Lakes Association
  3. Random Lake Association
  4. Round Lake Property Owners Association
  5. WDNR
  6. National Science Foundation Graduate Research Fellowship
  7. Anna Grant Birge Memorial Award

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This study combines laboratory and field data to identify the dominant loss processes of the herbicide 2,4-D in lakes, demonstrating the importance of microbial and photochemical degradation. Attempts to quantify transformation products were unsuccessful, but results suggest that their persistence is not a major concern.
Laboratory studies used to assess the environmental fate of organic chemicals such as pesticides fail to replicate environmental conditions, resulting in large errors in predicted transformation rates. We combine laboratory and field data to identify the dominant loss processes of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) in lakes for the first time. Microbial and photochemical degradation are individually assessed using laboratory-based microcosms and irradiation studies, respectively. Field campaigns are conducted in six lakes to quantify 2,4-D loss following large-scale herbicide treatments. Irradiation studies show that 2,4-D undergoes direct photodegradation, but modeling efforts demonstrated that this process is negligible under environmental conditions. Microcosms constructed using field inocula show that sediment microbial communities are responsible for degradation of 2,4-D in lakes. Attempts to quantify transformation products are unsuccessful in both laboratory and field studies, suggesting that their persistence is not a major concern. The synthesis of laboratory and field experiments is used to demonstrate best practices in designing laboratory persistence studies and in using those results to mechanistically predict contaminant fate in complex aquatic environments.

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