This article is part of the Data Science for Advancing Environmental Science, Engineering, and Technology special issue. Figure 1. We should leverage the advantages (right side) that ChatGPT offers us while also exercising caution regarding potential hidden pitfalls (left side). The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.3c01818. Ten example interactions with ChatGPT covering different areas of environmental research (PDF) Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html. Zhiyong Jason Ren is a Professor in the Department of Civil and Environmental Engineering and the Andlinger Center for Energy and the Environment at Princeton University. His research focuses on the decarbonization and digitalization of the environmental and chemical sectors. His group uses electrochemistry, microbiology, and data science tools to understand the fundamental determining factors and develop models and technologies for resource recovery during environmental and chemical processes. Prof. Ren is an Associate Editor of Environmental Science & Technology and Environmental Science & Technology Letters. The authors are thankful for the financial support via the Paul L. Busch Award from the Water Research Foundation. The authors used ChatGPT, a language model developed by OpenAI, to generate writing and testing examples. This article references 10 other publications. Smart citations by scite.ai include citation statements extracted from the full text of the citing article. The number of the statements may be higher than the number of citations provided by ACS Publications if one paper cites another multiple times or lower if scite has not yet processed some of the citing articles. This article is cited by 28 publications. Figure 1. We should leverage the advantages (right side) that ChatGPT offers us while also exercising caution regarding potential hidden pitfalls (left side). Zhiyong Jason Ren is a Professor in the Department of Civil and Environmental Engineering and the Andlinger Center for Energy and the Environment at Princeton University. His research focuses on the decarbonization and digitalization of the environmental and chemical sectors. His group uses electrochemistry, microbiology, and data science tools to understand the fundamental determining factors and develop models and technologies for resource recovery during environmental and chemical processes. Prof. Ren is an Associate Editor of Environmental Science & Technology and Environmental Science & Technology Letters. This article references 10 other publications. The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.3c01818. Ten example interactions with ChatGPT covering different areas of environmental research (PDF) Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

中文翻译：

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ChatGPT 和环境研究

本文是该文章的一部分推进环境科学、工程和技术的数据科学专刊。图 1. 我们应该利用 ChatGPT 为我们提供的优势（右侧），同时对潜在的隐藏陷阱（左侧）保持谨慎。支持信息可在 https://pubs.acs.org/doi/10.1021/acs.est.3c01818 免费获取。十个与 ChatGPT 交互的示例，涵盖环境研究的不同领域 (PDF) 大多数电子支持信息文件无需订阅 ACS 网络版即可获得。此类文件可以按文章下载用于研究用途（如果有链接到相关文章的公共使用许可证，则该许可证可能允许其他用途）。可以通过 RightsLink 许可系统提出请求，从 ACS 获得许可用于其他用途：http://pubs.acs.org/page/copyright/permissions.html。任志勇是普林斯顿大学土木与环境工程系和安德林格能源与环境中心的教授。他的研究重点是环境和化学领域的脱碳和数字化。他的团队使用电化学、微生物学和数据科学工具来了解基本的决定因素，并开发环境和化学过程中资源回收的模型和技术。任教授是《Environmental Science & Technology》和《Environmental Science & Technology Letters》的副主编。作者感谢水研究基金会 Paul L. Busch 奖提供的财政支持。作者使用 OpenAI 开发的语言模型 ChatGPT 来生成编写和测试示例。本文参考了其他 10 篇出版物。scite.ai的智能引文  包括从施引文章全文中提取的引文语句。如果一篇论文多次引用另一篇论文，则语句的数量可能会高于 ACS Publications 提供的引用次数；如果 scite 尚未处理某些施引文章，则语句的数量可能会低于 ACS Publications 提供的引用次数。这篇文章被 28 家出版物引用。图 1. 我们应该利用 ChatGPT 为我们提供的优势（右侧），同时对潜在的隐藏陷阱（左侧）保持谨慎。任志勇是普林斯顿大学土木与环境工程系和安德林格能源与环境中心的教授。他的研究重点是环境和化学领域的脱碳和数字化。他的团队使用电化学、微生物学和数据科学工具来了解基本的决定因素，并开发环境和化学过程中资源回收的模型和技术。任教授是Environmental Science & Technology和Environmental Science & Technology的副主编。环境科学与技术快报。本文参考了其他 10 篇出版物。支持信息可在 https://pubs.acs.org/doi/10.1021/acs.est.3c01818 免费获取。十个与 ChatGPT 交互的示例，涵盖环境研究的不同领域 (PDF) 大多数电子支持信息文件无需订阅 ACS 网络版即可获得。此类文件可以按文章下载用于研究用途（如果有链接到相关文章的公共使用许可证，则该许可证可能允许其他用途）。可以通过 RightsLink 许可系统提出请求，从 ACS 获得许可用于其他用途：http://pubs.acs.org/page/copyright/permissions.html。