The article, led by Wen Fang and Xuxiang Zhang of Nanjing University’s School of the Environment together with colleagues from Tiangong University, Beijing University of Technology, Tsinghua University, Harbin Institute of Technology and other institutions, grew out of a dedicated session on Environmental Engineering and Intelligent Equipment. The authors frame their argument around a simple observation: environmental engineering has always been closely connected with practical engineering needs, but advancing the discipline requires not only addressing those needs but also identifying the fundamental scientific questions embedded within them. In their view, the danger is not that the field is too applied, but that it risks remaining purely reactive, solving each new problem as it arrives without asking why the problem arises in the first place.

The context for this argument is a period of unusually rapid technological and industrial transformation. The authors point to several converging forces that are reshaping what environmental engineers are being asked to do. Industrial upgrading is changing the composition and toxicity of waste streams. Artificial intelligence is entering monitoring, control and equipment design. The systems that engineers must manage are becoming more complex, coupling water, energy, materials and information flows in ways that resist simple treatment recipes. And entirely new industries are generating pollutant profiles and environmental challenges that did not exist a decade ago. Each of these forces, the authors argue, creates new opportunities for scientific discovery precisely because existing engineering knowledge cannot fully explain or predict what is happening.

At the heart of the article is a proposed methodology for converting engineering needs into scientific questions. Rather than treating a treatment plant malfunction or an equipment limitation as merely a problem to be patched, the authors suggest three complementary approaches. The first is to focus on critical system stages: the specific points in an environmental process where performance breaks down, where mass and energy transfer becomes limiting, or where small changes produce large effects. These bottlenecks, they argue, are often the surface expression of deeper gaps in understanding, and isolating them is the first step toward formulating a question worth studying.

The second approach is to explore the underlying scientific principles behind observed engineering phenomena. When a membrane fouls faster than predicted, when a catalyst deactivates under real industrial conditions, or when an intelligent control system behaves unexpectedly on a full-scale plant, the discrepancy between design expectation and field behavior signals that some physical, chemical or biological mechanism is not yet understood. The authors argue that these gaps, systematically pursued, can yield fundamental insights into reaction kinetics, interfacial processes, microbial ecology and transport phenomena, insights that no amount of incremental equipment optimization would have produced.

The third approach is interdisciplinary collaboration. The authors emphasize that the scientific questions emerging from modern environmental engineering rarely respect disciplinary boundaries. Answering them may require materials science, data science, microbiology, chemistry and process control working in concert. The forum discussion highlighted that intelligent equipment, in particular, sits at the intersection of environmental process knowledge and advances in sensing, computation and automation, and that progress depends on researchers who can communicate across those domains rather than treating each as a separate specialty.

A substantial portion of the article is addressed directly to early-career researchers, the constituency the Youth Forum was designed to serve. The authors offer three recommendations. First, strengthening university–industry collaboration: direct exposure to real engineering operations is presented as the most reliable way to encounter the unexplained phenomena that mature into scientific questions. Second, building a strong foundation in basic science, so that when an anomaly appears in practice, a researcher has the theoretical tools to recognize which fundamental principle is at stake. Third, engaging in interdisciplinary research, which the authors describe as essential both for identifying meaningful questions and for translating scientific advances back into engineering innovation.

The article is candid about the structural obstacles that make this translation difficult. Engineering projects run on timelines and performance metrics that reward incremental improvement, while fundamental research requires the freedom to pursue anomalies that may not pay off for years. Academic evaluation systems do not always credit the slow work of moving between field observation and laboratory mechanism. The authors’ response is not to lament these tensions but to propose institutional habits that bridge them: sustained partnerships with industrial partners, forum formats that force engineers and scientists to interrogate each other’s assumptions, and training that equips young researchers to move fluently between the plant floor and the laboratory bench.

The unifying concept of the article is a continuous feedback loop between engineering and science. In this loop, engineering practice generates observations that exceed current understanding; those observations are refined into scientific questions; research answers them with new principles and mechanisms; and those principles are engineered back into equipment, processes and intelligent systems that perform better and generate new observations in turn. The authors argue that establishing this loop deliberately, rather than leaving it to chance, will be critical for advancing environmental engineering through the current era of technological and industrial transformation. Fields that manage this coupling, they suggest, convert practical urgency into intellectual depth; fields that do not risk stagnating at the level of trial and error.

As an opinion piece, the article does not present new experimental data, and its claims rest on the collective experience of its nineteen authors rather than on a systematic study. Its value lies instead in articulating a research philosophy at a moment when the discipline’s inputs are changing quickly. The message to the field is straightforward: the pressures of industrial transformation, artificial intelligence, system complexity and emerging industries are not merely burdens to be managed, but a supply of unanswered scientific questions waiting to be recognized. For a discipline whose ultimate purpose is protecting the environment at industrial scale, the authors conclude, the surest path forward runs through both directions of the bridge between what engineering needs and what science can explain.

Subject of Research: Bridging environmental engineering practice and fundamental scientific research

Article Title: From engineering needs to scientific questions: bridging environmental engineering and science

Article References: Fang, W., Wang, H., Yang, Q., Xu, K., Shen, L., Zhou, Q., Chen, Y., Wen, G., Zhang, L., Deng, B., Shi, P., Zhang, C., Liang, S., Zhao, Y., Tan, J., Lin, W., Tang, H., Li, X., & Zhang, X. (2026). From engineering needs to scientific questions: bridging environmental engineering and science. ENGINEERING Environment, 20(12), Article 196. https://doi.org/10.1007/s11783-026-2296-4

Image Credits: AI Generated

DOI: 10.1007/s11783-026-2296-4

Keywords: environmental engineering, scientific questions, engineering needs, interdisciplinary collaboration, artificial intelligence, intelligent equipment, university-industry collaboration, early-career researchers, industrial transformation, feedback loop, basic science, Engineering Environment