[Chinese Mainland] AI Enters the Core of Process Control: Seven-Department Document Sets the Tone, "Aeration + Chemical Dosing" Are the First Two Links to Prove Their Worth

2026 年 9 月At the beginning, the Cyberspace Administration of China, the National Development and Reform Commission, the Ministry of Industry and Information Technology, the Ministry of Ecology and Environment and three other departments jointly issued the "Implementation Plan for Promoting the Coordinated Transformation and Development of Digitalization and Greening (2026—2030 年)", which for the first time elevated digitalization from an auxiliary tool to a foundational mechanism driving green goals that are quantifiable and verifiable. The engineering side simultaneously provided verification data: at a wastewater treatment plant with a capacity of 2 万 m³/day in Pinghu, Zhejiang, the power consumption of the blowers alone dropped by 10% compared with before; 9 月 16 日a set of intelligent biological oxidation solutions released in Chengdu claims to achieve aeration energy consumption reduction of 30%—50%, carbon source dosing reduction of more than 50%, and treatment capacity improvement of 10%—20%.

The policy side has introduced new assessment criteria

The key change in this plan is the shift in what is assessed. In the past, environmental assessment looked at end-of-pipe indicators, that is, whether the effluent met standards; now it requires extending to the source and process, bringing energy consumption, chemical consumption, and carbon emissions into the management scope.

• Digitalization is no longer a bonus item—the document positions digitalization as a foundational mechanism that makes green goals measurable, controllable, and optimizable, rather than an optional management aid;
• The time anchor is clear—it proposes that by 2030 年, artificial intelligence will deeply empower green and low-carbon technological innovation, and digital and intelligent technologies will continuously enhance the capacity for ecological and environmental governance;
• Three questions must be answered—for wastewater treatment plants, beyond meeting discharge standards, they must also be able to answer "how many chemicals were used, how much electricity was consumed, and how much carbon was saved."

The direct consequence of this shift is that the operating costs that wastewater treatment plants previously found hard to explain are now becoming data that must be clearly accounted for.

Engineering side: benefits are first seen in two stages

From the publicly available implementation data, the energy-saving benefits are most concentrated in two high-energy-consumption stages.

• Aeration stage—oxygen-consuming microorganisms in the biochemical tank require continuous oxygen supply, and the power consumption of blowers typically accounts for about half of the plant's total electricity use. At the wastewater treatment plant with a capacity of 2 万 m³/day in Pinghu, relying on an intelligent process control system, while maintaining the bottom line of meeting effluent standards, the blower power consumption dropped by 10% compared with before. The approach is to rely on real-time data such as Dissolved Oxygen and ammonia nitrogen fed back by instruments in the biochemical tank for real-time analysis, dynamically adjust the operating status of the blowers, and move the control threshold forward from "post-adjustment" to "pre-prediction."
• Chemical dosing stage—the dosing of phosphorus removal chemicals and external carbon sources has long relied on empirical judgment, with obvious lag. Intelligent phosphorus removal dosing and carbon source dosing systems that have achieved production-level application generally save chemicals in the range of 8% to more than 10%; some systems adopt a closed-loop control mode of "feedforward plus model plus feedback," directly sinking down to programmable logic controllers and underlying equipment.
• The effect of the combined approach is more obvious—the solution released in Chengdu forms a closed loop from four parts: intelligent biochemical sensing, low Dissolved Oxygen micro-aerobic reaction, precise multi-point influent, and biological model algorithms. It claims that in-situ upgrading of wastewater plants without production stoppage can be achieved without large-scale civil construction. Existing projects have verified that zero dosing of external carbon sources can be achieved, with annual cost savings of more than 60 万 yuan and an investment payback period of 2 to 3 年.

Why it was not done in the past

The automation foundation of wastewater plants is actually not poor; the problem lies at three levels.

• Insufficient data availability—instruments drift over time and lack regular calibration, and online data for influent and effluent are incomplete, so even if the model runs, it is built on distorted data;
• Stuck at the dashboard stage—the digitalization of many water plants is still limited to data collection and large-screen display, which looks good but does not generate benefits, and on-site operation still relies on the experience of veteran operators;
• Unclear attribution of benefits—energy-saving retrofits require upfront investment, while the saved electricity and chemical costs are difficult to measure separately, and the two parties cannot agree on the revenue-sharing ratio, so the project remains on paper.

The business model is filling in the last link

What truly drives this round of implementation is actually the spread of mechanisms such as energy performance contracting.

• Zero upfront investment for the owner — the technology provider advances the funds for the retrofit and shares in the energy-saving revenue, which has significantly improved acceptance among county-level and industrial park wastewater treatment plants;
• Three paths for contract-based water conservation — benefit-sharing, performance-guaranteed, and water cost trusteeship models, available for owners with different risk preferences;
• A unified scale for measurement — as electricity and chemical consumption are converted into measurable carbon emission data, the construction requirements of digital energy-carbon management centers are turning this accounting into reality.

Industry Reminder: Beware of Three Pitfalls

Amid the boom, calm judgment is also needed.

• Calibrate meters first, then discuss models — without reliable online data, any algorithm is merely armchair strategy. It is recommended to treat instrument calibration and data governance as Phase I, and then launch intelligent control as Phase II.
• Retain manual-priority switching capability — under conditions such as sudden changes in influent quality or equipment failure, manual intervention must always take priority over algorithm commands, and the switching logic must be explicitly locked down in the contract.
• Energy savings must have a baseline — the core of the sharing model is the measurement basis for energy savings, which must be established through baseline testing before the retrofit and confirmed by both parties; otherwise, disputes are highly likely to arise later.
• Beware of over-promising — proposals claiming energy savings exceeding 40% are often based on the premise that the original system operates at a poor level. Evaluation should be based on the actual electricity and chemical consumption of the unit itself, rather than directly applying promotional data.

Our Assessment

TIANYI TECH has long provided wastewater treatment and reclaimed water reuse system solutions for municipal and industrial clients. We believe that the value anchor of artificial intelligence in wastewater treatment plants is very clear: whoever can reduce the electricity and chemical consumption of aeration and dosing — these two processes — will have stronger policy compliance and more stable profitability. However, the prerequisite for this capability is not algorithms, but data and measurement. We recommend that owners intending to advance intelligent control place the first step on instrument calibration, data governance, and baseline testing; the second step on algorithms; and the third step on business model design.

About TIANYI LIMITED: TIANYI TECH is deeply engaged in the field of wastewater treatment and reclaimed water reuse, committed to providing efficient, low-carbon, and sustainable water treatment solutions for municipal and industrial clients.