Lihe News | New Product Debuts at the 2025 Symposium on Odour in Urban Water Supply and the 2025 IWA Symposium on Odour and Algal Toxins in Drinking Water Sources and Aquaculture

The 2025 Symposium on Precise Odour Detection and Comprehensive Prevention Technologies for Urban Water Supply Systems and the 2025 International Water Association (IWA) Symposium on Odour and Algal Toxins in Drinking Water Sources and Aquaculture were jointly hosted by the Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences; Shanghai National Engineering Centre for Urban Water Resources Development and Utilisation Co., Ltd.; Xi'an University of Architecture and Technology; Zhejiang University; and other institutions. The events took place in Shanghai from 28 August to 1 September. Keynote presentations were delivered by distinguished experts including Academician Qu Jiuhui of the Chinese Academy of Sciences and Researcher Yang Min from the Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences.

Photo: On-site of the 2025 Symposium on Odour in Urban Water Supply Systems

At the Odour Response Specialised Forum, our company's Chief Engineer of the R&D Centre, Chen Yang, delivered a presentation entitled ‘Drinking Water Odour Monitoring and Early Warning Technology System’. The presentation focused on current odour issues within water supply systems, systematically outlining cutting-edge advancements in odour monitoring and early warning technologies. It highlighted that algal-derived odorous compounds such as geosmin and 2-methylisoborneol, triggered by algal blooms, have emerged as significant threats to drinking water safety.

Photo: On-site of the Presentation by Chen Yang, Chief Engineer of the Company's R&D Center

01 New Product Launch

Lihe Technology has established an in-depth industry-academia-research collaboration with Professor Yang Min's research group at the Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. This partnership has successfully developed the industry's first automated detection instrument for odour-producing algae genes (GWD-1500). This equipment achieves a breakthrough by enabling online monitoring and intelligent analysis of odour-producing genes. Combined with an odour prediction model driven by environmental parameters and auxiliary diagnostic techniques based on algal morphology, it establishes a risk early-warning model. This technological system now extends the odour occurrence identification window by 7-10 days, effectively advancing the strategic shift in odour management from reactive post-event response to proactive pre-emptive intervention. It provides reliable technical support for safeguarding drinking water safety.

02 Core Products

The Intelligent Algal Image Analyser and Online Intelligent Algal Analyser were designed and developed in accordance with the standard ‘Water Quality - Determination of Phytoplankton - 0.1 mL Counting Frame-Microscope Counting Method’ (HJ 1216-2021). Utilising deep learning technology combined with an expert knowledge base, these instruments construct an AI algal recognition model. Through automated sampling technology and fully automated microscopic imaging techniques, they provide detailed information on algal genera, algal density, dominance, and diversity within water bodies, thereby achieving automated, intelligent, and non-specialist-dependent algal genus analysis.

Developed based on the HS-SPME-GCMS method, this technique targets multiple common odorous compounds including geosmin (GSM), 2-Methylisoborneol (2-MIB), Dimethyl disulphide (DMDS), Dimethyl trisulphide (DMTS) and other common odorous compounds. It enables automated, unmanned continuous online monitoring, encompassing automated water sampling, spiking, curve calibration, needle replacement, solid-phase microextraction, and liquid injection.

Building upon conventional manual chlorophyll a determination methods, this product leverages the distinct fluorescence spectra of different algal phyla. Utilising excitation wavelengths at 470nm, 525nm, and 610nm, it detects algal fluorescence signals at 680nm to enable online measurement of chlorophyll a concentrations and cell densities in cyanobacteria, green algae, and diatoms.