A high-resolution multi-scale industrial water use dataset in China

Area of Science:

• Environmental Science
• Water Resource Management
• Industrial Ecology

Background:

• The industrial sector is a significant contributor to global water use and pollution.
• Effective water management is essential for achieving UN Sustainable Development Goal 6 (SDG 6).
• Existing industrial water data often lacks the accuracy, granularity, and coverage needed for robust analysis.

Purpose of the Study:

• To present a novel, high-resolution, open dataset of industrial water use in China.
• To provide comprehensive data on water use, recycling, pollution, and wastewater treatment at the plant level.
• To facilitate advanced multi-scale and multi-method analysis for improved water management strategies.

Main Methods:

• Compilation of an open dataset from 1,480,265 plant-level industrial reports in China.
• Data organization to support analysis at province, city, and county levels.
• Inclusion of detailed information across 2-digit, 3-digit, and 4-digit industrial classifications.

Main Results:

• A high-resolution, multi-scale dataset detailing China's industrial water use is now available.
• The dataset encompasses crucial metrics including water consumption, recycling rates, pollution discharge, and wastewater treatment.
• The data supports diverse analytical approaches, from input-output modeling to machine learning applications.

Conclusions:

• This dataset offers an unprecedented resource for researchers and policymakers focused on sustainable water management.
• It enables refined macro- and micro-level analyses to address water challenges in the industrial sector.
• The findings support efforts to align industrial practices with global sustainability objectives, particularly SDG 6.