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Algorithm developed for dynamic quantification of coal consumption for and emission from rural winter heating
Yuzhe Zhang1, Guorui Zhi2, Sicong Guo3
1State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; College of Science, China University of Petroleum, Beijing 102249, China.
The Science of the Total Environment
|June 11, 2020
Summary
Rural coal consumption for winter heating can be estimated daily using a new composite temperature metric. This method helps predict coal emissions and supports timely haze mitigation strategies.
Area of Science:
- Environmental Science
- Atmospheric Chemistry
- Energy Policy
Background:
- Coal combustion for rural winter heating in China is a significant contributor to regional haze.
- Limited understanding of daily coal consumption patterns hinders effective haze mitigation.
- Existing data often aggregates coal use, obscuring real-time emission dynamics.
Purpose of the Study:
- To investigate the relationship between daily rural coal consumption and experienced cold temperatures.
- To develop a method for estimating real-time (daily) coal usage for winter heating.
- To provide a basis for dynamic air pollution control strategies.
Main Methods:
- A field study was conducted in a village to monitor coal addition instances.
- Daily coal consumption (WDAY) was calculated by summing all recorded coal additions.
- A composite temperature (TCOM) index was developed to represent experienced cold.
Main Results:
- A strong negative linear correlation was found between daily coal consumption (WDAY) and composite temperature (TCOM) (WDAY = -0.75TCOM + 11.86, R2 = 0.75).
- The findings validate the hypothesis that coal burning strength for heating is related to experienced temperatures.
- An algorithm was developed to estimate regional coal consumption based on TCOM and household numbers (NH).
Conclusions:
- Daily coal consumption for winter heating can be reliably estimated using weather data.
- The developed algorithm offers a scalable approach for estimating heating-related emissions across different regions.
- This method has potential global applicability for countries relying on energy for winter heating, aiding in air quality management.
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