Prediction and health impact assessment of municipal solid waste generation in Tianjin: Based on GRA-BiLSTM model

Bingchun Liu ^1,2, Xinming Zhang ¹, Jiali Chen ¹

⁰School of Economics and Management, Hebei University of Technology, Tianjin, P.R. China.

Waste Management & Research : the Journal of the International Solid Wastes and Public Cleansing Association, Iswa +

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November 17, 2025

View abstract on PubMed

Summary

Municipal solid waste (MSW) incineration in Tianjin may cause premature mortality rates of 1.7-2.7% by 2035. A GRA-BiLSTM model predicts MSW generation, highlighting the need for waste separation policies to mitigate health impacts.

Area Of Science

Environmental Science
Public Health
Data Science

Background

Incineration is a primary municipal solid waste (MSW) treatment, but generates air pollution impacting public health.
The specific health effects of MSW incineration gases, particularly PM2.5, require further investigation.

Purpose Of The Study

To develop a multi-factor prediction model for premature mortality linked to MSW incineration in Tianjin by 2035.
To quantitatively assess the health impacts of MSW incineration under various future policy and development scenarios.

Main Methods

Integration of Grey Correlation Analysis (GRA) and Bidirectional Long Short-Term Memory (BiLSTM) neural network for predictive modeling.
Analysis of three distinct scenarios considering future policies and development trends in Tianjin.
Quantitative evaluation of the relationship between MSW incineration and premature mortality.

Main Results

The GRA-BiLSTM model demonstrated high applicability for predicting MSW generation in Tianjin, with low error metrics (MAE: 12.14, MAPE: 15.78, RMSE: 4.75).
MSW generation in Tianjin is projected to reach 6.42 million tonnes by 2035.
Premature mortality rates are estimated between 1.7% and 2.7% under different incineration scenarios by 2035.

Conclusions

The study provides a robust model for predicting MSW generation and associated health risks.
Effective waste management strategies, including promoting domestic waste separation and recycling, are crucial for mitigating public health impacts.
Strengthening sanitation administrative departments is recommended to support waste management initiatives.

Keywords:

GRA-BiLSTM model Municipal solid waste PM2.5 emissions air pollution health assessment waste generation prediction