A city-level dataset of heavy metal emissions into the atmosphere across China from 2015-2020.

ABSTRACT: The absence of nationwide distribution data regarding heavy metal emissions into the atmosphere poses a significant constraint in environmental research and public health assessment. In response to the critical data deficiency, we have established a dataset covering Cr, Cd, As, and Pb emissions into the atmosphere (HMEAs, unit: ton) across 367 municipalities in China. Initially, we collected HMEAs data and covariates such as industrial emissions, vehicle emissions, meteorological variables, among other ten indicators. Following this, nine machine learning models, including Linear Regression (LR), Ridge, Bayesian Ridge (Bayesian), K-Neighbors Regressor (KNN), MLP Regressor (MLP), Random Forest Regressor (RF), LGBM Regressor (LGBM), Lasso, and ElasticNet, were assessed using coefficient of d

SUBMITTER: Dong Q 

PROVIDER: S-EPMC10904851 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature