分析2018-2023年亚洲空气污染，发现南亚最严重且可预测。
Assessing and Predicting Air Pollution in Asia: A Regional and Temporal Study (2018-2023)
- 按区域聚类分组，识别高、中、低污染国家
- ARIMA模型预测2023年PM2.5误差低（MAE: 3.99）
- 南亚多国污染与死亡率高，需针对性治理
本研究分析并预测2018至2023年亚洲五个区域（中亚、东亚、南亚、东南亚、西亚）的空气污染情况，重点关注PM2.5水平。南亚污染最严重，孟加拉国、印度、巴基斯坦持续呈现最高PM2.5浓度与死亡率，尤以尼泊尔、巴基斯坦和印度为甚；东亚污染水平最低。通过K-means聚类将各国划分为高、中、低污染组。使用ARIMA模型预测2023年PM2.5，均方误差（MSE）为33.80，平均绝对误差（MAE）为3.99，均方根误差（RMSE）为5.81，相关系数（R）达0.86。结果强调针对南亚地区严重污染及健康风险采取精准干预的必要性。
原文摘要 · Abstract (English)
This study analyzes and predicts air pollution in Asia, focusing on PM 2.5 levels from 2018 to 2023 across five regions: Central, East, South, Southeast, and West Asia. South Asia emerged as the most polluted region, with Bangladesh, India, and Pakistan consistently having the highest PM 2.5 levels and death rates, especially in Nepal, Pakistan, and India. East Asia showed the lowest pollution levels. K-means clustering categorized countries into high, moderate, and low pollution groups. The ARIMA model effectively predicted 2023 PM 2.5 levels (MAE: 3.99, MSE: 33.80, RMSE: 5.81, R: 0.86). The findings emphasize the need for targeted interventions to address severe pollution and health risks in South Asia.
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