Temporal variation of outdoor particulate matter concentration in a village of the Qinghai-Tibet Plateau and its correlation with meteorological factors: based on long-term field measurement and machine learning approach

IF 3.1 4区环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES

Air Quality Atmosphere and Health Pub Date : 2026-09-23 DOI:10.1007/s11869-026-02094-2

Yumiao Li, Jialin Chen, Di Wu, Rongjiang Ma, Yuhao Yi, Tao Yu, Mengsi Deng

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引用次数: 0

Abstract

The incomplete combustion of yak dung on the Qinghai-Tibet Plateau (QTP) emitted a substantial amount of PM, causing severe environmental pollution in the villages. However, the temporal variation in pollutant concentrations and the impact of meteorological parameters in the villages of the QTP have not been thoroughly studied. Therefore, this study collected year-round PM concentrations and various meteorological parameters on the QTP. Temporal variation characteristics of PM were analyzed. An integrated analytical framework combining Spearman correlation analysis and machine learning methods was developed to evaluate the correlations between PM_2.5 concentration and meteorological factors. The results showed that the annual mean PM₁₀ and PM_2.5 concentrations were 24.3 ug/m³ and 18.5 ug/m³, the highest monthly mean concentrations of PM₁₀ and PM_2.5 were recorded in December, and the lowest were in July. The intense peaks of PM concentrations occurred in the 8:00-10:00 and 18:00-22:00 periods. The PM concentration peaks in the heating season were much higher than those in the non-heating season. PM_2.5 was the dominant part of the PM with the monthly PM_2.5/PM₁₀ ratio of 68.6%-76.2%. Random Forest (RF) outperformed the Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM) in the aspects of three evaluation metrics. PM_2.5 concentration was negatively correlated with solar radiation, temperature, and wind speed. The outdoor PM_2.5 concentrations during the yak dung stove-operation period in the villages of four cities on the QTP were predicted, which exhibited similar variation trends. The results could help propose future strategies for improving outdoor air quality and assess their environmental-health improvements.

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青藏高原某村庄室外颗粒物浓度的时空变化及其与气象因子的相关性——基于长期野外测量和机器学习方法

青藏高原牦牛粪的不完全燃烧排放了大量的PM，对村庄造成了严重的环境污染。然而，青藏高原村庄污染物浓度的时间变化和气象参数的影响尚未得到深入研究。因此，本研究收集了QTP的全年PM浓度和各种气象参数。分析了PM的时间变化特征。建立了Spearman相关分析与机器学习方法相结合的综合分析框架，评估PM2.5浓度与气象因子之间的相关性。结果表明：PM10和PM2.5的年平均浓度分别为24.3 ug/m3和18.5 ug/m3， PM10和PM2.5的月平均浓度在12月最高，在7月最低；PM浓度高峰出现在8:00 ~ 10:00和18:00 ~ 22:00时段。采暖季PM浓度峰值远高于非采暖季PM浓度峰值。PM2.5占主导地位，月PM2.5/PM10比值为68.6% ~ 76.2%。随机森林（RF）在三个评价指标上优于极端梯度增强（XGBoost）和光梯度增强机（LightGBM）。PM2.5浓度与太阳辐射、温度、风速呈负相关。对QTP上4个城市村庄牦牛粪开炉期间的室外PM2.5浓度进行了预测，结果显示出相似的变化趋势。研究结果有助于提出未来改善室外空气质量的策略，并评估其对环境健康的改善。

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来源期刊

Air Quality Atmosphere and Health ENVIRONMENTAL SCIENCES-

CiteScore

8.80

自引率

2.00%

发文量

146

审稿时长

>12 weeks

期刊介绍： Air Quality, Atmosphere, and Health is a multidisciplinary journal which, by its very name, illustrates the broad range of work it publishes and which focuses on atmospheric consequences of human activities and their implications for human and ecological health. It offers research papers, critical literature reviews and commentaries, as well as special issues devoted to topical subjects or themes. International in scope, the journal presents papers that inform and stimulate a global readership, as the topic addressed are global in their import. Consequently, we do not encourage submission of papers involving local data that relate to local problems. Unless they demonstrate wide applicability, these are better submitted to national or regional journals. Air Quality, Atmosphere & Health addresses such topics as acid precipitation; airborne particulate matter; air quality monitoring and management; exposure assessment; risk assessment; indoor air quality; atmospheric chemistry; atmospheric modeling and prediction; air pollution climatology; climate change and air quality; air pollution measurement; atmospheric impact assessment; forest-fire emissions; atmospheric science; greenhouse gases; health and ecological effects; clean air technology; regional and global change and satellite measurements. This journal benefits a diverse audience of researchers, public health officials and policy makers addressing problems that call for solutions based in evidence from atmospheric and exposure assessment scientists, epidemiologists, and risk assessors. Publication in the journal affords the opportunity to reach beyond defined disciplinary niches to this broader readership.