| 中国地表臭氧浓度估算及健康影响评估 |
| 摘要点击 3752 全文点击 1279 投稿时间：2021-08-10 修订日期：2021-08-16 |
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| 中文关键词 地表臭氧 极限梯度提升算法(XGBoost) 对流层观测仪(TROPOMI) 人口暴露 慢性阻塞性肺部疾病 |
| 英文关键词 surface ozone extreme gradient boosting(XGBoost) TROPOMI population exposure chronic obstructive pulmonary disease |
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| 中文摘要 |
| 在PM2.5浓度逐年下降的背景下，臭氧浓度不降反升，臭氧已成为中国暖季的主要污染物之一.基于大数据关联分析思路，构建并开发了极限梯度提升（XGBoost）臭氧浓度估算模型，用以估算2019年中国每日最大8 h平均臭氧浓度（O3_8h），用于人类暴露评估.该模型输入地面监测站点数据、高分辨率遥感卫星数据、气象数据、排放清单数据、数字高程模型（DEM）数据和人口数据，捕捉O3_8h的时空变化.本研究采用十折交叉验证的方式评估模型的估算性能（R2为0.871，RMSE为11.7 μg·m-3），与随机森林模型（RF）和核岭回归模型（KRR）相比，由于算法本身的提升和并行处理的推进，使得XGBoost模型估算结果表现出更高的准确性（RF：R2为0.864，RMSE为12.387 μg·m-3；KRR：R2为0.582，RMSE为23.1 μg·m-3）且模型运算效率明显提升.同时对中国各省市人口臭氧暴露水平和归因于臭氧暴露的慢性阻塞性肺部疾病（COPD）死亡相对风险进行评估，结果表明，在超标天数上，非达标天数排在前五的有山东省、河南省、河北省、安徽省和宁夏回族自治区；在暴露强度上，人口加权臭氧浓度排在前五的有河北省、山东省、山西省、天津市和江苏省；在健康影响上，COPD死亡相对风险表现出季节变化，夏季最高，冬季最低. |
| 英文摘要 |
| Within the context of PM2.5 concentrations decreasing annually, ozone concentrations have increased instead of decreased, and ozone has become one of the main pollutants in the warm season in China. Based on the idea of big data association analysis, the extreme gradient boosting (XGBoost) ozone concentration estimation model was constructed and developed to estimate the maximum daily 8 h average ozone concentration (O3_8h) in China in 2019 for human exposure assessment. The model input ground monitoring station data, high-resolution remote-sensing satellite data, meteorological data, emission inventory data, digital elevation model (DEM) data, and population data were used to capture the temporal and spatial variation of O3_8h. In this study, ten-fold cross-validation was used to evaluate the estimation performance of the model (R2=0.871, RMSE=11.7 μg·m-3). Compared to those with the random forest (RF) model and kernel ridge regression (KRR) model, due to the improvement in the algorithm itself and the advancement of parallel processing, the estimation results of the XGBoost model showed higher accuracy (RF:R2=0.864, RMSE=12.387 μg·m-3). The KRR model was as follows:R2=0.582, RMSE=23.1 μg·m-3, and the computational efficiency of the model was significantly improved. At the same time, the level of ozone exposure and the relative risk of death due to chronic obstructive pulmonary disease (COPD) in China's provinces and cities were evaluated. The results showed that the top five number of days exceeding the standard occurred in Shandong Province, Henan Province, Hebei Province, Anhui Province, and the Ningxia Hui Autonomous Region. In terms of exposure intensity, Hebei Province, Shandong Province, Shanxi Province, Tianjin City, and Jiangsu Province ranked the top five in terms of population weighted ozone concentration. In terms of health effects, the relative risk of COPD death showed seasonal changes, with the highest in summer and the lowest in winter. |
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