School of Energy and Mining Engineering,China University of Mining and Technology-Beijing

针对露天矿粉尘无秩序排放引发的生态环境退化问题,选取河曲露天煤矿粉尘产生区域为研究靶区,利用粉尘监测体系获取靶区TSP、PM10、PM2.5及环境指标数据,结合粉尘浓度对不同粒径粉尘分布差异性进行对比分析,引入空气质量浓度分指数法、Pearson关联矩阵分析法和灰色关联法对靶区内核心污染物、不同粒径粉尘内在关联性及环境指标与粉尘浓度的关联度进行深入探讨,基于单变量、多元线性和主成分得分-多元线性回归分析法对粒子变迁演化规律及环境指标对微粉尘权重的影响规律进行定量解析,同时运用均值误差法对MLR和PCA-MLR模型预测的精确度进行验证。结果表明:①区域1(采掘场)和3(煤场)不同粒径粉尘浓度均存在超过现行标准二级限值的情况,区域2(交通干道)仅存在超过一级限值的情况。②不同区域粉尘污染能力的强弱与IAQI评估结果一致,均为区域1>3>2;当不同区域TSP浓度一致时,域内粉尘污染能力的强弱顺序转变为区域2>3>1,且各区域核心污染物均为PM2.5。③不同区域粉尘浓度线性关系较为显著。④不同区域MLR模型演算出的多元线性方程的拟合度排序规律与粉尘浓度Pearson关联度趋于一致,且多变量拟合度优于单变量拟合度,结合MRE法检验出不同区域MLR模型预测精度区域3(3.02%)>2(9.46%)>1(10.75%)。⑤区域1中TSP和PM10与气压呈强正相关,PM2.5与相对湿度呈强负相关;区域2中各粒径粉尘均与温度和风速呈强负相关;区域3中仅与温度呈强负相关。⑥微粉尘权重与环境指标的PCA-MLR模型相对于直接MLR模型,预测精确度提高了56.63%和13.41%。

As disorderly dust emission of open-pit mines often leads to ecological degradation,this study therefore conducts a quantitative analysis on the evolution patterns of particle changes and the influence of environmental indicators on the weights of microdust. Taking the main regions of dust occurrence in Hequ open-pit coal mine as the subject for research,this study uses the dust monitoring system to obtain data on TSP,PM10,PM2. 5 and environmental indicators in different target regions. We conducted comparative analysis on the differences in the distribution of particles with different sizes based on dust concentration and introduced the Institute for Administrative Quality Improvement method,Pearson cor relation matrix analysis and Grey Relation Analysis to explore the core pollutants, the intrinsic correlation of dust with different particle sizes,and the correlation between environmental indicators and dust concentration in the target regions. Based on the univariate regression analysis,MLR and PCA MLR,we verified the predictions of the MLR and the PCA-MLR model by MRE. The results show that:The concentration of dust with different particle sizes in Region No. 1 ( excavation site) and Region No. 3 ( coal yard )exceeded the secondary limit in the current standard, while the concentration in Region No. 2 (traffic artery) only exceeded the primary limit. ②The dust pollution capacity of different regions was consistent with results from IAQI assessment:Region 1 >Region 3 > Region 2,where the core pollutants were all PM2. 5. When the concentration of TSP was consistent in different regions,we found Region 2>Region 3>Region 1 in terms of their dust pollution capacity. ③ Dust concentrations in different areas were found to be linearly significant. ④The patterns of fitting in multivariate linear equations based on MLR models of different regions tended to be consistent with the Pearson correlation of dust concentration,with the multivariate fit outperforming the univariate fit. We also found Region No. 3 (3. 02% ) > Region 2 (9. 46% ) >Region 1 (10. 75% ) in terms of the pre diction accuracy of MLR model. ⑤TSP and PM10 were strongly positively correlated with barometric pressure while PM2. 5 was strongly negatively correlated with relative humidity in Region No. 1;dust with different particle sizes was strongly negatively correlated with temperature and wind speed in Re gion No. 2 yet only negatively correlated with temperature in Region No. 3. ⑥The PCA-MLR model outperformed the direct MLR model with a 56. 63% and 13. 41% increase in microdust weights and environmental indicators.

国家自然科学基金(51474220);中央高校基本科研业务费专项资金(BBJ2023004)

赵洪宝,翟汝鹏,戈海宾,等.基于统计学模型的矿区粉尘污染特征及影响因素的定量分析[J].矿业科学学报,2024,9(2):243-257.

ZHAO Hongbao,ZHAI Rupeng,GE Haibin,et al. Quantitative analysis of dust pollution characteristics and influencing factors in mining areas based onstatistical modelling[J]. Journal of Mining Science and Technology,2024,9(2):243-257.