③利用APCS-MLR模型进一步量化了各类人为和天然因素对流域内地下水质量影响的贡献,5项因子对特征指标的平均贡献率分别为45.15%、70.76%、45.54%、54.1%和44.59%。 研究成果不仅有利于更加清晰掌握滇池流域地下水质量状况,还可为区域地下水防...
如PM2.5的浓度与APCS建立多元线性回归方程，通过回归系数计算每个因子的贡献即可
本研究在评价流域地下水质量及主要影响指标的基础上,利用主成分分析法(PCA)归纳主要影响水质的驱动因子,并结合绝对主成分得分-多元线性回归受体模型(APCS-MLR模型)进一步量化了人为和天然因素对流域内地下水质量的影响程度. 结果表明: ①滇...
如PM2.5的浓度与APCS建立多元线性回归方程，通过回归系数计算每个因子的贡献即可虚拟VCC卡申请成功之后，...
多环芳烃(PAHs)分布特征来源解析为明确典型矿业活动区浅层地下水多环芳烃(PAHs)污染特征及来源,通过水样采集与测试分析,综合采用多元统计分析方法,正矩阵因子分解(PMF)和绝对主成分得分-多元线性回归(APCS-MLR)模型,研究了某煤矿区地下水中PAHs的分布特征与影响因素,污染来源及贡献率.结果表明:研究区地下水中PAHs的...
Gholizadeh MH, Melesse AM, Reddi L (2016) Water quality assessment and apportionment of pollution sources using APCS-MLR and PMF receptor modeling techniques in three major rivers of South Florida. Sci Total Environ 566:1552–1567. https://doi.org/10.1016/j.scitotenv.2016.06.046 Article CAS...
Both PMF and FA-NNC have a nonnegative constraint process, which may be the main reason why their results were much more similar to each other than to those of PCA-MLR. PCA-MLR distinguishes variables into several groups that have the greatest variances from each other, whereas the other ...
The APCS-MLR model considered the average contribution of each different potential pollution source to these categories separately. The potential pollution sources in the groundwater presented an obvious spatial distribution with an area of high concentration distributed mainly in the western and ...
Higher R and smaller proportion of unexplained variability in the PMF model suggested that PMF approach could provide more physically plausible source apportionment in the study area and a more realistic representation of groundwater pollution than solutions from PCA-APCS-MLR model. The study showed ...
Furthermore, absolute principal components score combined with multivariate linear regression (APCS-MLR) was conducted. The results illustrated that domestic wastewater contributes more than 70% of N pollution and river-bottom sediments contribute more than 50% of P pollution under dry conditions. On ...