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Updated: Feb 14, 2026

Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
Spatial patterns of pollutants in water of metropolitan drain in Lahore, Pakistan, using multivariate statistical
Shumaila Majeed1,2, Sajid Rashid3, Abdul Qadir3
1College of Earth and Environmental Sciences, University of the Punjab, Lahore, Pakistan. shumaeela78@gmail.com.
Abstract:
The present study was conducted to investigate the pollutant load in surface water of the Sattukatla drain in Lahore, Pakistan. This drain is receiving high volumes of pollutants from industries and municipal sewage. To study the pollution status of this urban drain, different parameters such as pH, EC, TDS, BOD, NO3, PO4, COD, K, Mg, Ca, Ni, Fe, Co, Pb, Cu, Cd, and Zn were analyzed. These 17 parameters were monitored along the longitudinal gradient of drain consisting of 15 key sampling sites. The studied parameters were subjected to hierarchical cluster analysis (HCA) and factor analysis (FA). The HCA divided 15 sampling sites into three zones, i.e., low pollution, medium pollution, and high pollution. The PCA identified three major contributors, industrial followed by municipal sewage and agricultural sources. The trend of heavy metal levels was observed as Cu > Zn > Fe > Pb > Co > Ni > Cd. The results indicate levels of pollutants above the permissible limits described by NEQS, Pakistan for wastewater. There is an urgent need to address the issue and install treatment plants to reduce the pollution load on this urban drain in Lahore city.
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