Journal Article

Water quality assessment and pollution source apportionment using multi-statistic and APCS-MLR modeling techniques in Min River Basin, China

Zhang, Han, Cheng, Siqian, Yu, Haoran, Li, Hongfei

2020

Overview

Anthropogenic activities pose challenges on security of water quality. Identifying potential sources of pollution and quantifying their corresponding contributions are essential for water management and pollution control. In our study, 2-year (2017–2018) water quality dataset of 15 parameters from eight sampling sites in tributaries and mainstream of the Min River was analyzed with multivariate statistical analysis methods and absolute principal component score-multiple linear regression (APCS-MLR) receptor modeling technique to reveal potential sources of pollution and apportion their contributions. Temporal and spatial cluster analysis (CA) classified 12 months into three periods exactly consistent with dry, wet, and normal seasons, and eight monitoring sites into two regions, lightly polluted (LP) and highly polluted (HP) regions, based on different levels of pollution caused by physicochemical properties and anthropogenic activities. The principal component analysis (PCA) identified five latent factors accounting for 75.84% and 73.46% of the total variance in the LP and HP regions, respectively. The main pollution sources in the two regions included agricultural activities, domestic sewage, and industrial wastewater discharge. APCS-MLR results showed that in the LP region, contribution of five potential pollution sources was ranked as agricultural non-point source pollution (22.13%) > seasonal effect and phytoplankton growth (19.86%) > leakage of septic tanks (15.73%) > physicochemical effect (12.86%) > industrial effluents and domestic sewage (11.59%), while in the HP region ranked as point source pollution from domestic and industrial discharges (20.81%) > municipal sewage (16.66%) > agricultural non-point source pollution (15.23%) > phytoplankton growth (14.82%) > natural and seasonal effects (12.67%). Based on the quantitative assessment of main pollution sources, the study can help policymakers to formulate strategies to improve water quality in different regions.

• Publisher: Springer Berlin Heidelberg,Springer Nature B.V
• Subject: Agricultural management / Agricultural wastes / Anthropogenic factors / Aquatic Pollution / Atmospheric Protection/Air Quality Control/Air Pollution / China / Cluster analysis / data collection / Discharge / Earth and Environmental Science / Ecotoxicology / Environment / Environmental Chemistry / Environmental Health / Environmental Monitoring / Environmental science / Household wastes / Industrial effluents / Industrial pollution / Industrial wastes / Industrial wastewater / Linear Models / Modelling / Multivariate statistical analysis / Municipal wastes / Municipal wastewater / Nonpoint source pollution / Physicochemical properties / Phytoplankton / Plankton / Point source pollution / Pollution / Pollution control / Pollution levels / Pollution monitoring / Pollution sources / Principal Component Analysis / Principal components analysis / Quality assessment / Quality control / Regression analysis / Research Article / River basins / Rivers / seasonal variation / Septic tanks / Sewage / Sewage effluents / Sewage tanks / Statistical analysis / Statistical methods / Tributaries / variance / Waste Water Technology / Wastewater / Wastewater discharges / Water Management / Water Pollutants, Chemical - analysis / Water pollution / Water Pollution - analysis / Water Pollution Control / Water Quality / Water quality assessments / watersheds