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Spatial distribution of microplastic pollution and its relation to pollution index-based water quality status in Progo River, Indonesia

Emerging contaminants 2025 3 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 48 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Prieskarinda Lestari, Bayu Dwi Apri Nugroho, Hanggar Ganara Mawandha, Chandra Setyawan, Eka Riskawati, Anggraeni Intan Maharani, Brillian Ravi Alvriano, Dhanny Riski Hutama, Nashita Andjani Ludmila Saraswita

Summary

Researchers mapped microplastic distribution along Indonesia's heavily polluted Progo River, finding 75 to 436 plastic particles per cubic meter of water and showing that lower oxygen levels, higher organic pollution, and faster water flow all correlated with higher microplastic concentrations — evidence that plastic particles actively degrade river water quality.

Progo River, one of the largest rivers on Java Island, serves as the primary source of clean water and irrigation for Central Java and the Special Region of Yogyakarta, Indonesia. Despite its importance, the Progo ranks among the top 20 global plastic-polluted rivers. Therefore, the objectives of this study were 1) to investigate spatial distribution and characteristics of microplastic (MP) pollution in the Progo River, and 2) to examine MP relation to the Nemerow Pollution Index (NPI) based water quality status, 15 physicochemical biological water quality parameters, flow velocity and anthropogenic factors, marking the first comprehensive effort in Indonesia. Water and MP samples were collected simultaneously from eight sampling locations. MP abundance in the Progo River ranged from 75.02 to 435.53 particles/m 3 . The MP characteristics were predominantly large, transparent, film-shaped particles, and identified variably as LDPE, PET, PP, PS, PAA, cellophane. The Pearson Correlation Test results revealed positive correlations between MP abundance and nine water quality parameters (TSS, turbidity, salinity, BOD, COD, phosphate, nitrate, detergent, Cd) and flow velocity. The other six parameters (pH, temperature, TDS, DO, total coliforms, Pb) and two anthropogenic factors (population number and density) were negatively correlated with MP abundance. Notably, DO exhibited a strong and significant negative correlation with MP abundance ( r = -0.770, p = 0.043 ). NPI scores (2.10–16.02) revealed slight to heavy polluted levels in the Progo River and were positively correlated with MP abundance ( r=0.336, p=0.461 ). Multiple Linear Regression analysis ( R 2 = 0.639 ) identified flow velocity, BOD, COD, turbidity, total coliform, and population number as significant predictors of MP distribution. These findings emphasize the impact of MP pollution on river water quality status, highlighting the need of a novel approach to incorporate MP pollution in periodic water quality assessment to address ecological risks. • Microplastic pollution was positively correlated to the Nemerow Pollution Index. • Higher microplastic abundance leads to higher NPI score, worsening water quality. • 15 water quality parameters showed certain correlations to microplastic abundance. • Multiple driving environmental factors influence microplastic spatial distribution. • Poly (acrylic acid) was first reported in microplastics from Indonesian rivers.

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