Аннотация
Microplastics (MPs) are increasingly detected in wastewater treatment systems, where treatment plants act simultaneously as interception nodes and point sources via treated effluents and sludge management. This contribution synthesizes a PRISMA-guided critical review focused on Kazakhstan and Central Asia, benchmarking the region against a harmonized global dataset while explicitly interrogating how methodological choices drive inter-study variability.A structured evidence map (2010–Sept 2025) was compiled and curated into a comparable database of 63 wastewater-treatment studies worldwide, yielding 402 matrix–stage observations across influent, effluent, and sludge streams. Observation-level descriptive statistics show that global raw influent concentrations cluster around 100 particles/L (median ≈65 particles/L), whereas final/tertiary effluents are typically 1 particles/L (median ≈2.2 particles/L). Overall MP removal increases from secondary treatment (median ≈85.5%) to tertiary/advanced trains (median ≈95.0%), while sludge acts as the dominant sink, retaining MP burdens on the order of 1000–100.000 particles/kg dry weight. Across matrices, fibers dominate the reported morphologies and polymer signatures are consistently led by PET/PES, PP, and PE, consistent with textile and packaging sources.Central Asian plant-level evidence remains extremely limited (two eligible wastewater treatment plants case studies, both in Kazakhstan), but when comparisons are restricted to like-for-like analytical windows, influent levels align with the global interquartile range. In contrast, secondary-only configurations tend to place effluent concentrations in the upper half of the global envelope, supporting the inference that the presence/absence of post-secondary barriers (filtration, DAF/BAF, membranes/MBR) is the primary determinant of regional performance relative to international benchmarks. The review identifies three dominant uncertainty drivers—sampling representativeness (grab vs. composite), minimum size cut-offs (especially