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MP-GERE — Field-measurement dataset for "Detection-threshold drift distorts global assessments of microplastic exposure"
AI summary Read the abstract
Studies that use finer detection methods find much more microplastic pollution than those using coarser tools, which means older or less sensitive studies may have badly underestimated contamination worldwide. Analyzing over 9,000 measurements from 102 countries, researchers found about 42% of sites exceed safe pollution thresholds, with pollution appearing to rise nearly 30% per year, a trend partly driven by better detection, not just more plastic.
Dataset accompanying the manuscript "Detection-threshold drift distorts global assessments of microplastic exposure" (11,268 field-standardized measurements from 10,289 publications across 102 countries). Version: v2.1.1 (2026-09-02) — README aligned with the final manuscript title and reporting policy; data files unchanged from v2.1 (2026-08-29, production re-extraction of 10,289 papers with the GLM-5.3 extraction model). Files File Records Description field_measurements_11268.jsonl 11,268 Normalized field-measurement records (pre-deduplication), one JSON object per line harmonized_field_records_10304.csv 10,304 Harmonized records after de-duplication (see Record counts below) ecological_effect_db.json 27 Ecological effect-size estimates from 8 independent meta-analyses (2019–2026) analysis_outputs/ — All analysis outputs used in the manuscript (see Analysis outputs) Record counts — how the three numbers relate Stage n Explanation Field measurements (pre-dedup) 11,268 All direct field measurements after excluding nanoplastic-derived records (1,899) and cross-column extraction errors (13); title count of the manuscript Harmonized (post-dedup) 10,304 After de-duplication of records sharing study, location and concentration (harmonization key) Analysis set 9,460 After excluding 1,808 records flagged as unreliable/ invalid/ physically impossible by the exclusion policy (below) All downstream statistics (exceedance, trends, spatial evidence) are computed on the analysis set (9,460) except the sensitivity exceedance (pre-deduplication, n = 6,770) and the planetary-boundary subset (n = 5,833, records with valid concentration and matrix-matched PNEC). Column dictionary (harmonized_field_records_10304.csv) Column Type Meaning record_id str Unique record identifier (MP-GERE-…) study_id / doi str Source publication DOI year int Publication year (records 1880–2026; 26 records < 1990) country str Country of sampling, if reported latitude / longitude float Coordinates if reported; empty otherwise matrix str Environmental matrix: sediment, freshwater, marine_water, soil, wastewater, other (or None) raw_value / raw_unit float / str Value and unit as reported in the source (124 distinct raw unit strings in the full corpus; 46 in the field set) standard_value / standard_unit float / str Standardized concentration — particles·kg⁻¹ (solids) or particles·L⁻¹ (water) polymer_type str Reported polymer (e.g. PE, mixed) shape str Reported shape (fiber, fragment, pellet, film, mixed, …) size_min_um / size_max_um float Particle-size range in μm (lower bound = detection threshold; 35% of records lack it) analytical_method str Detection method (visual, FTIR, Raman, μFTIR, …) source_page int Page of the source document where the value appears source_quote str Verbatim evidence excerpt used for extraction verification confidence float Extraction confidence 0–1 needs_manual_review bool Flagged for manual review during extraction standardization_path str Trace of the unit-standardization steps applied bias_tags str Methodological bias tags (visual_only, small_particle_excluded, …) qa_flags str Quality flags, |-separated (see below) qa_flags semantics Flags used by the exclusion policy (common/analysis_policy.py in the code repository): Flag prefix Meaning Excluded from analysis? mass_conversion_blocked Mass-based unit could not be converted to particles without density/size assumptions Yes (1,568 records) schema_error Failed schema validation (e.g. invalid land-use enum) Yes non_mp_substance Record refers to a non-microplastic substance Yes (260) std_dev_as_value Value actually a standard deviation Yes (24) outlier: above maximum Physically impossible concentration (above matrix-specific plausibility ceiling) Yes outlier: below minimum Concentration below the matrix-specific plausibility floor No (retained — open-ocean abundances routinely fall below common floors; excluding them would bias exceedance upward) unknown_unit Raw unit unrecognized Depends on downstream availability cross_matrix_blocked Matrix cross-conversion not applicable Not excluded Unit standardization All raw units (124 distinct strings in the corpus, 46 in the field set) were mapped to particles·kg⁻¹ (solids) and particles·L⁻¹ (water). Mass-to-particle conversions were applied only when polymer density and size distribution were reported; otherwise the record was flagged mass_conversion_blocked and excluded rather than estimated. Superscripts and suffixes (e.g. ×10³, items/L⁻¹) are normalized. Analysis outputs (analysis_outputs/) File Contents Manuscript claim planetary_boundary_assessment.json PEC/PNEC assessment, CV2 (proportion of sites exceeding), per-matrix stats 41.6% exceedance (n = 5,833; median 0.46; P95 70) temporal_analysis.json Linear mixed-effects trend model + per-matrix trends +29.5% yr⁻¹ (n = 7,328, p < 0.0001; quadratic model) sensitivity_matrix.json Exceedance by matrix × detection threshold (coarse/fine/unknown) 17% coarse / 54% fine / 42% overall (n = 6,770) — Table 1 spatial_evidence.json Per-country exceedance hotspots (≥3 geo-referenced records per country) 1,984 records / 53 countries; Brazil 95%, USA 84%, China 82%, UK 81% size_abundance.json log-log OLS of concentration on minimum detected size Slope −1.034 (n = 5,502, p < 0.0001), 10.8× per tenfold size decrease Exclusion of exploratory spatial-model outputs The manuscript does not use the spatial interpolation model. Its outputs (spatial_report.json, global_exposure_surface.csv, ters_exposure_surface.tif, ters_uncertainty_surface.tif) are excluded from this release: the exposure surfaces carried placeholder uncertainty values (grid_std = 0.1) and were validated on only 15 leave-one-site-out points. The descriptive spatial evidence (spatial_evidence.json, country-level hotspots from measured coordinates) is included because it is used in the manuscript. Users needing the exploratory surfaces can regenerate them from the code repository (analysis/spatial_model.py, marked as exploratory there). License and citation Dataset: CC BY 4.0 (attribution to the authors of this manuscript). Underlying measurement values remain the property of their original studies (DOIs retained in each record).
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