Long-Term Cross-Border PM2.5 Transport Coupling in Southeast Asia, 2003–2024

Transboundary fine particulate matter (PM2.5) in Southeast Asia is commonly assessed using static source–receptor frameworks or descriptive associations that may not resolve how directional dependence changes through time under shifting meteorological conditions. This study examines regional PM2.5 as a time-varying, meteorology-adjusted directional coupling system using monthly data for 2003–2024 from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) meteorological covariates, climate controls, and administrative aggregation. Using a rolling-window directed network framework based on Peter and Clark Momentary Conditional Independence (PCMCI) causal discovery, we inferred lagged conditional-dependence networks from covariate-adjusted PM2.5 anomalies and summarized their structure at national and first-order administrative levels. The inferred network structure varies over time but retains measurable continuity across rolling windows. At the country level, cross-border links consistently account for a large share of the directed structure, indicating that PM2.5 variability within the study domain is strongly shaped by transboundary coupling rather than by country-contained dynamics alone. A recurrent backbone of country-level directional coupling corridors emerges, including persistent links among China, Indonesia, Myanmar, and Thailand. At the first administrative level, stable gateways and receptor basins become more evident, especially the bidirectional coupling corridor between Yunnan Province, China, and Shan State, Myanmar, which appears throughout the full window sequence. These results show that subnational structure can reveal transport-relevant coupling patterns that national summaries may conceal. The framework provides an interpretable basis for corridor-oriented monitoring and regime-aware early warning, while the inferred links should be interpreted as directional statistical dependence rather than direct emissions attribution or resolved physical transport pathways.