Abstract Background  Airborne microbial and viral assemblages originate from soil, water, wastewater systems, vegetation, and human-associated environments, creating a dynamic aerobiome that links surface ecosystems and built environments. These communities include bacteria, fungi, viruses and genetic material, and can transport cells and genes, including antimicrobial resistance determinants, across spatial scales via particulate matter and atmospheric transport. The airborne microbiome and virome, and their contribution to antimicrobial resistance (AMR) dissemination, remain poorly characterised due to low biomass, temporal and spatial variability in bioaerosol concentrations, and limited ability to interpret viral sequences without concurrent source-reference data. Methods  We applied a cross-matrix, event-resolved sampling strategy combining real-time bioaerosol sensing with ultra-low-input nucleic-acid recovery to enable nanopore-based metagenomic, metaviromic, and AMR profiling. Sampling targeted engineered and agricultural emission settings, including wastewater treatment plants and poultry and dairy facilities, alongside urban and rural background sites, with reference sampling from water, wastewater, compost and soil. A Spectral Intensity Bioaerosol Sensor (SIBS) was co-located with a Coriolis μ sampler to record particle size and fluorescence while collecting biological material. Optical signals informed targeted collections during high-bioaerosol periods, with time-integrated sampling retained for comparison. Results  Downstream readouts comprise nanopore metagenomes, metaviromes and AMR gene profiles. Bacteriophages are prioritised as indicators to link viral diversity with putative bacterial hosts and support interpretation beyond detection alone. Cross-matrix reference profiles support attribution of airborne signatures. Conclusion  This approach supports exposure-relevant surveillance across connected environmental matrices. It provides a practical basis for One Health interpretation of airborne microbial and viral signals.