What Does Sensor Performance Really Mean? A Four-Layer Framework for Interpreting Air Quality Sensor Performance Evaluations

Air quality (AQ) sensors are increasingly used to complement sparse reference-grade monitoring networks, enabling denser spatial coverage, rapid deployment, and new monitoring approaches. Yet, sensor performance evaluations (SPEs) are often communicated through headline metrics and comparative benchmarks that may obscure how results were produced and what they can legitimately support. Under real-world decision constraints, such results may be treated as decision-ready evidence, even when their underlying basis remains incomplete. Here, we propose a four-layer framework for interpreting SPE claims for fixed outdoor AQ sensors. The framework is organized around four main questions: who led the evaluation, what data product was actually evaluated, under what context it was evaluated, and what the reported metrics convey (and do not). From these, we derive a set of guiding questions to help users identify what information is available, missing, or uncertain, avoid overinterpreting underdescribed results, and make more grounded comparisons across studies and sources. The framework is not intended to determine fitness for purpose or prescribe a decision. Rather, it helps end users make the evidential basis of a performance claim more explicit so that they can decide what information matters for their particular use case and whether further clarification or evidence is needed.