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The current biodiversity and climate crises highlight the need for efficient tools to monitor terrestrial ecosystems. Here, we provide evidence for the use of airborne eDNA analyses as a novel method for detecting terrestrial vertebrate communities in nature. Metabarcoding of 143 airborne eDNA samples collected during 3 days in a mixed forest in Denmark yielded 64 bird, mammal, fish and amphibian taxa, of which the detected 57 'wild' taxa represent over a quarter of the around 210 terrestrial vertebrates that occur in the overall area. We provide evidence for the spatial movement and temporal patterns of airborne eDNA and for the influence of weather conditions on vertebrate detections. This study demonstrates airborne eDNA for high‐resolution biomonitoring of vertebrates in terrestrial systems and elucidates its potential to guide global nature management and conservation efforts in the ongoing biodiversity crisis. see also the Perspective by David M. Lodge [ABSTRACT FROM AUTHOR]

A network of five low-cost air pollution sensor (LCS) nodes was deployed vertically on the exterior of the H. C. Ørsted Institute at the University of Copenhagen, Denmark, to investigate the transport of pollution from the road below. All LCS nodes measured PM 2.5 , NO 2 , and O 3 at 1-min time resolution, and one of them also measured noise. Traffic was monitored with a webcam, where traffic type and levels were derived using a machine-learning algorithm. We investigated how well traffic-related air pollution, noise, and real-time traffic counts serve as proxies for one another. The correlations between NO 2 , noise, and traffic count exhibited relatively low values when considering all the data. However, these correlations significantly increased under southwesterly wind direction and low wind speed, reaching R 2 = 0.40 for NO 2 and noise, R 2 = 0.51 for NO 2 and traffic volume, and R 2 = 0.70 for noise and traffic volume. These results indicate a common source, namely traffic, for all three parameters. The five LCS nodes spanning 25 m vertically had extremely low intervariability with minimum R 2 -values of 0.98 for PM 2.5 , 0.89 for NO 2 , and 0.97 for O 3. The system could not detect a vertical gradient in pollution levels. Large-eddy simulation model runs using the PALM model system generally supported the lack of gradient observed in measured observations. Under slightly unstable stratification, concentration remained relatively constant with height for southwesterly and southerly winds. Conversely, winds from the north, west, and northwest showed an increase in concentration with height. For other wind directions, the concentration decreased with height by approximately 40 % to 50 %, which is not as strong as for neutral stratification, attributed to enhanced vertical mixing under unstable stratification. Based on the measurements and modeling, we conclude that the vertical concentration profile is very sensitive to stratification, and under these conditions, the concentration outside the window of a fifth-floor office is almost the same as for an office on the ground floor. [Display omitted] • Investigation of pollution concentrations from street to urban background using low-cost sensors. • A moderate correlation was found between traffic-related air pollution, noise, and traffic counts, influenced by wind speed and direction. • No vertical gradient was detected with low-cost sensors, despite low sensor intervariability. • Large-eddy simulation model runs using the PALM model system generally supported the measured observations. • Vertical concentration profile is very sensitive to stratification. [ABSTRACT FROM AUTHOR]