Evidence map›Paper›PMID 40618262›Full record

ReviewEnvironmental science & technology2025

Copter-Type UAV-Based Sensing in Atmospheric Chemistry: Recent Advances, Applications, and Future Perspectives.

Yaowei Li, Chen Zhang, Weifeng Su, Shaojie Jiang, Dongyang Nie, Yaying Wang, Yuzheng Wang, Hongdi He, Qi Chen, Scot T Martin and 1 more

Abstract readReview
In one paragraph

Review in Environmental science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yaowei LiSchool of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States.ORCID 0000-0003-0725-6108
Chen ZhangShenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
Weifeng SuShenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
Shaojie JiangShenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
Dongyang NieShenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
Yaying WangShenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
Yuzheng WangShenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
Hongdi HeCenter for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Qi ChenState Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.ORCID 0000-0003-3559-8914
Scot T MartinSchool of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States.ORCID 0000-0002-8996-7554
Jianhuai YeShenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.ORCID 0000-0002-9063-3260

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Copter-type unmanned aerial vehicles (UAVs) have emerged as cutting-edge platforms for environmental research, offering rapid and cost-effective solutions for atmospheric sensing and sampling. This review highlights recent advancements and explores future prospects for their application in atmospheric chemistry. The UAV-based techniques have demonstrated excellent capabilities in characterizing the spatial distribution of gaseous pollutants using both real-time, low-cost sensors, and offline analytical methods. These platforms have also proven effective in profiling the physicochemical properties of airborne particulate matter, providing insights into its sources, chemical transformation, and environmental and climate impacts. In regard to the applications, this review underscores the diverse roles of UAVs related to atmospheric chemistry, including emission characterization (e.g., forest volatile and bioaerosol emissions), hazard assessment (e.g., wildfire and volcanic plume monitoring), and meteorology and climate research (e.g., aerosol-cloud interactions). The review also addresses key challenges in current UAV techniques, such as payload and battery limitations, regulatory constraints, propeller-induced disturbances, and explores emerging directions, such as UAVs in biosphere-atmosphere interactions and indoor air quality monitoring. Overall, UAVs are reshaping atmospheric chemistry research by providing high-resolution spatial data sets that complement traditional methods. These advancements further enhance our understanding of atmospheric processes and facilitate the development of precise and adaptable environmental monitoring strategies.

Indexed as

AircraftAtmosphereEnvironmental MonitoringAerosolsAir PollutantsParticulate MatterAerosolsAir PollutantsParticulate Matteratmospheric chemistrycopter-type UAVsemission characterizationhazard assessmentmeteorology and climate application

Identifiers

PMID40618262
PMCPMC12356195

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.