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Soil and litter emission sources as important contributors to ozone production from volatile organic compounds in island tropical forests.

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Titel: Soil and litter emission sources as important contributors to ozone production from volatile organic compounds in island tropical forests.
Autoren: Zhou H; Key Laboratory of Tropical Island Land Surface Processes and Environmental Changes of Hainan Province, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China; Sanya Land-Sea Interface Critical Zone Field Scientific Observation and Research Station, Sanya, 572022, China; Chengmai Meiting Agroforestry Complex Ecosystem Hainan Observation and Research Station, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China., Fang M; Sanya Land-Sea Interface Critical Zone Field Scientific Observation and Research Station, Sanya, 572022, China; Haikou Marine Geological Survey Center, China Geological Survey, Haikou, 571127, China., Chang Y; Key Laboratory of Meteorological Disaster (KLME), Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044, China., Li Z; State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China., Wang F; State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China., Yu Y; Key Laboratory of Tropical Island Land Surface Processes and Environmental Changes of Hainan Province, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China; Sanya Land-Sea Interface Critical Zone Field Scientific Observation and Research Station, Sanya, 572022, China; Chengmai Meiting Agroforestry Complex Ecosystem Hainan Observation and Research Station, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China., Zeng M; Key Laboratory of Tropical Island Land Surface Processes and Environmental Changes of Hainan Province, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China; Sanya Land-Sea Interface Critical Zone Field Scientific Observation and Research Station, Sanya, 572022, China; Chengmai Meiting Agroforestry Complex Ecosystem Hainan Observation and Research Station, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China., Zhan H; Sanya Land-Sea Interface Critical Zone Field Scientific Observation and Research Station, Sanya, 572022, China; Haikou Marine Geological Survey Center, China Geological Survey, Haikou, 571127, China., Zhao Z; Key Laboratory of Tropical Island Land Surface Processes and Environmental Changes of Hainan Province, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China; Sanya Land-Sea Interface Critical Zone Field Scientific Observation and Research Station, Sanya, 572022, China; Chengmai Meiting Agroforestry Complex Ecosystem Hainan Observation and Research Station, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China. Electronic address: zhizhong@hainnu.edu.cn., Zhou X; Key Laboratory of Tropical Island Land Surface Processes and Environmental Changes of Hainan Province, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China; Sanya Land-Sea Interface Critical Zone Field Scientific Observation and Research Station, Sanya, 572022, China; Chengmai Meiting Agroforestry Complex Ecosystem Hainan Observation and Research Station, School of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China. Electronic address: zhouxi13_lzu@163.com.
Quelle: Environmental research [Environ Res] 2025 Nov 15; Vol. 285 (Pt 1), pp. 122297. Date of Electronic Publication: 2025 Jul 04.
Publikationsart: Journal Article
Sprache: English
Info zur Zeitschrift: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0147621 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1096-0953 (Electronic) Linking ISSN: 00139351 NLM ISO Abbreviation: Environ Res Subsets: MEDLINE
Imprint Name(s): Publication: <2000- > : Amsterdam : Elsevier
Original Publication: New York, Academic Press.
MeSH-Schlagworte: Ozone*/analysis , Volatile Organic Compounds*/analysis , Forests* , Air Pollutants*/analysis, Soil/chemistry ; Tropical Climate ; Environmental Monitoring ; Machine Learning ; Aerosols/analysis
Abstract: Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
While studies have confirmed that volatile organic compounds (VOCs) emitted directly by tropical island forest vegetation significantly influence ozone (O 3 ) production and climate change through atmospheric oxidation processes, the environmental effects of long-neglected soil and litter emission sources as key potential contributors to VOCs, particularly their driving mechanisms in near-surface O 3 pollution formation, remain understudied. This investigation combines field observations with machine learning models to investigate the emission characteristics, sources, and contributions of VOCs from tropical island forests to O 3 and secondary organic aerosol (SOA) formation. The results reveal discrepancies between traditional ozone formation potential (OFP) estimates and machine learning-based assessments. OFP calculations identified acetaldehyde and methanol as the dominant contributors to O 3 formation, while toluene and monoterpenes were primary drivers of SOA formation. However, the XGBoost model integrated with the SHapley Additive exPlanations (SHAP) framework, which quantifies the dynamic impacts of VOCs under real-world atmospheric conditions, demonstrated that isoprene made the most significant contribution to O 3 formation (|SHAP| = 5.9), surpassing other VOCs. For SOA formation, benzene and toluene showed the highest contributions, with |SHAP| values of 1.2 and 0.8, respectively. By calculating initial VOC concentrations and applying the Positive Matrix Factorization (PMF) model, we identified four VOC sources: soil and litter emissions (41 %), oxidative formation (28.5 %), anthropogenic transport (16.6 %), and direct plant emissions (13.9 %). Photochemical reactions caused significant losses of plant-derived VOCs during transport; after accounting for photochemical losses, the contribution of direct plant emissions increased from 4.6 % to 13.9 %. SHAP analysis highlighted that soil and litter emissions contributed most significantly to O 3 formation (|SHAP| = 14.7), offering theoretical advantages over traditional OFP estimates that prioritized plant emissions. The SHAP framework, derived from observational data mining, effectively mitigated biases caused by temporal or regional variations and provided a more accurate quantification of rapidly consumed VOCs during active photochemical processes, thereby addressing limitations of conventional OFP methods. These findings indicate that VOCs from soil and litter emissions in tropical forest regions exert a substantial influence on local O 3 formation.
(Copyright © 2025 Elsevier Inc. All rights reserved.)
Contributed Indexing: Keywords: Hainan; Ozone; Tropical forests; Volatile organic compounds; XGboost
Substance Nomenclature: 66H7ZZK23N (Ozone)
0 (Volatile Organic Compounds)
0 (Air Pollutants)
0 (Soil)
0 (Aerosols)
Entry Date(s): Date Created: 20250705 Date Completed: 20251017 Latest Revision: 20251017
Update Code: 20251018
DOI: 10.1016/j.envres.2025.122297
PMID: 40617566
Datenbank: MEDLINE
Beschreibung
Abstract:Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br />While studies have confirmed that volatile organic compounds (VOCs) emitted directly by tropical island forest vegetation significantly influence ozone (O <subscript>3</subscript> ) production and climate change through atmospheric oxidation processes, the environmental effects of long-neglected soil and litter emission sources as key potential contributors to VOCs, particularly their driving mechanisms in near-surface O <subscript>3</subscript> pollution formation, remain understudied. This investigation combines field observations with machine learning models to investigate the emission characteristics, sources, and contributions of VOCs from tropical island forests to O <subscript>3</subscript> and secondary organic aerosol (SOA) formation. The results reveal discrepancies between traditional ozone formation potential (OFP) estimates and machine learning-based assessments. OFP calculations identified acetaldehyde and methanol as the dominant contributors to O <subscript>3</subscript> formation, while toluene and monoterpenes were primary drivers of SOA formation. However, the XGBoost model integrated with the SHapley Additive exPlanations (SHAP) framework, which quantifies the dynamic impacts of VOCs under real-world atmospheric conditions, demonstrated that isoprene made the most significant contribution to O <subscript>3</subscript> formation (|SHAP| = 5.9), surpassing other VOCs. For SOA formation, benzene and toluene showed the highest contributions, with |SHAP| values of 1.2 and 0.8, respectively. By calculating initial VOC concentrations and applying the Positive Matrix Factorization (PMF) model, we identified four VOC sources: soil and litter emissions (41 %), oxidative formation (28.5 %), anthropogenic transport (16.6 %), and direct plant emissions (13.9 %). Photochemical reactions caused significant losses of plant-derived VOCs during transport; after accounting for photochemical losses, the contribution of direct plant emissions increased from 4.6 % to 13.9 %. SHAP analysis highlighted that soil and litter emissions contributed most significantly to O <subscript>3</subscript> formation (|SHAP| = 14.7), offering theoretical advantages over traditional OFP estimates that prioritized plant emissions. The SHAP framework, derived from observational data mining, effectively mitigated biases caused by temporal or regional variations and provided a more accurate quantification of rapidly consumed VOCs during active photochemical processes, thereby addressing limitations of conventional OFP methods. These findings indicate that VOCs from soil and litter emissions in tropical forest regions exert a substantial influence on local O <subscript>3</subscript> formation.<br /> (Copyright © 2025 Elsevier Inc. All rights reserved.)
ISSN:1096-0953
DOI:10.1016/j.envres.2025.122297