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Environmental Factors Affecting Monoterpene Emissions from Terrestrial Vegetation
Tanzil Gaffar Malik1,2, Lokesh Kumar Sahu2, Mansi Gupta2
1Department of Botany, Guru Ghasidas Central University, Bilaspur 495009, Chhattisgarh, India.
Monoterpenes are volatile organic compounds crucial for atmospheric chemistry and plant functions. This review synthesizes emission data, highlighting environmental factors like temperature and light that influence these biogenic emissions.
Area of Science:
- Atmospheric Chemistry
- Plant Physiology
- Biogeochemistry
Background:
- Monoterpenes are volatile organic compounds with significant roles in atmospheric processes, plant physiology, and ecological interactions.
- Understanding monoterpene emissions is vital for atmospheric modeling and ecological studies.
Purpose of the Study:
- To compile and review existing data on monoterpene emission fluxes from terrestrial plant species.
- To highlight the influence of abiotic environmental factors on biogenic monoterpene emissions.
- To identify knowledge gaps and suggest future research directions.
Main Methods:
- Literature review and data compilation of monoterpene emission flux studies.
- Analysis of reported data concerning environmental variables and seasonal variations.
- Synthesis of findings to identify trends and influencing factors.
Main Results:
- Monoterpene emissions are significantly influenced by environmental factors, notably ambient air temperature and light intensity.
- Higher emission rates are typically observed during warmer seasons, such as summer in temperate regions.
- Factors like CO2, O3, soil moisture, and nutrient availability also affect emission rates, though data is less comprehensive.
Conclusions:
- Environmental factors, particularly temperature and light, are key drivers of monoterpene emissions.
- Further research is needed to fully understand the impact of CO2, O3, soil moisture, and nutrient availability on monoterpene emission rates.
- Addressing these knowledge gaps will improve atmospheric and ecological models.
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