Dataset Information

Intermediate-scale horizontal isoprene concentrations in the near-canopy forest atmosphere and implications for emission heterogeneity.

ABSTRACT: The emissions, deposition, and chemistry of volatile organic compounds (VOCs) are thought to be influenced by underlying landscape heterogeneity at intermediate horizontal scales of several hundred meters across different forest subtypes within a tropical forest. Quantitative observations and scientific understanding at these scales, however, remain lacking, in large part due to a historical absence of canopy access and suitable observational approaches. Herein, horizontal heterogeneity in VOC concentrations in the near-canopy atmosphere was examined by sampling from an unmanned aerial vehicle (UAV) flown horizontally several hundred meters over the plateau and slope forests in central Amazonia during the morning and early afternoon periods of the wet season of 2018. Unlike terpene concentrations, the isoprene concentrations in the near-canopy atmosphere over the plateau forest were 60% greater than those over the slope forest. A gradient transport model constrained by the data suggests that isoprene emissions differed by 220 to 330% from these forest subtypes, which is in contrast to a 0% difference implemented in most present-day biosphere emissions models (i.e., homogeneous emissions). Quantifying VOC concentrations, emissions, and other processes at intermediate horizontal scales is essential for understanding the ecological and Earth system roles of VOCs and representing them in climate and air quality models.

SUBMITTER: Batista CE

PROVIDER: S-EPMC6765269 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Intermediate-scale horizontal isoprene concentrations in the near-canopy forest atmosphere and implications for emission heterogeneity.

Batista Carla E CE Ye Jianhuai J Ribeiro Igor O IO Guimarães Patricia C PC Medeiros Adan S S ASS Barbosa Rafael G RG Oliveira Rafael L RL Duvoisin Sergio S Jardine Kolby J KJ Gu Dasa D Guenther Alex B AB McKinney Karena A KA Martins Leila D LD Souza Rodrigo A F RAF Martin Scot T ST

Proceedings of the National Academy of Sciences of the United States of America 20190909 39

The emissions, deposition, and chemistry of volatile organic compounds (VOCs) are thought to be influenced by underlying landscape heterogeneity at intermediate horizontal scales of several hundred meters across different forest subtypes within a tropical forest. Quantitative observations and scientific understanding at these scales, however, remain lacking, in large part due to a historical absence of canopy access and suitable observational approaches. Herein, horizontal heterogeneity in VOC c ...[more]

PMID: 31501347

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Project description:BackgroundNear-road exposures of traffic-related air pollutants have been receiving increased attention due to evidence linking emissions from high-traffic roadways to adverse health outcomes. To date, most epidemiological and risk analyses have utilized simple but crude exposure indicators, most typically proximity measures, such as the distance between freeways and residences, to represent air quality impacts from traffic. This paper derives and analyzes a simplified microscale simulation model designed to predict short- (hourly) to long-term (annual average) pollutant concentrations near roads. Sensitivity analyses and case studies are used to highlight issues in predicting near-road exposures.MethodsProcess-based simulation models using a computationally efficient reduced-form response surface structure and a minimum number of inputs integrate the major determinants of air pollution exposures: traffic volume and vehicle emissions, meteorology, and receptor location. We identify the most influential variables and then derive a set of multiplicative submodels that match predictions from "parent" models MOBILE6.2 and CALINE4. The assembled model is applied to two case studies in the Detroit, Michigan area. The first predicts carbon monoxide (CO) concentrations at a monitoring site near a freeway. The second predicts CO and PM2.5 concentrations in a dense receptor grid over a 1 km2 area around the intersection of two major roads. We analyze the spatial and temporal patterns of pollutant concentration predictions.ResultsPredicted CO concentrations showed reasonable agreement with annual average and 24-hour measurements, e.g., 59% of the 24-hr predictions were within a factor of two of observations in the warmer months when CO emissions are more consistent. The highest concentrations of both CO and PM(2.5) were predicted to occur near intersections and downwind of major roads during periods of unfavorable meteorology (e.g., low wind speeds) and high emissions (e.g., weekday rush hour). The spatial and temporal variation among predicted concentrations was significant, and resulted in unusual distributional and correlation characteristics, including strong negative correlation for receptors on opposite sides of a road and the highest short-term concentrations on the "upwind" side of the road.ConclusionsThe case study findings can likely be generalized to many other locations, and they have important implications for epidemiological and other studies. The reduced-form model is intended for exposure assessment, risk assessment, epidemiological, geographical information systems, and other applications.

Dataset Information

Intermediate-scale horizontal isoprene concentrations in the near-canopy forest atmosphere and implications for emission heterogeneity.

Publications

Intermediate-scale horizontal isoprene concentrations in the near-canopy forest atmosphere and implications for emission heterogeneity.

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