Water-quality data for pesticides, nutrients, and volatile organic compounds in near-surface aquifers of the midcontinental United States, 1992-1994

The quantitative understanding of the transport behavior of volatile organic compounds (VOCs) in near-surface soils is highly important in light of the potential impacts of soil VOC emissions on the air quality and climate. Previous studies have suggested that temperature changes affect the transport behavior; however, the effects are not well understood. Indeed, much larger changes in the VOC flux under in situ dynamic temperatures than those expected from the temperature dependence of the diffusion coefficients of VOCs in the air have been suggested but rarely investigated experimentally. Here, we present the results of a set of experiments on the upward vertical vapor-phase diffusive transport of benzene and trichloroethylene (TCE) in sandy soils with water contents ranging from an air-dried value to 10 wt% during sinusoidal temperature variation between 20 and 30 °C. In all experiments, the flux from the soil surface was correlated with the temperature, as expected. However, the changes in flux under wet conditions were unexpectedly large and increased with increasing water content; they were also larger for TCE, the volatility of which depended more strongly on the temperature. Additionally, the larger flux changes were accompanied by a recently discovered water-induced inverse correlation between temperature and flux into the overlying soil. These results demonstrated that the flux changes of VOCs under dynamic temperatures could be increased by volatilization-dissolution interactions of VOCs with water. Future extensive studies on this newly discovered phenomenon would contribute to a better understanding of the impacts of soil VOC emissions on the air quality and climate.

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Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

Geoscientific Model Development ◽

10.5194/gmd-9-1959-2016 ◽

2016 ◽

Vol 9 (5) ◽

pp. 1959-1976 ◽

Cited By ~ 14

Author(s):

Chun Zhao ◽

Maoyi Huang ◽

Jerome D. Fast ◽

Larry K. Berg ◽

Yun Qian ◽

...

Keyword(s):

Air Quality ◽

Volatile Organic Compounds ◽

Organic Compounds ◽

Land Surface ◽

Aerosol Formation ◽

Biogenic Volatile Organic Compounds ◽

Vegetation Map ◽

Near Surface ◽

Volatile Organic ◽

The Impact

Abstract. Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.

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