A numerical study of the effects of aerosol hygroscopic properties to dry deposition on a broad-leaved forest

Katata, Genki; Kajino, Mizuo; Matsuda, Kazuhide; Takahashi, Akira; Nakaya, Ko

doi:10.1016/j.atmosenv.2013.11.028

Cited by 16 publications

(9 citation statements)

References 23 publications

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“…By analyzing and comparing the variations of PM 10 and PM 2.5 concentrations from 0:00 to 7:00 of the three days, the average concentrations of PM 10 and PM 2.5 on the wetland were 120.33 µg•m −3 and 157.23 µg•m −3 , respectively, higher than that on the bare land, with the ratios of 19.51% and 45.41%. The reason was that the air relative humidity under the cloudy and hazy weather lasts for 100% at night, which is to the disadvantage of the diffusion of atmospheric particulate matter and promotes the accumulation of fine particulate matter in forests on the contrary [44]. Therefore, the wetland under cloudy and hazy weather in spring will aggravate the accumulation of particulate matter, while it may reduce the concentration of particulate matter on sunny days.…”

Section: Pm Mass Concentrationmentioning

confidence: 99%

The Concentrations and Removal Effects of PM10 and PM2.5 on a Wetland in Beijing

Huang

Guo

et al. 2019

Sustainability

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Particulate matter (PM) is an essential source of atmospheric pollution in metropolitan areas since it has adverse effects on human health. However, previous research suggested wetlands can remove particulate matter from the atmosphere to land surfaces. This study was conducted in the Hanshiqiao Wetland National Nature Reserve in Beijing during 2016. The concentrations of PM10 and PM2.5 on a wetland and bare land in the park, as well as metrological data, were collected during the whole year. Based on the observed data, removal efficiency of each land use type was calculated by empirical models and the relationships between concentrations and metrological factors were also analyzed. The results indicated that: (1) In general, the PM10 and PM2.5 concentrations on the bare land surface were higher than those on the wetland surface, in both of which the highest value appeared at night and evening, while the lowest value appeared near noon. In terms of season, the average concentration of PM10 was higher in winter (wetland: 137.48 μg·m−3; bare land: 164.75 μg·m−3) and spring (wetland: 205.18 μg·m−3; bare land: 244.85 μg·m−3) in general. The concentration of PM2.5 on the wetland surface showed the same pattern, while that on the bare land surface was higher in spring and summer. (2) Concentrations of PM10 and PM2.5 were significantly correlated with the relative humidity (p < 0.01) and inversely correlated with wind speed (p < 0.05). The relationship between PM10 and PM2.5 concentrations and temperature was more complicated—it showed a significantly negative correlation (p < 0.01) between them in winter and spring, however, the correlation was insignificant in autumn. In summer, only the correlation between PM10 concentration and temperature on the wetland surface was significant (p < 0.01). (3) The dry removal efficiency of PM10 was greater than that of PM2.5. The dry removal efficiencies of PM10 and PM2.5 followed the order of spring > winter > autumn > summer on the wetland. This study seeks to provide practical measures to improve air quality and facilitate sustainable development in Beijing.

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Section: Pm Mass Concentrationmentioning

confidence: 99%

The Concentrations and Removal Effects of PM10 and PM2.5 on a Wetland in Beijing

Huang

Guo

et al. 2019

Sustainability

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“…where RH is the relative humidity (%) and AR is the ratio of total acid/NH 3 , represented as ( As explained in Katata et al (2014), the aerosol deposition rate F p (µg m −2 s −1 or # m −2 s −1 ) of each inorganic species in each canopy layer is represented as…”

Section: Dry Depositionmentioning

confidence: 99%

“…In aerosol dynamics modeling, the moment method is used to reduce computational cost and include general processes such as condensation, coagulation, below-cloud scavenging processes (e.g., Binkowski and Shankar, 1995), and dry deposition (Bae et al, 2009). These processes are implemented into a multi-layer atmosphere-SOiL-VEGetation model (SOLVEG) that includes particle (aerosol and fog droplet) deposition and hygroscopic 45 aerosol growth processes (Katata et al, 2014). We apply the model to a Japanese mixed forest for calibration and validation.Finally, we use numerical experiments to examine the impacts of two key processes on dry deposition flux over the canopy; gas-particle conversion of inorganic nitrogen compounds and hygroscopic growth.…”

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confidence: 99%

Aerosol dynamics and gas-particle conversion in dry deposition of inorganic reactive nitrogen in a temperate forest

Katata¹,

Matsuda²,

Kajino³

et al. 2019

Preprint

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Although dry deposition has an impact on nitrogen status in the forest environments, the mechanism for high dry deposition rates of fine nitrate aerosols (NO − 3 ) observed in forests remains unknown and is a potential source of error in chemical transport models. Here we developed a new multi-layer land surface model coupled with dry deposition and aerosol dynamics processes for a temperate mixed forest in Japan. The processes of thermodynamics, kinetics, and dry deposition for mixed inorganic aerosols are modeled by a triple-moment modal method. The new model overall reproduces observed turbulent 5 fluxes above the canopy and vertical micrometeorological profiles, as well as inorganic mass and size-resolved total number concentrations within the canopy. Sensitivity tests revealed that the within-canopy evaporation of ammonium nitrate (NH 4 NO 3 ) under dry conditions significantly enhances deposition flux for fine NO − 3 and NH + 4 aerosols, while reducing deposition flux for nitric acid gas (HNO 3 ). A dry deposition scheme coupled with aerosol dynamics may be required to improve the predictive accuracy of chemical transport models for the surface concentration of inorganic reactive nitrogen. 10 15 Sakamoto et al., 2018; Nakahara et al., 2019). As long as physical deposition processes are dominant, the deposition velocities of SO 2− 4 and NO − 3 aerosols are expected to be similar because both species exist in the same sub-micron size range (e.g., Wolff et al., 2011). However, Sakamoto et al. (2018) showed observed deposition velocity of NO − 3 as high as those of HNO 3 at a temperate mixed forest, using the relaxed eddy accumulation method (Matsuda et al., 2015). Nakahara et al. (2019) also observed a higher concentration gradient of fine NO − 3 than of fine SO 2− 4 at a cool-temperate forest, using a thermodynamic 20 equilibrium model to explain this difference by evaporation of NH 4 NO 3 aerosols in the NH 4 NO 3 -NH 3 -HNO 3 triad within1 https://doi.the canopy. Numerical studies of chemical transport models for the East Asian region have demonstrated that the models have overestimated total (gas + aerosol) nitrate concentration at many locations (Kajino et al., 2013; Shimadera et al., 2018; Morino et al., 2015; Sakurai et al., 2015). Despite the many uncertain factors (e.g., the emission inventory; grid resolution; chemistry, physics, dynamics, and deposition modules), Shimadera et al. (2014) demonstrated that the surface concentration 25of total nitrate could be reproduced by increasing dry deposition velocity of HNO 3 by a factor of twenty, in reference to past numerical studies. Hence, the deposition velocity of NO − 3 of fine aerosols and/or HNO 3 is among the major uncertainties in the chemical transport modeling.Modeling studies for dry deposition have demonstrated the importance of NH 4 NO 3 volatilization during dry deposition of gaseous and particulate nitrates (Brost et al., 1988;van Oss et al., 1998;Kramm and Dlugi, 1994). All these studies used 30 the "big-leaf" concept for the canopy represen...

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“…Therefore, we apply a process-based land surface model that can simulate both physical (snow and freeze-thaw) and biological processes (carbon allocation under cold stresses) and which includes sink limitations. This integrated model is based on a multi-layer atmosphere-soil-vegetation model (SOLVEG; Katata et al, 2014), and is run at two managed grassland sites in the German pre-Alpine region. The simulation period cov-ers a number of years that include normal (2011-2012 and 2012-2013) and extremely warm (2013)(2014) winters.…”

Section: Introductionmentioning

confidence: 99%

Wintertime grassland dynamics may influence belowground biomass under climate change: a model analysis

et al. 2020

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Abstract. Rising temperatures and changes in snow cover, as can be expected under a warmer global climate, may have large impacts on mountain grassland productivity limited by cold and long winters. Here, we combined two existing models, the multi-layer atmosphere-SOiL-VEGetation model (SOLVEG) and the BASic GRAssland model (BASGRA), which accounts for snow, freeze–thaw events, grass growth, and soil carbon balance. The model was applied to simulate the responses of managed grasslands to anomalously warm winter conditions. The grass growth module considered key ecological processes under a cold environment, such as leaf formation, elongation and death, tillering, carbon allocation, and cold acclimation, in terms of photosynthetic activity. Input parameters were derived for two pre-Alpine grassland sites in Germany, for which the model was run using 3 years of data that included a winter with an exceptionally small amount of snow. The model reproduced the temporal variability of observed daily mean heat fluxes, soil temperatures, and snow depth throughout the study period. High physiological activity levels during the extremely warm winter led to a simulated CO2 uptake of 100 gC m−2, which was mainly allocated into the belowground biomass and only to a minor extent used for additional plant growth during early spring. If these temporary dynamics are representative of long-term changes, this process, which is so far largely unaccounted for in scenario analysis using global terrestrial biosphere models, may lead to carbon accumulation in the soil and/or carbon loss from the soil as a response to global warming.

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A numerical study of the effects of aerosol hygroscopic properties to dry deposition on a broad-leaved forest

Cited by 16 publications

References 23 publications

The Concentrations and Removal Effects of PM10 and PM2.5 on a Wetland in Beijing

The Concentrations and Removal Effects of PM10 and PM2.5 on a Wetland in Beijing

Aerosol dynamics and gas-particle conversion in dry deposition of inorganic reactive nitrogen in a temperate forest

Wintertime grassland dynamics may influence belowground biomass under climate change: a model analysis

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