scholarly journals A revised parameterization for gaseous dry deposition in air-quality models

2003 ◽  
Vol 3 (6) ◽  
pp. 2067-2082 ◽  
Author(s):  
L. Zhang ◽  
J. R. Brook ◽  
R. Vet
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Stomatal Resistance ◽  
Model Output ◽  
Gaseous Species ◽  
Area Index ◽  
Quality Models ◽  
Deposition Velocities ◽  
Study Results ◽  
Land Types

Abstract. A parameterization scheme for calculating gaseous dry deposition velocities in air-quality models is revised based on recent study results on non-stomatal uptake of O3 and SO2 over 5 different vegetation types. Non-stomatal resistance, which includes in-canopy aerodynamic, soil and cuticle resistances, for SO2 and O3 is parameterized as a function of friction velocity, relative humidity, leaf area index, and canopy wetness. Non-stomatal resistance for other chemical species is scaled to those of SO2 and O3 based on their chemical and physical characteristics. Stomatal resistance is calculated using a two-big-leaf stomatal resistance sub-model for all gaseous species of interest. The improvements in the present model compared to its earlier version include a newly developed non-stomatal resistance formulation, a realistic treatment of cuticle and ground resistance in winter, and the handling of seasonally-dependent input parameters. Model evaluation shows that the revised parameterization can provide more realistic deposition velocities for both O3 and SO2, especially for wet canopies. Example model output shows that the parameterization provides reasonable estimates of dry deposition velocities for different gaseous species, land types and diurnal and seasonal variations. Maximum deposition velocities from model output are close to reported measurement values for different land types. The current parameterization can be easily adopted into different air-quality models that require inclusion of dry deposition processes.

scholarly journals A revised parameterization for gaseous dry deposition in air-quality models

2003 ◽  
Vol 3 (2) ◽  
pp. 1777-1804 ◽  
Author(s):  
L. Zhang ◽  
J. R. Brook ◽  
R. Vet
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Stomatal Resistance ◽  
Model Output ◽  
Gaseous Species ◽  
Area Index ◽  
Quality Models ◽  
Deposition Velocities ◽  
Study Results ◽  
Land Types

Abstract. A parameterization scheme for calculating gaseous dry deposition velocities in air-quality models is revised based on recent study results on non-stomatal uptake of O3 and SO2 over 5 different vegetation types. Non-stomatal resistance, which includes in-canopy aerodynamic resistance, soil resistance and cuticle resistance, for SO2 and  O3 is parameterized as a function of friction velocity, relative humidity, leaf area index, and canopy wetness. Non-stomatal resistance for all other species is scaled to those of SO2 and  O3 based on their chemical and physical characteristics. Stomatal resistance is calculated using a leaf-stomatal-resistance model for all gaseous species of interest. The improvements in the present model compared to its earlier version include a newly developed non-stomatal resistance formulation, a realistic treatment of cuticle and ground resistance in winter and the handling of seasonally-dependent input parameters. Model evaluation shows that the revised parameterization can provide more realistic deposition velocities for both  O3 and SO2, especially for wet canopies. Example model output shows that the parameterization provides reasonable estimates of dry deposition velocities for different gaseous species, land types and diurnal and seasonal variations. Maximum deposition velocities from model output are close to reported measurement values for different land types. The current parameterization can be easily adopted into different air-quality models that require inclusion of dry deposition processes.

scholarly journals Particle dry deposition algorithms in CMAQ version 5.3: characterization of critical parameters and land use dependence using DepoBoxTool version 1.0

2021 ◽  
Author(s):  
Qian Shu ◽  
Benjamin Murphy ◽  
Jonathan E. Pleim ◽  
Donna Schwede ◽  
Barron H. Henderson ◽  
...  
Keyword(s):  
Land Use ◽  
Particle Size ◽  
Air Quality ◽  
Dry Deposition ◽  
Box Model ◽  
Critical Parameters ◽  
Average Particle ◽  
Area Index ◽  
Deposition Velocities ◽  
Use Categories

Abstract. This study investigates particle dry deposition by characterizing critical parameters and land-use dependence in a 0-D box model as well as quantifying the resulting impact of dry deposition parameterizations on regional-scale 3-D model predictions. A publicly available box model configured with several land-use dependent dry deposition schemes is developed to evaluate predictions of several model approaches with available measurements. The 0-D box model results suggest that current dry deposition schemes in 3-D regional models underestimate particle dry deposition velocities, but this varies with size distribution properties and land-use categories. We propose two revised schemes to improve dry deposition performance in air quality models and test them in the Community Multiscale Air Quality (CMAQ) model. The first scheme improves the previous CMAQ scheme by preserving the original dry deposition impaction calculation but turning off redundant integration across particle size for each aerosol mode. The second scheme adds a dependence on leaf area index (LAI) to better estimate uptake to vegetative surfaces while using a settling velocity that is integrated across particle size for the Stokes number calculation. CMAQ model performance was evaluated for a month in July 2011 for the conterminous U.S. based on available observations of ambient sulfate (SO4) aerosol concentrations from multiple routine particulate matter monitoring networks. Incorporation of the first scheme has a larger impact on coarse particles than fine particles, systematically reducing monthly domain-wide average particle dry deposition velocities (Vd) by approximately 96% and 35%, respectively, and increasing monthly average SO4 concentrations by 395% and 21%. After incorporating LAI into the boundary layer resistance (Rb), the second scheme creates more spatial diversity of Vd and changes SO4 concentrations (coarse = −76% to +336%; fine = −7% to +18%) with land-use categories. These modifications are incorporated into the current publicly available version of CMAQ (v5.3 and beyond).

scholarly journals Coupling between surface ozone and leaf area index in a chemical transport model: strength of feedback and implications for ozone air quality and vegetation health

2018 ◽  
Vol 18 (19) ◽  
pp. 14133-14148 ◽  
Author(s):  
Shan S. Zhou ◽  
Amos P. K. Tai ◽  
Shihan Sun ◽  
Mehliyar Sadiq ◽  
Colette L. Heald ◽  
...  
Keyword(s):  
Air Quality ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Deposition ◽  
Transport Model ◽  
Surface Ozone ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Area Index ◽  
Ozone Levels

Abstract. Tropospheric ozone is an air pollutant that substantially harms vegetation and is also strongly dependent on various vegetation-mediated processes. The interdependence between ozone and vegetation may constitute feedback mechanisms that can alter ozone concentration itself but have not been considered in most studies to date. In this study we examine the importance of dynamic coupling between surface ozone and leaf area index (LAI) in shaping ozone air quality and vegetation. We first implement an empirical scheme for ozone damage on vegetation in the Community Land Model (CLM) and simulate the steady-state responses of LAI to long-term exposure to a range of prescribed ozone levels (from 0 to 100 ppb). We find that most plant functional types suffer a substantial decline in LAI as ozone level increases. Based on the CLM-simulated results, we develop and implement in the GEOS-Chem chemical transport model a parameterization that computes fractional changes in monthly LAI as a function of local mean ozone levels. By forcing LAI to respond to ozone concentrations on a monthly timescale, the model simulates ozone–LAI coupling dynamically via biogeochemical processes including biogenic volatile organic compound (VOC) emissions and dry deposition, without the complication from meteorological changes. We find that ozone-induced damage on LAI can lead to changes in ozone concentrations by −1.8 to +3 ppb in boreal summer, with a corresponding ozone feedback factor of −0.1 to +0.6 that represents an overall self-amplifying effect from ozone–LAI coupling. Substantially higher simulated ozone due to strong positive feedbacks is found in most tropical forests, mainly due to the ozone-induced reductions in LAI and dry deposition velocity, whereas reduced isoprene emission plays a lesser role in these low-NOx environments. In high-NOx regions such as the eastern US, Europe, and China, however, the feedback effect is much weaker and even negative in some regions, reflecting the compensating effects of reduced dry deposition and reduced isoprene emission (which reduces ozone in high-NOx environments). In remote, low-LAI regions, including most of the Southern Hemisphere, the ozone feedback is generally slightly negative due to the reduced transport of NOx–VOC reaction products that serve as NOx reservoirs. This study represents the first step to accounting for dynamic ozone–vegetation coupling in a chemical transport model with ramifications for a more realistic joint assessment of ozone air quality and ecosystem health.

scholarly journals Modeling atmospheric ammonia and ammonium using a stochastic Lagrangian air quality model (STILT-Chem v0.7)

2013 ◽  
Vol 6 (2) ◽  
pp. 327-344 ◽  
Author(s):  
D. Wen ◽  
J. C. Lin ◽  
L. Zhang ◽  
R. Vet ◽  
M. D. Moran
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Chemical Conversion ◽  
Air Quality Model ◽  
Quality Model ◽  
Gaseous Species ◽  
Time Step ◽  
Back Trajectories ◽  
Atmospheric Ammonia ◽  
Chemistry Module

Abstract. A new chemistry module that simulates atmospheric ammonia (NH3) and ammonium (NH+4) was incorporated into a backward-in-time stochastic Lagrangian air quality model (STILT-Chem) that was originally developed to simulate the concentrations of a variety of gas-phase species at receptors. STILT-Chem simulates the transport of air parcels backward in time using ensembles of fictitious particles with stochastic motions, while accounting for emissions, deposition and chemical transformation forward in time along trajectories identified by the backward-in-time simulations. The incorporation of the new chemistry module allows the model to simulate not only gaseous species, but also multi-phase species involving NH3 and NH+4. The model was applied to simulate concentrations of NH3 and particulate NH+4 at six sites in the Canadian province of Ontario for a six-month period in 2006. The model-predicted concentrations of NH3 and particulate NH+4 were compared with observations, which show broad agreement between simulated concentrations and observations. Since the model is based on back trajectories, the influence of each major process such as emission, deposition and chemical conversion on the concentration of a modeled species at a receptor can be determined for every upstream location at each time step. This makes it possible to quantitatively investigate the upstream processes affecting receptor concentrations. The modeled results suggest that the concentrations of NH3 at those sites were significantly and frequently affected by Ohio, Iowa, Minnesota, Michigan, Wisconsin, southwestern Ontario and nearby areas. NH3 is mainly contributed by emission sources whereas particulate NH+4 is mainly contributed by the gas-to-aerosol chemical conversion of NH3. Dry deposition is the largest removal process for both NH3 and particulate NH+4. This study revealed the contrast between agricultural versus forest sites. Not only were emissions of NH3 higher, but removal mechanisms (especially chemical loss for NH3 and dry deposition for NH+4) were less efficient for agricultural sites. This combination explains the significantly higher concentrations of NH3 and particulate NH+4 observed at agricultural sites.

scholarly journals Technical Note – AQMEII4 Activity 1: Evaluation of Wet and Dry Deposition Schemes as an Integral Part of Regional-Scale Air Quality Models

2021 ◽  
Author(s):  
Stefano Galmarini ◽  
Paul Makar ◽  
Olivia Clifton ◽  
Christian Hogrefe ◽  
Jesse Bash ◽  
...  
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Model Evaluation ◽  
Regional Scale ◽  
Technical Note ◽  
Air Pollutant ◽  
Evaluation Activity ◽  
Quality Models ◽  
Wet And Dry Deposition ◽  
Regional Air Quality

Abstract. We present in this technical note the research protocol for Phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This research initiative is divided in two activities, collectively having three goals: (i) to define the current state of the science with respect to representations of wet and especially dry deposition in regional models, (ii) to quantify the extent to which different dry deposition parameterizations influence retrospective air pollutant concentration and flux predictions, and (iii) to identify, through the use of a common set of detailed diagnostics, sensitivity simulations, model evaluation, and reducing input uncertainty, the specific causes for the current range of these predictions. Activity 1 is dedicated to the diagnostic evaluation of wet and dry deposition processes in regional air quality models (described in this paper), and Activity 2 to the evaluation of dry deposition point models against ozone flux measurements at multiple towers with multiyear observations (Part 2). The scope of these papers is to present the scientific protocols for AQMEII4, as well to summarize the technical information associated with the different dry deposition approaches used by the participating research groups of AQMEII4. In addition to describing all common aspects and data used for this multi-model evaluation activity, most importantly, we present the strategy devised to allow a common process-level comparison of dry deposition obtained from models using sometimes very different dry deposition schemes. The strategy is based on adding detailed diagnostics to the algorithms used in the dry deposition modules of existing regional air quality models, in particular archiving land use/land cover (LULC)-specific diagnostics and creating standardized LULC categories to facilitate cross-comparison of LULC-specific dry deposition parameters and processes, as well as archiving effective conductance and effective flux as means for comparing the relative influence of different pathways towards the net or total dry deposition. This new approach, along with an analysis of precipitation and wet deposition fields, will provide an unprecedented process-oriented comparison of deposition in regional air-quality models. Examples of how specific dry deposition schemes used in participating models have been reduced to the common set of comparable diagnostics defined for AQMEII4 are also presented.

The LQ-WARN Project – Development of a Model Output Statistics Product for Air Quality Warnings

2021 ◽  
Author(s):  
Sabine Robrecht ◽  
Andreas Lambert ◽  
Stefan Gilge
Keyword(s):  
Air Quality ◽  
Meteorological Parameters ◽  
Phase 1 ◽  
Weather Prediction ◽  
Model Output ◽  
Operational Mode ◽  
Quality Models ◽  
Air Quality Forecast ◽  
Direct Model ◽  
Model Output Statistics

<p>In order to reach legal air quality limits, several municipalities in Germany have decided to take actions if concentrations of NO<sub>2</sub> and Particulate Matter (PM) exceed certain thresholds. The decision for concrete measures is usually based on observations or use the Direct Model Output (DMO) of air quality models. However, due to large biases of state-of-the-art numerical air quality models, the skill of DMO forecasts to predict periods of polluted air up to four days ahead is very limited.</p><p>The project LQ-WARN aims to develop a system for warning of poor air quality based on Model Output Statistics (MOS). Therefore, air quality related observations, model results provided by the Copernicus Atmosphere Monitoring Service (CAMS) and meteorological parameters from the ECMWF numerical weather prediction model are used as predictors to forecast the air quality by applying Multiple Linear Regression (MLR). In this way MOS equations are calculated for four seasons. The final forecast product will comprise post-processed probabilistic as well as deterministic (e.g. mass concentration) parameters for the species NO<sub>2</sub>, O<sub>3</sub>, PM<sub>10</sub> and PM<sub>2.5</sub>. Forecasts will be available for several hundred German locations and cover lead times up to 96 hours.</p><p>Here, we show first results of our phase 1 MOS prototype, for which observational, meteorological and empirical predictors are applied. Despite of the preliminary exclusion of CAMS predictors, the verifications of the MOS equations imply a considerable reduction of variance and a significant reduction of RMSE (Root Mean Square Error) compared to the climatological values for all four species. Hence, the MOS system can already provide a reasonably good air quality forecast. Furthermore, our analysis of used meteorological predictors, enables a detailed analysis of the importance of specific meteorological parameters for improved statistical air quality forecasts.  As an outlook we will provide detailed information about the final phase 2 LQ-WARN product, which will also include the MOS predictors of CAMS and is expected to be launched in pre-operational mode by 2022.</p>

scholarly journals Modeling atmospheric ammonia and ammonium using a backward-in-time stochastic Lagrangian air quality model (STILT-Chem v0.7)

2012 ◽  
Vol 5 (3) ◽  
pp. 2745-2788
Author(s):  
D. Wen ◽  
J. C. Lin ◽  
L. Zhang ◽  
R. Vet ◽  
M. D. Moran
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Chemical Conversion ◽  
Air Quality Model ◽  
Quality Model ◽  
Gaseous Species ◽  
Time Step ◽  
Back Trajectories ◽  
Atmospheric Ammonia ◽  
Chemistry Module

Abstract. A new chemistry module of atmospheric ammonia (NH3) and ammonium (NH4+) was incorporated into a backward-in-time stochastic Lagrangian air quality model (STILT-Chem) that was originally developed to simulate the concentrations of a variety of gas-phase species at receptors. STILT-Chem simulates the transport of air parcels backward in time using ensembles of fictitious particles with stochastic motions, while simulating emissions, deposition and chemical transformation forward in time along trajectories identified by the backward-in-time simulations. The incorporation of the new chemistry module allows the model to simulate not only gaseous species, but also multi-phase species involving NH3 and NH4+. The model was applied to simulate concentrations of NH3 and particulate NH4+ at six sites in the Canadian province of Ontario for a six-month period in 2006. The model-predicted concentrations of NH3 and particulate NH4+ were compared with observations, which show broad agreement between simulated concentrations and observations. Since the model is based on back trajectories, the influence of each major process such as emission, deposition and chemical conversion on the concentration of a modeled species at a receptor can be determined for every upstream location at each time step. This makes it possible to quantitatively investigate the upstream processes affecting receptor concentrations. The modeled results suggest that the concentrations of NH3 at those sites were significantly and frequently affected by southwestern Ontario, northern Ohio, and nearby areas. NH3 is mainly contributed by emission sources whereas particulate NH4+ is mainly contributed by the gas-to-aerosol chemical conversion of NH3. Dry deposition is the largest removal process for both NH3 and particulate NH4+. This study revealed the contrast between agricultural versus forest sites. Not only were emissions of NH3 higher, but removal mechanisms (especially chemical loss for NH3 and dry deposition for NH4+) were less efficient for agricultural sites. This combination explains the significantly higher concentrations of NH3 and particulate NH4+ observed at agricultural sites.

scholarly journals Non-stomatal exchange in ammonia dry deposition models: Comparison of two state-of-the-art approaches

2016 ◽  
Author(s):  
Frederik Schrader ◽  
Christian Brümmer ◽  
Chris R. Flechard ◽  
Roy J. Wichink Kruit ◽  
Margreet C. van Zanten ◽  
...  
Keyword(s):  
Air Quality ◽  
Large Scale ◽  
Leaf Surface ◽  
State Of The Art ◽  
Temperature Response ◽  
Stomatal Resistance ◽  
Quality Models ◽  
Response Parameter ◽  
Leaf Surface Chemistry ◽  
Models Comparison

Abstract. The accurate representation of bidirectional ammonia (NH3) biosphere-atmosphere exchange is an important part of modern air quality models. However, the cuticular (or external leaf surface) pathway, as well as other non-stomatal ecosystem surfaces, still pose a major challenge of translating our knowledge into models. Dynamic mechanistic models including complex leaf surface chemistry have been able to accurately reproduce measured bidirectional fluxes in the past, but their computational expense and challenging implementation into existing air quality models call for steady-state simplifications. We here qualitatively compare two semi-empirical state-of-the-art parameterizations of a unidirectional non-stomatal resistance (Rw) model after Massad et al. (2010), and a quasi-bidirectional non-stomatal compensation point (χw) model after Wichink Kruit et al. (2010), with NH3 flux measurements from five European sites. In addition, we tested the feasibility of using backward-looking moving averages of air NH3 concentrations as a proxy for prior NH3 uptake and driver of an alternative parameterization of non-stomatal emission potentials (Γw) for bidirectional non-stomatal exchange models. Results indicate that the Rw-only model has a tendency to underestimate fluxes, while the χw model mainly overestimates fluxes, although systematic underestimations can occur under certain conditions, depending on temperature and ambient NH3 concentrations at the site. The proposed Γw parameterization appears to have potential for improvement, but cannot be recommended for use in large scale simulations in its present state due to large uncertainties. As an interim solution for improving flux predictions, we recommend to reduce the minimum allowed Rw and the temperature response parameter in the unidirectional model and to revisit the temperature dependent Γw parameterization of the bidirectional model.

scholarly journals Correlation of Dry Deposition Velocity and Friction Velocity over Different Surfaces for PM2.5 and Particle Number Concentrations

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Antonio Donateo ◽  
Daniele Contini
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Friction Velocity ◽  
Particle Number ◽  
Deposition Velocity ◽  
Atmospheric Stability ◽  
Linear Increase ◽  
Climate Modelling ◽  
Average Value ◽  
Deposition Velocities

Dry deposition of particles is an important way of aerosol removal from the atmosphere and a key process in surface-atmosphere exchanges. The deposition velocities, Vd, are often parameterised in air quality and climate modelling as function of the friction velocity,u*, atmospheric stability, and particle size (if size-segregated information is available). In this work, a study of the correlation between Vd andu*over different surfaces is presented for both PM2.5 and particle number fluxes. Results indicate an almost linear increase of Vd withu*with slopes similar for PM2.5 fluxes and particle number fluxes over the different surfaces analysed. This means that the ratios Vd/u*tend to collapse over similar values even if Vd andu*are significantly different becauseu*take into account most of the surface effects. There is a limited difference between stable cases and unstable/neutral cases with slightly lower deposition velocities in stable cases for fixed values ofu*. The average value of Vd/u*is 0.010 ± 0.0017 (median 0.0062 ± 0.0015) (considering all stabilities) and 0.0097 ± 0.002 (median 0.005 ± 0.001) for stable cases. This could be the base for an empirical parameterisation of deposition velocities in air quality models.

scholarly journals Non-stomatal exchange in ammonia dry deposition models: comparison of two state-of-the-art approaches

2016 ◽  
Vol 16 (21) ◽  
pp. 13417-13430 ◽  
Author(s):  
Frederik Schrader ◽  
Christian Brümmer ◽  
Chris R. Flechard ◽  
Roy J. Wichink Kruit ◽  
Margreet C. van Zanten ◽  
...  
Keyword(s):  
Air Quality ◽  
Leaf Surface ◽  
State Of The Art ◽  
Temperature Response ◽  
Stomatal Resistance ◽  
Moving Averages ◽  
Quality Models ◽  
Response Parameter ◽  
Leaf Surface Chemistry ◽  
Models Comparison

Abstract. The accurate representation of bidirectional ammonia (NH3) biosphere–atmosphere exchange is an important part of modern air quality models. However, the cuticular (or external leaf surface) pathway, as well as other non-stomatal ecosystem surfaces, still pose a major challenge to translating our knowledge into models. Dynamic mechanistic models including complex leaf surface chemistry have been able to accurately reproduce measured bidirectional fluxes in the past, but their computational expense and challenging implementation into existing air quality models call for steady-state simplifications. Here we qualitatively compare two semi-empirical state-of-the-art parameterizations of a unidirectional non-stomatal resistance (Rw) model after Massad et al. (2010), and a quasi-bidirectional non-stomatal compensation-point (χw) model after Wichink Kruit et al. (2010), with NH3 flux measurements from five European sites. In addition, we tested the feasibility of using backward-looking moving averages of air NH3 concentrations as a proxy for prior NH3 uptake and as a driver of an alternative parameterization of non-stomatal emission potentials (Γw) for bidirectional non-stomatal exchange models. Results indicate that the Rw-only model has a tendency to underestimate fluxes, while the χw model mainly overestimates fluxes, although systematic underestimations can occur under certain conditions, depending on temperature and ambient NH3 concentrations at the site. The proposed Γw parameterization revealed a clear functional relationship between backward-looking moving averages of air NH3 concentrations and non-stomatal emission potentials, but further reduction of uncertainty is needed for it to be useful across different sites. As an interim solution for improving flux predictions, we recommend reducing the minimum allowed Rw and the temperature response parameter in the unidirectional model and revisiting the temperature-dependent Γw parameterization of the bidirectional model.

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