77 research outputs found
Assimilation of Satellite Data in Regional Air Quality Models
In terms of important uncertainty in regional-scale air-pollution models, probably no other aspect ranks any higher than the current ability to specify clouds and soil moisture on the regional scale. Because clouds in models are highly parameterized, the ability of models to predict the correct spatial and radiative characteristics is highly suspect and subject to large error. The poor representation of cloud fields from point measurements at National Weather Services stations and the almost total absence of surface moisture availability observations has made assimilation of these variables difficult to impossible. Yet, the correct inclusion of clouds and surface moisture are of first-order importance in regional-scale photochemistry
Estimating NH3 emissions from agricultural fertilizer application in China using the bi-directional CMAQ model coupled to an agro-ecosystem model
Atmospheric ammonia (NH3) plays an important role in atmospheric aerosol chemistry. China is one of the largest NH3 emitting countries with the majority of NH3 emissions coming from agricultural practices, such as fertilizer application and livestock production. The current NH3 emission estimates in China are mainly based on pre-defined emission factors that lack temporal or spatial details, which are needed to accurately predict NH3 emissions. This study provides the first online estimate of NH3 emissions from agricultural fertilizer application in China, using an agricultural fertilizer modeling system which couples a regional air quality model (the Community Multi-scale Air Quality model, or CMAQ) and an agro-ecosystem model (the Environmental Policy Integrated Climate model, or EPIC). This method improves the spatial and temporal resolution of NH3 emissions from this sector. We combined the cropland area data of 14 crops from 2710 counties with the Moderate Resolution Imaging Spectroradiometer (MODIS) land use data to determine the crop distribution. The fertilizer application rates and methods for different crops were collected at provincial or agricultural region levels. The EPIC outputs of daily fertilizer application and soil characteristics were input into the CMAQ model and the hourly NH3 emissions were calculated online with CMAQ running. The estimated agricultural fertilizer NH3 emissions in this study were approximately 3 Tg in 2011. The regions with the highest modeled emission rates are located in the North China Plain. Seasonally, peak ammonia emissions occur from April to July. Compared with previous researches, this study considers an increased number of influencing factors, such as meteorological fields, soil and fertilizer application, and provides improved NH3 emissions with higher spatial and temporal resolution
Incremental testing of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7
This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to observations and results from previous model versions in a series of simulations conducted to incrementally assess the effect of each change. The focus of this paper is on five major scientific upgrades: (a) updates to the heterogeneous N<sub>2</sub>O<sub>5</sub> parameterization, (b) improvement in the treatment of secondary organic aerosol (SOA), (c) inclusion of dynamic mass transfer for coarse-mode aerosol, (d) revisions to the cloud model, and (e) new options for the calculation of photolysis rates. Incremental test simulations over the eastern United States during January and August 2006 are evaluated to assess the model response to each scientific improvement, providing explanations of differences in results between v4.7 and previously released CMAQ model versions. Particulate sulfate predictions are improved across all monitoring networks during both seasons due to cloud module updates. Numerous updates to the SOA module improve the simulation of seasonal variability and decrease the bias in organic carbon predictions at urban sites in the winter. Bias in the total mass of fine particulate matter (PM<sub>2.5</sub>) is dominated by overpredictions of unspeciated PM<sub>2.5</sub> (PM<sub>other</sub>) in the winter and by underpredictions of carbon in the summer. The CMAQv4.7 model results show slightly worse performance for ozone predictions. However, changes to the meteorological inputs are found to have a much greater impact on ozone predictions compared to changes to the CMAQ modules described here. Model updates had little effect on existing biases in wet deposition predictions
Lateral terrestrial water flow contribution to summer precipitation at continental scale â A comparison between Europe and West Africa with WRFâHydroâtag ensembles
It is well accepted that summer precipitation can be altered by soil moisture condition. Coupled land surface â atmospheric models have been routinely used to quantify soil moisture â precipitation feedback processes. However, most of the land surface models (LSMs) assume a vertical soil water transport and neglect lateral terrestrial water flow at the surface and in the subsurface, which potentially reduces the realism of the simulated soil moisture â precipitation feedback. In this study, the contribution of lateral terrestrial water flow to summer precipitation is assessed in two different climatic regions, Europe and West Africa, for the period JuneâSeptember 2008. A version of the coupled atmospheric-hydrological model WRF-Hydro with an option to tag and trace land surface evaporation in the modelled atmosphere, named WRF-Hydro-tag, is employed. An ensemble of 30âsimulations with terrestrial routing and 30âsimulations without terrestrial routing is generated with random realizations of turbulent energy with the stochastic kinetic energy backscatter scheme, for both Europe and West Africa. The ensemble size allows to extract random noise from continental-scale averaged modelled precipitation. It is found that lateral terrestrial water flow increases the relative contribution of land surface evaporation to precipitation by 3.6% in Europe and 5.6% in West Africa, which enhances a positive soil moisture â precipitation feedback and generates more uncertainty in modelled precipitation, as diagnosed by a slight increase in normalized ensemble spread. This study demonstrates the small but non-negligible contribution of lateral terrestrial water flow to precipitation at continental scale
Evaluation of the diurnal cycle in the atmospheric boundary layer over land as represented by a variety of single-column models: the second GABLS experiment
Postprint (published version
Sensitivity of northeastern US surface ozone predictions to the representation of atmospheric chemistry in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMMv1.0)
Chemical mechanisms describe how emissions of gases and particles evolve in
the atmosphere and are used within chemical transport models to evaluate
past, current, and future air quality. Thus, a chemical mechanism must
provide robust and accurate predictions of air pollutants if it is to be
considered for use by regulatory bodies. In this work, we provide an initial
evaluation of the Community Regional Atmospheric Chemistry Multiphase
Mechanism (CRACMMv1.0) by assessing CRACMMv1.0 predictions of surface ozone
(O3) across the northeastern US during the summer of 2018 within the
Community Multiscale Air Quality (CMAQ) modeling system. CRACMMv1.0 O3
predictions of hourly and maximum daily 8âh average (MDA8) ozone were
lower than those estimated by the Regional Atmospheric Chemistry Mechanism with aerosol module 6
(RACM2_ae6), which better matched surface network
observations in the northeastern US (RACM2_ae6 mean bias of
+4.2âppb for all hours and +4.3âppb for MDA8; CRACMMv1.0 mean bias of
+2.1âppb for all hours and +2.7âppb for MDA8). Box model calculations
combined with results from CMAQ emission reduction simulations indicated
a high sensitivity of O3 to compounds with biogenic sources. In addition,
these calculations indicated the differences between CRACMMv1.0 and
RACM2_ae6 O3 predictions were largely explained by
updates to the inorganic rate constants (reflecting the latest assessment
values) and by updates to the representation of monoterpene chemistry.
Updates to other reactive organic carbon systems between
RACM2_ae6 and CRACMMv1.0 also affected ozone predictions and
their sensitivity to emissions. Specifically, CRACMMv1.0 benzene, toluene,
and xylene chemistry led to efficient NOx cycling such that CRACMMv1.0 predicted controlling aromatics reduces ozone without rural O3
disbenefits. In contrast, semivolatile and intermediate-volatility alkanes
introduced in CRACMMv1.0 acted to suppress O3 formation across the
regional background through the sequestration of nitrogen oxides (NOx)
in organic nitrates. Overall, these analyses showed that the CRACMMv1.0 mechanism within the CMAQ model was able to reasonably simulate ozone
concentrations in the northeastern US during the summer of 2018 with similar
magnitude and diurnal variation as the current operational Carbon Bond
(CB6r3_ae7) mechanism and good model performance compared to recent
modeling studies in the literature.</p
A single-point modeling approach for the intercomparison and evaluation of ozone dry deposition across chemical transport models (Activity 2 of AQMEII4)
A primary sink of air pollutants and their precursors is dry
deposition. Dry deposition estimates differ across chemical transport
models, yet an understanding of the model spread is incomplete. Here, we
introduce Activity 2 of the Air Quality Model Evaluation International
Initiative Phase 4 (AQMEII4). We examine 18 dry deposition schemes
from regional and global chemical transport models as well as standalone
models used for impact assessments or process understanding. We configure
the schemes as single-point models at eight Northern Hemisphere locations
with observed ozone fluxes. Single-point models are driven by a common set
of site-specific meteorological and environmental conditions. Five of eight
sites have at least 3Â years and up to 12Â years of ozone fluxes. The
interquartile range across models in multiyear mean ozone deposition
velocities ranges from a factor of 1.2 to 1.9 annually across sites and
tends to be highest during winter compared with summer. No model is within
50â% of observed multiyear averages across all sites and seasons, but some
models perform well for some sites and seasons. For the first time, we
demonstrate how contributions from depositional pathways vary across models.
Models can disagree with respect to relative contributions from the pathways, even when
they predict similar deposition velocities, or agree with respect to the relative
contributions but predict different deposition velocities. Both stomatal and
nonstomatal uptake contribute to the large model spread across sites. Our
findings are the beginning of results from AQMEII4 Activity 2, which brings
scientists who model air quality and dry deposition together with scientists
who measure ozone fluxes to evaluate and improve dry deposition schemes in
the chemical transport models used for research, planning, and regulatory
purposes.</p
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