scholarly journals A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

2016 ◽  
Author(s):  
Kathleen M. Fahey ◽  
Annmarie G. Carlton ◽  
Havala O. T. Pye ◽  
Jaemeen Baek ◽  
William T. Hutzell ◽  
...  
Keyword(s):  
Mass Transfer ◽  
Air Quality ◽  
Transport Model ◽  
Chemical Mechanism ◽  
Chemical Transport Model ◽  
Cloud Chemistry ◽  
Stiff System ◽  
Monthly Average ◽  
Hourly Concentration ◽  
Phase Chemistry

Abstract. This paper describes the development and implementation of an extendable aqueous phase chemistry option (AQCHEM-KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ODEs that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the U.S. reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM-KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM-KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the SOAS field campaign period. The added in-cloud chemistry leads to a monthly-average increase of 11–18 % in "cloud" SOA at the surface in the eastern U.S. for June 2013.

scholarly journals A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

2017 ◽  
Vol 10 (4) ◽  
pp. 1587-1605 ◽  
Author(s):  
Kathleen M. Fahey ◽  
Annmarie G. Carlton ◽  
Havala O. T. Pye ◽  
Jaemeen Baek ◽  
William T. Hutzell ◽  
...  
Keyword(s):  
Mass Transfer ◽  
Air Quality ◽  
Transport Model ◽  
Chemical Mechanism ◽  
Eastern United States ◽  
Chemical Transport Model ◽  
Cloud Chemistry ◽  
Stiff System ◽  
Monthly Average ◽  
Hourly Concentration

Abstract. This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM − KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM − KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the Southern Oxidant and Aerosol Study (SOAS) period. The added in-cloud chemistry leads to a monthly average increase of 11–18 % in cloud SOA at the surface in the eastern United States for June 2013.

scholarly journals Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 91
Author(s):  
Santiago Lopez-Restrepo ◽  
Andres Yarce ◽  
Nicolás Pinel ◽  
O.L. Quintero ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Transport Model ◽  
Cost Model ◽  
Low Cost ◽  
Model Performance ◽  
Monitoring Network ◽  
Correlation Factor ◽  
Chemical Transport Model ◽  
High Quality

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

scholarly journals Assessing Douro Vineyards Exposure to Tropospheric Ozone

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 200
Author(s):  
Ana Ascenso ◽  
Carla Gama ◽  
Daniel Blanco-Ward ◽  
Alexandra Monteiro ◽  
Carlos Silveira ◽  
...  
Keyword(s):  
Air Quality ◽  
Tropospheric Ozone ◽  
Transport Model ◽  
Sugar Content ◽  
Productivity Loss ◽  
Ozone Exposure ◽  
Vitis Vinifera L ◽  
Chemical Transport Model ◽  
Wine Production ◽  
Exposure Response

Tropospheric ozone (O3) can strongly damage vegetation. Grapevines (Vitis vinifera L.), in particular, have intermediate sensitivity to ozone. Wine production is an important economic activity, as well as a pillar to the cultural identity of several countries in the world. This study aims to evaluate the risk of Douro vineyards exposure to ozone, by estimating its concentration and deposition in the Demarcated Region of Douro in Portugal. Based on an assessment of the climatology of the area, the years 2003 to 2005 were selected among the hottest years of the recent past, and the chemical transport model CHIMERE was used to estimate the three-dimensional field of ozone and its dry deposition over the Douro region with 1 km2 of horizontal resolution. Model results were validated by comparison with measured data from the European air quality database (AirBase). The exposure indicator AOT40 (accumulated concentration of ozone above 40 ppb) was calculated and an exposure–response function was applied to determine the grapevine risk to ozone exposure. The target value for the protection of vegetation established by the Air Quality Framework Directive was exceeded on most of the Douro region, especially over the Baixo Corgo and Cima Corgo sub-regions. The results of the exposure–response functions suggest that the productivity loss can reach 27% and that the sugar content of the grapes could be reduced by 32%, but these values are affected by the inherent uncertainty of the used methodology.

scholarly journals A new diagnostic for tropospheric ozone production

2017 ◽  
Author(s):  
Peter M. Edwards ◽  
Mathew J. Evans
Keyword(s):  
Air Quality ◽  
Tropospheric Ozone ◽  
Transport Model ◽  
Chemical Transport ◽  
Ozone Production ◽  
Chemical Transport Model ◽  
Organic Species ◽  
Earth’S Climate ◽  
Oxidation Of Organics

Abstract. Tropospheric ozone is important for the Earth’s climate and air quality. It is produced during the oxidation of organics in the presence of nitrogen oxides. Due to the range of organic species emitted and the chain like nature of their oxidation, this chemistry is complex and understanding the role of different processes (emission, deposition, chemistry) is difficult. We demonstrate a new methodology for diagnosing ozone production based on the processing of bonds contained within emitted molecules, the fate of which is determined by the conservation of spin of the bonding electrons. Using this methodology to diagnose ozone production in the GEOS-Chem chemical transport model, we demonstrate its advantages over the standard diagnostic. We show that the number of bonds emitted, their chemistry and lifetime, and feedbacks on OH are all important in determining the ozone production within the model and its sensitivity to changes. This insight may allow future model-model comparisons to better identify the root causes of model differences.

scholarly journals The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

2014 ◽  
Vol 7 (2) ◽  
pp. 1645-1689
Author(s):  
E. Hache ◽  
J.-L. Attié ◽  
C. Tourneur ◽  
P. Ricaud ◽  
L. Coret ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Statistical Tests ◽  
Surface Ozone ◽  
A Priori ◽  
Thermal Infrared ◽  
Added Value ◽  
Chemical Transport Model ◽  
Geo Satellite ◽  
Sky Conditions

Abstract. Ozone is a tropospheric pollutant and plays a key role in determining the air quality that affects human wellbeing. In this study, we compare the capability of two hypothetical grating spectrometers onboard a geostationary (GEO) satellite to sense ozone in the lowermost troposphere (surface and the 0–1 km column). We consider one week during the Northern Hemisphere summer simulated by a chemical transport model, and use the two GEO instrument configurations to measure ozone concentration (1) in the thermal infrared (GEO TIR) and (2) in the thermal infrared and the visible (GEO TIR+VIS). These configurations are compared against each other, and also against an ozone reference state and a priori ozone information. In a first approximation, we assume clear sky conditions neglecting the influence of aerosols and clouds. A number of statistical tests are used to assess the performance of the two GEO configurations. We consider land and sea pixels and whether differences between the two in the performance are significant. Results show that the GEO TIR+VIS configuration provides a better representation of the ozone field both for surface ozone and the 0–1 km ozone column during the daytime especially over land.

scholarly journals Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

2018 ◽  
Author(s):  
Scott D. Chambers ◽  
Elise-Andree Guérette ◽  
Khalia Monk ◽  
Alan D. Griffiths ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Diurnal Cycle ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
Potential Health ◽  
Meteorological Model ◽  
Model Skill ◽  
Chemical Transport Models

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

scholarly journals Ethane, ethyne and carbon monoxide concentrations in the upper troposphere and lower stratosphere from ACE and GEOS-Chem: a comparison study

2011 ◽  
Vol 11 (4) ◽  
pp. 13099-13139 ◽  
Author(s):  
G. González Abad ◽  
N. D. C. Allen ◽  
P. F. Bernath ◽  
C. D. Boone ◽  
S. D. McLeod ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Chemical Mechanism ◽  
Chemical Transport Model ◽  
Spectrometer Data ◽  
Chemistry Experiment ◽  
Global Mean ◽  
Tropospheric Concentrations ◽  
Good Agreement

Abstract. Near global upper tropospheric concentrations of carbon monoxide (CO), ethane (C2H6) and ethyne (C2H2) from ACE (Atmospheric Chemistry Experiment) Fourier transform spectrometer on board the Canadian satellite SCISAT-1 are presented and compared with the output from the Chemical Transport Model (CTM) GEOS-Chem. The retrievals of ethane and ethyne from ACE have been improved for this paper by using new sets of microwindows compared with those for previous versions of ACE data. With the improved ethyne retrieval we have been able to produce a near global upper tropospheric distribution of C2H2 from space. Carbon monoxide, ethane and ethyne concentrations retrieved using ACE spectra show the expected seasonality linked to variations in the anthropogenic emissions and destruction rates as well as seasonal biomass burning activity. The GEOS-Chem model was run using the dicarbonyl chemistry suite, an extended chemical mechanism in which ethyne is treated explicitly. Seasonal cycles observed from satellite data are well reproduced by the model output, however the simulated CO concentrations are found to be systematically biased low over the Northern Hemisphere. An average negative global mean bias of 12% and 7% of the model relative to the satellite observations has been found for CO and C2H6 respectively and a positive global mean bias of 1% has been found for C2H2. ACE data are compared for validation purposes with MkIV spectrometer data and Global Tropospheric Experiment (GTE) TRACE-A campaign data showing good agreement with all of them.

scholarly journals Evaluating the performance of pyrogenic and biogenic emission inventories against one decade of space-based formaldehyde columns

2008 ◽  
Vol 8 (5) ◽  
pp. 16981-17036 ◽  
Author(s):  
T. Stavrakou ◽  
J.-F. Müller ◽  
I. De Smedt ◽  
M. Van Roozendael ◽  
G. R. van der Werf ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Amazon Basin ◽  
Transport Model ◽  
Correlation Coefficients ◽  
Global Scale ◽  
Chemical Mechanism ◽  
Emission Inventories ◽  
Chemical Transport Model ◽  
Emissions Inventory ◽  
Fire Emissions

Abstract. A new one-decade dataset of formaldehyde (HCHO) columns retrieved from GOME and SCIAMACHY is compared with HCHO columns simulated by an updated version of the IMAGES global chemical transport model. This model version includes an optimized chemical scheme with respect to HCHO production, where the short-term and final HCHO yields from pyrogenically emitted non-methane volatile organic compounds (NMVOCs) are estimated from the Master Chemical Mechanism (MCM) and an explicit speciation profile of pyrogenic emissions. The model is driven by the Global Fire Emissions Database (GFED) version 1 or 2 for biomass burning, whereas biogenic emissions are provided either by the Global Emissions Inventory Activity (GEIA), or by a newly developed inventory based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) algorithms driven by meteorological fields from the European Centre for Medium-Range Weather Forecasts (ECMWF). The comparisons focus on tropical ecosystems, North America and China, which experience strong biogenic and biomass burning NMVOC emissions reflected in the enhanced measured HCHO columns. These comparisons aim at testing the ability of the model to reproduce the observed features of the HCHO distribution on the global scale and at providing a first assessment of the performance of the current emission inventories. The high correlation coefficients (r>0.8) between the observed and simulated columns over most regions indicate a very good consistency between the model, the implemented inventories and the HCHO dataset. The use of the MEGAN-ECMWF inventory improves the model/data agreement in almost all regions, but biases persist over parts of Africa and the Northern Australia. Although neither GFED version is consistent with the data over all regions, a better match is achieved over Indonesia and Southern Africa when GFEDv2 is used, but GFEDv1 succeeds better in getting the correct seasonal patterns and intensities of the fire episodes over the Amazon basin, as reflected by the higher correlations calculated in this region.

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 Impacts of Current and Projected Oil Palm Plantation Expansion on Air Quality Over Southeast Asia

2016 ◽  
Author(s):  
Sam J. Silva ◽  
Colette L. Heald ◽  
Jeffrey A. Geddes ◽  
Kemen G. Austin ◽  
Prasad S. Kasibhatla ◽  
...  
Keyword(s):  
Air Quality ◽  
Southeast Asia ◽  
Oil Palm ◽  
Urban Areas ◽  
Transport Model ◽  
Chemical Transport Model ◽  
Oil Palm Plantation ◽  
Deposition Velocities ◽  
Current Constellation ◽  
The Impact

Abstract. Over recent decades oil palm plantations have rapidly expanded across Southeast Asia (SEA). According to the United Nations, oil palm production in SEA increased by a factor of 3 from 1995 to 2010. We investigate the impacts of current (2010) and future (2020) oil palm expansion in SEA on surface-atmosphere exchange and the resulting air quality in the region. For this purpose, we use satellite data, high-resolution land maps, and the chemical transport model GEOS-Chem. Relative to a no oil palm plantation scenario (~ 1990), overall simulated isoprene emissions in the region increase by 13 % due to oil palm plantations in 2010 and a further 11 % by 2020. In addition, the expansion of palm plantations leads to local increases in ozone deposition velocities of up to 20 %. The net result of these changes is that oil palm expansion in SEA increases surface O3 by up to 3.5 ppbv over dense urban regions, and could rise more than 4.5 ppbv above baseline levels by 2020. Biogenic secondary organic aerosol loadings also increase by up to 1 μg m−3 due to oil palm expansion, and could increase a further 2.5 μg m−3 by 2020. Our analysis indicates that while the impact of recent oil palm expansion on air quality in the region has been significant, the retrieval error and sensitivity of the current constellation of satellite measurements limit our ability to observe these impacts from space. Oil palm expansion is likely to continue to degrade air quality in the region in the coming decade and hinder efforts to achieve air quality regulations in major urban areas such as Kuala Lumpur and Singapore.

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