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 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 An evaluation of ambient ammonia concentrations over southern Ontario simulated with different dry deposition schemes within STILT-Chem v0.8

2013 ◽  
Vol 6 (4) ◽  
pp. 6075-6115 ◽  
Author(s):  
D. Wen ◽  
L. Zhang ◽  
J. C. Lin ◽  
R. Vet ◽  
M. D. Moran
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Air Quality Model ◽  
Quality Model ◽  
Surface Exchange ◽  
Southern Ontario ◽  
Lagrangian Transport ◽  
Atmospheric Ammonia ◽  
Sensitivity Tests ◽  
Stochastic Time

Abstract. A bi-directional air-surface exchange scheme for atmospheric ammonia was incorporated into the Stochastic Time-Inverted Lagrangian Transport air quality model (STILT-Chem v0.8). STILT-Chem v0.8 was then applied to simulate atmospheric ammonia concentrations at 53 measurement sites in the province of Ontario, Canada for a six-month period from 1 June to 30 November 2006. In addition to the bi-directional scheme, two uni-directional dry deposition schemes were tested. Comparisons of modeled ammonia concentrations against observations show that all three schemes can reasonably predict observations. For sites with low observed ammonia concentrations, the bi-directional scheme clearly overestimated ammonia concentrations. Although all three schemes tend to underestimate ammonia concentrations for locations with elevated observed concentrations, the bi-directional scheme performed better due mainly to its introduction of compensation points into flux calculation parameterizations. The results of additional sensitivity tests suggest that uncertainties in the input values of emission potentials in the bi-directional scheme greatly affect the accuracy of modeled ammonia concentrations. The use of much larger emission potentials than provided in the scheme is required for accurate prediction of elevated ammonia concentrations at intensive agricultural locations.

scholarly journals Contribution of ship emissions to the concentration and deposition of air pollutants in Europe

2016 ◽  
Vol 16 (4) ◽  
pp. 1895-1906 ◽  
Author(s):  
Sebnem Aksoyoglu ◽  
Urs Baltensperger ◽  
André S. H. Prévôt
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Wet Deposition ◽  
Nox Emissions ◽  
English Channel ◽  
Air Quality Model ◽  
Quality Model ◽  
Ship Emissions ◽  
The North ◽  
The North Sea

Abstract. Emissions from the marine transport sector are one of the least-regulated anthropogenic emission sources and contribute significantly to air pollution. Although strict limits were introduced recently for the maximum sulfur content in marine fuels in the SECAs (sulfur emission control areas) and in EU ports, sulfur emissions outside the SECAs and emissions of other components in all European maritime areas have continued to increase in the last two decades. We have used the air quality model CAMx (Comprehensive Air Quality Model with Extensions) with and without ship emissions for the year 2006 to determine the effects of international shipping on the annual as well as seasonal concentrations of ozone, primary and secondary components of PM2.5, and the dry and wet deposition of nitrogen and sulfur compounds in Europe. The largest changes in pollutant concentrations due to ship emissions were predicted for summer. Concentrations of particulate sulfate increased due to ship emissions in the Mediterranean (up to 60 %), the English Channel and the North Sea (30–35 %), while increases in particulate nitrate levels were found especially in the north, around the Benelux area (20 %), where there were high NH3 land-based emissions. Our model results showed that not only are the atmospheric concentrations of pollutants affected by ship emissions, but also depositions of nitrogen and sulfur compounds increase significantly along the shipping routes. NOx emissions from the ships, especially in the English Channel and the North Sea, cause a decrease in the dry deposition of reduced nitrogen at source regions by moving it from the gas phase to the particle phase which then contributes to an increase in the wet deposition at coastal areas with higher precipitation. In the western Mediterranean region, on the other hand, model results show an increase in the deposition of oxidized nitrogen (mostly HNO3) due to the ship traffic. Dry deposition of SO2 seems to be significant along the shipping routes, whereas sulfate wet deposition occurs mainly along the Scandinavian and Adriatic coasts. The results presented in this paper suggest that evolution of NOx emissions from ships and land-based NH3 emissions will play a significant role in future European air quality.

scholarly journals An evaluation of ambient ammonia concentrations over southern Ontario simulated with different dry deposition schemes within STILT-Chem v0.8

2014 ◽  
Vol 7 (3) ◽  
pp. 1037-1050 ◽  
Author(s):  
D. Wen ◽  
L. Zhang ◽  
J. C. Lin ◽  
R. Vet ◽  
M. D. Moran
Keyword(s):  
Dry Deposition ◽  
Emission Inventory ◽  
Air Quality Model ◽  
Quality Model ◽  
Surface Exchange ◽  
Southern Ontario ◽  
Atmospheric Ammonia ◽  
Nh3 Emission ◽  
Sensitivity Tests ◽  
Stochastic Time

Abstract. A bidirectional air–surface exchange scheme for atmospheric ammonia was incorporated into the Stochastic Time-Inverted Lagrangian Transport air quality model (STILT-Chem v0.8). STILT-Chem v0.8 was then applied to simulate atmospheric ammonia concentrations at 53 measurement sites in the province of Ontario, Canada for a six-month period from 1 June to 30 November 2006. In addition to the bidirectional scheme, two unidirectional dry deposition schemes were tested. Comparisons of modeled ammonia concentrations against observations show that all three schemes can reasonably predict observations. For sites with low observed ammonia concentrations, the bidirectional scheme clearly overestimated ammonia concentrations during crop-growing season. Although all three schemes tended to underestimate ammonia concentrations after mid-October and for sites with elevated observed concentrations, mainly due to underestimated NH3 emission inventory after mid-October and/or underestimated emission potentials for those sites, the bidirectional scheme performed better because of its introduction of compensation points into the flux calculation parameterization. In addition to uncertainties in the emission inventory, the results of additional sensitivity tests suggest that uncertainties in the input values of emission potentials in the bidirectional scheme greatly affect the accuracy of modeled ammonia concentrations. The use of much larger emission potentials in the bidirectional scheme and larger anthropogenic NH3 emission after mid-October than provided in the model emissions files is needed for accurate prediction of elevated ammonia concentrations at intensive agricultural locations.

Ammonia measurements from space with the Cross-track Infrared Sounder (CrIS): characteristics and applications

2020 ◽  
Author(s):  
Mark Shephard ◽  
Chris McLinden ◽  
Enrico Dammers ◽  
Shailesh Kharol ◽  
Karen Cady-Pereira ◽  
...  
Keyword(s):  
Air Quality ◽  
North America ◽  
Dry Deposition ◽  
Forecast Model ◽  
Satellite Observations ◽  
Spatiotemporal Variability ◽  
Air Quality Model ◽  
Quality Model ◽  
Air Quality Forecast ◽  
The Impact

<p>Satellite data are helping to fill monitoring gaps in order to better inform decision makers and assess the impact of ammonia-related policies.  Presented is an overview demonstrating the current capabilities of the ammonia (NH<sub>3</sub>) data product derived from the CrIS satellite instrument for monitoring, air quality forecast model evaluation, dry deposition estimates, and emissions estimates.  This includes examples of daily, seasonal, and annual observations of CrIS ammonia that demonstrate the spatiotemporal variability of ammonia globally. These results further demonstrate the ability of CrIS to observe regional changes in ammonia concentrations, such as spring maximum values over agricultural regions from the fertilizing of crops.  Also shown is the importance contribution of wildfires, especially in regions where there is little or no agriculture sources, such as the northern latitudes in North America during summer.  Initial comparisons of CrIS NH<sub>3</sub> satellite observations with air quality model simulations show that while there is general agreement on the spatial distribution of the anthropogenic hotspots, some areas are markedly different.  Some key findings are that dry deposition estimates of NH<sub>3</sub> and NO<sub>2</sub> from CrIS and the Ozone Monitoring Instrament (OMI), respectively, indicate that the NH<sub>3</sub> dominates over most regions across North America. Their 2013 annual ratio shows NH<sub>3</sub> accounting for ~82% and ~55 % of the combined reactive nitrogen dry deposition from these two species over Canada and the U.S.  Furthermore, we show the use of CrIS satellite observations to estimate annual and seasonal emissions over Concentrated Animal Feeding Operations (CAFOs).  These results are used to evaluate the seasonal and temporal emissions profiles used in bottom-up inventories over an agriculture hotspot, which are often underreported</p>

scholarly journals MP CBM-Z V1.0: design for a new Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical mechanism architecture for next-generation processors

2019 ◽  
Vol 12 (2) ◽  
pp. 749-764
Author(s):  
Hui Wang ◽  
Junmin Lin ◽  
Qizhong Wu ◽  
Huansheng Chen ◽  
Xiao Tang ◽  
...  
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Air Quality Model ◽  
Quality Model ◽  
Gas Phase Chemistry ◽  
Phase Chemistry ◽  
Bond Mechanism ◽  
Chemistry Module ◽  
Phase Chemical ◽  
Intel Xeon

Abstract. Precise and rapid air quality simulations and forecasting are limited by the computational performance of the air quality model used, and the gas-phase chemistry module is the most time-consuming function in the air quality model. In this study, we designed a new framework for the widely used the Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical kinetics kernel to adapt the single-instruction, multiple-data (SIMD) technology in next-generation processors to improve its calculation performance. The optimization implements the fine-grain level parallelization of CBM-Z by improving its vectorization ability. Through constructing loops and integrating the main branches, e.g., diverse chemistry sub-schemes, multiple spatial points in the model can be operated simultaneously on vector processing units (VPUs). Two generation CPUs – Intel Xeon E5-2680 V4 CPU and Intel Xeon Gold 6132 – and Intel Xeon Phi 7250 Knights Landing (KNL) are used as the benchmark processors. The validation of the CBM-Z module outputs indicates that the relative bias reaches a maximum of 0.025 % after 10 h integration with -fp-model fast =1 compile flag. The results of the module test show that the Multiple-Points CBM-Z (MP CBM-Z) resulted in 5.16× and 8.97× speedup on a single core of Intel Xeon E5-2680 V4 and Intel Xeon Gold 6132 CPUs, respectively, and KNL had a speedup of 3.69× compared with the performance of CBM-Z on the Intel Xeon E5-2680 V4 platform. For the single-node tests, the speedup on the two generation CPUs can reach 104.63× and 198.50× using message passing interface (MPI) and 101.02× and 194.60× using OpenMP, and the speedup on the KNL node can reach 175.23× using MPI and 167.45× using OpenMP. The speedup of the optimized CBM-Z is approximately 40 % higher on a one-socket KNL platform than on a two-socket Broadwell platform and about 13 %–16 % lower than on a two-socket Skylake platform. We also tested a three-dimensional chemistry transport model (CTM) named Nested Air Quality Prediction Model System (NAQPMS) equipped with the MP CBM-Z. The tests illustrate an obvious improvement on the performance for the CTM after adopting the MP CBM-Z. The results show that the MP CBM-Z leads to a speedup of 3.32 and 1.96 for the gas-phase chemistry module and the CTM on the Intel Xeon E5-2680 platform. Moreover, on the new Intel Xeon Gold 6132 platform, the MP CBM-Z gains 4.90× and 2.22× speedups for the gas-phase chemistry module and the whole CTM. For the KNL, the MP CBM-Z enables a 3.52× speedup for the gas-phase chemistry module, but the whole model lost 24.10 % performance compared to the CPU platform due to the poor performance of other modules. In addition, since this optimization seeks to improve the utilization of the VPU, the model is more suitable for the new generation processors adopting the more advanced SIMD technology. The results of our tests already show that the benefit of updating CPU improved by about 47 % by using the MP CBM-Z since the optimized code has better adaptability for the new hardware. This work improves the performance of the CBM-Z chemical kinetics kernel as well as the calculation efficiency of the air quality model, which can directly improve the practical value of the air quality model in scientific simulations and routine forecasting.

Use of a Dynamic Air Quality Model to Reduce the Uncertainties of Seasonal and Annual Atmospheric Depositions for Mercury TMDLs

2005 ◽  
Vol 2005 (3) ◽  
pp. 1393-1414
Author(s):  
Kuo-Liang Lai ◽  
Janet Kremer ◽  
Susan Sciarratta ◽  
R. Dwight Atkinson ◽  
Tom Myers
Keyword(s):  
Air Quality ◽  
Air Quality Model ◽  
Quality Model ◽  
Atmospheric Depositions

scholarly journals Assessment of Emission Reduction and Meteorological Change in PM2.5 and Transport Flux in Typical Cities Cluster during 2013–2017

2021 ◽  
Vol 13 (10) ◽  
pp. 5685
Author(s):  
Panbo Guan ◽  
Hanyu Zhang ◽  
Zhida Zhang ◽  
Haoyuan Chen ◽  
Weichao Bai ◽  
...  
Keyword(s):  
Air Quality ◽  
Action Plan ◽  
Influence Factors ◽  
Pollution Prevention ◽  
Weather Conditions ◽  
Yangtze River Delta ◽  
Control Measures ◽  
Joint Control ◽  
Air Quality Model ◽  
Quality Model

Under the Air Pollution Prevention and Control Action Plan (APPCAP) implemented, China has witnessed an air quality change during the past five years, yet the main influence factors remain relatively unexplored. Taking the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions as typical cluster cities, the Weather Research Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were introduced to demonstrate the meteorological and emission contribution and PM2.5 flux distribution. The results showed that the PM2.5 concentration in BTH and YRD significantly declined with a descend ratio of −39.6% and −28.1%, respectively. For the meteorological contribution, those regions had a similar tendency with unfavorable conditions in 2013–2015 (contribution concentration 1.6–3.8 μg/m3 and 1.1–3.6 μg/m3) and favorable in 2016 (contribution concentration −1.5 μg/m3 and −0.2 μg/m3). Further, the absolute value of the net flux’s intensity was positively correlated with the degree of the favorable/unfavorable weather conditions. When it came to emission intensity, the total net inflow flux increased, and the outflow flux decreased significantly across the border with the emission increasing. In short: the aforementioned results confirmed the effectiveness of the regional joint emission control and provided scientific support for the proposed effective joint control measures.

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