scholarly journals Comparison of OMI NO<sub>2</sub> tropospheric columns with an ensemble of global and European regional air quality models

2009 ◽  
Vol 9 (5) ◽  
pp. 22271-22330 ◽  
Author(s):  
V. Huijnen ◽  
H. J. Eskes ◽  
B. Amstrup ◽  
R. Bergstrom ◽  
K. F. Boersma ◽  
...  

Abstract. We present model results for tropospheric NO2 from 9 regional models and 2 global models that are part of the GEMS-RAQ forecast system, for July 2008 to June 2009 over Europe. These modeled NO2 columns are compared with OMI NO2 satellite retrievals and surface observations from the Dutch Air Quality Network. The participating models apply principally the same emission inventory, but vary in model resolution (0.15 to 0.5°), chemical mechanism, meteorology and transport scheme. For area-averaged columns only a small bias is found when the averaging kernel is neglected in the comparison to OMI NO2 columns. The reason for this is that TM4 a priori profiles have higher NOx concentrations in the free troposphere (where sensitivity to NO2 is high) and higher NOx concentrations in the surface layers (where sensitivity to NO2 is low) than RAQ models, effectively cancelling the effect of applying the averaging kernel. We attribute these low NO2 concentrations in the RAQ models to missing emissions from aircraft and lightning. It is also shown that the NO2 concentrations from the upper part of the troposphere (higher than 500 hPa) contribute up to 20% of the total tropospheric NO2 signal observed by OMI. Compared to the global models the RAQ models show a better correlation to the OMI NO2 observations, which are characterized by high spatial variation due to the short lifetime for NO2. The spread in the modeled tropospheric NO2 column is on average 20–40%. In summer the mean of all models is on average 46% below the OMI observations, whereas in winter the models are more in line with OMI. On the other hand the models on average under-predict surface concentrations in winter by 24% and are more in line with observations in summer. These findings suggest that OMI tropospheric columns in summer over polluted regions are biased high by about 40%. The diurnal cycle and profiles in the regional models are well in line, and the profile shapes correspond well to results from the global models. The analyses against OMI observations have proven to be very useful to initiate model improvements, and to quantify uncertainties in the retrieval product.

2010 ◽  
Vol 10 (7) ◽  
pp. 3273-3296 ◽  
Author(s):  
V. Huijnen ◽  
H. J. Eskes ◽  
A. Poupkou ◽  
H. Elbern ◽  
K. F. Boersma ◽  
...  

Abstract. We present a comparison of tropospheric NO2 from OMI measurements to the median of an ensemble of Regional Air Quality (RAQ) models, and an intercomparison of the contributing RAQ models and two global models for the period July 2008–June 2009 over Europe. The model forecasts were produced routinely on a daily basis in the context of the European GEMS ("Global and regional Earth-system (atmosphere) Monitoring using Satellite and in-situ data") project. The tropospheric vertical column of the RAQ ensemble median shows a spatial distribution which agrees well with the OMI NO2 observations, with a correlation r=0.8. This is higher than the correlations from any one of the individual RAQ models, which supports the use of a model ensemble approach for regional air pollution forecasting. The global models show high correlations compared to OMI, but with significantly less spatial detail, due to their coarser resolution. Deviations in the tropospheric NO2 columns of individual RAQ models from the mean were in the range of 20–34% in winter and 40–62% in summer, suggesting that the RAQ ensemble prediction is relatively more uncertain in the summer months. The ensemble median shows a stronger seasonal cycle of NO2 columns than OMI, and the ensemble is on average 50% below the OMI observations in summer, whereas in winter the bias is small. On the other hand the ensemble median shows a somewhat weaker seasonal cycle than NO2 surface observations from the Dutch Air Quality Network, and on average a negative bias of 14%. Full profile information was available for two RAQ models and for the global models. For these models the retrieval averaging kernel was applied. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of replacing the a priori profiles by the RAQ model profiles is on average small. However, the contrast between major hotspots and rural areas is stronger for the direct modeled vertical columns than the columns where the averaging kernels are applied, related to a larger relative contribution of the free troposphere and the coarse horizontal resolution in the a priori profiles compared to the RAQ models. In line with validation results reported in the literature, summertime concentrations in the lowermost boundary layer in the a priori profiles from the DOMINO product are significantly larger than the RAQ model concentrations and surface observations over the Netherlands. This affects the profile shape, and contributes to a high bias in OMI tropospheric columns over polluted regions. The global models indicate that the upper troposphere may contribute significantly to the total column and it is important to account for this in comparisons with RAQ models. A combination of upper troposphere model biases, the a priori profile effects and DOMINO product retrieval issues could explain the discrepancy observed between the OMI observations and the ensemble median in summer.


2017 ◽  
Author(s):  
Uarporn Nopmongcol ◽  
Zhen Liu ◽  
Till Stoeckenius ◽  
Greg Yarwood

Abstract. Inter-continental ozone (O3) transport extends the geographic range of O3 air pollution impacts and makes local air pollution management more difficult. Phase 3 of the Air Quality Modeling Evaluation International Initiative (AQMEII-3) is examining the contribution of inter-continental transport to regional air quality by applying regional scale atmospheric models jointly with global models. We investigate methods for tracing O3 from global models within regional models. The CAMx photochemical grid model was used to track contributions from boundary condition (BC) O3 over a North America modeling domain for calendar year 2010 using a built-in tracer module called RTCMC. RTCMC can track BC contributions using chemically reactive tracers and also using inert tracers in which deposition is the only sink for O3. Lack of O3 destruction chemistry in the inert tracer approach leads to over estimation biases that can exceed 10 ppb. The flexibility of RTCMC also allows tracking O3 contributions made by groups of vertical BC layers. The largest BC contributions to seasonal average daily maximum 8-hour averages (MDA8) of O3 over the US are found to be from the mid-troposphere with small contributions from the upper troposphere-lower stratosphere. Contributions from the lower troposphere are shown to not penetrate very far inland. Higher contributions in the Western than the Eastern US, reaching an average of 57 ppb in Denver for the 30 days with highest MDA8 O3 in 2010, present a significant challenge to air quality management approaches based solely on local or US-wide emission reductions. The substantial BC contribution to MDA8 O3 in the Intermountain West means regional models are particularly sensitive to any biases and errors in the BCs. A sensitivity simulation with reduced BC O3 in response to 20 % lower emissions in Asia found a near linear relationship between the BC O3 changes and surface O3 changes in the Western US in all seasons and across the US in fall and winter. However, the surface O3 decreases are small: below 1 ppb in spring and below 0.5 ppb in other seasons.


2017 ◽  
Vol 17 (16) ◽  
pp. 9931-9943 ◽  
Author(s):  
Uarporn Nopmongcol ◽  
Zhen Liu ◽  
Till Stoeckenius ◽  
Greg Yarwood

Abstract. Intercontinental ozone (O3) transport extends the geographic range of O3 air pollution impacts and makes local air pollution management more difficult. Phase 3 of the Air Quality Modeling Evaluation International Initiative (AQMEII-3) is examining the contribution of intercontinental transport to regional air quality by applying regional-scale atmospheric models jointly with global models. We investigate methods for tracing O3 from global models within regional models. The CAMx photochemical grid model was used to track contributions from boundary condition (BC) O3 over a North American modeling domain for calendar year 2010 using a built-in tracer module called RTCMC. RTCMC can track BC contributions using chemically reactive tracers and also using inert tracers in which deposition is the only sink for O3. Lack of O3 destruction chemistry in the inert tracer approach leads to overestimation biases that can exceed 10 ppb. The flexibility of RTCMC also allows tracking O3 contributions made by groups of vertical BC layers. The largest BC contributions to seasonal average daily maximum 8 h averages (MDA8) of O3 over the US are found to be from the mid-troposphere (over 40 ppb) with small contributions (a few ppb) from the upper troposphere–lower stratosphere. Contributions from the lower troposphere are shown to not penetrate very far inland. Higher contributions in the western than the eastern US, reaching an average of 57 ppb in Denver for the 30 days with highest MDA8 O3 in 2010, present a significant challenge to air quality management approaches based solely on local or US-wide emission reductions. The substantial BC contribution to MDA8 O3 in the Intermountain West means regional models are particularly sensitive to any biases and errors in the BCs. A sensitivity simulation with reduced BC O3 in response to 20 % lower emissions in Asia found a near-linear relationship between the BC O3 changes and surface O3 changes in the western US in all seasons and across the US in fall and winter. However, the surface O3 decreases are small: below 1 ppb in spring and below 0.5 ppb in other seasons.


1997 ◽  
Vol 31 (19) ◽  
pp. 3259-3279 ◽  
Author(s):  
H. Hass ◽  
P.J.H. Builtjes ◽  
D. Simpson ◽  
R. Sternii

2018 ◽  
Vol 10 (11) ◽  
pp. 1789 ◽  
Author(s):  
Hugo Mak ◽  
Joshua Laughner ◽  
Jimmy Fung ◽  
Qindan Zhu ◽  
Ronald Cohen

Improving air quality and reducing human exposure to unhealthy levels of airborne chemicals are important global missions, particularly in China. Satellite remote sensing offers a powerful tool to examine regional trends in NO2, thus providing a direct measure of key parameters that strongly affect surface air quality. To accurately resolve spatial gradients in NO2 concentration using satellite observations and thus understand local and regional aspects of air quality, a priori input data at sufficiently high spatial and temporal resolution to account for pixel-to-pixel variability in the characteristics of the land and atmosphere are required. In this paper, we adapt the Berkeley High Resolution product (BEHR-HK) and meteorological outputs from the Weather Research and Forecasting (WRF) model to describe column NO2 in southern China. The BEHR approach is particularly useful for places with large spatial variabilities and terrain height differences such as China. There are two major objectives and goals: (1) developing new BEHR-HK v3.0C product for retrieving tropospheric NO2 vertical column density (TVCD) within part of southern China, for four months of 2015, based upon satellite datasets from Ozone Monitoring Instrument (OMI); and (2) evaluating BEHR-HK v3.0C retrieval result through validation, by comparing with MAX-DOAS tropospheric column measurements conducted in Guangzhou. Results show that all BEHR-HK retrieval algorithms (with R-value of 0.9839 for v3.0C) are of higher consistency with MAX-DOAS measurements than OMI-NASA retrieval (with R-value of 0.7644). This opens new windows into research questions that require high spatial resolution, for example retrieving NO2 vertical column and ground pollutant concentration in China and other countries.


2018 ◽  
Vol 18 (12) ◽  
pp. 8727-8744 ◽  
Author(s):  
Stefano Galmarini ◽  
Ioannis Kioutsioukis ◽  
Efisio Solazzo ◽  
Ummugulsum Alyuz ◽  
Alessandra Balzarini ◽  
...  

Abstract. In this study we introduce a hybrid ensemble consisting of air quality models operating at both the global and regional scale. The work is motivated by the fact that these different types of models treat specific portions of the atmospheric spectrum with different levels of detail, and it is hypothesized that their combination can generate an ensemble that performs better than mono-scale ensembles. A detailed analysis of the hybrid ensemble is carried out in the attempt to investigate this hypothesis and determine the real benefit it produces compared to ensembles constructed from only global-scale or only regional-scale models. The study utilizes 13 regional and 7 global models participating in the Hemispheric Transport of Air Pollutants phase 2 (HTAP2)–Air Quality Model Evaluation International Initiative phase 3 (AQMEII3) activity and focuses on surface ozone concentrations over Europe for the year 2010. Observations from 405 monitoring rural stations are used for the evaluation of the ensemble performance. The analysis first compares the modelled and measured power spectra of all models and then assesses the properties of the mono-scale ensembles, particularly their level of redundancy, in order to inform the process of constructing the hybrid ensemble. This study has been conducted in the attempt to identify that the improvements obtained by the hybrid ensemble relative to the mono-scale ensembles can be attributed to its hybrid nature. The improvements are visible in a slight increase of the diversity (4 % for the hourly time series, 10 % for the daily maximum time series) and a smaller improvement of the accuracy compared to diversity. Root mean square error (RMSE) improved by 13–16 % compared to G and by 2–3 % compared to R. Probability of detection (POD) and false-alarm rate (FAR) show a remarkable improvement, with a steep increase in the largest POD values and smallest values of FAR across the concentration ranges. The results show that the optimal set is constructed from an equal number of global and regional models at only 15 % of the stations. This implies that for the majority of the cases the regional-scale set of models governs the ensemble. However given the high degree of redundancy that characterizes the regional-scale models, no further improvement could be expected in the ensemble performance by adding yet more regional models to it. Therefore the improvement obtained with the hybrid set can confidently be attributed to the different nature of the global models. The study strongly reaffirms the importance of an in-depth inspection of any ensemble of opportunity in order to extract the maximum amount of information and to have full control over the data used in the construction of the ensemble.


2010 ◽  
Vol 10 (8) ◽  
pp. 4013-4031 ◽  
Author(s):  
Y. F. Lam ◽  
J. S. Fu

Abstract. Recently, downscaling global atmospheric model outputs (GCTM) for the USEPA Community Multiscale Air Quality (CMAQ) Initial (IC) and Boundary Conditions (BC) have become practical because of the rapid growth of computational technologies that allow global simulations to be completed within a reasonable time. The traditional method of generating IC/BC by profile data has lost its advocates due to the weakness of the limited horizontal and vertical variations found on the gridded boundary layers. Theoretically, high quality GCTM IC/BC should yield a better result in CMAQ. Unfortunately, several researchers have found that the outputs from GCTM IC/BC are not necessarily better than profile IC/BC due to the excessive transport of O3 aloft in GCTM IC/BC. In this paper, we intend to investigate the effects of using profile IC/BC and global atmospheric model data. In addition, we are suggesting a novel approach to resolve the existing issue in downscaling. In the study, we utilized the GEOS-Chem model outputs to generate time-varied and layer-varied IC/BC for year 2002 with the implementation of tropopause determining algorithm in the downscaling process (i.e., based on chemical (O3) tropopause definition). The comparison between the implemented tropopause approach and the profile IC/BC approach is performed to demonstrate improvement of considering tropopause. It is observed that without using tropopause information in the downscaling process, unrealistic O3 concentrations are created at the upper layers of IC/BC. This phenomenon has caused over-prediction of surface O3 in CMAQ. In addition, the amount of over-prediction is greatly affected by temperature and latitudinal location of the study domain. With the implementation of the algorithm, we have successfully resolved the incompatibility issues in the vertical layer structure between global and regional chemistry models to yield better surface O3 predictions than profile IC/BC for both summer and winter conditions. At the same time, it improved the vertical O3 distribution of CMAQ outputs. It is strongly recommended that the tropopause information should be incorporated into any two-way coupled global and regional models, where the tropospheric regional model is used, to solve the vertical incompatibility that exists between global and regional models. We have discovered that the previously published paper was not the latest version of the manuscript we intended to use. Some corrections made during the second ACPD reviewing process were not incorporated in the text. As a result, the figure numbers (i.e., figure number below the graph) were not referenced correctly in the manuscript. Therefore, we have decided to re-publish this paper as a corrigendum.


Author(s):  
Hugo Wai Leung Mak ◽  
Joshua L. Laughner ◽  
Jimmy Chi Hung Fung ◽  
Qindan Zhu ◽  
Ronald C. Cohen

Improving air quality and reducing human exposure to unhealthy levels of airborne chemicals are important global missions, particularly in China. Satellite remote sensing offers a powerful tool to examine regional trends in NO2, thus providing a direct measure of key parameters that strongly affect surface air quality. To accurately resolve spatial gradients in NO2 concentration using satellite observations and thus understand local and regional aspects of air quality, a priori input data at sufficiently high spatial and temporal resolution to account for pixel-to-pixel variability in the characteristics of the land and atmosphere are required. In this paper, we adapt the Berkeley High Resolution product (BEHR v3.0A, v3.0B and v3.0C) and meteorological outputs from the Weather Research and Forecasting (WRF) model to describe column NO2 in southern China. The BEHR approach is particularly useful for places with large spatial variabilities and terrain height differences such as China. We retrieved tropospheric NO2 vertical column density (TVCD) within part of southern China, for four seasons of 2015, based upon satellite datasets from Ozone Monitoring Instrument (OMI). Retrieval results are validated by comparing with MAX-DOAS tropospheric column measurements conducted in Guangzhou. BEHR retrieval algorithms are more consistent with MAX-DOAS measurements than OMI-NASA retrieval, opening new windows into research questions that require high spatial resolution, for example retrieving NO2 vertical column and ground pollutant concentration in China and other countries.


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