scholarly journals Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

2017 ◽  
Vol 17 (9) ◽  
pp. 5829-5849 ◽  
Author(s):  
Theano Drosoglou ◽  
Alkiviadis F. Bais ◽  
Irene Zyrichidou ◽  
Natalia Kouremeti ◽  
Anastasia Poupkou ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Monitoring Site ◽  
Air Quality Model ◽  
Ozone Monitoring Instrument ◽  
Quality Model ◽  
Meteorological Model ◽  
Tropospheric No2 ◽  
Ozone Monitoring

Abstract. One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32  ×  1015 and 10.21 ± 8.87  × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71  ×  1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01  ×  1015 molecules cm−2.

scholarly journals Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over Thessaloniki area, Greece

2016 ◽  
Author(s):  
Theano Drosoglou ◽  
Alkiviadis F. Bais ◽  
Irene Zyrichidou ◽  
Natalia Kouremeti ◽  
Anastasia Poupkou ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Monitoring Site ◽  
Air Quality Model ◽  
Quality Model ◽  
Meteorological Model ◽  
Multi Scale ◽  
Tropospheric No2 ◽  
Urban Monitoring ◽  
The Difference

Abstract. The main issue arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two datasets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which was lasted for about six months was held at the greater area of Thessaloniki, Greece. Three DOAS/MAX-DOAS systems performed measurements of tropospheric NO2 columns at different sites representative of urban, sub-urban and rural conditions. The direct comparison of these ground-based measurements with corresponding OMI/Aura and GOME-2/MetOp-A and GOME2/MetOp-B products showed good agreement only over the rural area. GOME2A and GOME2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 9.12 ± 7.33 × 1015 and 9.58 ± 8.21 × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.03 ± 6.04 × 1015 molecules cm−2), mainly due to the higher spatial resolution of OMI. OMI data were adjusted using factors calculated by an air quality modelling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multi-scale photochemical transport model. This approach resulted to significant improvement of the comparisons over the urban monitoring site. The average negative difference of OMI observations from Phaethon measurements was reduced to 1.15 ± 6.32 × 1015 molecules cm−2.

scholarly journals Comparison of tropospheric NO<sub>2</sub> columns from MAX-DOAS retrievals and regional air quality model simulations

2020 ◽  
Vol 20 (5) ◽  
pp. 2795-2823
Author(s):  
Anne-Marlene Blechschmidt ◽  
Joaquim Arteta ◽  
Adriana Coman ◽  
Lyana Curier ◽  
Henk Eskes ◽  
...  
Keyword(s):  
Air Quality ◽  
Regional Model ◽  
Tropospheric Chemistry ◽  
Optical Absorption Spectroscopy ◽  
Air Quality Model ◽  
Quality Model ◽  
Vertical Column ◽  
Diurnal Cycles ◽  
Tropospheric No2 ◽  
Regional Air Quality

Abstract. Multi-axis differential optical absorption spectroscopy (MAX-DOAS) tropospheric NO2 column retrievals from four European measurement stations are compared to simulations from five regional air quality models which contribute to the European regional ensemble forecasts and reanalyses of the operational Copernicus Atmosphere Monitoring Service (CAMS). Compared to other observational data usually applied for regional model evaluation, MAX-DOAS data are closer to the regional model data in terms of horizontal and vertical resolution, and multiple measurements are available during daylight, so that, for example, diurnal cycles of trace gases can be investigated. In general, there is good agreement between simulated and retrieved NO2 column values for individual MAX-DOAS measurements with correlations between 35 % and 70 % for individual models and 45 % to 75 % for the ensemble median for tropospheric NO2 vertical column densities (VCDs), indicating that emissions, transport and tropospheric chemistry of NOx are on average well simulated. However, large differences are found for individual pollution plumes observed by MAX-DOAS. Most of the models overestimate seasonal cycles for the majority of MAX-DOAS sites investigated. At the urban stations, weekly cycles are reproduced well, but the decrease towards the weekend is underestimated and diurnal cycles are overall not well represented. In particular, simulated morning rush hour peaks are not confirmed by MAX-DOAS retrievals, and models fail to reproduce observed changes in diurnal cycles for weekdays versus weekends. The results of this study show that future model development needs to concentrate on improving representation of diurnal cycles and associated temporal scalings.

scholarly journals MAX-DOAS tropospheric nitrogen dioxide column measurements compared with the Lotos-Euros air quality model

2015 ◽  
Vol 15 (3) ◽  
pp. 1313-1330 ◽  
Author(s):  
T. Vlemmix ◽  
H. J. Eskes ◽  
A. J. M. Piters ◽  
M. Schaap ◽  
F. J. Sauter ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Region ◽  
Optical Absorption Spectroscopy ◽  
Air Quality Model ◽  
Quality Model ◽  
Data Set ◽  
Weekly Cycle ◽  
Significant Difference ◽  
Tropospheric No2 ◽  
Long Time

Abstract. A 14-month data set of MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) tropospheric NO2 column observations in De Bilt, the Netherlands, has been compared with the regional air quality model Lotos-Euros. The model was run on a 7×7 km2 grid, the same resolution as the emission inventory used. A study was performed to assess the effect of clouds on the retrieval accuracy of the MAX-DOAS observations. Good agreement was found between modeled and measured tropospheric NO2 columns, with an average difference of less than 1% of the average tropospheric column (14.5 · 1015 molec cm−2). The comparisons show little cloud cover dependence after cloud corrections for which ceilometer data were used. Hourly differences between observations and model show a Gaussian behavior with a standard deviation (σ) of 5.5 · 1015 molec cm−2. For daily averages of tropospheric NO2 columns, a correlation of 0.72 was found for all observations, and 0.79 for cloud free conditions. The measured and modeled tropospheric NO2 columns have an almost identical distribution over the wind direction. A significant difference between model and measurements was found for the average weekly cycle, which shows a much stronger decrease during the weekend for the observations; for the diurnal cycle, the observed range is about twice as large as the modeled range. The results of the comparison demonstrate that averaged over a long time period, the tropospheric NO2 column observations are representative for a large spatial area despite the fact that they were obtained in an urban region. This makes the MAX-DOAS technique especially suitable for validation of satellite observations and air quality models in urban regions.

The Impact of Nudging in the Meteorological Model for Retrospective Air Quality Simulations. Part I: Evaluation against National Observation Networks

2008 ◽  
Vol 47 (7) ◽  
pp. 1853-1867 ◽  
Author(s):  
Tanya L. Otte
Keyword(s):  
Air Quality ◽  
Meteorological Conditions ◽  
Daily Maximum ◽  
Air Quality Model ◽  
Quality Model ◽  
Meteorological Model ◽  
Model Simulations ◽  
Dynamic Analyses ◽  
The Impact ◽  
Over Time

Abstract It is common practice to use Newtonian relaxation, or nudging, throughout meteorological model simulations to create “dynamic analyses” that provide the characterization of the meteorological conditions for retrospective air quality model simulations. Given the impact that meteorological conditions have on air quality simulations, it has been assumed that the resultant air quality simulations would be more skillful by using dynamic analyses rather than meteorological forecasts to characterize the meteorological conditions, and that the statistical trends in the meteorological model fields are also reflected in the air quality model. This article, which is the first of two parts, demonstrates the impact of nudging in the meteorological model on retrospective air quality model simulations. Here, meteorological simulations are generated by the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) using both the traditional dynamic analysis approach and using forecasts for a summertime period. The resultant fields are then used to characterize the meteorological conditions for emissions processing and air quality simulations using the Community Multiscale Air Quality (CMAQ) Modeling System. As expected, on average, the near-surface meteorological fields show a significant degradation over time in the forecasts (when nudging is not used), while the dynamic analyses maintain nearly constant statistical scores in time. The use of nudged MM5 fields in CMAQ generally results in better skill scores for daily maximum 1-h ozone mixing ratio simulations. On average, the skill of the daily maximum 1-h ozone simulation deteriorates significantly over time when nonnudged MM5 fields are used in CMAQ. The daily maximum 1-h ozone mixing ratio also degrades over time in the CMAQ simulation that uses MM5 dynamic analyses, although to a much lesser degree, despite no aggregate loss of skill over time in the dynamic analyses themselves. These results affirm the advantage of using nudging in MM5 to create the meteorological characterization for CMAQ for retrospective simulations, and it is shown that MM5-based dynamic analyses are robust at the surface throughout 5.5-day simulations.

scholarly journals First estimates of global free-tropospheric NO<sub>2</sub> abundances derived using a cloud-slicing technique applied to satellite observations from the Aura Ozone Monitoring Instrument (OMI)

2014 ◽  
Vol 14 (19) ◽  
pp. 10565-10588 ◽  
Author(s):  
S. Choi ◽  
J. Joiner ◽  
Y. Choi ◽  
B. N. Duncan ◽  
A. Vasilkov ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Profile Analysis ◽  
Middle Latitude ◽  
Optical Absorption Spectroscopy ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Monitoring Instrument ◽  
Single Orbit ◽  
Tropospheric No2 ◽  
Ozone Monitoring

Abstract. We derive free-tropospheric NO2 volume mixing ratios (VMRs) by applying a cloud-slicing technique to data from the Ozone Monitoring Instrument (OMI) on the Aura satellite. In the cloud-slicing approach, the slope of the above-cloud NO2 column versus the cloud scene pressure is proportional to the NO2 VMR. In this work, we use a sample of nearby OMI pixel data from a single orbit for the linear fit. The OMI data include cloud scene pressures from the rotational-Raman algorithm and above-cloud NO2 vertical column density (VCD) (defined as the NO2 column from the cloud scene pressure to the top of the atmosphere) from a differential optical absorption spectroscopy (DOAS) algorithm. We compare OMI-derived NO2 VMRs with in situ aircraft profiles measured during the NASA Intercontinental Chemical Transport Experiment Phase B (INTEX-B) campaign in 2006. The agreement is generally within the estimated uncertainties when appropriate data screening is applied. We then derive a global seasonal climatology of free-tropospheric NO2 VMR in cloudy conditions. Enhanced NO2 in the free troposphere commonly appears near polluted urban locations where NO2 produced in the boundary layer may be transported vertically out of the boundary layer and then horizontally away from the source. Signatures of lightning NO2 are also shown throughout low and middle latitude regions in summer months. A profile analysis of our cloud-slicing data indicates signatures of lightning-generated NO2 in the upper troposphere. Comparison of the climatology with simulations from the global modeling initiative (GMI) for cloudy conditions (cloud optical depth > 10) shows similarities in the spatial patterns of continental pollution outflow. However, there are also some differences in the seasonal variation of free-tropospheric NO2 VMRs near highly populated regions and in areas affected by lightning-generated NOx.

scholarly journals The use of hierarchical clustering for the design of optimized monitoring networks

2018 ◽  
Vol 18 (9) ◽  
pp. 6543-6566 ◽  
Author(s):  
Joana Soares ◽  
Paul Andrew Makar ◽  
Yayne Aklilu ◽  
Ayodeji Akingunola
Keyword(s):  
Time Series ◽  
Air Quality ◽  
Hierarchical Clustering ◽  
Spatial Information ◽  
Monitoring Site ◽  
Model Output ◽  
Monitoring Networks ◽  
Air Quality Model ◽  
Quality Model ◽  
Single Station

Abstract. Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity and can be used to assess the efficacy and design of air quality monitoring networks. We describe here our use of Kolmogorov–Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1−R, R being the Pearson correlation coefficient, and the Euclidean distance; we find that both should be used in evaluating monitoring site similarity. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We demonstrate that clustering results depend on the air contaminant analysed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter timescales (hourly to daily) due to short-term variation of concentrations and that longer-term averages in data collection may lose the information needed to identify local sources. However, the methodology identifies stations mainly influenced by seasonality, if larger timescales (weekly to monthly) are considered. We have performed the first dissimilarity analysis based on gridded air quality model output and have shown that the methodology is capable of generating maps of subregions within which a single station will represent the entire subregion, to a given level of dissimilarity. We have also shown that our approach is capable of identifying different sampling methodologies as well as outliers (stations' time series which are markedly different from all others in a given dataset).

scholarly journals Evaluate of air pollution dispersion and propose planing scenerios to reduce air pollution for livestock activities in Tan Thanh district, Ba Ria – Vung Tau province

2019 ◽  
Vol 2 (2) ◽  
pp. 26-37 ◽  
Author(s):  
Dung Minh Ho ◽  
Bang Quoc Ho ◽  
Thang Viet Le
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Air Pollutants ◽  
Agricultural Sector ◽  
Ambient Air ◽  
Air Quality Model ◽  
Quality Model ◽  
Meteorological Model ◽  
Pollution Dispersion ◽  
Air Pollution Dispersion

Livestock is one of the main activities of the agricultural sector in Tan Thanh district, Ba Ria – Vung Tau province. Beside of pollution sources such as waste water, solid waste, livestock activity in Tan Thanh district, Ba Ria - Vung Tau province in recent years has caused air pollution in the livestock area and surrounding area. This research was carried out to evaluate the process of air pollution dispersion from livestock activities based on applying the TAPM meteorological model and AERMOD air quality model. The results showed that the maximum concentrations of air pollutants from livestock area such as NH3, H2S and CH3SH exceeded the National Technical Regulation on Ambient Air Quality (average hour) in the centre of Tan Thanh district, such as Toc Tien commune, part of Tan Phuoc and Phuoc Hoa communes, is 505 μg/m3; 57.4 μg/m3 and 111 μg/m3, respectively. Phu My district and other suburban communes (Hac Dich, Song Xoai, Chau Pha, Tan Hoa, Tan Hai, My Xuan, etc.) have distribution of lower concentrations of air pollutants. Base on the present results of modeling, the authors have proposed livestock development scenarios to control air pollution from this activity, contributing to environmental protection for Tan Thanh district.

scholarly journals Comparison of tropospheric NO<sub>2</sub> columns from MAX-DOAS retrievals and regional air quality model simulations

2017 ◽  
Author(s):  
Anne-Marlene Blechschmidt ◽  
Joaquim Arteta ◽  
Adriana Coman ◽  
Lyana Curier ◽  
Henk Eskes ◽  
...  
Keyword(s):  
Air Quality ◽  
Global Scale ◽  
Regional Model ◽  
Tropospheric Chemistry ◽  
Pollution Transport ◽  
Model Ensemble ◽  
Air Quality Model ◽  
Quality Model ◽  
Tropospheric No2 ◽  
Regional Air Quality

Abstract. Tropospheric NO2 is hazardous to human health and can lead to tropospheric ozone formation, eutrophication of ecosystems and acid rain production. It is therefore important to establish accurate data based on models and observations to understand and monitor tropospheric NO2 concentrations on a regional and global scale. In the present study, MAX-DOAS tropospheric NO2 column retrievals from four European measurement stations are compared to regional model ensemble simulations. The latter are based on regional air quality models which contribute to the European regional ensemble forecasts and reanalyses of the operational Copernicus Atmosphere Monitoring Service (CAMS). Compared to other observational data usually applied for regional model validation, MAX-DOAS data is closer to the regional model data in terms of horizontal and vertical resolution and measurements are available during daylight. In general, there is a good agreement between simulated and retrieved NO2 column values for individual MAX-DOAS measurements with correlations between 45 and 75 % for tropospheric NO2 VCDs, indicating that the model ensemble represents the emission and tropospheric chemistry of NOx (NO + NO2) well. Pollution transport towards the stations is on average well represented by the models. However, large differences are found for individual pollution plumes. Seasonal cycles are overestimated, weekly cycles are reproduced well and diurnal cycles poorly represented by the model ensemble. In particular, simulated morning rush hour peaks are not confirmed by MAX-DOAS retrievals. Our results demonstrate that a large number of validation points are available from MAX-DOAS measurements, which should therefore be used more extensively in future regional air quality modelling studies.

scholarly journals Global, High-Resolution, Reduced-Complexity Air Quality Modeling Using InMAP(Intervention Model for Air Pollution)

2021 ◽  
Author(s):  
Sumil Thakrar ◽  
Christopher Tessum ◽  
Joshua Apte ◽  
Srinidhi Balasubramanian ◽  
Dylan B Millet ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Transport Model ◽  
The United States ◽  
Air Quality Modeling ◽  
Air Quality Model ◽  
Quality Model ◽  
Desktop Computer ◽  
Quality Modeling ◽  
Reduced Complexity

<p>Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM<sub>2.5</sub>). Designing policies to reduce deaths relies on air quality modeling for estimating changes in PM<sub>2.5</sub> concentrations from many policy scenarios at high spatial resolution. However, air quality modeling typically has high requirements for computation and expertise, which limits policy design, especially in countries where most PM<sub>2.5</sub>-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM<sub>2.5</sub> concentrations across a global-through-urban spatial domain: “Global InMAP”. Global InMAP uses a variable resolution grid, with 4 km horizontal grid cell widths in cities. We evaluate Global InMAP performance both against measurements and a state-of-the-science chemical transport model, GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%–121%. Global InMAP can be run on a desktop computer; simulations here took 2.6–4.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate air pollution policy assessment worldwide, providing a tool for reducing the deaths where they occur most.</p>

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