scholarly journals Multiscale observations of NH<sub>3</sub> around Toronto, Canada

2021 ◽  
Vol 14 (2) ◽  
pp. 905-921
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Erik Lutsch ◽  
Dylan B. A. Jones ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Grid Point ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Spatial And Temporal Variability ◽  
Predictive Capacity ◽  
Total Column

Abstract. Ammonia (NH3) is a major source of nitrates in the atmosphere and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, 3 years of surface in situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the representativeness of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.89 %/yr from 2002 to 2018 in the FTIR columns, 8.88 ± 5.08 %/yr from 2013 to 2017 in the surface in situ data, and 8.38 ± 1.54 %/yr from 2008 to 2018 in the IASI columns. To assess the representative scale of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤25 km and ≤20 min, with r=0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in situ measurements were standardized and correlated. Comparison of 24 d averages and monthly averages resulted in correlation coefficients of r=0.72 and r=0.75, respectively, although correlation without averaging to reduce high-frequency variability led to a poorer correlation, with r=0.39. The GEOS-Chem model, run at 2∘ × 2.5∘ resolution, was compared to FTIR and IASI to assess model performance and investigate the correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35 to 53∘ N and 93.75 to 63.75∘ W) resulted in r=0.57 and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2=0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2=0.13, indicating that a finer spatial resolution is needed for modeling NH3.

scholarly journals Multiscale observations of NH<sub>3</sub> around Toronto, Canada

2020 ◽  
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Erik Lutsch ◽  
Dylan B. A. Jones ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Grid Point ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Spatial And Temporal Variability ◽  
Predictive Capacity ◽  
Total Column

Abstract. Ammonia (NH3) is a major source of nitrates in the atmosphere, and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, three years of surface in-situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the observational footprint of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.46 %/year from 2002 to 2018 in the FTIR columns, 8.88 ± 2.83 %/year from 2013 to 2017 in the surface in-situ data, and 8.38 ± 0.77 %/year from 2008 to 2018 in the IASI columns. To assess the observational footprint of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤ 25 km and ≤ 20 minutes, with r = 0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in-situ measurements were standardized and correlated. Comparison of 24-day averages and monthly averages resulted in correlation coefficients of r = 0.72 and r = 0.75, respectively, although correlation without resampling to reduce high-frequency variability led to a poorer correlation, with r = 0.39. The GEOS-Chem model, run at 2° × 2.5° resolution, was compared against FTIR and IASI to assess model performance and investigate correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35° N to 53° N, and 93.75° W to 63.75° W) resulted in r = 0.57, and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2 = 0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2 = 0.13, indicating that a finer spatial resolution is needed for modeling NH3.

scholarly journals Multiscale observations of NH3 around Toronto, Canada

2020 ◽  
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Dylan B. A. Jones ◽  
Cathy Clerbaux ◽  
...  
Keyword(s):  
Case Studies ◽  
Biomass Burning ◽  
Grid Point ◽  
Fine Particulate Matter ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Predictive Capacity

&lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;p&gt;Ammonia (NH&lt;sub&gt;3&lt;/sub&gt;) is a major source of nitrates in the atmosphere, and a major source of fine particulate matter. As such, there have been increasing efforts to monitor NH&lt;sub&gt;3&lt;/sub&gt;. This study examines long-term measurements of NH&lt;sub&gt;3&lt;/sub&gt; around Toronto, Canada, derived from three multiscale datasets: 16 years of total column measurements using ground-based Fourier transform infrared (FTIR) spectroscopy, three years of surface in-situ measurements, and ten years of total columns from the Infrared Atmospheric Sounding Interferometer (IASI) sensor onboard the Metop satellites. These datasets were used to quantify NH&lt;sub&gt;3&lt;/sub&gt; temporal variabilities (trends, inter-annual, seasonal) over Toronto to assess the observational footprint of the FTIR measurements, and two case studies of pollution events due to transport of biomass burning plumes.&lt;/p&gt; &lt;p&gt;All three timeseries showed increasing trends in NH&lt;sub&gt;3&lt;/sub&gt; over Toronto: 3.34 &amp;#177; 0.44 %/year from 2002 to 2018 in the FTIR columns, 8.88 &amp;#177; 2.49 %/year from 2013 to 2017 in the surface in-situ data, and 8.78 &amp;#177; 0.84 %/year from 2008 to 2018 in the IASI columns. To assess the observational footprint of the FTIR NH&lt;sub&gt;3&lt;/sub&gt; columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was found for coincidence criterion of &amp;#8804; 50 km and &amp;#8804; 20 minutes, with r = 0.66 and a slope of 0.988 &amp;#177; 0.058. The FTIR column and in-situ measurements were standardized and correlated, with 24-day averages and monthly averages yielding correlation coefficients of r = 0.72 and r = 0.75, respectively.&lt;br&gt;FTIR and IASI were also compared against the GEOS-Chem model, run at 2&amp;#176; by 2.5&amp;#176; resolution, to assess model performance and investigate correlation of the model output with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (domain spanning from 35&amp;#176;N to 53&amp;#176;N, and 93.75&amp;#176;W to 63.75&amp;#176;W) resulted in r = 0.62, and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r&lt;sup&gt;2&lt;/sup&gt; = 0.38, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r&lt;sup&gt;2&lt;/sup&gt; = 0.26, indicating that a finer spatial resolution is needed to adequately model the variability of NH&lt;sub&gt;3&lt;/sub&gt;. This study also examines two case studies of NH&lt;sub&gt;3&lt;/sub&gt; enhancements due to biomass burning plumes, in August 2014 and May 2016. In these events, enhancements in both the total columns and surface NH3, were observed.&lt;/p&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt;

scholarly journals Validation of aerosol backscatter profiles from Raman lidar and ceilometer using balloon-borne measurements

2021 ◽  
Vol 21 (3) ◽  
pp. 2267-2285
Author(s):  
Simone Brunamonti ◽  
Giovanni Martucci ◽  
Gonzague Romanens ◽  
Yann Poltera ◽  
Frank G. Wienhold ◽  
...  
Keyword(s):  
Remote Sensing ◽  
In Situ Measurements ◽  
Aerosol Size Distribution ◽  
Spatial And Temporal Variability ◽  
Raman Lidar ◽  
Backscatter Coefficient ◽  
Custom Made ◽  
Aerosol Backscatter ◽  
Good Agreement

Abstract. Remote-sensing measurements by light detection and ranging (lidar) instruments are fundamental for the monitoring of altitude-resolved aerosol optical properties. Here we validate vertical profiles of aerosol backscatter coefficient (βaer) measured by two independent lidar systems using co-located balloon-borne measurements performed by Compact Optical Backscatter Aerosol Detector (COBALD) sondes. COBALD provides high-precision in situ measurements of βaer at two wavelengths (455 and 940 nm). The two analyzed lidar systems are the research Raman Lidar for Meteorological Observations (RALMO) and the commercial CHM15K ceilometer (Lufft, Germany). We consider in total 17 RALMO and 31 CHM15K profiles, co-located with simultaneous COBALD soundings performed throughout the years 2014–2019 at the MeteoSwiss observatory of Payerne (Switzerland). The RALMO (355 nm) and CHM15K (1064 nm) measurements are converted to 455 and 940 nm, respectively, using the Ångström exponent profiles retrieved from COBALD data. To account for the different receiver field-of-view (FOV) angles between the two lidars (0.01–0.02∘) and COBALD (6∘), we derive a custom-made correction using Mie-theory scattering simulations. Our analysis shows that both lidar instruments achieve on average a good agreement with COBALD measurements in the boundary layer and free troposphere, up to 6 km altitude. For medium-high-aerosol-content measurements at altitudes below 3 km, the mean ± standard deviation difference in βaer calculated from all considered soundings is −2 % ± 37 % (−0.018 ± 0.237 Mm−1 sr−1 at 455 nm) for RALMO−COBALD and +5 % ± 43 % (+0.009 ± 0.185 Mm−1 sr−1 at 940 mm) for CHM15K−COBALD. Above 3 km altitude, absolute deviations generally decrease, while relative deviations increase due to the prevalence of air masses with low aerosol content. Uncertainties related to the FOV correction and spatial- and temporal-variability effects (associated with the balloon's drift with altitude and different integration times) contribute to the large standard deviations observed at low altitudes. The lack of information on the aerosol size distribution and the high atmospheric variability prevent an accurate quantification of these effects. Nevertheless, the excellent agreement observed in individual profiles, including fine and complex structures in the βaer vertical distribution, shows that under optimal conditions, the discrepancies with the in situ measurements are typically comparable to the estimated statistical uncertainties in the remote-sensing measurements. Therefore, we conclude that βaer profiles measured by the RALMO and CHM15K lidar systems are in good agreement with in situ measurements by COBALD sondes up to 6 km altitude.

scholarly journals Leveraging Very-High Spatial Resolution Hyperspectral and Thermal UAV Imageries for Characterizing Diurnal Indicators of Grapevine Physiology

2020 ◽  
Vol 12 (19) ◽  
pp. 3216 ◽  
Author(s):  
Matthew Maimaitiyiming ◽  
Vasit Sagan ◽  
Paheding Sidike ◽  
Maitiniyazi Maimaitijiang ◽  
Allison J. Miller ◽  
...  
Keyword(s):  
Canopy Temperature ◽  
Crop Productivity ◽  
In Situ Measurements ◽  
Sensor Technology ◽  
Stress Index ◽  
Coefficient Of Determination ◽  
Neural Net ◽  
Water Stress Index ◽  
Very High

Efficient and accurate methods to monitor crop physiological responses help growers better understand crop physiology and improve crop productivity. In recent years, developments in unmanned aerial vehicles (UAV) and sensor technology have enabled image acquisition at very-high spectral, spatial, and temporal resolutions. However, potential applications and limitations of very-high-resolution (VHR) hyperspectral and thermal UAV imaging for characterization of plant diurnal physiology remain largely unknown, due to issues related to shadow and canopy heterogeneity. In this study, we propose a canopy zone-weighting (CZW) method to leverage the potential of VHR (≤9 cm) hyperspectral and thermal UAV imageries in estimating physiological indicators, such as stomatal conductance (Gs) and steady-state fluorescence (Fs). Diurnal flights and concurrent in-situ measurements were conducted during grapevine growing seasons in 2017 and 2018 in a vineyard in Missouri, USA. We used neural net classifier and the Canny edge detection method to extract pure vine canopy from the hyperspectral and thermal images, respectively. Then, the vine canopy was segmented into three canopy zones (sunlit, nadir, and shaded) using K-means clustering based on the canopy shadow fraction and canopy temperature. Common reflectance-based spectral indices, sun-induced chlorophyll fluorescence (SIF), and simplified canopy water stress index (siCWSI) were computed as image retrievals. Using the coefficient of determination (R2) established between the image retrievals from three canopy zones and the in-situ measurements as a weight factor, weighted image retrievals were calculated and their correlation with in-situ measurements was explored. The results showed that the most frequent and the highest correlations were found for Gs and Fs, with CZW-based Photochemical reflectance index (PRI), SIF, and siCWSI (PRICZW, SIFCZW, and siCWSICZW), respectively. When all flights combined for the given field campaign date, PRICZW, SIFCZW, and siCWSICZW significantly improved the relationship with Gs and Fs. The proposed approach takes full advantage of VHR hyperspectral and thermal UAV imageries, and suggests that the CZW method is simple yet effective in estimating Gs and Fs.

scholarly journals Simulating Secondary Inorganic Aerosols using the chemistry transport model MOCAGE version R2.15.0

2015 ◽  
Vol 8 (4) ◽  
pp. 3593-3651 ◽  
Author(s):  
J. Guth ◽  
B. Josse ◽  
V. Marécal ◽  
M. Joly
Keyword(s):  
North America ◽  
Transport Model ◽  
Regional Scale ◽  
In Situ Measurements ◽  
Aerosol Composition ◽  
Chemistry Transport Model ◽  
Inorganic Aerosols ◽  
Modis Aod ◽  
Inorganic Aerosol

Abstract. In this study we develop a Secondary Inorganic Aerosol (SIA) module for the chemistry transport model MOCAGE developed at CNRM. Based on the thermodynamic equilibrium module ISORROPIA II, the new version of the model is evaluated both at the global scale and at the regional scale. The results show high concentrations of secondary inorganic aerosols in the most polluted regions being Europe, Asia and the eastern part of North America. Asia shows higher sulfate concentrations than other regions thanks to emissions reduction in Europe and North America. Using two simulations, one with and the other without secondary inorganic aerosol formation, the model global outputs are compared to previous studies, to MODIS AOD retrievals, and also to in situ measurements from the HTAP database. The model shows a better agreement in all geographical regions with MODIS AOD retrievals when introducing SIA. It also provides a good statistical agreement with in situ measurements of secondary inorganic aerosol composition: sulfate, nitrate and ammonium. In addition, the simulation with SIA gives generally a better agreement for secondary inorganic aerosols precursors (nitric acid, sulfur dioxide, ammonia) in particular with a reduction of the Modified Normalised Mean Bias (MNMB). At the regional scale, over Europe, the model simulation with SIA are compared to the in situ measurements from the EMEP database and shows a good agreement with secondary inorganic aerosol composition. The results at the regional scale are consistent with those obtained with the global simulations. The AIRBASE database was used to compare the model to regulated air quality pollutants being particulate matter, ozone and nitrogen dioxide concentrations. The introduction of the SIA in MOCAGE provides a reduction of the PM2.5 MNMB of 0.44 on a yearly basis and even 0.52 on a three spring months period (March, April, May) when SIA are maximum.

Regional scale spatial and temporal variability of soil moisture in a prairie region

2016 ◽  
Vol 30 (20) ◽  
pp. 3639-3649 ◽  
Author(s):  
Travis T. Burns ◽  
Aaron A. Berg ◽  
Jaclyn Cockburn ◽  
Erica Tetlock
Keyword(s):  
Soil Moisture ◽  
Temporal Variability ◽  
Regional Scale ◽  
Spatial And Temporal Variability

scholarly journals DERIVING INHERENT OPTICAL PROPERTIES FROM MERIS IMAGERY AND IN SITU MEASUREMENT USING QUASI-ANALYTICAL ALGORITHM

2014 ◽  
Vol 10 (1) ◽  
Author(s):  
Wiwin Ambarwulan ◽  
Widiatmaka ◽  
Syarif Budhiman
Keyword(s):  
Optical Properties ◽  
Optical Measurement ◽  
In Situ Measurements ◽  
In Situ Measurement ◽  
Coefficient Of Determination ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Inherent Optical Properties ◽  
Analytical Algorithm

The  paper  describes inherent optical properties  (IOP)  of  the  Berau  coastal  waters  derived from in  situ measurements  and Medium  Resolution  Imaging  Spectrometer  (MERIS) satellite  data. Field  measurements  of optical  water,  total  suspended  matter  (TSM), and  chlorophyll-a  (Chl-a) concentrations were carried out during the dry season of 2007. During this periode, only four MERISdata were  coincided with in  situ measurements on 31 August  2007. The MERIS  top-of-atmosphere radiances were atmospherically corrected using the MODTRAN radiative transfer model. The in situ optical  measurement  have  been  processed  into apparent optical properties  (AOP) and sub  surface irradiance. The remote sensing reflectance of in situ measurement as well as MERIS data were inverted into  the  IOP  using quasi-analytical algorithm  (QAA).  The  result  indicated  that coefficient  of determination (R 2) of backscattering coefficients of suspended particles (bbp) increased with increasing wavelength,  however  the  R2 of  absorption  spectra  of  phytoplankton  (aph)  decreased  with  increasing wavelength.

scholarly journals Validation of aerosol backscatter profiles from Raman lidar and ceilometer using balloon-borne measurements

2020 ◽  
Author(s):  
Simone Brunamonti ◽  
Giovanni Martucci ◽  
Gonzague Romanens ◽  
Yann Poltera ◽  
Frank G. Wienhold ◽  
...  
Keyword(s):  
In Situ Measurements ◽  
Spatial And Temporal Variability ◽  
Free Troposphere ◽  
Raman Lidar ◽  
Backscatter Coefficient ◽  
Custom Made ◽  
Standard Deviations ◽  
Aerosol Backscatter ◽  
Good Agreement

Abstract. Remote sensing measurements by light detection and ranging (lidar) instruments are fundamental for the monitoring of altitude-resolved aerosol optical properties. Here, we validate vertical profiles of aerosol backscatter coefficient (βaer) measured by two independent lidar systems using co-located balloon-borne measurements performed by Compact Optical Backscatter Aerosol Detector (COBALD) sondes. COBALD provides high-precision in-situ measurements of βaer at two wavelengths (455 and 940 nm). The two analyzed lidar systems are the research Raman Lidar for Meteorological Observations (RALMO) and the commercial CHM15K ceilometer (Lufft, Germany). We consider in total 17 RALMO and 31 CHM15K profiles, co-located with simultaneous COBALD soundings performed throughout the years 2014–2019 at the MeteoSwiss observatory of Payerne (Switzerland). The RALMO (355 nm) and CHM15K (1064 nm) measurements are converted to respectively 455 nm and 940 nm using the Angstrom exponent profiles retrieved from COBALD data. To account for the different receiver field of view (FOV) angles between the two lidars (0.01–0.02°) and COBALD (6°), we derive a custom-made correction using Mie-theory scattering simulations. Our analysis shows that both RALMO and CHM15K achieve a good agreement with COBALD measurements in the boundary layer and free troposphere, up to 6 km altitude, and including fine structures in the aerosol’s vertical distribution. For altitudes below 2 km, the mean ± standard deviation difference in βaer is + 6 % ± 40 % (+ 0.005 ± 0.319 Mm−1 sr−1) for RALMO – COBALD at 455 nm, and + 13 % ± 51 % (+ 0.038 ± 0.207 Mm−1 sr−1) for CHM15K – COBALD at 940 nm. The large standard deviations can be at least partly attributed to atmospheric variability effects, associated with the balloon’s horizontal drift with altitude (away from the lidar beam) and the different integration times of the two techniques. Combined with the high spatial and temporal variability of atmospheric aerosols, these effects often lead to a slight altitude displacement between aerosol backscatter features that are seen by both techniques. For altitudes between 2–6 km, the absolute standard deviations of both RALMO and CHM15K decrease (below 0.13 and 0.16 Mm−1sr−1, respectively), while their corresponding relative deviations increase (often exceeding 100 % COBALD of the signal). This is due to the low aerosol content (i.e. low absolute backscattered signal) in the free troposphere, and the vertically decreasing signal-to-noise ratio of the lidar measurements (especially CHM15K). Overall, we conclude that the βaer profiles measured by the RALMO and CHM15K lidar systems are in good agreement with in-situ measurements by COBALD sondes up to 6 km altitude.

scholarly journals Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements

2021 ◽  
Vol 14 (7) ◽  
pp. 5241-5269
Author(s):  
Vinod Kumar ◽  
Julia Remmers ◽  
Steffen Beirle ◽  
Joachim Fallmann ◽  
Astrid Kerkweg ◽  
...  
Keyword(s):  
High Resolution ◽  
Atmospheric Chemistry ◽  
Temporal Variability ◽  
Model System ◽  
West Germany ◽  
Optical Absorption Spectroscopy ◽  
Anthropogenic Emissions ◽  
Spatial And Temporal Variability ◽  
Daily Variability

Abstract. We present high spatial resolution (up to 2.2×2.2 km2) simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n) (MESSy-fied ECHAM and COSMO models nested n times). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMRs) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly-resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS (Multiple AXis Differential Optical Absorption Spectroscopy) measurements performed at Mainz (49.99∘ N, 8.23∘ E) were used to evaluate the simulated tropospheric vertical column densities (VCDs) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles (≤8∘), small biases in the range of −14 % to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases, indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly-resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when vertical mixing is suppressed, and the atmospheric lifetime of NO2 is relatively long.

Sign in / Sign up

Export Citation Format

Share Document