scholarly journals Estimating ground-level PM<sub>2.5</sub> in Eastern China using aerosol optical depth determined from the GOCI Satellite Instrument

2015 ◽  
Vol 15 (12) ◽  
pp. 17251-17281 ◽  
Author(s):  
J. Xu ◽  
R. V. Martin ◽  
A. van Donkelaar ◽  
J. Kim ◽  
M. Choi ◽  
...  
Keyword(s):  
Organic Matter ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Eastern China ◽  
Ground Level ◽  
East China ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Significant Agreement

Abstract. We determine and interpret fine particulate matter (PM2.5) concentrations in East China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean Geostationary Ocean Color Imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of −1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5/AOD ratio exhibits high consistency with ground-based measurements (MFB = −0.52–8.0 %). We evaluate the satellite-derived PM2.5 vs. the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in-situ observations in both annual averages (r = 0.81, N = 494) and monthly averages (MFB = 13.1 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical speciation of GOCI-derived PM2.5 reveals that secondary inorganics (SO42−, NO3−, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating are responsible for an increase in the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over East China for 2013 is 53.8 μg m−3, threatening the health and life expectancy of its 600 million residents.

scholarly journals Estimating ground-level PM<sub>2.5</sub> in eastern China using aerosol optical depth determined from the GOCI satellite instrument

2015 ◽  
Vol 15 (22) ◽  
pp. 13133-13144 ◽  
Author(s):  
J.-W. Xu ◽  
R. V. Martin ◽  
A. van Donkelaar ◽  
J. Kim ◽  
M. Choi ◽  
...  
Keyword(s):  
Organic Matter ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Eastern China ◽  
Ground Level ◽  
World Health ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Significant Agreement

Abstract. We determine and interpret fine particulate matter (PM2.5) concentrations in eastern China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean geostationary ocean color imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of −1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5 / AOD ratio exhibits high consistency with ground-based measurements in Taiwan (MFB = −0.52 %) and Beijing (MFB = −8.0 %). We evaluate the satellite-derived PM2.5 versus the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in situ observations in both annual averages (r2 = 0.66, N = 494) and monthly averages (relative RMSE = 18.3 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical composition of GOCI-derived PM2.5 reveals that secondary inorganics (SO42-, NO3-, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating increase the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over eastern China for 2013 is 53.8 μg m−3, with 400 million residents in regions that exceed the Interim Target-1 of the World Health Organization.

scholarly journals Estimated total emissions of trace gases from the Canberra wildfires of 2003: a new method using satellite measurements of aerosol optical depth and the MOZART chemical transport model

2010 ◽  
Vol 10 (1) ◽  
pp. 977-1004
Author(s):  
C. Paton-Walsh ◽  
L. K. Emmons ◽  
S. R. Wilson
Keyword(s):  
Carbon Monoxide ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Trace Gases ◽  
Chemical Transport ◽  
New Method ◽  
Chemical Transport Model ◽  
Additional Tool ◽  
Vegetation Fires

Abstract. In this paper we describe a new method for estimating trace gas emissions from large vegetation fires using measurements of aerosol optical depth from the MODIS instruments onboard NASA's Terra and Aqua satellites, combined with the atmospheric chemical transport model MOZART. The model allows for an estimate of double counting of enhanced levels of aerosol optical depth in consecutive satellite overpasses. Using this method we infer an estimated total emission of 10±3 Tg of carbon monoxide from the Canberra fires of 2003. Emissions estimates for several other trace gases are also given. An assessment of the uncertainties in the new method is made and we show that our estimate agrees (within expected uncertainties) with estimates made using current conventional methods of multiplying together factors for the area burned, fuel load, the combustion efficiency and the emission factor for carbon monoxide. The new method for estimating emissions from large vegetation fires described in this paper has some significant uncertainties, but these are mainly quantifiable and largely independent of the uncertainties inherent in conventional techniques. Thus we conclude that the new method is a useful additional tool for characterising emissions from vegetation fires.

scholarly journals Estimated total emissions of trace gases from the Canberra Wildfires of 2003: a new method using satellite measurements of aerosol optical depth & the MOZART chemical transport model

2010 ◽  
Vol 10 (12) ◽  
pp. 5739-5748 ◽  
Author(s):  
C. Paton-Walsh ◽  
L. K. Emmons ◽  
S. R. Wilson
Keyword(s):  
Carbon Monoxide ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Chemical Transport ◽  
New Method ◽  
Chemical Transport Model ◽  
Satellite Measurements ◽  
Additional Tool ◽  
Vegetation Fires

Abstract. In this paper we describe a new method for estimating trace gas emissions from large vegetation fires using satellite measurements of aerosol optical depth (AOD) at 550 nm, combined with an atmospheric chemical transport model. The method uses a threshold value to screen out normal levels of AOD that may be caused by raised dust, sea salt aerosols or diffuse smoke transported from distant fires. Using this method we infer an estimated total emission of 15±5 Tg of carbon monoxide, 0.05±0.02 Tg of hydrogen cyanide, 0.11±0.03 Tg of ammonia, 0.25±0.07 Tg of formaldehyde, 0.03±0.01 of acetylene, 0.10±0.03 Tg of ethylene, 0.03±0.01 Tg of ethane, 0.21±0.06 Tg of formic acid and 0.28±0.09 Tg of methanol released to the atmosphere from the Canberra fires of 2003. An assessment of the uncertainties in the new method is made and we show that our estimate agrees (within expected uncertainties) with estimates made using current conventional methods of multiplying together factors for the area burned, fuel load, the combustion efficiency and the emission factor for carbon monoxide. A simpler estimate derived directly from the satellite AOD measurements is also shown to be in agreement with conventional estimates, suggesting that the method may, under certain meteorological conditions, be applied without the complication of using a chemical transport model. The new method is suitable for estimating emissions from distinct large fire episodes and although it has some significant uncertainties, these are largely independent of the uncertainties inherent in conventional techniques. Thus we conclude that the new method is a useful additional tool for characterising emissions from vegetation fires.

scholarly journals Comparison of PMCAMx aerosol optical depth predictions over Europe with AERONET and MODIS measurements

2016 ◽  
Vol 9 (11) ◽  
pp. 4257-4272
Author(s):  
Antigoni Panagiotopoulou ◽  
Panagiotis Charalampidis ◽  
Christos Fountoukis ◽  
Christodoulos Pilinis ◽  
Spyros N. Pandis
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Chemical Transport Model ◽  
Secondary Aerosol ◽  
The Balkans ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
High Dust

Abstract. The ability of chemical transport model (CTM) PMCAMx to reproduce aerosol optical depth (AOD) measurements by the Aerosol Robotic Network (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) over Europe during the photochemically active period of May 2008 (EUCAARI campaign) is evaluated. Periods with high dust or sea-salt levels are excluded, so the analysis focuses on the ability of the model to simulate the mostly secondary aerosol and its interactions with water. PMCAMx reproduces the monthly mean MODIS and AERONET AOD values over the Iberian Peninsula, the British Isles, central Europe, and Russia with a fractional bias of less than 15 % and a fractional error of less than 30 %. However, the model overestimates the AOD over northern Europe, most probably due to an overestimation of organic aerosol and sulfates. At the other end, PMCAMx underestimates the monthly mean MODIS AOD over the Balkans, the Mediterranean, and the South Atlantic. These errors appear to be related to an underestimation of sulfates. Sensitivity tests indicate that the evaluation results of the monthly mean AODs are quite sensitive to the relative humidity (RH) fields used by PMCAMx, but are not sensitive to the simulated size distribution and the black carbon mixing state. The screening of the satellite retrievals for periods with high dust (or coarse particles in general) concentrations as well as the combination of the MODIS and AERONET datasets lead to more robust conclusions about the ability of the model to simulate the secondary aerosol components that dominate the AOD during this period.

scholarly journals The spatiotemporal relationship between PM<sub>2.5</sub> and aerosol optical depth in China: influencing factors and implications for satellite PM<sub>2.5</sub> estimations using MAIAC aerosol optical depth

2021 ◽  
Vol 21 (24) ◽  
pp. 18375-18391
Author(s):  
Qingqing He ◽  
Mengya Wang ◽  
Steve Hung Lam Yim
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Spatial Scales ◽  
Pearson Correlation ◽  
Eastern China ◽  
Atmospheric Correction ◽  
Mainland China ◽  
Ground Level ◽  
Central China ◽  
The Relationship

Abstract. Satellite aerosol retrievals have been a popular alternative to monitoring the surface-based PM2.5 concentration due to their extensive spatial and temporal coverage. Satellite-derived PM2.5 estimations strongly rely on an accurate representation of the relationship between ground-level PM2.5 and satellite aerosol optical depth (AOD). Due to the limitations of satellite AOD data, most studies have examined the relationship at a coarse resolution (i.e., ≥ 10 km); thus, more effort is still needed to better understand the relationship between “in situ” PM2.5 and AOD at finer spatial scales. While PM2.5 and AOD could have obvious temporal variations, few studies have examined the diurnal variation in their relationship. Therefore, considerable uncertainty still exists in satellite-derived PM2.5 estimations due to these research gaps. Taking advantage of the newly released fine-spatial-resolution satellite AOD data derived from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm and real-time ground aerosol and PM2.5 measurements, this study explicitly explored the relationship between PM2.5 and AOD as well as its plausible impact factors, including meteorological parameters and topography, in mainland China during 2019, at various spatial and temporal scales. The coefficient of variation, the Pearson correlation coefficient and the slope of the linear regression model were used. Spatially, stronger correlations mainly occurred in northern and eastern China, and the linear slope was larger on average in northern inland regions than in other areas. Temporally, the PM2.5–AOD correlation peaked at noon and in the afternoon, and reached a maximum in winter. Simultaneously, considering relative humidity (RH) and the planetary boundary layer height (PBLH) in the relationship can improve the correlation, but the effect of RH and the PBLH on the correlation varied spatially and temporally with respect to both strength and direction. In addition, the largest correlation occurred at 400–600 m primarily in basin terrain such as the Sichuan Basin, the Shanxi–Shaanxi basins and the Junggar Basin. MAIAC 1 km AOD can better represent the ground-level fine particulate matter in most domains with exceptions, such as in very high terrain (i.e., Tibetan Plateau) and northern central China (i.e., Qinghai and Gansu). The findings of this study have useful implications for satellite-based PM2.5 monitoring and will further inform the understanding of the aerosol variation and PM2.5 pollution status of mainland China.

scholarly journals The European aerosol budget in 2006

2010 ◽  
Vol 10 (9) ◽  
pp. 21391-21437 ◽  
Author(s):  
J. M. J. Aan de Brugh ◽  
M. Schaap ◽  
E. Vignati ◽  
F. Dentener ◽  
M. Kahnert ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Ground Level ◽  
Sea Salt ◽  
Optical Measurements ◽  
Aerosol Size Distribution ◽  
Anthropogenic Aerosols ◽  
Removal Rates ◽  
Wet Removal

Abstract. This paper presents the aerosol budget over Europe in 2006 calculated with the global transport model TM5 coupled to the size-resolved aerosol module M7. Comparison with ground observations indicates that the model reproduces the observed concentrations quite well with an expected slight underestimation of PM10 due to missing emissions (e.g. resuspension). We observe that a little less than half of the anthropogenic aerosols emitted in Europe are exported and the rest is removed by deposition. The anthropogenic aerosols are removed mostly by rain (95%) and only 5% is removed by dry deposition. For the larger natural aerosols, especially sea salt, a larger fraction is removed by dry processes (sea salt: 70%, mineral dust: 35%). We observe transport of aerosols in the jet stream in the higher atmosphere and an import of Sahara dust from the south at high altitudes. Comparison with optical measurements shows that the model reproduces the Ångström parameter very well, which indicates a correct simulation of the aerosol size distribution. However, we observe an underestimation of the aerosol optical depth. Because the surface concentrations are close to the observations, the shortage of aerosol in the model is probably at higher altitudes. We show that the discrepancies are mainly caused by an overestimation of wet-removal rates. To match the observations, the wet-removal rates have to be scaled down by a factor of about 5. In that case the modelled ground-level concentrations of sulphate and sea salt increase by 50% (which deteriorates the match), while other components stay roughly the same. Finally, it is shown that in particular events, improved fire emission estimates may significantly improve the ability of the model to simulate the aerosol optical depth. We stress that discrepancies in aerosol models can be adequately analysed if all models would provide (regional) aerosol budgets, as presented in the current study.

Estimating long-term PM2.5 concentrations in China using satellite-based aerosol optical depth and a chemical transport model

2015 ◽  
Vol 166 ◽  
pp. 262-270 ◽  
Author(s):  
Guannan Geng ◽  
Qiang Zhang ◽  
Randall V. Martin ◽  
Aaron van Donkelaar ◽  
Hong Huo ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model

scholarly journals Up/Down trend in the MODIS Aerosol Optical Depth and its relationship to the Sulfur Dioxide Emission Changes in China during 2000 and 2010

2011 ◽  
Vol 11 (8) ◽  
pp. 21971-21993 ◽  
Author(s):  
S. Itahashi ◽  
I. Uno ◽  
K. Yumimoto ◽  
H. Irie ◽  
K. Osada ◽  
...  
Keyword(s):  
East Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Power Plants ◽  
Transport Model ◽  
Chemical Transport ◽  
Chinese Government ◽  
Chemical Transport Model ◽  
So2 Emissions ◽  
So2 Emission

Abstract. Anthropogenic SO2 emissions increased alongside economic development in China at a rate of 12.7 % yr−1 from 2000 to 2005. However, under new Chinese government policy, SO2 emissions declined by 3.9 % yr−1 between 2005 and 2009. Between 2000 and 2010, we found that the variability in the fine-mode (submicron) aerosol optical depth (AOD) over the oceans adjacent to East Asia increased by 4–8 % yr−1 to a peak around 2005–2006 and subsequently decreased by 4–7 % yr−1, based on observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Terra satellite and simulations by a chemical transport model. This trend is consistent with ground-based observations of the number-size distribution of aerosol particles at a mountainous background observation site in central Japan. These fluctuations in SO2 emission intensity and AOD are thought to reflect the widespread installation of fuel-gas desulfurization (FGD) devices in power plants in China because aerosol sulfate is a major determinant of the AOD in East Asia. Using a chemical transport model, we confirmed that the above-mentioned fluctuation in AOD is mainly caused by changes in SO2 emission rather than by varying meteorological conditions in East Asia. High correlation was also found between satellite-retrieved SO2 vertical column density and bottom-up SO2 emissions, both of which were also consistent with observed AOD trends. We proposed a simplified approach for evaluating changes in SO2 emissions in China, combining the use of modeled sensitivity coefficients that describe the variation of AOD with changes in SO2 emissions and satellite retrieval. Satellite measurements of the AOD above Sea of Japan marked the 4.1 % yr−1 declining between 2007 and 2010, and this correspond to the SO2 emissions from China decreased by ~9 % yr−1 between the same period.

scholarly journals Interannual variation in the fine-mode MODIS aerosol optical depth and its relationship to the changes in sulfur dioxide emissions in China between 2000 and 2010

2012 ◽  
Vol 12 (5) ◽  
pp. 2631-2640 ◽  
Author(s):  
S. Itahashi ◽  
I. Uno ◽  
K. Yumimoto ◽  
H. Irie ◽  
K. Osada ◽  
...  
Keyword(s):  
East Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Chemical Transport ◽  
Chinese Government ◽  
Chemical Transport Model ◽  
So2 Emissions ◽  
So2 Emission ◽  
Fine Mode

Abstract. Anthropogenic SO2 emissions increased alongside economic development in China at a rate of 12.7% yr−1 from 2000 to 2005. However, under new Chinese government policy, SO2 emissions declined by 3.9% yr−1 between 2005 and 2009. Between 2000 and 2010, we found that the variability in the fine-mode (submicron) aerosol optical depth (AOD) over the oceans adjacent to East Asia increased by 3–8% yr−1 to a peak around 2005–2006 and subsequently decreased by 2–7% yr−1, based on observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Terra satellite and simulations by a chemical transport model. This trend is consistent with ground-based observations of aerosol particles at a mountainous background observation site in central Japan. These fluctuations in SO2 emission intensity and fine-mode AOD are thought to reflect the widespread installation of fuel-gas desulfurization (FGD) devices in power plants in China, because aerosol sulfate is a major determinant of the fine-mode AOD in East Asia. Using a chemical transport model, we confirmed that the contribution of particulate sulfate to the fine-mode AOD is more than 70% of the annual mean and that the abovementioned fluctuation in fine-mode AOD is caused mainly by changes in SO2 emission rather than by other factors such as varying meteorological conditions in East Asia. A strong correlation was also found between satellite-retrieved SO2 vertical column density and bottom-up SO2 emissions, both of which were also consistent with observed fine-mode AOD trends. We propose a simplified approach for evaluating changes in SO2 emissions in China, combining the use of modeled sensitivity coefficients that describe the variation of fine-mode AOD with changes in SO2 emissions and satellite retrieval. Satellite measurements of fine-mode AOD above the Sea of Japan marked a 4.1% yr−1 decline between 2007 and 2010, which corresponded to the 9% yr−1 decline in SO2 emissions from China during the same period.

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