scholarly journals Case-Crossover Spatial Lag Grid Differences Between Aerosol Optical Depth-PM2.5 and Respiratory-Cardiovascular Emergency Department Visits and Inpatient Hospitalizations in Baltimore, Maryland, USA: Identification of Homogeneous Spatial Areas

2022 ◽  
Author(s):  
John T. Braggio ◽  
Eric S. Hall ◽  
Stephanie A. Weber ◽  
Amy K Huff
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Rural Areas ◽  
Warm Season ◽  
Spatial Dimension ◽  
Cold Season ◽  
Epidemiologic Studies ◽  
Emergency Department Visits ◽  
Case Crossover ◽  
Spatial Area

Optimal use of aerosol optical depth (AOD)-PM2.5 fused surfaces in epidemiologic studies requires homogeneous temporal and spatial fused surfaces. No analytic method is currently available to evaluate the spatial dimension. The temporal case-crossover design was modified to assess the association between Community Multiscale Air Quality (CMAQ) lag grids and four respiratory-cardiovascular hospital events. The maximum number of adjacent lag grids with the expo-sure-health outcome association determined the size of the homogeneous spatial area. The largest homogeneous spatial area included 5 grids (720 km2) and the smallest 2 grids (288 km2). PMC and PMCK analyses of ED asthma, IP asthma, IP MI, and IP HF were significantly higher in rural grids without air monitors than in urban with air monitors at lag grids 0, 1, and 01. Grids without air monitors had higher AOD-PM2.5 concentration levels, poverty percent, population density, and environmental hazards than grids with air monitors. ED asthma, IP MI, and HF PMCK ORs were significantly higher during the warm season than during the cold season at lag grids 0, 1, 01, and 04. The possibility of elevated fine PM and other demographic and environmental risk factors contributing to elevated respiratory-cardiovascular diseases in persons residing in rural areas was discussed.

scholarly journals Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 209
Author(s):  
John T. Braggio ◽  
Eric S. Hall ◽  
Stephanie A. Weber ◽  
Amy K. Huff
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Rural Areas ◽  
Conditional Logistic Regression ◽  
Fine Particulate Matter ◽  
Warm Season ◽  
Ambient Air ◽  
Cold Season ◽  
Model Predictions ◽  
Pm2.5 Concentration

The fine particulate matter baseline (PMB), which includes PM2.5 monitor readings fused with Community Multiscale Air Quality (CMAQ) model predictions, using the Hierarchical Bayesian Model (HBM), is less accurate in rural areas without monitors. To address this issue, an upgraded HBM was used to form four experimental aerosol optical depth (AOD)-PM2.5 concentration surfaces. A case-crossover design and conditional logistic regression evaluated the contribution of the AOD-PM2.5 surfaces and PMB to four respiratory-cardiovascular hospital events in all 99 12 km2 CMAQ grids, and in grids with and without ambient air monitors. For all four health outcomes, only two AOD-PM2.5 surfaces, one not kriged (PMC) and the other kriged (PMCK), had significantly higher Odds Ratios (ORs) on lag days 0, 1, and 01 than PMB in all grids, and in grids without monitors. In grids with monitors, emergency department (ED) asthma PMCK on lag days 0, 1 and 01 and inpatient (IP) heart failure (HF) PMCK ORs on lag days 01 were significantly higher than PMB ORs. Warm season ORs were significantly higher than cold season ORs. Independent confirmation of these results should include AOD-PM2.5 concentration surfaces with greater temporal-spatial resolution, now easily available from geostationary satellites, such as GOES-16 and GOES-17.

scholarly journals Retrieving High-Resolution Aerosol Optical Depth from GF-4 PMS Imagery in Eastern China

2021 ◽  
Vol 13 (18) ◽  
pp. 3752
Author(s):  
Zhendong Sun ◽  
Jing Wei ◽  
Ning Zhang ◽  
Yulong He ◽  
Yu Sun ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Zenith Angle ◽  
Rural Areas ◽  
Urban Areas ◽  
Eastern China ◽  
Practical Significance ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Surface Reflectance

Gaofen 4 (GF-4) is a geostationary satellite, with a panchromatic and multispectral sensor (PMS) onboard, and has great potential in observing atmospheric aerosols. In this study, we developed an aerosol optical depth (AOD) retrieval algorithm for the GF-4 satellite. AOD retrieval was realized based on the pre-calculated surface reflectance database and 6S radiative transfer model. We customized the unique aerosol type according to the long time series aerosol parameters provided by the Aerosol Robotic Network (AERONET) site. The solar zenith angle, relative azimuth angle, and satellite zenith angle of the GF-4 panchromatic multispectral sensor image were calculated pixel-by-pixel. Our 1 km AOD retrievals were validated against AERONET Version 3 measurements and compared with MOD04 C6 AOD products at different resolutions. The results showed that our GF-4 AOD algorithm had a good robustness in both bright urban areas and dark rural areas. A total of 71.33% of the AOD retrievals fell within the expected errors of ±(0.05% + 20%); root-mean-square error (RMSE) and mean absolute error (MAE) were 0.922 and 0.122, respectively. The accuracy of GF-4 AOD in rural areas was slightly higher than that in urban areas. In comparison with MOD04 products, the accuracy of GF-4 AOD was much higher than that of MOD04 3 km and 10 km dark target AOD, but slightly worse than that of MOD04 10 km deep blue AOD. For different values of land surface reflectance (LSR), the accuracy of GF-4 AOD gradually deteriorated with an increase in the LSR. These results have theoretical and practical significance for aerosol research and can improve retrieval algorithms using the GF-4 satellite.

Nighttime smoke aerosol optical depth over U.S. rural areas: First retrieval from VIIRS moonlight observations

2021 ◽  
Vol 267 ◽  
pp. 112717
Author(s):  
Meng Zhou ◽  
Jun Wang ◽  
Xi Chen ◽  
Xiaoguang Xu ◽  
Peter R. Colarco ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Rural Areas ◽  
Smoke Aerosol

scholarly journals Biomass burning aerosol properties over the Northern Great Plains during the 2012 warm season

2013 ◽  
Vol 13 (12) ◽  
pp. 32269-32289
Author(s):  
T. Logan ◽  
B. Xi ◽  
X. Dong
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Great Plains ◽  
Biomass Burning ◽  
Chemical Properties ◽  
Warm Season ◽  
Northern Great Plains ◽  
Aerosol Composition ◽  
Coarse Mode ◽  
Smoke Plumes

Abstract. Biomass burning aerosols can have a large impact on atmospheric processes as well as human health. During the 2012 warm season, a large outbreak of wildfires originating from the intermountain and Pacific states provided many opportunities to observe the physical and chemical properties of biomass smoke aerosols. Six biomass burning smoke plumes (26 June–15 September) have been observed by the newly installed Grand Forks, North Dakota, AERONET site (47.91° N, 97.32° W) and are selected for this study. To identify the source regions, HYSPLIT backward trajectory model data and satellite imagery are used to track these events. The volume size distribution and spectral aerosol optical depth (AOD) dependence showed the relative influences of fine and coarse mode particles. Case II (4 July) had the strongest fine mode influence as evidenced by a strong spectral AOD dependence while Case VI (15 September) had the strongest coarse mode influence with the weakest spectral dependence. The spectral dependences of absorption aerosol optical depth (AAOD) and single scattering co-albedo (ωoabs) illustrated the varying absorption of the smoke plumes by inferring the relative contributions of strongly and weakly absorbing carbonaceous species. More specifically, the AAOD parameter is primarily influenced by aerosol particle size while ωoabs is more dependent on aerosol composition. The AAOD spectral dependences for Cases I (26 June), III (31 July), and VI were weaker than those from Cases II, IV (28 August), and V (30 August). However, the spectral ωoabs dependences were different in that the smoke particles in Cases III and VI had the strongest absorption while Cases I, II, IV, and V had moderate to weakly absorbing particles. In addition, a weak correlation was found between plume transport time and particle absorption where strongly absorbing carbon was converted to weakly absorbing carbon.

scholarly journals Association between air pollution and case-specific mortality in north-eastern part of Poland. Case crossover study with 4,500,000 person-years of follow-up

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
L Kuzma ◽  
A Kurasz ◽  
E J Dabrowski ◽  
M Swieczkowski ◽  
S Dobrzycki ◽  
...  
Keyword(s):  
Air Pollution ◽  
Warm Season ◽  
Cold Season ◽  
Funding Sources ◽  
Case Crossover ◽  
North Eastern ◽  
The Impact ◽  
Related Mortality ◽  
Cvd Mortality

Abstract Background Recent studies have reported associations between air pollution and daily mortality. The majority of them are conducted in highly polluted areas. Taking into consideration the scarce number of surveys from cities with moderate air quality we decided to conduct a study in this type of region. Purpose To assess the short-term impact of air pollution on cardiovascular (CVD), coronary artery-related (CAD), and cerebrovascular-related (CbVD) mortality. Methods The analysis with almost 4,500,000 person-years of follow-up with a time-stratified case-crossover design was performed. Results are reported as odds ratio (OR) associated with an increase in interquartile range (IQR). Results The analysed region was inhabited by almost 500,000 residents. From 2008 to 2017 in Bialystok, Lomza, and Suwalki we recorded 49,573 deaths – 34,005, 8,082, 7,486, respectively. The median daily concentrations of PM10 (23.8 μg/m3, IQR=16.9) was the highest in Lomza, Median daily concentration of PM2.5 was the highest in Bialystok (16.2 μg/m3, IQR=15.9). In the case of Suwalki, daily median PM2.5 concentration was 9.8 μg/m3 (IQR=8.7), and PM10 – 18.0 μg/m3 (IQR=14.3). The IQR increase in PM2.5 (OR 1.036, 95% CI 1.016–1.056, P<0.001) and PM10 concentration (OR 1.034, 95% CI 1.015–1.053, P<0.001) was associated with increased CVD mortality on lag 0 and this effect persisted on following days. The effects of PMs were more expressed in association with CAD-related mortality (OR for PM2.5 = 1.045, 95% CI 1.012–1.080, P=0.008), (OR for PM10 = 1.044, 95% CI 1.010–1.078, P=0.011) and CbVD mortality (OR for PM2.5 = 1.046, 95% CI 1.013–1.080, P=0.006), (OR=1.041 for PM10, 95% CI 1.002–1.082, P=0.038). Additionally, IQR increase in NO2 concentration was associated with increased CAD-related mortality at lag 0–1 (OR=1.055, 95% CI 1.004–1.108, P=0.032). The highest OR for PMs was noted in Suwalki compared to Bialystok and Lomza. The trend was noted regardless of the cause of death from lag 0 to lag 0–3. In a comparison of seasons, we noted higher CVD mortality OR in the cold season for PM10 in Suwalki (P=0.047) and Bialystok (p=0.001). However, the impact of NO2 (P=0.02) and PM10 (P=0.03) on CAD related mortality was higher in the warm season. Conclusions The impact of air pollution on CVD mortality is also observed in moderately polluted areas. PMs and NO2 had the greatest impact on CAD-related mortality. Differences in effect size and seasonality may depend on the source of air pollution. FUNDunding Acknowledgement Type of funding sources: None.

scholarly journals WRF-Chem simulation of aerosol seasonal variability in the San Joaquin Valley

2016 ◽  
Author(s):  
Longtao Wu ◽  
Hui Su ◽  
Olga V. Kalashnikova ◽  
Jonathan H. Jiang ◽  
Chun Zhao ◽  
...  
Keyword(s):  
Rural Areas ◽  
Seasonal Variability ◽  
Urban Areas ◽  
Transport Model ◽  
Vertical Mixing ◽  
Dust Emission ◽  
Warm Season ◽  
Cold Season ◽  
San Joaquin Valley ◽  
Fire Emissions

Abstract. WRF-Chem simulations of aerosol seasonal variability in the San Joaquin Valley (SJV), California are evaluated by satellite and in-situ observations. Results show that the WRF-Chem model successfully captures the distribution, magnitude and variation of SJV aerosols in cold season. However, the aerosols are not well represented in warm season. Aerosol simulations in urban areas during the cold season are sensitive to model horizontal resolution, with better simulations at 4 km resolution than at 20 km resolution, mainly due to inhomogeneous distribution of anthropogenic emissions. In rural areas, the model sensitivity to grid size is rather small. Our observational analysis show that dust is a primary contributor to aerosols in the SJV, especially in the warm season. Aerosol simulations in the warm season are sensitive to parameterization of dust emission in the WRF-Chem model. The GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) dust scheme produces very little dust in the SJV while the DUSTRAN (DUST TRANsport model) scheme overestimates dust emission. Vertical mixing of aerosols is not adequately represented in the model comparing to CALIPSO (Cloud-Aerosol Lidar and Infrared pathfinder Satellite Observation) aerosol extinction profiles. Improved representation of dust emission and vertical mixing are needed for better simulations of aerosols in warm season in the SJV. Aerosols generated by wild fires are not captured in the simulations with climatological fire emissions, underscoring the need of fire emission observations for operational usage.

scholarly journals Retrieval of Aerosol Optical Depth Using Satellite Data Associated with Ground-based Observations over Urban and Rural Areas

2019 ◽  
Vol 18 (32) ◽  
pp. 4-17
Author(s):  
Le Thi Le ◽  
Lin Tang-Huang ◽  
Canh Van Le ◽  
Lan Thi Pham ◽  
Ha Thi Thu Le ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Rural Areas ◽  
Urban Areas ◽  
Spatial Information ◽  
Satellite Image ◽  
Spatial Coverage ◽  
Modis Aod ◽  
Sun Photometer ◽  
Urban And Rural Areas

Aerosol optical depth (AOD) can be retrieved accurately with sequential ground-based measurements of direct and diffuse solar radiance. However, spatial coverage and location frequency cause certain limitations. Hence, satellite image data are a proper tool for obtaining aerosol optical depth products with more spatial information and patterns of aerosol distribution. Currently, aerosol remote sensing may enhance our understanding of the optimal approach to AOD retrieval over urban and rural areas, and how it differs due to the characteristics of surface reflectivity. The article deals with the concepts of contrast reduction, and dark target approaches are examined using Landsat imaging and the observation of a sun photometer for integrating aerosol optical depth distribution over the city of Taipei in Taiwan. For areas with bright surfaces, such as urban areas, the above concepts were applied using the dispersion coefficient method with a sun photometer, in order to reduce errors considerably in the product. In contrast, a dark target algorithm with a relationship of surface reflectance between the blue (0.49 μm), red (0.66 μm), and infrared (2.1 μm) spectral bands is suitable for moist soils and vegetation areas. The retrieval of AOD spatial distribution is compared with MODIS AOD products and AERONET to verify the accuracy of the results. The RMSE ranged from 0.2 to 0.4, and about 50% of the data were within expected error margins (EE=± (0.05+0.15 AODsunphotometer).

scholarly journals WRF-Chem simulation of aerosol seasonal variability in the San Joaquin Valley

2017 ◽  
Vol 17 (12) ◽  
pp. 7291-7309 ◽  
Author(s):  
Longtao Wu ◽  
Hui Su ◽  
Olga V. Kalashnikova ◽  
Jonathan H. Jiang ◽  
Chun Zhao ◽  
...  
Keyword(s):  
Rural Areas ◽  
Seasonal Variability ◽  
Urban Areas ◽  
Transport Model ◽  
Vertical Mixing ◽  
Dust Emission ◽  
Warm Season ◽  
Cold Season ◽  
Horizontal Resolution ◽  
San Joaquin Valley

Abstract. WRF-Chem simulations of aerosol seasonal variability in the San Joaquin Valley (SJV), California, are evaluated by satellite and in situ observations. Results show that the WRF-Chem model successfully captures the distribution and magnitude of and variation in SJV aerosols during the cold season. However, aerosols are not well represented in the warm season. Aerosol simulations in urban areas during the cold season are sensitive to model horizontal resolution, with better simulations at 4 km resolution than at 20 km resolution, mainly due to inhomogeneous distribution of anthropogenic emissions and precipitation that is represented better in the 4 km simulation. In rural areas, the model sensitivity to grid size is rather small. Our observational analysis reveals that dust is a primary contributor to aerosols in the SJV, especially during the warm season. Aerosol simulations in the warm season are sensitive to the parameterization of dust emission in WRF-Chem. The GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) dust scheme produces very little dust in the SJV, while the DUSTRAN (DUST TRANsport model) scheme overestimates dust emission. Vertical mixing of aerosols is not adequately represented in the model based on CALIPSO (Cloud-Aerosol Lidar and Infrared pathfinder Satellite Observation) aerosol extinction profiles. Improved representation of dust emission and vertical mixing in the boundary layer is needed for better simulations of aerosols during the warm season in the SJV.

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