Using Chemical Transport Model Predictions To Improve Exposure Assessment of PM2.5 Constituents

2019 ◽  
Vol 6 (8) ◽  
pp. 456-461 ◽  
Author(s):  
Jianlin Hu ◽  
Bart Ostro ◽  
Hongliang Zhang ◽  
Qi Ying ◽  
Michael J. Kleeman
2012 ◽  
Vol 12 (2) ◽  
pp. 5939-6018
Author(s):  
C. A. Stroud ◽  
M. D. Moran ◽  
P. A. Makar ◽  
S. Gong ◽  
W. Gong ◽  
...  

Abstract. Observations from the 2007 Border Air Quality and Meteorology Study (BAQS-Met 2007) in southern Ontario (ON), Canada, were used to evaluate Environment Canada's regional chemical transport model predictions of primary organic aerosol (POA). Environment Canada's operational numerical weather prediction model and the 2006 Canadian and 2005 US national emissions inventories were used as input to the chemical transport model (named AURAMS). Particle-component-based factor analysis was applied to aerosol mass spectrometer measurements made at one urban site (Windsor, ON) and two rural sites (Harrow and Bear Creek, ON) to derive hydrocarbon-like organic aerosol (HOA) factors. Co-located carbon monoxide (CO), PM2.5 black carbon (BC), and PM1 SO4 measurements were also used for evaluation and interpretation, permitting a detailed diagnostic model evaluation. At the urban site, good agreement was observed for the comparison of daytime campaign PM1 POA and HOA mean values: 1.1 μg m−3 vs. 1.2 μg m−3, respectively. However, a POA overprediction was evident on calm nights due to an overly-stable model surface layer. Biases in model POA predictions trended from positive to negative with increasing HOA values. This trend has several possible explanations, including (1) underweighting of urban locations in particulate matter (PM) spatial surrogate fields, (2) overly-coarse model grid spacing for resolving urban-scale sources, and (3) lack of a model particle POA evaporation process during dilution of vehicular POA tail-pipe emissions to urban scales. Furthermore, a trend in POA bias was observed at the urban site as a function of the BC/HOA ratio, suggesting a possible association of POA underprediction for diesel combustion sources. For several time periods, POA overprediction was also observed for sulphate-rich plumes, suggesting that our model POA fractions for the PM2.5 chemical speciation profiles may be too high for these point sources. At the rural Harrow site, significant underpredictions in PM1 POA concentration were found compared to observed HOA concentration and were associated, based on back-trajectory analysis, with (1) transport from the Detroit/Windsor urban complex, (2) longer-range transport from the US Midwest, and (3) biomass burning. Daytime CO concentrations were significantly overpredicted at Windsor but were unbiased at Harrow. Collectively, these biases provide support for a hypothesis that combines a current underweighting of PM spatial surrogate fields for urban locations with insufficient model vertical mixing for sources close to the urban measurement sites. The magnitude of the area POA emissions sources in the US and Canadian inventories (e.g., food cooking, road and soil dust, waste disposal burning) suggests that more effort should be placed at reducing uncertainties in these sectors, especially spatial and temporal surrogates.


1999 ◽  
Vol 104 (D9) ◽  
pp. 11755-11781 ◽  
Author(s):  
Eugene V. Rozanov ◽  
Vladimir A. Zubov ◽  
Michael E. Schlesinger ◽  
Fanglin Yang ◽  
Natalia G. Andronova

2012 ◽  
Vol 12 (15) ◽  
pp. 7073-7085 ◽  
Author(s):  
J. Kuttippurath ◽  
S. Godin-Beekmann ◽  
F. Lefèvre ◽  
G. Nikulin ◽  
M. L. Santee ◽  
...  

Abstract. We present a detailed discussion of the chemical and dynamical processes in the Arctic winters 1996/1997 and 2010/2011 with high resolution chemical transport model (CTM) simulations and space-based observations. In the Arctic winter 2010/2011, the lower stratospheric minimum temperatures were below 195 K for a record period of time, from December to mid-April, and a strong and stable vortex was present during that period. Simulations with the Mimosa-Chim CTM show that the chemical ozone loss started in early January and progressed slowly to 1 ppmv (parts per million by volume) by late February. The loss intensified by early March and reached a record maximum of ~2.4 ppmv in the late March–early April period over a broad altitude range of 450–550 K. This coincides with elevated ozone loss rates of 2–4 ppbv sh−1 (parts per billion by volume/sunlit hour) and a contribution of about 30–55% and 30–35% from the ClO-ClO and ClO-BrO cycles, respectively, in late February and March. In addition, a contribution of 30–50% from the HOx cycle is also estimated in April. We also estimate a loss of about 0.7–1.2 ppmv contributed (75%) by the NOx cycle at 550–700 K. The ozone loss estimated in the partial column range of 350–550 K exhibits a record value of ~148 DU (Dobson Unit). This is the largest ozone loss ever estimated in the Arctic and is consistent with the remarkable chlorine activation and strong denitrification (40–50%) during the winter, as the modeled ClO shows ~1.8 ppbv in early January and ~1 ppbv in March at 450–550 K. These model results are in excellent agreement with those found from the Aura Microwave Limb Sounder observations. Our analyses also show that the ozone loss in 2010/2011 is close to that found in some Antarctic winters, for the first time in the observed history. Though the winter 1996/1997 was also very cold in March–April, the temperatures were higher in December–February, and, therefore, chlorine activation was moderate and ozone loss was average with about 1.2 ppmv at 475–550 K or 42 DU at 350–550 K, as diagnosed from the model simulations and measurements.


2016 ◽  
Vol 9 (8) ◽  
pp. 2741-2754 ◽  
Author(s):  
Elham Baranizadeh ◽  
Benjamin N. Murphy ◽  
Jan Julin ◽  
Saeed Falahat ◽  
Carly L. Reddington ◽  
...  

Abstract. The particle formation scheme within PMCAMx-UF, a three-dimensional chemical transport model, was updated with particle formation rates for the ternary H2SO4–NH3–H2O pathway simulated by the Atmospheric Cluster Dynamics Code (ACDC) using quantum chemical input data. The model was applied over Europe for May 2008, during which the EUCAARI-LONGREX (European Aerosol Cloud Climate and Air Quality Interactions–Long-Range Experiment) campaign was carried out, providing aircraft vertical profiles of aerosol number concentrations. The updated model reproduces the observed number concentrations of particles larger than 4 nm within 1 order of magnitude throughout the atmospheric column. This agreement is encouraging considering the fact that no semi-empirical fitting was needed to obtain realistic particle formation rates. The cloud adjustment scheme for modifying the photolysis rate profiles within PMCAMx-UF was also updated with the TUV (Tropospheric Ultraviolet and Visible) radiative-transfer model. Results show that, although the effect of the new cloud adjustment scheme on total number concentrations is small, enhanced new-particle formation is predicted near cloudy regions. This is due to the enhanced radiation above and in the vicinity of the clouds, which in turn leads to higher production of sulfuric acid. The sensitivity of the results to including emissions from natural sources is also discussed.


2017 ◽  
Author(s):  
Peter M. Edwards ◽  
Mathew J. Evans

Abstract. Tropospheric ozone is important for the Earth’s climate and air quality. It is produced during the oxidation of organics in the presence of nitrogen oxides. Due to the range of organic species emitted and the chain like nature of their oxidation, this chemistry is complex and understanding the role of different processes (emission, deposition, chemistry) is difficult. We demonstrate a new methodology for diagnosing ozone production based on the processing of bonds contained within emitted molecules, the fate of which is determined by the conservation of spin of the bonding electrons. Using this methodology to diagnose ozone production in the GEOS-Chem chemical transport model, we demonstrate its advantages over the standard diagnostic. We show that the number of bonds emitted, their chemistry and lifetime, and feedbacks on OH are all important in determining the ozone production within the model and its sensitivity to changes. This insight may allow future model-model comparisons to better identify the root causes of model differences.


2020 ◽  
Vol 4 (2) ◽  
pp. 321-327 ◽  
Author(s):  
Amit Sharma ◽  
Narendra Ojha ◽  
Tabish U. Ansari ◽  
Som K. Sharma ◽  
Andrea Pozzer ◽  
...  

2011 ◽  
Vol 11 (24) ◽  
pp. 12773-12786 ◽  
Author(s):  
S. Dhomse ◽  
M. P. Chipperfield ◽  
W. Feng ◽  
J. D. Haigh

Abstract. We have used an off-line 3-D chemical transport model (CTM) to investigate the 11-yr solar cycle response in tropical stratospheric ozone. The model is forced with European Centre for Medium-Range Weather Forecasts (ECMWF) (re)analysis (ERA-40/operational and ERA-Interim) data for the 1979–2005 time period. We have compared the modelled solar response in ozone to observation-based data sets that are constructed using satellite instruments such as Total Ozone Mapping Spectrometer (TOMS), Solar Backscatter UltraViolet instrument (SBUV), Stratospheric Aerosol and Gas Experiment (SAGE) and Halogen Occultation Experiment (HALOE). A significant difference is seen between simulated and observed ozone during the 1980s, which is probably due to inhomogeneities in the ERA-40 reanalyses. In general, the model with ERA-Interim dynamics shows better agreement with the observations from 1990 onwards than with ERA-40. Overall both standard model simulations are partially able to simulate a "double peak"-structured ozone solar response with a minimum around 30 km, and these are in better agreement with HALOE than SAGE-corrected SBUV (SBUV/SAGE) or SAGE-based data sets. In the tropical lower stratosphere (TLS), the modelled solar response with time-varying aerosols is amplified through aliasing with a volcanic signal, as the model overestimates ozone loss during high aerosol loading years. However, the modelled solar response with fixed dynamics and constant aerosols shows a positive signal which is in better agreement with SBUV/SAGE and SAGE-based data sets in the TLS. Our model simulations suggests that photochemistry contributes to the ozone solar response in this region. The largest model-observation differences occur in the upper stratosphere where SBUV/SAGE and SAGE-based data show a significant (up to 4%) solar response whereas the standard model and HALOE do not. This is partly due to a positive solar response in the ECMWF upper stratospheric temperatures which reduces the modelled ozone signal. The large positive upper stratospheric solar response seen in SBUV/SAGE and SAGE-based data can be reproduced in model runs with fixed dynamical fields (i.e. no inter-annual meteorological changes). As these runs effectively assume no long-term temperature changes (solar-induced or otherwise), it should provide an upper limit of the ozone solar response. Overall, full quantification of the solar response in stratospheric ozone is limited by differences in the observed data sets and by uncertainties in the solar response in stratospheric temperatures.


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