scholarly journals The Potential Ozone Impacts of Landfills

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 877
Author(s):  
Eduardo P. Olaguer
Keyword(s):  
Transport Model ◽  
Landfill Gas ◽  
The United States ◽  
Anthropogenic Source ◽  
Ozone Pollution ◽  
Chemical Transport Model ◽  
Gas Combustion ◽  
Ozone Precursors ◽  
Chemical Conditions ◽  
Ozone Precursor

Landfill gas produces ozone precursors such as nitrogen oxides and formaldehyde when combusted in flares or stationary engines. Solid waste landfills are also the third largest anthropogenic source of methane in the United States. Methane is both a greenhouse gas and a tropospheric ozone precursor. Despite its low photochemical reactivity, methane may noticeably affect urban ozone if released in large quantities along with other organic compounds in landfill gas. A fine-scale 3D Eulerian chemical transport model was used to demonstrate that, under meteorological and background chemical conditions conducive to high ozone concentrations, typical emissions of ozone precursors from a single hypothetical landfill may result in persistent daytime additions to ozone of over 1 part per billion (ppb) by volume tens of kilometers downwind. Large leaks of landfill gas can enhance this ozone pollution by over a tenth of a ppb, and external sources of non-methane ozone precursors may further exacerbate this impact. In addition, landfill gas combustion may increase near-source exposure to toxic formaldehyde by well over half a ppb. In Southeast Michigan, the combined influence of several landfills upwind of key monitoring sites may contribute significantly to observed exceedances of the U.S. ozone standard.

scholarly journals Can a global model reproduce observed trends in summertime surface ozone levels?

2012 ◽  
Vol 12 (1) ◽  
pp. 2025-2056 ◽  
Author(s):  
S. Koumoutsaris ◽  
I. Bey
Keyword(s):  
Transport Model ◽  
Control Strategies ◽  
Surface Ozone ◽  
The United States ◽  
Daily Maximum ◽  
Chemical Transport Model ◽  
Ozone Precursors ◽  
Ozone Concentrations ◽  
Western Us ◽  
Ozone Trends

Abstract. Quantifying trends in surface ozone concentrations are critical for assessing pollution control strategies. Here we use observations and results from a global chemical transport model to examine the trends (1991–2005) in daily maximum 8-hour average concentrations in summertime surface ozone at rural sites in Europe and the United States. We find a decrease in observed ozone concentrations at the high end of the probability distribution at many of the sites in both regions. The model attributes these trends to a decrease in local anthropogenic ozone precursors, although simulated decreasing trends are overestimated in comparison with observed ones. The low end of observed distribution show small upward trends over Europe and the western US and downward trends in Eastern US. The model cannot reproduce these observed trends, especially over Europe and the western US. In particular, simulated changes between the low and high end of the distributions in these two regions are not significant. Sensitivity simulations indicate that emissions from far away source regions do not affect significantly ozone trends at both ends of the distribution. This is in contrast with previously available results, which indicated that increasing ozone trends at the low percentiles may reflect an increase in ozone background associated with increasing remote sources of ozone precursors. Possible reasons for discrepancies between observed and simulated trends are discussed.

scholarly journals Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change

2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Multiple Linear Regression Model ◽  
The United States ◽  
Chemical Transport Model ◽  
Modes Of Variability ◽  
The Us ◽  
Cyclone Frequency

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

scholarly journals The Canadian atmospheric transport model for simulating greenhouse gas evolution on regional scales: GEM-MACH-GHG v.137-reg

2019 ◽  
Author(s):  
Jinwoong Kim ◽  
Saroja Polavarapu ◽  
Douglas Chan ◽  
Michael Neish
Keyword(s):  
Greenhouse Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Forecast Error ◽  
Regional Scale ◽  
The United States ◽  
Regional Model ◽  
Boreal Summer ◽  
Chemical Transport Model ◽  
Atmospheric Transport Model

Abstract. In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high spatio-temporal resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km × 10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations, based on comparisons to surface and aircraft observations. In addition, reduced bias and standard deviation of forecast error in boreal summer are obtained by the regional model. Better representation of model topography in the regional model reduces transport and representation errors significantly compared to the global model, especially in regions of complex topography, as revealed by the more precise and detailed structure of the CO2 diurnal cycle produced at observation sites and in model space. The new regional model will form the basis of a flux inversion system that estimates regional scale fluxes of GHGs over Canada.

scholarly journals Potential of multispectral synergism for observing ozone pollution by combining IASI-NG and UVNS measurements from EPS-SG satellite

2016 ◽  
Author(s):  
Lorenzo Costantino ◽  
Juan Cuesta ◽  
Emanuele Emili ◽  
Adriana Coman ◽  
Gilles Foret ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Transport Model ◽  
Lower Troposphere ◽  
Real Data ◽  
Satellite Observations ◽  
Maximum Sensitivity ◽  
Ozone Pollution ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Multispectral Method

Abstract. Present and future satellite observations offer a great potential for monitoring air quality on daily and global basis. However, measurements from currently in orbit satellites do not allow using a single sensor to probe accurately surface concentrations of gaseous pollutants such as tropospheric ozone (Liu et al., 2010). Using single-band approaches based on spaceborne measurements of either thermal infrared radiance (TIR, Eremenko et al., 2008) or ultraviolet reflectance (UV, Liu et al., 2010) only ozone down to the lower troposphere (3 km) may be observed. A recent multispectral method (referred to as IASI+GOME-2) combining the information of IASI and GOME-2 (both onboard MetOp satellites) spectra, respectively from the TIR and UV, has shown enhanced sensitivity for probing ozone at the lowermost troposphere (LMT, below 3 km of altitude) with maximum sensitivity down to 2.20 km a.s.l. over land, while sensitivity for IASI or GOME-2 only peaks at 3 to 4 km at lowest (Cuesta et al., 2013). Future spatial missions will be launched in the upcoming years, such as EPS-SG, carrying new-generation sensors of IASI and GOME-2 (respectively IASI-NG and UVNS) that will enhance the capacity to observe ozone pollution and particularly by synergism of TIR and UV measurements. In this work we develop a pseudo-observation simulator and evaluate the potential of future EPS-SG satellite observations through IASI-NG+UVNS multispectral method to observer near-surface O3. The pseudo-real state of atmosphere (nature run) is provided by the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Échelle) chemical transport model. Simulations are calibrated by careful comparisons with real data, to ensure the best consistency between pseudo-reality and reality, as well as between the pseudo-observation simulator and existing satellite products. We perform full and accurate forward and inverse radiative transfer calculations for a period of 4 days (8–11 July 2010) over Europe. In the LMT, there is a remarkable agreement in the geographical distribution of O3 partial columns, calculated between the surface and 3 km of altitude, between IASI-NG+UVNS pseudo-observations and the corresponding MOCAGE pseudo-reality. With respect to synthetic IASI+GOME-2 products, IASI-NG+UVNS shows a higher correlation between pseudo-observations and pseudo-reality, enhanced by about 11 %. The bias on high ozone retrieval is reduced and the average accuracy increases by 22 %. The sensitivity to LMT ozone is enhanced on average with 154 % (from 0.29 to 0.75, over land) and 208 % (from 0.21 to 0.66, over ocean) higher degrees of freedom. The mean height of maximum sensitivity for the LMT peaks at 1.43 km over land and 2.02 km over ocean, respectively 1.03 km and 1.30 km below that of IASI+GOME-2. IASI-NG+UVNS shows also good retrieval skill in the surface-2 km altitude range with a mean DOF (degree of freedom) of 0.52 (land) and 0.42 (ocean), and an average Hmax (altitude of maximum sensitivity) of 1.29 km (land) and 1.96 km (ocean). Unique of its kind for retrieving ozone layers of 2–3 km thickness, in the first 2–3 km of the atmosphere, IASI-NG+UVNS is expected to largely enhance the capacity to observe ozone pollution from space.

scholarly journals Improving WRF-Chem meteorological analyses and forecasts over aerosol polluted regions by incorporating NAAPS aerosol analyses

2021 ◽  
Author(s):  
Brittany N. Carson-Marquis ◽  
Jianglong Zhang ◽  
Peng Xian ◽  
Jeffrey S. Reid ◽  
Jared Marquis
Keyword(s):  
Boundary Conditions ◽  
Surface Temperature ◽  
Great Plains ◽  
Transport Model ◽  
Weather Prediction ◽  
The United States ◽  
Northern Great Plains ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Initial And Boundary Conditions

AbstractWhen unaccounted for in numerical weather prediction (NWP) models, heavy aerosol events can cause significant unrealized biases in forecasted meteorological parameters such as surface temperature. To improve near-surface forecasting accuracies during heavy aerosol loadings, we demonstrate the feasibility of incorporating aerosol fields from a global chemical transport model as initial and boundary conditions into a higher resolution NWP model with aerosol-meteorological coupling. This concept is tested for a major biomass burning smoke event over the Northern Great Plains region of the United States that occurred during summer of 2015. Aerosol analyses from the global Navy Aerosol Analysis and Prediction System (NAAPS) are used as initial and boundary conditions for Weather Research and Forecasting with Chemistry (WRF-Chem) simulations. Through incorporating more realistic aerosol direct effects into the WRF-Chem simulations, errors in WRF-Chem simulated surface downward shortwave radiative fluxes and near-surface temperature are reduced compared with surface-based observations. This study confirms the ability to decrease biases induced by the aerosol direct effect for regional NWP forecasts during high-impact aerosol episodes through the incorporation of analyses and forecasts from a global aerosol transport model.

scholarly journals Interannual variability of ammonia concentrations over the United States: sources and implications

2016 ◽  
Vol 16 (18) ◽  
pp. 12305-12328 ◽  
Author(s):  
Luke D. Schiferl ◽  
Colette L. Heald ◽  
Martin Van Damme ◽  
Lieven Clarisse ◽  
Cathy Clerbaux ◽  
...  
Keyword(s):  
United States ◽  
Interannual Variability ◽  
Model Comparison ◽  
Transport Model ◽  
The United States ◽  
Ammonia Concentration ◽  
Phase Changes ◽  
Spatial And Temporal Variability ◽  
Ammonia Emissions ◽  
Chemical Transport Model

Abstract. The variability of atmospheric ammonia (NH3), emitted largely from agricultural sources, is an important factor when considering how inorganic fine particulate matter (PM2.5) concentrations and nitrogen cycling are changing over the United States. This study combines new observations of ammonia concentration from the surface, aboard aircraft, and retrieved by satellite to both evaluate the simulation of ammonia in a chemical transport model (GEOS-Chem) and identify which processes control the variability of these concentrations over a 5-year period (2008–2012). We find that the model generally underrepresents the ammonia concentration near large source regions (by 26 % at surface sites) and fails to reproduce the extent of interannual variability observed at the surface during the summer (JJA). Variability in the base simulation surface ammonia concentration is dominated by meteorology (64 %) as compared to reductions in SO2 and NOx emissions imposed by regulation (32 %) over this period. Introduction of year-to-year varying ammonia emissions based on animal population, fertilizer application, and meteorologically driven volatilization does not substantially improve the model comparison with observed ammonia concentrations, and these ammonia emissions changes have little effect on the simulated ammonia concentration variability compared to those caused by the variability of meteorology and acid-precursor emissions. There is also little effect on the PM2.5 concentration due to ammonia emissions variability in the summer when gas-phase changes are favored, but variability in wintertime emissions, as well as in early spring and late fall, will have a larger impact on PM2.5 formation. This work highlights the need for continued improvement in both satellite-based and in situ ammonia measurements to better constrain the magnitude and impacts of spatial and temporal variability in ammonia concentrations.

scholarly journals Can a global model reproduce observed trends in summertime surface ozone levels?

2012 ◽  
Vol 12 (15) ◽  
pp. 6983-6998 ◽  
Author(s):  
S. Koumoutsaris ◽  
I. Bey
Keyword(s):  
Transport Model ◽  
Control Strategies ◽  
Surface Ozone ◽  
The United States ◽  
Daily Maximum ◽  
Chemical Transport Model ◽  
Ozone Concentrations ◽  
Western Us ◽  
Ozone Trends ◽  
Rural Sites

Abstract. Quantifying trends in surface ozone concentrations is critical for assessing pollution control strategies. Here we use observations and results from a global chemical transport model to examine the trends (1991–2005) in daily maximum 8-h average concentrations in summertime surface ozone at rural sites in Europe and the United States (US). We find a decrease in observed ozone concentrations at the high end of the probability distribution at many of the sites in both regions. The model attributes these trends to a decrease in local anthropogenic ozone precursors, although simulated decreasing trends are overestimated in comparison with observed ones. The low end of observed distribution show small upward trends over Europe and the western US and downward trends in Eastern US. The model cannot reproduce these observed trends, especially over Europe and the western US. In particular, simulated changes between the low and high end of the distributions in these two regions are not significant. Sensitivity simulations indicate that emissions from far away source regions do not affect significantly summer ozone trends at both ends of the distribution in both Europe and US. Possible reasons for discrepancies between observed and simulated trends are discussed.

scholarly journals Sources of springtime surface black carbon in the Arctic: an adjoint analysis for April 2008

2017 ◽  
Vol 17 (15) ◽  
pp. 9697-9716 ◽  
Author(s):  
Ling Qi ◽  
Qinbin Li ◽  
Daven K. Henze ◽  
Hsien-Liang Tseng ◽  
Cenlin He
Keyword(s):  
Natural Gas ◽  
Black Carbon ◽  
Biomass Burning ◽  
Transport Model ◽  
Lower Troposphere ◽  
Anthropogenic Sources ◽  
The Arctic ◽  
Anthropogenic Source ◽  
Chemical Transport Model ◽  
Gas Flaring

Abstract. We quantify source contributions to springtime (April 2008) surface black carbon (BC) in the Arctic by interpreting surface observations of BC at five receptor sites (Denali, Barrow, Alert, Zeppelin, and Summit) using a global chemical transport model (GEOS-Chem) and its adjoint. Contributions to BC at Barrow, Alert, and Zeppelin are dominated by Asian anthropogenic sources (40–43 %) before 18 April and by Siberian open biomass burning emissions (29–41 %) afterward. In contrast, Summit, a mostly free tropospheric site, has predominantly an Asian anthropogenic source contribution (24–68 %, with an average of 45 %). We compute the adjoint sensitivity of BC concentrations at the five sites during a pollution episode (20–25 April) to global emissions from 1 March to 25 April. The associated contributions are the combined results of these sensitivities and BC emissions. Local and regional anthropogenic sources in Alaska are the largest anthropogenic sources of BC at Denali (63 % of total anthropogenic contributions), and natural gas flaring emissions in the western extreme north of Russia (WENR) are the largest anthropogenic sources of BC at Zeppelin (26 %) and Alert (13 %). We find that long-range transport of emissions from Beijing–Tianjin–Hebei (also known as Jing–Jin–Ji), the biggest urbanized region in northern China, contribute significantly (∼ 10 %) to surface BC across the Arctic. On average, it takes ∼ 12 days for Asian anthropogenic emissions and Siberian biomass burning emissions to reach the Arctic lower troposphere, supporting earlier studies. Natural gas flaring emissions from the WENR reach Zeppelin in about a week. We find that episodic transport events dominate BC at Denali (87 %), a site outside the Arctic front, which is a strong transport barrier. The relative contribution of these events to surface BC within the polar dome is much smaller (∼ 50 % at Barrow and Zeppelin and ∼ 10 % at Alert). The large contributions from Asian anthropogenic sources are predominately in the form of chronic pollution (∼ 40 % at Barrow, 65 % at Alert, and 57 % at Zeppelin) on about a 1-month timescale. As such, it is likely that previous studies using 5- or 10-day trajectory analyses strongly underestimated the contribution from Asia to surface BC in the Arctic.

scholarly journals Skill in forecasting extreme ozone pollution episodes with a global atmospheric chemistry model

2014 ◽  
Vol 14 (15) ◽  
pp. 7721-7739 ◽  
Author(s):  
J. L. Schnell ◽  
C. D. Holmes ◽  
A. Jangam ◽  
M. J. Prather
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Climate Models ◽  
Transport Model ◽  
Surface Ozone ◽  
The United States ◽  
Ozone Pollution ◽  
Mapping Algorithm ◽  
The Individual ◽  
Pollution Episodes

Abstract. From the ensemble of stations that monitor surface air quality over the United States and Europe, we identify extreme ozone pollution events and find that they occur predominantly in clustered, multiday episodes with spatial extents of more than 1000 km. Such scales are amenable to forecasting with current global atmospheric chemistry models. We develop an objective mapping algorithm that uses the heterogeneous observations of the individual surface sites to calculate surface ozone averaged over 1° by 1° grid cells, matching the resolution of a global model. Air quality extreme (AQX) events are identified locally as statistical extremes of the ozone climatology and not as air quality exceedances. With the University of California, Irvine chemistry-transport model (UCI CTM) we find there is skill in hindcasting these extreme episodes, and thus identify a new diagnostic using global chemistry–climate models (CCMs) to identify changes in the characteristics of extreme pollution episodes in a warming climate.

scholarly journals Skill in forecasting extreme ozone pollution episodes with a global atmospheric chemistry model

2014 ◽  
Vol 14 (5) ◽  
pp. 6261-6310 ◽  
Author(s):  
J. L. Schnell ◽  
C. D. Holmes ◽  
A. Jangam ◽  
M. J. Prather
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Climate Models ◽  
Transport Model ◽  
Surface Ozone ◽  
The United States ◽  
Ozone Pollution ◽  
Mapping Algorithm ◽  
The Individual ◽  
Pollution Episodes

Abstract. From the ensemble of stations that monitor surface air quality over the United States and Europe, we identify extreme ozone pollution events and find that they occur predominantly in clustered, multi-day episodes with spatial extents of more than 1000 km. Such scales are amenable to forecasting with current global atmospheric chemistry models. We develop an objective mapping algorithm that uses the heterogeneous observations of the individual surface sites to calculate surface ozone averaged over 1° by 1° grid cells, matching the resolution of a global model. Air quality extreme (AQX) events are identified locally as statistical extremes of the ozone climatology and not as air quality exceedances. With the University of California, Irvine chemistry-transport model (CTM) we find there is skill in hindcasting these extreme episodes, and thus identify a new diagnostic using global chemistry-climate models (CCM) to identify changes in the characteristics of extreme pollution episodes in a warming climate.

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