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- Author or Editor: Gregory R. Carmichael x
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Abstract
A detailed gas-phase chemistry mechanism is combined with dust surface uptake processes to explore possible impacts of mineral dust on tropospheric chemistry. The formations of sulfate and nitrate on dust are studied along with the dust effects on the photochemical oxidant cycle for the long-range-transported particles with a diameter of 0.1–40 μm.
The results show that mineral dust may influence tropospheric sulfate, nitrate, and O3 formation by affecting trace gas concentrations and the tropospheric oxidation capacity through surface processes. The postulated heterogeneous mechanism provides a plausible interpretation for the observed high nitrate and sulfate on dust and the anticorrelation between O3 and dust in East Asia. The presence of dust results in decreases in the concentrations of SO2 (10%–53%),
Abstract
A detailed gas-phase chemistry mechanism is combined with dust surface uptake processes to explore possible impacts of mineral dust on tropospheric chemistry. The formations of sulfate and nitrate on dust are studied along with the dust effects on the photochemical oxidant cycle for the long-range-transported particles with a diameter of 0.1–40 μm.
The results show that mineral dust may influence tropospheric sulfate, nitrate, and O3 formation by affecting trace gas concentrations and the tropospheric oxidation capacity through surface processes. The postulated heterogeneous mechanism provides a plausible interpretation for the observed high nitrate and sulfate on dust and the anticorrelation between O3 and dust in East Asia. The presence of dust results in decreases in the concentrations of SO2 (10%–53%),
Abstract
The spatiotemporal distribution of observations plays an essential role in the data assimilation process. An adjoint sensitivity method is applied to the problem of adaptive location of the observational system for a nonlinear transport-chemistry model in the context of 4D variational data assimilation. The method is presented in a general framework and it is shown that in addition to the initial state of the model, sensitivity with respect to emission and deposition rates and certain types of boundary values may be obtained at a minimal additional cost. The adjoint modeling is used to evaluate the influence function and to identify the domain of influence associated with the observations. These essential tools are further used to develop a novel algorithm for targeting observations that takes into account the interaction among observations at different instants in time and spatial locations. Issues related to the case of multiple observations are addressed and it is shown that by using the adjoint modeling an efficient implementation may be achieved. Computational and practical aspects are discussed and this analysis indicates that it is feasible to implement the proposed method for comprehensive air quality models. Numerical experiments performed with a two-dimensional test model show promising results.
Abstract
The spatiotemporal distribution of observations plays an essential role in the data assimilation process. An adjoint sensitivity method is applied to the problem of adaptive location of the observational system for a nonlinear transport-chemistry model in the context of 4D variational data assimilation. The method is presented in a general framework and it is shown that in addition to the initial state of the model, sensitivity with respect to emission and deposition rates and certain types of boundary values may be obtained at a minimal additional cost. The adjoint modeling is used to evaluate the influence function and to identify the domain of influence associated with the observations. These essential tools are further used to develop a novel algorithm for targeting observations that takes into account the interaction among observations at different instants in time and spatial locations. Issues related to the case of multiple observations are addressed and it is shown that by using the adjoint modeling an efficient implementation may be achieved. Computational and practical aspects are discussed and this analysis indicates that it is feasible to implement the proposed method for comprehensive air quality models. Numerical experiments performed with a two-dimensional test model show promising results.
Abstract
The dry deposition model was created to estimate SO2 and sulfate dry deposition velocities over nine land use types in Asia. The study domain is 20°S–50°N, 39°–154°E. Monthly averaged 1° × 1° dry deposition velocities are estimated for four seasons. Model results show that the dry deposition velocity of SO2 demonstrates strong seasonal and diurnal variability in summer, fall, and spring. In summer, the daytime velocity (in centimeters per second) for SO2 forests is 0.4, over cultivation is 0.2, grassland is 0.5, and ocean is 0.8. Nighttime values of SO2 are two or three times less than daytime values. In winter, the deposition velocity of SO2 does not show much diurnal variability—the value is 0.1–0.2 except over ocean, when it is 0.5. Contrary to SO2, the dry deposition velocity of sulfate only slightly varies with seasons and time of the day. Generally, its value is less than 0.1.
Abstract
The dry deposition model was created to estimate SO2 and sulfate dry deposition velocities over nine land use types in Asia. The study domain is 20°S–50°N, 39°–154°E. Monthly averaged 1° × 1° dry deposition velocities are estimated for four seasons. Model results show that the dry deposition velocity of SO2 demonstrates strong seasonal and diurnal variability in summer, fall, and spring. In summer, the daytime velocity (in centimeters per second) for SO2 forests is 0.4, over cultivation is 0.2, grassland is 0.5, and ocean is 0.8. Nighttime values of SO2 are two or three times less than daytime values. In winter, the deposition velocity of SO2 does not show much diurnal variability—the value is 0.1–0.2 except over ocean, when it is 0.5. Contrary to SO2, the dry deposition velocity of sulfate only slightly varies with seasons and time of the day. Generally, its value is less than 0.1.
Abstract
The singular vectors of a chemical transport model are the directions of maximum perturbation growth over a finite time interval. They have proved useful for the estimation of error growth, the initialization of ensemble forecasts, and the optimal placement of adaptive observations. The aim of this paper is to address computational aspects of singular vector analysis for atmospheric chemical transport models. The distinguishing feature of these models is the presence of stiff chemical interactions. A projection approach to preserve the symmetry of the tangent linear–adjoint operator for stiff systems is discussed, and extended to 3D chemical transport simulations. Numerical results are presented for a simulation of atmospheric pollution in East Asia in March 2001. The singular values and the structure of the singular vectors depend on the length of the simulation interval, the meteorological data, the location of the optimization region and the selection of optimization species, the choice of error norms, and the size of the optimization region.
Abstract
The singular vectors of a chemical transport model are the directions of maximum perturbation growth over a finite time interval. They have proved useful for the estimation of error growth, the initialization of ensemble forecasts, and the optimal placement of adaptive observations. The aim of this paper is to address computational aspects of singular vector analysis for atmospheric chemical transport models. The distinguishing feature of these models is the presence of stiff chemical interactions. A projection approach to preserve the symmetry of the tangent linear–adjoint operator for stiff systems is discussed, and extended to 3D chemical transport simulations. Numerical results are presented for a simulation of atmospheric pollution in East Asia in March 2001. The singular values and the structure of the singular vectors depend on the length of the simulation interval, the meteorological data, the location of the optimization region and the selection of optimization species, the choice of error norms, and the size of the optimization region.
Abstract
The characteristics of the transport of chemically reactive species under land- and sea-breeze (LSB) circulations are investigated using a detailed transport/chemistry model, which includes 84 gas-phase and 10 heterogeneous chemical reactions. Model applications are presented which use flow fields derived from a modified version of the Asai and Mitsumoto model and eddy diffusivity profiles predicted by the boundary-layer model of Yamada and Mellor as inputs. The effects of nonprecipitating clouds associated with the LSB circulation on the calculated concentration fields are also studied.
Mass transports by updrafts and counterflows associated with the LSB circulation and diurnally varying eddy diffusion processes show transitions between double and single maxima within a 24-hour cycle. The vertical profiles of some secondary pollutants such as O3 generally agree with field observations. Clouds are also shown to affect the predicted distributions of both the soluble and less soluble species by reducing the below-cloud photon flux, by removing soluble species from the air at cloud level, and/or by in-cloud production processes. Deposition processes reduce the species concentrations near the surface, and these effects propagate upward through mass transport processes. However, the qualitative characteristic vertical concentration profiles are similar to the cases where deposition is not included. Finally, the results demonstrate the effectiveness of the divergence correction method used in the numerical calculations in eliminating the fictitious production and consumption reactions introduced by nonzero divergence wind fields.
Abstract
The characteristics of the transport of chemically reactive species under land- and sea-breeze (LSB) circulations are investigated using a detailed transport/chemistry model, which includes 84 gas-phase and 10 heterogeneous chemical reactions. Model applications are presented which use flow fields derived from a modified version of the Asai and Mitsumoto model and eddy diffusivity profiles predicted by the boundary-layer model of Yamada and Mellor as inputs. The effects of nonprecipitating clouds associated with the LSB circulation on the calculated concentration fields are also studied.
Mass transports by updrafts and counterflows associated with the LSB circulation and diurnally varying eddy diffusion processes show transitions between double and single maxima within a 24-hour cycle. The vertical profiles of some secondary pollutants such as O3 generally agree with field observations. Clouds are also shown to affect the predicted distributions of both the soluble and less soluble species by reducing the below-cloud photon flux, by removing soluble species from the air at cloud level, and/or by in-cloud production processes. Deposition processes reduce the species concentrations near the surface, and these effects propagate upward through mass transport processes. However, the qualitative characteristic vertical concentration profiles are similar to the cases where deposition is not included. Finally, the results demonstrate the effectiveness of the divergence correction method used in the numerical calculations in eliminating the fictitious production and consumption reactions introduced by nonzero divergence wind fields.
Abstract
The influence of dust on the tropospheric photochemical oxidant cycle is studied through the use of a detailed coupled aerosol and gas-phase chemistry model. Dust is a significant component of the troposphere throughout Asia and provides a surface for a variety of heterogeneous reactions. Dust is found to be an important surface for particulate nitrate formation. For dust loading and ambient concentrations representative of conditions in East Asia, particulate nitrate levels of 1.5–11.5 µg m−3 are predicted, consistent with measured levels in this region. Dust is also found to reduce NOx levels by up to 50%, HO2 concentrations by 20%–80%, and ozone production rates by up to 25%. The magnitude of the influence of dust is sensitive to the mass concentration of the aerosol, relative humility, and the value of the accommodation coefficient.
Abstract
The influence of dust on the tropospheric photochemical oxidant cycle is studied through the use of a detailed coupled aerosol and gas-phase chemistry model. Dust is a significant component of the troposphere throughout Asia and provides a surface for a variety of heterogeneous reactions. Dust is found to be an important surface for particulate nitrate formation. For dust loading and ambient concentrations representative of conditions in East Asia, particulate nitrate levels of 1.5–11.5 µg m−3 are predicted, consistent with measured levels in this region. Dust is also found to reduce NOx levels by up to 50%, HO2 concentrations by 20%–80%, and ozone production rates by up to 25%. The magnitude of the influence of dust is sensitive to the mass concentration of the aerosol, relative humility, and the value of the accommodation coefficient.
Abstract
A comparison between transport models is done to study the sulfur deposition in East Asia. A single-layer Lagrangian model with simple chemistry is compared to a multilayered 3D Eulerian model. The comparison is done for two-month-long episodes of winter (February) and summer (August) 1989. The model-predicted sulfur deposition is about 0.1 g S (m2 month)−1 for regions with the largest emissions. A comparison between the model-predicted and the observed values at a network of monitoring stations in Japan shows similar temporal trends. The sulfur deposition due to volcanic emissions in Japan has been shown to be about 20% of the total deposition in that country.
Abstract
A comparison between transport models is done to study the sulfur deposition in East Asia. A single-layer Lagrangian model with simple chemistry is compared to a multilayered 3D Eulerian model. The comparison is done for two-month-long episodes of winter (February) and summer (August) 1989. The model-predicted sulfur deposition is about 0.1 g S (m2 month)−1 for regions with the largest emissions. A comparison between the model-predicted and the observed values at a network of monitoring stations in Japan shows similar temporal trends. The sulfur deposition due to volcanic emissions in Japan has been shown to be about 20% of the total deposition in that country.
Abstract
Monitoring and modeling/predicting air pollution are crucial to understanding the links between emissions and air pollution levels, to supporting air quality management, and to reducing human exposure. Yet, current monitoring networks and modeling capabilities are unfortunately inadequate to understand the physical and chemical processes above ground and to support attribution of sources. We highlight the need for the development of an international stereoscopic monitoring strategy that can depict three-dimensional (3D) distribution of atmospheric composition to reduce the uncertainties and to advance diagnostic understanding and prediction of air pollution. There are three reasons for the implementation of stereoscopic monitoring: 1) current observation networks provide only partial view of air pollution, and this can lead to misleading air quality management actions; 2) satellite retrievals of air pollutants are widely used in air pollution studies, but too often users do not acknowledge that they have large uncertainties, which can be reduced with measurements of vertical profiles; and 3) air quality modeling and forecasting require 3D observational constraints. We call on researchers and policymakers to establish stereoscopic monitoring networks and share monitoring data to better characterize the formation of air pollution, optimize air quality management, and protect human health. Future directions for advancing monitoring and modeling/predicting air pollution are also discussed.
Abstract
Monitoring and modeling/predicting air pollution are crucial to understanding the links between emissions and air pollution levels, to supporting air quality management, and to reducing human exposure. Yet, current monitoring networks and modeling capabilities are unfortunately inadequate to understand the physical and chemical processes above ground and to support attribution of sources. We highlight the need for the development of an international stereoscopic monitoring strategy that can depict three-dimensional (3D) distribution of atmospheric composition to reduce the uncertainties and to advance diagnostic understanding and prediction of air pollution. There are three reasons for the implementation of stereoscopic monitoring: 1) current observation networks provide only partial view of air pollution, and this can lead to misleading air quality management actions; 2) satellite retrievals of air pollutants are widely used in air pollution studies, but too often users do not acknowledge that they have large uncertainties, which can be reduced with measurements of vertical profiles; and 3) air quality modeling and forecasting require 3D observational constraints. We call on researchers and policymakers to establish stereoscopic monitoring networks and share monitoring data to better characterize the formation of air pollution, optimize air quality management, and protect human health. Future directions for advancing monitoring and modeling/predicting air pollution are also discussed.
Abstract
Further long-term investments in high-quality, research-driven, fit-for-purpose observations of atmospheric composition are needed globally to meet urgent societal needs related to weather, climate, air quality, and other environmental issues. Challenges include maintaining current observing systems in the face of eroding budgets for long-term monitoring and filling the geographical gaps for key constituents needed for sound services and policies. The observing systems can be bolstered through science-for-services applications, by embracing interoperable observation systems and standardized metadata, and ensuring that the data are findable, accessible, interoperable, and reusable. There is an urgent need to move from opportunities-driven one-component observations to more systematic, planned multifunctional infrastructure, where the observational data flow is coupled with Earth system models to serve both operational and research purposes. This approach fosters a community where user experience feeds back into the research components and where mature research results are translated into operational applications. This will lead to faster exploration and exploitation of atmospheric composition information and more impactful applications for science and society. We discuss here the urgent need to (i) achieve global coverage, (ii) harmonize infrastructure operations, (iii) establish focused policies, and (iv) strengthen coordination of atmospheric composition infrastructure.
Abstract
Further long-term investments in high-quality, research-driven, fit-for-purpose observations of atmospheric composition are needed globally to meet urgent societal needs related to weather, climate, air quality, and other environmental issues. Challenges include maintaining current observing systems in the face of eroding budgets for long-term monitoring and filling the geographical gaps for key constituents needed for sound services and policies. The observing systems can be bolstered through science-for-services applications, by embracing interoperable observation systems and standardized metadata, and ensuring that the data are findable, accessible, interoperable, and reusable. There is an urgent need to move from opportunities-driven one-component observations to more systematic, planned multifunctional infrastructure, where the observational data flow is coupled with Earth system models to serve both operational and research purposes. This approach fosters a community where user experience feeds back into the research components and where mature research results are translated into operational applications. This will lead to faster exploration and exploitation of atmospheric composition information and more impactful applications for science and society. We discuss here the urgent need to (i) achieve global coverage, (ii) harmonize infrastructure operations, (iii) establish focused policies, and (iv) strengthen coordination of atmospheric composition infrastructure.
