On trusting models or observations

Models and observations relative to the CO₂-climate controversy are analyzed in a manner similar to Ellsaesser's recent analysis of models and observations relative to the supersonic transport threat to the ozone layer. As in that earlier analysis, and as is explicit in all formulations of the scientific method, observations of surface air temperature prove to be much more reliable than atmospheric general circulation models in reconstructing recent climatic history. This finding leaves grave doubts about the ability of the models to predict our climatic future, specifically with respect to the effects of increasing atmospheric CO₂ concentrations.     

Application of artificial neural networks to modeling and prediction of ambient ozone concentrations

The deterministic modeling of ambient O3 concentrations is difficult because of the complexity of the atmospheric system in terms of the number of chemical species; the availability of accurate, time-resolved emissions data; and the required rate constants. However, other complex systems have been successfully approximated using artificial neural networks (ANNs). In this paper, ANNs are used to model and predict ambient O3 concentrations based on a limited number of measured hydrocarbon species, NOx compounds, temperature, and radiant energy. In order to examine the utility of these approaches, data from the Coastal Oxidant Assessment for Southeast Texas (COAST) program in Houston, TX, have been used. In this study, 53 hydrocarbon compounds, along with O3, nitrogen oxides, and meteorological data were continuously measured during summer 1993. Steady-state ANN models were developed to examine the ability of these models to predict current O3 concentrations from measured VOC and NOx concentrations. To predict the future concentrations of O3, dynamic models were also explored and were used for extraction of chemical information such as reactivity estimations for the VOC species. The steady-state model produced an approximation of O3 data and demonstrated the functional relationship between O3 and VOC-NOx concentrations. The dynamic models were able to the adequately predict the O3 concentration and behavior of VOC-NOx-O3 system a number of hourly intervals into the future. For 3 hr into the future, O3 concentration could be predicted with a root-mean squared error (RMSE) of 8.21 ppb. Extending the models further in time led to an RMSE of 11.46 ppb for 5-hr-ahead values. This prediction capability could be useful in determining when control actions are needed to maintain measured concentrations within acceptable value ranges.     

Application of Artificial Neural Networks to Modeling and Prediction of Ambient Ozone Concentrations

ABSTRACT

The deterministic modeling of ambient O₃ concentrations is difficult because of the complexity of the atmospheric system in terms of the number of chemical species; the availability of accurate, time-resolved emissions data; and the required rate constants. However, other complex systems have been successfully approximated using artificial neural networks (ANNs). In this paper, ANNs are used to model and predict ambient O₃ concentrations based on a limited number of measured hydrocarbon species, NO_x compounds, temperature, and radiant energy. In order to examine the utility of these approaches, data from the Coastal Oxidant Assessment for Southeast Texas (COAST) program in Houston, TX, have been used. In this study, 53 hydrocarbon compounds, along with O₃, nitrogen oxides, and meteorological data were continuously measured during summer 1993. Steady-state ANN models were developed to examine the ability of these models to predict current O₃ concentrations from measured VOC and NO concentrations. To predict the future concentrations of O₃, dynamic models were also explored and were used for extraction of chemical information such as reactivity estimations for the VOC species.

The steady-state model produced an approximation of O₃ data and demonstrated the functional relationship between O₃ and VOC-NO_x concentrations. The dynamic models were able to the adequately predict the O₃ concentration and behavior of VOC-NO_x-O₃ system a number of hourly intervals into the future. For 3 hr into the future, O₃ concentration could be predicted with a root-mean squared error (RMSE) of 8.21 ppb. Extending the models further in time led to an RMSE of 11.46 ppb for 5-hr-ahead values. This prediction capability could be useful in determining when control actions are needed to maintain measured concentrations within acceptable value ranges.     

Isoprene emissions and climate

Biogenic volatile organic compounds (BVOCs) play an important role in atmospheric chemistry and the carbon cycle. Isoprene is quantitatively the most important of the non-methane BVOCs (NMBVOCs), with an annual emission of about 400–600 TgC; about 90% of this is emitted by terrestrial plants. Incorporating a mechanistic treatment of isoprene emissions within land-surface schemes has recently become a focus for the modelling community, the aim being to quantify the potential magnitude of associated climate feedbacks. However, these efforts are hampered by major uncertainties about why plants emit isoprene and the relative importance of different environmental controls on isoprene emission. The availability and reliability of observations of isoprene fluxes from different types of vegetation is limited, and this also imposes constraints on model development. Nevertheless, progress is being made towards the development of mechanistic models of isoprene emission which, in conjunction with atmospheric chemistry models, will ultimately allow improved quantification of the feedbacks between the terrestrial biosphere and climate under past and future climate states.     

Compilation of a database on the composition of anthropogenic VOC emissions for atmospheric modeling in Europe

To analyse and generate air pollution control strategies and policies, e.g. efficient abatement strategies or action plans that lead to a fulfilment of air quality aims, atmospheric dispersion models (CTMs) have to be used. These models include a chemical model, where the numerous volatile organic compounds (VOCs) species are lumped together in classes. On the other hand, emission inventories usually report only total non-methane VOC (NMVOC), but not a subdivision into these classes. Thus, VOC species profiles are needed that resolve total NMVOC emission data. The objective of this publication is to present the results of a compilation of VOC species profiles that dissolve total VOC into single-species profiles for all relevant anthropogenic emission source categories and the European situation. As in atmospheric dispersion models usually modules for generating biogenic emissions are directly included, only anthropogenic emissions are addressed. VOC species profiles for 87 emission source categories have been developed. The underlying data base can be used to generate the data for all chemical mechanisms. The species profiles have been generated using recent measurements and studies on VOC species resolution and thus represent the current state of knowledge in this area. The results can be used to create input data for atmospheric dispersion models in Europe.The profiles, especially those for solvent use, still show large uncertainties. There is still an enormous need for further measurements to achieve an improved species resolution. In addition, the solvent use directive and the DECOPAINT directive of the European Commission will result in a change of the composition of paints; more water-based and high-solid paints will be used; thus the species resolution will change drastically in the next years. Of course, the species resolution for combustion and production processes also requires further improvement.     

A diagnostic evaluation of modeled mercury wet depositions in Europe using atmospheric speciated high-resolution observations

This study is part of the Global Mercury Observation System (GMOS), a European FP7 project dedicated to the improvement and validation of mercury models to assist in establishing a global monitoring network and to support political decisions. One key question about the global mercury cycle is the efficiency of its removal out of the atmosphere into other environmental compartments. So far, the evaluation of modeled wet deposition of mercury was difficult because of a lack of long-term measurements of oxidized and elemental mercury. The oxidized mercury species gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) which are found in the atmosphere in typical concentrations of a few to a few tens pg/m³ are the relevant components for the wet deposition of mercury. In this study, the first European long-term dataset of speciated mercury taken at Waldhof/Germany was used to evaluate deposition fields modeled with the chemistry transport model (CTM) Community Multiscale Air Quality (CMAQ) and to analyze the influence of the governing parameters. The influence of the parameters precipitation and atmospheric concentration was evaluated using different input datasets for a variety of CMAQ simulations for the year 2009. It was found that on the basis of daily and weekly measurement data, the bias of modeled depositions could be explained by the bias of precipitation fields and atmospheric concentrations of GOM and PBM. A correction of the modeled wet deposition using observed daily precipitation increased the correlation, on average, from 0.17 to 0.78. An additional correction based on the daily average GOM and PBM concentration lead to a 50 % decrease of the model error for all CMAQ scenarios. Monthly deposition measurements were found to have a too low temporal resolution to adequately analyze model deficiencies in wet deposition processes due to the nonlinear nature of the scavenging process. Moreover, the general overestimation of atmospheric GOM by the CTM in combination with an underestimation of low precipitation events in the meteorological models lead to a good agreement of total annual wet deposition besides the large error in weekly deposition estimates. Moreover, it was found that the current speciation profiles for GOM emissions are the main factor for the overestimation of atmospheric GOM concentrations and might need to be revised in the future. The assumption of zero emissions of GOM lead to an improvement of the mean normalized bias for three-hourly observations of atmospheric GOM from 9.7 to 0.5, Furthermore, the diurnal correlation between model and observation increased from 0.01 to 0.64. This is a strong indicator that GOM is not directly emitted from primary sources but is mainly created by oxidation of GEM.     

Investigation of the time evolved spatial distribution of urban PM2.5 concentrations and aerosol composition during episodic high PM events in Yuma,AZ

An interdisciplinary field study designed to investigate the spatial and temporal variability of atmospheric aerosols during high particulate matter (PM) events along the US–Mexico border near Yuma, AZ was run during the week of March 18, 2007. The experiments were designed to quantify chemical composition and physical phenomena governing the transport of aerosols generated from episodic high PM events. The field study included two micrometeorological monitoring sites; one rural and one urban, equipped with sonic anemometers, continuous particulate concentration monitors and ambient aerosol collection equipment. In addition to the two main monitoring sites, five additional locations were equipped with optical particle counters to allow for the investigation of the spatial and temporal distribution of PM_2.5 in the urban environment. In this paper, the meteorological and turbulence parameters governing the distribution and concentration of PM_2.5 in the urban environment for two high-wind erosion events and one burning event are compared. The interaction between local atmospheric conditions and the particulate distribution is investigated. Results indicate that a single point measurement in the urban area of Yuma may not be sufficient for determining the ambient PM concentrations that the local population experiences; all three high PM events indicated PM_2.5 varied considerably with maximum urban concentrations 5–10 times greater than the measured minima. A comparison of inorganic and carbonaceous content of the aerosols for the three high PM events is presented. The comparison shows an increase in silicon during crustal dust events and an increase in elemental and organic carbon during the burn event. Additional surface chemistry analysis, using time-of-flight secondary ion mass spectrometry (ToF-SIMS), for aerosols collected at the urban and rural sites during the burn event are discussed. The surface chemistry analysis provides positive ion mass spectra of organic and inorganic species in the ambient aerosol, and can be used to determine the type of combustion process that contributed to an increase in PM concentration during the burn event.     

Modeling excessive nutrient loading in the environment

Models addressing excessive nutrient loading in the environment originated over 50 years ago with the simple nutrient concentration thresholds proposed by Sawyer (1947. Fertilization of lakes by agricultural and urban drainage. New Engl. Water Works Assoc. 61, 109-127). Since then, models have improved due to progress in modeling techniques and technology as well as enhancements in scientific knowledge. Several of these advances are examined here. Among the recent approaches in modeling techniques we review are error propagation, model confirmation, generalized sensitivity analysis, and Bayesian analysis. In the scientific arena and process characterization, we focus on advances in surface water modeling, discussing enhanced modeling of organic carbon, improved hydrodynamics, and refined characterization of sediment diagenesis. We conclude with some observations on future needs and anticipated developments.     

An adaptive reduction algorithm for efficient chemical calculations in global atmospheric chemistry models

We present a computationally efficient adaptive method for calculating the time evolution of the concentrations of chemical species in global 3-D models of atmospheric chemistry. Our strategy consists of partitioning the computational domain into fast and slow regions for each chemical species at every time step. In each grid box, we group the fast species and solve for their concentration in a coupled fashion. Concentrations of the slow species are calculated using a simple semi-implicit formula. Separation of species between fast and slow is done on the fly based on their local production and loss rates. This allows for example to exclude short-lived volatile organic compounds (VOCs) and their oxidation products from chemical calculations in the remote troposphere where their concentrations are negligible, letting the simulation determine the exclusion domain and allowing species to drop out individually from the coupled chemical calculation as their production/loss rates decline. We applied our method to a 1-year simulation of global tropospheric ozone-NO_x-VOC-aerosol chemistry using the GEOS-Chem model. Results show a 50% improvement in computational performance for the chemical solver, with no significant added error.     

An urban emissions inventory for South America and its application in numerical modeling of atmospheric chemical composition at local and regional scales

This work describes the development of an urban vehicle emissions inventory for South America, based on the analysis and aggregation of available inventories for major cities, with emphasis on its application in regional atmospheric chemistry modeling. Due to the limited number of available local inventories, urban emissions were extrapolated based on the correlation between city vehicle density and mobile source emissions of carbon monoxide (CO) and nitrogen oxides (NOx). Emissions were geographically distributed using a methodology that delimits urban areas using high spatial resolution remote sensing products. This numerical algorithm enabled a more precise representation of urban centers. The derived regional inventory was evaluated by analyzing the performance of a chemical weather forecast model in relation to observations of CO, NOx and O₃ in two different urban areas, São Paulo and Belo Horizonte. The gas mixing ratios simulated using the proposed regional inventory show good agreement with observations, consistently representing their hourly and daily variability. These results show that the integration of municipal inventories in a regional emissions map and their precise distribution in fine scale resolutions are important tools in regional atmospheric chemistry modeling.     

Approaches for quantifying reactive and low-volatility biogenic organic compound emissions by vegetation enclosure techniques - part A

The high reactivity and low vapor pressure of many biogenic volatile organic compounds (BVOC) make it difficult to measure whole-canopy fluxes of BVOC species using common analytical techniques. The most appropriate approach for estimating these BVOC fluxes is to determine emission rates from dynamic vegetation enclosure measurements. After scaling leaf- and branch-level emission rates to the canopy level, these fluxes can then be used in models to determine BVOC influences on atmospheric chemistry and aerosol processes. Previously published reports from enclosure measurements show considerable variation among procedures with limited guidelines or standard protocols to follow. This article reviews this literature and describes the variety of enclosure types, materials, and analysis techniques that have been used to determine BVOC emission rates. The current review article is followed by a companion paper which details a comprehensive enclosure technique that incorporates both recommendations from the literature as well as insight gained from theoretical calculations and practical experiences. These methods have yielded new BVOC emission data for highly reactive monoterpenes (MT) and sesquiterpenes (SQT) from a variety of vegetation species.     

Atmospheric composition change: Climate–Chemistry interactions

Chemically active climate compounds are either primary compounds like methane (CH₄), removed by oxidation in the atmosphere, or secondary compounds like ozone (O₃), sulfate and organic aerosols, both formed and removed in the atmosphere. Man-induced climate–chemistry interaction is a two-way process: Emissions of pollutants change the atmospheric composition contributing to climate change through the aforementioned climate components, and climate change, through changes in temperature, dynamics, the hydrological cycle, atmospheric stability, and biosphere-atmosphere interactions, affects the atmospheric composition and oxidation processes in the troposphere. Here we present progress in our understanding of processes of importance for climate–chemistry interactions, and their contributions to changes in atmospheric composition and climate forcing. A key factor is the oxidation potential involving compounds like O₃ and the hydroxyl radical (OH). Reported studies represent both current and future changes. Reported results include new estimates of radiative forcing based on extensive model studies of chemically active climate compounds like O₃, and of particles inducing both direct and indirect effects. Through EU projects like ACCENT, QUANTIFY, and the AeroCom project, extensive studies on regional and sector-wise differences in the impact on atmospheric distribution are performed. Studies have shown that land-based emissions have a different effect on climate than ship and aircraft emissions, and different measures are needed to reduce the climate impact. Several areas where climate change can affect the tropospheric oxidation process and the chemical composition are identified. This can take place through enhanced stratospheric–tropospheric exchange of ozone, more frequent periods with stable conditions favoring pollution build up over industrial areas, enhanced temperature induced biogenic emissions, methane releases from permafrost thawing, and enhanced concentration through reduced biospheric uptake. During the last 5–10 years, new observational data have been made available and used for model validation and the study of atmospheric processes. Although there are significant uncertainties in the modeling of composition changes, access to new observational data has improved modeling capability. Emission scenarios for the coming decades have a large uncertainty range, in particular with respect to regional trends, leading to a significant uncertainty range in estimated regional composition changes and climate impact.     

Reviews on atmospheric selenium: Emissions,speciation and fate

The atmosphere is an important transient reservoir of selenium (Se). According to recent evaluations of the global Se budget, approximately 13,000–19,000 tons of Se is cycled through the troposphere annually. Most studies suggest that atmospheric deposition is an important source of Se contamination and it is therefore critical to evaluate the source emissions and fate of Se in the atmosphere. This paper presents a broad overview of current state of knowledge and understanding of major aspects of atmospheric Se and its natural and anthropogenic sources. The significant physical and chemical species encountered in the atmosphere are examined and special attention is paid to atmospheric speciation and its atmospheric pathways and processes. In addition, thermodynamic and kinetic data for atmospheric Se speciation are provided, which aid our understanding and the modelling of Se behaviour in the atmospheric environment. We also document how Se isotopes might be useful for tracing atmospheric sources and pathways. Important gaps in our current knowledge of Se in the atmospheric environment are identified, and suggestions for future research are offered.     

Discussion of a lagrangian trajectory model describing long-range transport of oxides of nitrogen,the incorporation of pan in the chemical mechanism,and supporting measurements of pan and nitrate species at rural sites in Ontario,Canada

The derivation of a highly simplified parameterization of NO_x chemistry for use with the AES Lagrangian trajectory model is described. Two versions, both employing essentially independent first-order kinetics are discussed:

• 1.(1) a one step mechanism: NO₂→ inorganic nitrate and
• 2.(2) a somewhat more involved reaction scheme including PAN chemistry.

Evaluation of model performance is attempted with data from the Canadian Air and Precipitation Monitoring Network (APN). It is shown that both model versions are able to reproduce trends of annual and monthly average atmospheric nitrate concentrations, although the models tend to suggest transport over larger distances than is apparent from the field data. The inclusion of PAN chemistry appears to improve the model performance. However, the model predicts a winter maximum and a summer minimum for the annual profile of PAN, and this is in direct contradiction with field measurements of PAN elsewhere. Initial results from a PAN measurement program conducted at three sites in Ontario are also reported and compared with the second model version. Observations for summer 1982 are predicted quite well, but data collected during March 1983 are substantially overpredicted. It is indicated that during periods of rain, PAN constitutes the major oxidized NO_x component. The suggestion is made that this observation is due to a much more efficient precipitation scavenging of nitrate species than of PAN.     

Exploration of heterogeneous chemistry in model atmospheric particles using extended X-ray absorption fine structure analysis

As models of the composition and heterogeneous chemical reactions of the troposphere undergo refinement, novel application of state-of-the-art analytical techniques will be necessary to propound realistic characterizations of mineral dust chemistry. In this study, strontium carbonate particles treated with gaseous nitric acid and nitrogen dioxide were examined with X-ray absorption fine structure analysis (EXAFS). The X-ray spectra of carbonate and nitrate standards were fitted to ab initio calculations, which were used to determine the structure and consistency of strontium nitrate formed on strontium carbonate. By examining differences in mean square radial displacement and lattice spacing values obtained for bulk Sr(NO₃)₂ as compared to Sr(NO₃)₂ formed on SrCO₃, EXAFS proves effective as a tool for investigating the local structure and composition of heterogeneous aerosol particles. The implications of findings on reacted strontium carbonate for atmospheric models of calcium carbonate aerosol are discussed.     

Heterogeneous reactions of soot aerosols with nitrogen dioxide and nitric acid: atmospheric chamber and Knudsen cell studies

Heterogeneous chemical processes involving trace atmospheric gases with solid particulates, such as carbonaceous aerosol, are not well understood. In an effort to quantify some relevant carbon aerosol systems, the heterogeneous chemistry of NO₂ with both commercial and freshly prepared hexane soot was investigated in an atmospheric reaction chamber. At approximately an atmosphere of total pressure (760 Torr) and under dry conditions (relative humidities⩽1%), kinetic measurements gave an uptake coefficient of (2.4±0.6)×10⁻⁸ for n-hexane soot when referenced to the BET surface area of the sample. Commercial carbon black samples were found to yield a similar uptake coefficient. The reaction of HNO₃ with commercial carbon black was also investigated and gas phase NO₂ was detected as a reaction product. Low-pressure Knudsen cell experiments were carried out to facilitate a quantitative comparison between the two different techniques. The agreement between our current results and previously reported values of the uptake coefficient, with different soot samples and under varied pressure and surface coverage conditions, are discussed along with the possible implications for atmospheric chemistry.     

Testing the Potential for Predictive Modeling and Mapping and Extending Its Use as a Tool for Evaluating Management Scenarios and Economic Valuation in the Baltic Sea (PREHAB)

We evaluated performance of species distribution models for predictive mapping, and how models can be used to integrate human pressures into ecological and economic assessments. A selection of 77 biological variables (species, groups of species, and measures of biodiversity) across the Baltic Sea were modeled. Differences among methods, areas, predictor, and response variables were evaluated. Several methods successfully predicted abundance and occurrence of vegetation, invertebrates, fish, and functional aspects of biodiversity. Depth and substrate were among the most important predictors. Models incorporating water clarity were used to predict increasing cover of the brown alga bladderwrack Fucus vesiculosus and increasing reproduction area of perch Perca fluviatilis, but decreasing reproduction areas for pikeperch Sander lucioperca following successful implementation of the Baltic Sea Action Plan. Despite variability in estimated non-market benefits among countries, such changes were highly valued by citizens in the three Baltic countries investigated. We conclude that predictive models are powerful and useful tools for science-based management of the Baltic Sea.     

Global circulation of atmospheric mercury: a modelling study

This paper presents a comprehensive atmospheric global and regional mercury model and its capability in describing the atmospheric cycling of mercury. This is an on-line model (integrated within the Canadian operational environmental forecasting and data assimilation system) which can be used to understand the role of meteorology in mercury cycling (atmospheric pathways), the inter-annual variability of mercury and can be evaluated against observations on global scales. This is due to the fact that the model uses a combination of actual observed and predicted meteorological state of the atmosphere at high resolution to integrate the model as opposed to the climatological approach used in existing global mercury models. The model was integrated and evaluated on global scale using only anthropogenic emissions. North to south gradients in mercury concentrations, seasonal variability, dry and wet deposition and vertical structure are well simulated by the model. The model was used to explain the observed seasonal variations in atmospheric mercury circulation. The results from this study include a global animation of surface air concentrations of total gaseous mercury for 1997.     

Ammonia in the environment: from ancient times to the present

Recent research on atmospheric ammonia has made good progress in quantifying sources/sinks and environmental impacts. This paper reviews the achievements and places them in their historical context. It considers the role of ammonia in the development of agricultural science and air chemistry, showing how these arose out of foundations in 18th century chemistry and medieval alchemy, and then identifies the original environmental sources from which the ancients obtained ammonia. Ammonia is revealed as a compound of key human interest through the centuries, with a central role played by sal ammoniac in alchemy and the emergence of modern science. The review highlights how recent environmental research has emphasized volatilization sources of ammonia. Conversely, the historical records emphasize the role of high-temperature sources, including dung burning, coal burning, naturally burning coal seams and volcanoes. Present estimates of ammonia emissions from these sources are based on few measurements, which should be a future priority.     

Non-linear response of wet deposition to emissions reduction: A model study

An Eulerian atmospheric model with complex chemistry (Acidic Deposition and Oxidant Model) and a Lagrangian model with linear chemistry (Ontario Ministry of the Environment Trajectory Model) were used to simulate the wet SO₄²⁻ deposition pattern over eastern North America for 16 days during April 1981.The two model results agree reasonably well with each other when the 16 day average values are compared. They also show reasonable agreement with observed data. Having established the ability of the models to predict deposition patterns for 1981 emissions, reduction scenarios with 50% SO_x and 50% SO_x and NO_x of the 1981 emissions were studied through the Eulerian model. Near the heavy emissions area, the reduction in SO₄²⁻ wet deposition is only about 30–40%. In this respect the linear Lagrangian model departs significantly from the Eulerian model. This non-linearity in response is attributed to the role of oxidants in controlling the conversion of SO₂ to SO₄²⁻.