scholarly journals Assessment of parameters describing representativeness of air quality in-situ measurement sites

2009 ◽  
Vol 9 (5) ◽  
pp. 20019-20062 ◽  
Author(s):  
S. Henne ◽  
D. Brunner ◽  
D. Folini ◽  
S. Solberg ◽  
J. Klausen ◽  
...  
Keyword(s):  
Air Quality ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Wind Fields ◽  
Mixing Ratios ◽  
Air Quality Measurements ◽  
Novel Approach ◽  
Variable Surface ◽  
Catchment Areas ◽  
Rural Sites

Abstract. The atmospheric layer closest to the ground is strongly influenced by variable surface fluxes (emissions, surface deposition) and can therefore be very heterogeneous. In order to perform air quality measurements that are representative of a larger domain or a certain degree of pollution, observatories are placed away from population centres or within areas of specific population density. Sites are often categorised based on subjective criteria that are not uniformly applied within different administrative domains. A novel approach for the assessment of parameters reflecting site representativeness is presented here, taking emissions, deposition and transport towards 34 sites covering Western and Central Europe into account. These parameters are directly inter-comparable among the sites and can be used to select sites that are, on average, more or less suitable for data assimilation and comparison with satellite and model data. Advection towards these sites was simulated by backward Lagrangian Particle Dispersion Modelling (LPDM) to determine the sites' annual catchment areas for the year 2005 and advection times of 12, 24 and 48 h. Only variations caused by emissions and transport during these periods were considered assuming that these dominate the short-term variability of most but especially short lived trace gases. The parameters of representativeness derived were compared between sites and a novel, uniform and observation-independent categorisation of the sites based on a clustering approach was established. Six groups of European background sites were identified ranging from very remote coastal to polluted rural sites. These six categories explained 50 to 80% of the inter-site variability of median mixing ratios and their standard deviation for NO2 and O3, while differences between group means of the longer lived trace gas CO were insignificant. The derived annual catchment areas strongly depended on the applied LPDM and input wind fields, the catchment settings and the year of analysis. Nevertheless, the parameters of representativeness showed considerably less variability than the catchment geometry, supporting the robustness of the derived station categorisation.

scholarly journals Assessment of parameters describing representativeness of air quality in-situ measurement sites

2010 ◽  
Vol 10 (8) ◽  
pp. 3561-3581 ◽  
Author(s):  
S. Henne ◽  
D. Brunner ◽  
D. Folini ◽  
S. Solberg ◽  
J. Klausen ◽  
...  
Keyword(s):  
Air Quality ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Wind Fields ◽  
Mixing Ratios ◽  
Air Quality Measurements ◽  
Novel Approach ◽  
Variable Surface ◽  
Catchment Areas ◽  
Clustering Approach

Abstract. The atmospheric layer closest to the ground is strongly influenced by variable surface fluxes (emissions, surface deposition) and can therefore be very heterogeneous. In order to perform air quality measurements that are representative of a larger domain or a certain degree of pollution, observatories are placed away from population centres or within areas of specific population density. Sites are often categorised based on subjective criteria that are not uniformly applied by the atmospheric community within different administrative domains yielding an inconsistent global air quality picture. A novel approach for the assessment of parameters reflecting site representativeness is presented here, taking emissions, deposition and transport towards 34 sites covering Western and Central Europe into account. These parameters are directly inter-comparable among the sites and can be used to select sites that are, on average, more or less suitable for data assimilation and comparison with satellite and model data. Advection towards these sites was simulated by backward Lagrangian Particle Dispersion Modelling (LPDM) to determine the sites' average catchment areas for the year 2005 and advection times of 12, 24 and 48 h. Only variations caused by emissions and transport during these periods were considered assuming that these dominate the short-term variability of most but especially short lived trace gases. The derived parameters describing representativeness were compared between sites and a novel, uniform and observation-independent categorisation of the sites based on a clustering approach was established. Six groups of European background sites were identified ranging from generally remote to more polluted agglomeration sites. These six categories explained 50 to 80% of the inter-site variability of median mixing ratios and their standard deviation for NO2 and O3, while differences between group means of the longer-lived trace gas CO were insignificant. The derived annual catchment areas strongly depended on the applied LPDM and input wind fields, the catchment settings and the year of analysis. Nevertheless, the parameters describing representativeness showed considerably less variability than the catchment geometry, supporting the applicability of the derived station categorisation.

scholarly journals Trends of Rural Tropospheric Ozone at the Northwest of the Iberian Peninsula

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
S. Saavedra ◽  
A. Rodríguez ◽  
J. A. Souto ◽  
J. J. Casares ◽  
J. L. Bermúdez ◽  
...  
Keyword(s):  
Air Quality ◽  
Iberian Peninsula ◽  
Tropospheric Ozone ◽  
Air Quality Measurements ◽  
Meteorological Influences ◽  
Emission Changes ◽  
Rural Sites ◽  
Rural Character ◽  
Ozone Episodes ◽  
Ozone Levels

Tropospheric ozone levels around urban and suburban areas at Europe and North America had increased during 80’s–90’s, until the application of NOxreduction strategies. However, as it was expected, this ozone depletion was not proportional to the emissions reduction. On the other hand, rural ozone levels show different trends, with peaks reduction and average increments; this different evolution could be explained by either emission changes or climate variability in a region. In this work, trends of tropospheric ozone episodes at rural sites in the northwest of the Iberian Peninsula were analyzed and compared to others observed in different regions of the Atlantic European coast. Special interest was focused on the air quality sites characterization, in order to guarantee their rural character in terms of air quality. Both episodic local meteorological and air quality measurements along five years were considered, in order to study possible meteorological influences in ozone levels, different to other European Atlantic regions.

scholarly journals An integrated approach for the evaluation of technological hazard impacts on air quality: the case of the Val d'Agri oil/gas plant

2014 ◽  
Vol 2 (4) ◽  
pp. 2345-2376
Author(s):  
M. Calvello ◽  
F. Esposito ◽  
S. Trippetta
Keyword(s):  
Air Quality ◽  
Treatment Plant ◽  
Monitoring Network ◽  
Integrated Approach ◽  
Preliminary Evaluation ◽  
Air Quality Measurements ◽  
Novel Approach ◽  
Starting Point ◽  
Pre Treatment ◽  
Oil Gas

Abstract. The Val d'Agri area (southern Italy) hosts the biggest on-shore European reservoir and the largest oil/gas pre-treatment plant, named Centro Olio Val d'Agri (COVA), located in a rural/anthropized context. Several hazards are associated to this plant. These are mainly represented by possible impacts of the COVA atmospheric emissions on the local air quality and human health. This work uses a novel approach based on the integration of air quality measurements from the regional monitoring network, additional experimental measurements (i.e., sub-micrometric particulate matter – PM1 and Black Carbon – BC) and advanced statistical analyses to provide a preliminary evaluation of the Val d'Agri air quality state and give some indications of specific areas potentially affected by COVA hazards. Results show that the COVA plant emissions exert an impact especially on the air quality of the area closest to it. In this area several pollutants specifically related to the COVA combustion processes (i.e., nitrogen oxides, benzene and toluene) show the highest concentration values and significant correlations. The proposed approach represents a first step in the assessment of the risks associated to oil/gas exploration and pre-treatment activities and a starting point for the development of effective and exportable air quality monitoring strategies.

scholarly journals FLEXINVERT: an atmospheric Bayesian inversion framework for determining surface fluxes of trace species using an optimized grid

2014 ◽  
Vol 7 (5) ◽  
pp. 2223-2242 ◽  
Author(s):  
R. L. Thompson ◽  
A. Stohl
Keyword(s):  
Dispersion Model ◽  
Particle Dispersion ◽  
Linear Process ◽  
Surface Fluxes ◽  
Bayesian Inversion ◽  
Mixing Ratios ◽  
Trace Species ◽  
Methane Fluxes ◽  
Spatio Temporal ◽  
Atmospheric Loss

Abstract. We present a new modular Bayesian inversion framework, called FLEXINVERT, for estimating the surface fluxes of atmospheric trace species. FLEXINVERT can be applied to determine the spatio-temporal flux distribution of any species for which the atmospheric loss (if any) can be described as a linear process and can be used on continental to regional and even local scales with little or no modification. The relationship between changes in atmospheric mixing ratios and fluxes (the so-called source–receptor relationship) is described by a Lagrangian Particle Dispersion Model (LPDM) run in a backwards-in-time mode. In this study, we use FLEXPART but any LPDM could be used. The framework determines the fluxes on a nested grid of variable resolution, which is optimized based on the source–receptor relationships for the given observation network. Background mixing ratios are determined by coupling FLEXPART to the output of a global Eulerian model (or alternatively, from the observations themselves) and are also optionally optimized in the inversion. Spatial and temporal error correlations in the fluxes are taken into account using a simple model of exponential decay with space and time and, additionally, the aggregation error from the variable grid is accounted for. To demonstrate the use of FLEXINVERT, we present one case study in which methane fluxes are estimated in Europe in 2011 and compare the results to those of an independent inversion ensemble.

scholarly journals Modelling Global Tropical Cyclone Wind Footprints

2019 ◽  
Author(s):  
James M. Done ◽  
Ming Ge ◽  
Greg J. Holland ◽  
Ioana Dima-West ◽  
Samuel Phibbs ◽  
...  
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Decay Rates ◽  
Process Models ◽  
Wind Fields ◽  
Surface Drag ◽  
Regional Variability ◽  
Wind Field Model ◽  
Novel Approach ◽  
Variable Surface

Abstract. A novel approach to modelling the surface wind field of landfalling tropical cyclones (TCs) is presented. The modelling system simulates the evolution of the low-level wind fields of landfalling TCs, accounting for terrain effects. A two-step process models the gradient-level wind field using a parametric wind field model fitted to TC track data, then brings the winds down to the surface using a full numerical boundary layer model. The physical wind response to variable surface drag and terrain height produces substantial local modifications to the smooth wind field provided by the parametric wind profile model. For a set of U.S. historical landfalling TCs the simulated footprints compare favourably with surface station observations. The model is applicable from single event simulation to the generation of global catalogues. One application demonstrated here is the creation of a dataset of 714 global historical TC overland wind footprints. A preliminary analysis of this dataset shows regional variability in the inland wind speed decay rates and evidence of a strong influence of regional orography. This dataset can be used to advance our understanding of overland wind risk in regions of complex terrain and support wind risk assessments in regions of sparse historical data.

scholarly journals An integrated approach for the evaluation of technological hazard impacts on air quality: the case of the Val d'Agri oil/gas plant

2014 ◽  
Vol 14 (8) ◽  
pp. 2133-2144 ◽  
Author(s):  
M. Calvello ◽  
F. Esposito ◽  
S. Trippetta
Keyword(s):  
Air Quality ◽  
Treatment Plant ◽  
Monitoring Network ◽  
Integrated Approach ◽  
Preliminary Evaluation ◽  
Air Quality Measurements ◽  
Novel Approach ◽  
Starting Point ◽  
Pre Treatment ◽  
Oil Gas

Abstract. The Val d'Agri area (southern Italy) hosts one of the biggest onshore European reservoir and the largest oil/gas pre-treatment plant, named Centro Olio Val d'Agri (COVA), located in a rural/anthropized context. Several hazards are associated with this plant. These are mainly represented by possible impacts of the COVA atmospheric emissions on the local air quality and human health. This work uses a novel approach based on the integration of air quality measurements from the regional monitoring network, additional experimental measurements (i.e. sub-micrometre particulate matter (PM1) and black carbon (BC)) and advanced statistical analyses to provide a preliminary evaluation of the Val d'Agri air quality state and give some indication of specific areas potentially affected by COVA hazards. Results show that the COVA plant emissions have a particular impact on the air quality of the area closest to it. In this area several pollutants specifically related to the COVA combustion processes (i.e. nitrogen oxides, benzene and toluene) show the highest concentration values and significant correlations. The proposed approach represents a first step in the assessment of the risks associated with oil/gas exploration and pre-treatment activities and a starting point for the development of effective and exportable air quality monitoring strategies.

scholarly journals Modelling global tropical cyclone wind footprints

2020 ◽  
Vol 20 (2) ◽  
pp. 567-580 ◽  
Author(s):  
James M. Done ◽  
Ming Ge ◽  
Greg J. Holland ◽  
Ioana Dima-West ◽  
Samuel Phibbs ◽  
...  
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Decay Rates ◽  
Process Models ◽  
Wind Fields ◽  
Surface Drag ◽  
Regional Variability ◽  
Wind Field Model ◽  
Novel Approach ◽  
Variable Surface

Abstract. A novel approach to modelling the surface wind field of landfalling tropical cyclones (TCs) is presented. The modelling system simulates the evolution of the low-level wind fields of landfalling TCs, accounting for terrain effects. A two-step process models the gradient-level wind field using a parametric wind field model fitted to TC track data and then brings the winds down to the surface using a numerical boundary layer model. The physical wind response to variable surface drag and terrain height produces substantial local modifications to the smooth wind field provided by the parametric wind profile model. For a set of US historical landfalling TCs the accuracy of the simulated footprints compares favourably with contemporary modelling approaches. The model is applicable from single-event simulation to the generation of global catalogues. One application demonstrated here is the creation of a dataset of 714 global historical TC overland wind footprints. A preliminary analysis of this dataset shows regional variability in the inland wind speed decay rates and evidence of a strong influence of regional orography. This dataset can be used to advance our understanding of overland wind risk in regions of complex terrain and support wind risk assessments in regions of sparse historical data.

scholarly journals Technical Note: A novel approach to estimation of time-variable surface sources and sinks of carbon dioxide using empirical orthogonal functions and the Kalman filter

2011 ◽  
Vol 11 (20) ◽  
pp. 10305-10315 ◽  
Author(s):  
R. Zhuravlev ◽  
B. Khattatov ◽  
B. Kiryushov ◽  
S. Maksyutov
Keyword(s):  
Carbon Dioxide ◽  
Kalman Filter ◽  
Carbon Dioxide Emissions ◽  
Transport Model ◽  
Technical Note ◽  
Empirical Orthogonal Functions ◽  
Surface Fluxes ◽  
Orthogonal Functions ◽  
Novel Approach ◽  
Variable Surface

Abstract. In this work we propose an approach to solving a source estimation problem based on representation of carbon dioxide surface emissions as a linear combination of a finite number of pre-computed empirical orthogonal functions (EOFs). We used National Institute for Environmental Studies (NIES) transport model for computing response functions and Kalman filter for estimating carbon dioxide emissions. Our approach produces results similar to these of other models participating in the TransCom3 experiment. Using the EOFs we can estimate surface fluxes at higher spatial resolution, while keeping the dimensionality of the problem comparable with that in the regions approach. This also allows us to avoid potentially artificial sharp gradients in the fluxes in between pre-defined regions. EOF results generally match observations more closely given the same error structure as the traditional method. Additionally, the proposed approach does not require additional effort of defining independent self-contained emission regions.

scholarly journals FLEXINVERT: an atmospheric Bayesian inversion framework for determining surface fluxes of trace species using an optimized grid

2014 ◽  
Vol 7 (3) ◽  
pp. 3751-3801
Author(s):  
R. L. Thompson ◽  
A. Stohl
Keyword(s):  
Dispersion Model ◽  
Particle Dispersion ◽  
Linear Process ◽  
Surface Fluxes ◽  
Bayesian Inversion ◽  
Mixing Ratios ◽  
Trace Species ◽  
Methane Fluxes ◽  
Spatio Temporal ◽  
Atmospheric Loss

Abstract. We present a new modular Bayesian inversion framework, called FLEXINVERT, for estimating the surface fluxes of atmospheric trace species. FLEXINVERT can be applied to determine the spatio-temporal flux distribution of any species for which the atmospheric loss (if any) can be described as a linear process and can be used on continental to regional and even local scales with little or no modification. The relationship between changes in atmospheric mixing ratios and fluxes (the so-called source–receptor relationship) is described by a Lagrangian Particle Dispersion Model (LPDM) run in a backwards in time mode. In this study, we use FLEXPART but any LPDM could be used. The framework determines the fluxes on a nested grid of variable resolution, which is optimized based on the source–receptor relationships for the given observation network. Background mixing ratios are determined by coupling FLEXPART to the output of a global Eulerian model (or alternatively, from the observations themselves) and are also optionally optimized in the inversion. Spatial and temporal error correlations in the fluxes are taken into account using a simple model of exponential decay with space and time and, additionally, the aggregation error from the variable grid is accounted for. To demonstrate the use of FLEXINVERT, we present one case study in which methane fluxes are estimated in Europe in 2011 and compare the results to those of an independent inversion ensemble.

Inverse modeling of halocarbons: sensitivity to the baseline definition

2021 ◽  
Author(s):  
Martin Vojta ◽  
Rona Thompson ◽  
Christine Groot Zwaaftink ◽  
Andreas Stohl
Keyword(s):  
Atmospheric Chemistry ◽  
Inverse Modeling ◽  
Sulfur Hexafluoride ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Lagrangian Particle ◽  
Global Fields ◽  
Mixing Ratios ◽  
Model Based

<p>The identification of the baseline is an important task in inverse modeling of greenhouse gases, as it represents the influence of atmospheric chemistry and transport and surface fluxes from outside the inversion domain, or flux contributions prior to the length of the backward calculation for Lagrangian models. When modeling halocarbons, observation-based approaches are often used to calculate the baseline, although model-based approaches are an alternative. Model-based methods need global unbiased fields of mixing ratios of the observed species, which are not always easy to get and which need to be interfaced with the model used for the inversion. To find the best way to identify the baseline and to investigate whether the usage of observation-based approaches is suitable for inverse modeling of halocarbons, we use and analyze a model-based and two frequently used observation-based methods to determine the baseline and investigate their influence on inversion results. The model-based method couples global fields of mixing ratios with backwards-trajectories at their point of termination. We simulate those global fields with a Lagrangian particle dispersion model, FLEXPART_CTM, that uses a nudging routine to relax model data to observed values. The second method under investigation is the robust estimation of baseline signal (REBS) method, that is purely based on statistical analysis of observations. The third analyzed method is also primarily observation-based, but uses model information to subtract prior simulated mixing ratios from selected observations. We apply those three methods to sulfur hexafluoride (SF<sub>6</sub>) and use the Bayesian inversion framework FLEXINVERT for the inverse modeling and the Lagrangian particle dispersion model FLEXPART to calculate the source-receptor-relationship used in the inversion.</p>

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