scholarly journals Towards a new multiscale air quality transport model using the fully unstructured anisotropic adaptive mesh technology of Fluidity (version 4.1.9)

2015 ◽  
Vol 8 (10) ◽  
pp. 3421-3440 ◽  
Author(s):  
J. Zheng ◽  
J. Zhu ◽  
Z. Wang ◽  
F. Fang ◽  
C. C. Pain ◽  
...  

Abstract. An integrated method of advanced anisotropic hr-adaptive mesh and discretization numerical techniques has been, for first time, applied to modelling of multiscale advection–diffusion problems, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been set up for two-dimensional (2-D) advection phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes. Performance achieved in 3-D simulation of power plant plumes indicates that this new adaptive multiscale model has the potential to provide accurate air quality modelling solutions effectively.

2015 ◽  
Vol 8 (6) ◽  
pp. 4337-4374
Author(s):  
J. Zheng ◽  
J. Zhu ◽  
Z. Wang ◽  
F. Fang ◽  
C. C. Pain ◽  
...  

Abstract. A new anisotropic hr-adaptive mesh technique has been applied to modelling of multiscale transport phenomena, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been setup for two-dimensional (2-D) transport phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes.


SPE Journal ◽  
2016 ◽  
Vol 21 (06) ◽  
pp. 2250-2259 ◽  
Author(s):  
Peyman Mostaghimi ◽  
Fatemeh Kamali ◽  
Matthew D. Jackson ◽  
Ann H. Muggeridge ◽  
Christopher C. Pain

Summary Viscous fingering can be a major concern when waterflooding heavy-oil reservoirs. Most commercial reservoir simulators use low-order finite-volume/-difference methods on structured grids to resolve this phenomenon. However, this approach suffers from a significant numerical-dispersion error because of insufficient mesh resolution, which smears out some important features of the flow. We simulate immiscible incompressible two-phase displacements and propose the use of unstructured control-volume finite-element (CVFE) methods for capturing viscous fingering in porous media. Our approach uses anisotropic mesh adaptation where the mesh resolution is optimized on the basis of the evolving features of flow. The adaptive algorithm uses a metric tensor field dependent on solution-interpolation-error estimates to locally control the size and shape of elements in the metric. The mesh optimization generates an unstructured finer mesh in areas of the domain where flow properties change more quickly and a coarser mesh in other regions where properties do not vary so rapidly. We analyze the computational cost of mesh adaptivity on unstructured mesh and compare its results with those obtained by a commercial reservoir simulator on the basis of the finite-volume methods.


2012 ◽  
Vol 5 (6) ◽  
pp. 1565-1587 ◽  
Author(s):  
G. Lacressonnière ◽  
V.-H. Peuch ◽  
J. Arteta ◽  
B. Josse ◽  
M. Joly ◽  
...  

Abstract. Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period; analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run results in a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 5-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure, etc.) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities, etc.). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O3, NOx, SO2 and, with some bias that can be explained by the set-up, PM10. We study how the simulations driven by climate forcings differ, both due to the realism of the forcings (lack of data assimilated and lower resolution) and due to the lack of representation of the actual chronology of events. We conclude that the indicators such as mean bias, mean normalized bias, RMSE and deviation standards can be used to interpret the results with some confidence as well as the health-related indicators such as the number of days of exceedance of regulatory thresholds. These metrics are thus considered to be suitable for the interpretation of simulations of the future evolution of European air quality.


2012 ◽  
Vol 5 (3) ◽  
pp. 2083-2138
Author(s):  
G. Lacressonnière ◽  
V.-H. Peuch ◽  
J. Arteta ◽  
B. Josse ◽  
M. Joly ◽  
...  

Abstract. Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period: analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run is a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 6-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure \\ldots) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities . . .). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O3, NOx, SO2 and, with some bias that can be explained by the set-up, PM10. We study how the simulations driven by climate forcings differ, both due to the realism of the forcings (lack of data assimilated and lower resolution) and due to the lack of representation of the actual chronology of events. We conclude that the indicators such as mean bias, mean normalized bias, RMSE and deviation standards can be used to interpret the results with some confidence as well as the health-related indicators such as SOMO35 and the number of days of exceedance of regulatory thresholds. These metrics are thus considered to be suitable for the interpretation of simulations of the future evolution of European air quality.


2019 ◽  
Vol 490 (1) ◽  
pp. L52-L56
Author(s):  
Bastian Sander ◽  
Gerhard Hensler

ABSTRACT This paper aims at studying the reliability of a few frequently raised, but not proven, arguments for the modelling of cold gas clouds embedded in or moving through a hot plasma and at sensitizing modellers to a more careful consideration of unavoidable acting physical processes and their relevance. At first, by numerical simulations we demonstrate the growing effect of self-gravity on interstellar clouds and, by this, moreover argue against their initial set-up as homogeneous. We apply the adaptive-mesh refinement code flash with extensions to metal-dependent radiative cooling and external heating of the gas, self-gravity, mass diffusion, and semi-analytic dissociation of molecules, and ionization of atoms. We show that the criterion of Jeans mass or Bonnor–Ebert mass, respectively, provides only a sufficient but not a necessary condition for self-gravity to be effective, because even low-mass clouds are affected on reasonable dynamical time-scales. The second part of this paper is dedicated to analytically study the reduction of heat conduction by a magnetic dipole field. We demonstrate that in this configuration, the effective heat flow, i.e. integrated over the cloud surface, is suppressed by only 32 per cent by magnetic fields in energy equipartition and still insignificantly for even higher field strengths.


Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 91
Author(s):  
Santiago Lopez-Restrepo ◽  
Andres Yarce ◽  
Nicolás Pinel ◽  
O.L. Quintero ◽  
Arjo Segers ◽  
...  

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.


Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 467
Author(s):  
Rocío Baró ◽  
Christian Maurer ◽  
Jerome Brioude ◽  
Delia Arnold ◽  
Marcus Hirtl

This paper demonstrates the environmental impacts of the wildfires occurring at the beginning of April 2020 in and around the highly contaminated Chernobyl Exclusion Zone (CEZ). Due to the critical fire location, concerns arose about secondary radioactive contamination potentially spreading over Europe. The impact of the fire was assessed through the evaluation of fire plume dispersion and re-suspension of the radionuclide Cs-137, whereas, to assess the smoke plume effect, a WRF-Chem simulation was performed and compared to Tropospheric Monitoring Instrument (TROPOMI) satellite columns. The results show agreement of the simulated black carbon and carbon monoxide plumes with the plumes as observed by TROPOMI, where pollutants were also transported to Belarus. From an air quality and health perspective, the wildfires caused extremely bad air quality over Kiev, where the WRF-Chem model simulated mean values of PM2.5 up to 300 µg/m3 (during the first fire outbreak) over CEZ. The re-suspension of Cs-137 was assessed by a Bayesian inverse modelling approach using FLEXPART as the atmospheric transport model and Ukraine observations, yielding a total release of 600 ± 200 GBq. The increase in both smoke and Cs-137 emissions was only well correlated on the 9 April, likely related to a shift of the focus area of the fires. From a radiological point of view even the highest Cs-137 values (average measured or modelled air concentrations and modelled deposition) at the measurement site closest to the Chernobyl Nuclear Power Plant, i.e., Kiev, posed no health risk.


2018 ◽  
Author(s):  
Matthias Karl

Abstract. This paper describes the City-scale Chemistry (CityChem) extension of the urban dispersion model EPISODE with the aim to enable chemistry/transport simulations of multiple reactive pollutants on urban scales. The new model is called CityChem-EPISODE. The primary focus is on the simulation of urban ozone concentrations. Ozone is produced in photochemical reaction cycles involving nitrogen oxides (NOx) and volatile organic compounds (VOC) emitted by various anthropogenic activities in the urban area. The performance of the new model was evaluated with a series of synthetic tests and with a first application to the air quality situation in the city of Hamburg, Germany. The model performs fairly well for ozone in terms of temporal correlation and bias at the air quality monitoring stations in Hamburg. In summer afternoons, when photochemical activity is highest, modelled median ozone at an inner-city urban background station was about 30 % lower than the observed median ozone. Inaccuracy of the computed photolysis frequency of nitrogen dioxide (NO2) is the most probable explanation for this. CityChem-EPISODE reproduces the spatial variation of annual mean NO2 concentrations between urban background, traffic and industrial stations. However, the temporal correlation between modelled and observed hourly NO2 concentrations is weak for some of the stations. For daily mean PM10, the performance of CityChem-EPISODE is moderate due to low temporal correlation. The low correlation is linked to uncertainties in the seasonal cycle of the anthropogenic particulate matter (PM) emissions within the urban area. Missing emissions from domestic heating might be an explanation for the too low modelled PM10 in winter months. Four areas of need for improvement have been identified: (1) dry and wet deposition fluxes; (2) treatment of photochemistry in the urban atmosphere; (3) formation of secondary inorganic aerosol (SIA); and (4) formation of biogenic and anthropogenic secondary organic aerosol (SOA). The inclusion of secondary aerosol formation will allow for a better sectorial attribution of observed PM levels. Envisaged applications of the CityChem-EPISODE model are urban air quality studies, environmental impact assessment, sensitivity analysis of sector-specific emission and the assessment of local and regional emission abatement policy options.


Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 200
Author(s):  
Ana Ascenso ◽  
Carla Gama ◽  
Daniel Blanco-Ward ◽  
Alexandra Monteiro ◽  
Carlos Silveira ◽  
...  

Tropospheric ozone (O3) can strongly damage vegetation. Grapevines (Vitis vinifera L.), in particular, have intermediate sensitivity to ozone. Wine production is an important economic activity, as well as a pillar to the cultural identity of several countries in the world. This study aims to evaluate the risk of Douro vineyards exposure to ozone, by estimating its concentration and deposition in the Demarcated Region of Douro in Portugal. Based on an assessment of the climatology of the area, the years 2003 to 2005 were selected among the hottest years of the recent past, and the chemical transport model CHIMERE was used to estimate the three-dimensional field of ozone and its dry deposition over the Douro region with 1 km2 of horizontal resolution. Model results were validated by comparison with measured data from the European air quality database (AirBase). The exposure indicator AOT40 (accumulated concentration of ozone above 40 ppb) was calculated and an exposure–response function was applied to determine the grapevine risk to ozone exposure. The target value for the protection of vegetation established by the Air Quality Framework Directive was exceeded on most of the Douro region, especially over the Baixo Corgo and Cima Corgo sub-regions. The results of the exposure–response functions suggest that the productivity loss can reach 27% and that the sugar content of the grapes could be reduced by 32%, but these values are affected by the inherent uncertainty of the used methodology.


2016 ◽  
Author(s):  
Dipesh Rupakheti ◽  
Bhupesh Adhikary ◽  
Puppala S. Praveen ◽  
Maheswar Rupakheti ◽  
Shichang Kang ◽  
...  

Abstract. Lumbini, in southern Nepal, is a UNESCO world heritage site of universal value as the birthplace of Buddha. Poor air quality in Lumbini and surrounding regions is a great concern for public health as well as for preservation, protection and promotion of Buddhist heritage and culture. We present here results from measurements of ambient concentrations of key air pollutants (PM, BC, CO, O3) in Lumbini, first of its kind for Lumbini, conducted during an intensive measurement period of three months (April–June 2013) in the pre-monsoon season. The measurements were carried out as a part of the international air pollution measurement campaign; SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley – Atmospheric Brown Clouds). The ranges of hourly average concentrations were: PM10: 10.5–604.0 µg m−3, PM2.5: 6.1–272.2 µg m−3; BC: 0.3–30.0 µg m−3; CO: 125.0–1430.0 ppbv; and O3: 1.0–118.1 ppbv. These levels are comparable to other very heavily polluted sites throughout South Asia. The 24-h average PM2.5 and PM10 concentrations exceeded the WHO guideline very frequently (94 % and 85 % of the sampled period, respectively), which implies significant health risks for the residents and visitors in the region. These air pollutants exhibited clear diurnal cycles with high values in the morning and evening. During the study period, the worst air pollution episodes were mainly due to agro-residue burning and regional forest fires combined with meteorological conditions conducive of pollution transport to Lumbini. Fossil fuel combustion also contributed significantly, accounting for more than half of the ambient BC concentration according to aerosol spectral light absorption coefficients obtained in Lumbini. WRF-STEM, a regional chemical transport model, was used to simulate the meteorology and the concentrations of pollutants. The model was able to reproduce the variation in the pollutant concentrations well; however, estimated values were 1.5 to 5 times lower than the observed concentrations for CO and PM10 respectively. Regionally tagged CO tracers showed the majority of CO came from the upwind region of Ganges valley. The model was also used to examine the chemical composition of the aerosol mixture, indicating that organic carbon was the main constituent of fine mode PM2.5, followed by mineral dust. Given the high pollution level, there is a clear and urgent need for setting up a network of long-term air quality monitoring stations in the greater Lumbini region.


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