Modeled based analysis of fish farm emissions impact on the fjord biogeochemistry

2020 ◽  
Author(s):  
Evgeniy Yakushev ◽  
Anfisa Berezina
Keyword(s):  
Organic Matter ◽  
Transport Model ◽  
Model Performance ◽  
Oxygen Depletion ◽  
Horizontal Resolution ◽  
Fish Farm ◽  
Transformation Model ◽  
Model Data ◽  
Sulfur Reduction ◽  
Satisfactory Model

<p>To investigate the impacts of fish farm emissions, we coupled the biogeochemical C-N-P-Si-O-S-Mn-Fe transformation model BROM with a 2-Dimensional Benthic-Pelagic transport model (2DBP), considering vertical and horizontal transport in the water and upper 5 cm  sediments along a 10000 m transect centered on a fish farm. The 2DBP model had 25 m horizontal resolution and was forced by hydrophysical model data for the Hardangerfjord in western Norway. The model predicted significant impacts on seafloor biogeochemistry up to 500 meters from the fish farm (e.g., increased organic matter in sediments, oxygen depletion in water and sediments, denitrification, metal and sulfur reduction) as well as detectable decreases in oxygen and increases in ammonia, phosphate and organic matter in the water near to the fish farm cages. The model results are compared with field data from the Hardangerfjord in August 2016 and indicated satisfactory model performance.</p>

scholarly journals Understanding the Biogeochemical Impacts of Fish Farms Using a Benthic-Pelagic Model

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2384
Author(s):  
Evgeniy Yakushev ◽  
Philip Wallhead ◽  
Paul Renaud ◽  
Alisa Ilinskaya ◽  
Elizaveta Protsenko ◽  
...  
Keyword(s):  
Organic Matter ◽  
Transport Model ◽  
Ammonium Phosphate ◽  
Oxygen Depletion ◽  
Fish Farm ◽  
Transformation Model ◽  
Fish Farms ◽  
Spatial And Temporal Scales ◽  
Benthic Biogeochemistry ◽  
Farming Industry

Sustainable development of the salmon farming industry requires knowledge of the biogeochemical impacts of fish farm emissions. To investigate the spatial and temporal scales of farm impacts on the water column and benthic biogeochemistry, we coupled the C-N-P-Si-O-S-Mn-Fe transformation model BROM with a 2-dimensional benthic-pelagic transport model (2DBP), considering vertical and horizontal transport in the water and upper 5 cm of sediments along a 10 km transect centered on a fish farm. The 2DBP model was forced by hydrophysical model data for the Hardangerfjord in western Norway. Model simulations showed reasonable agreement with field data from the Hardangerfjord in August 2016 (correlations between the model and observations were significant for most variables, and model biases were mostly <35%). The model predicted significant impacts on seafloor biogeochemistry up to 1 km from the fish farm (e.g., increased organic matter in sediments, oxygen depletion in bottom water and sediments, denitrification, metal and sulfur reduction), as well as detectable decreases in oxygen and increases in ammonium, phosphate and organic matter in the surface water near to the fish farm.

scholarly journals Analysis of the potential of near ground measurements of CO<sub>2</sub> and CH<sub>4</sub> in London, UK for the monitoring of city-scale emissions using an atmospheric transport model

2015 ◽  
Vol 15 (22) ◽  
pp. 33003-33048
Author(s):  
A. Boon ◽  
G. Broquet ◽  
D. J. Clifford ◽  
F. Chevallier ◽  
D. M. Butterfield ◽  
...  
Keyword(s):  
Reference Site ◽  
Emission Inventory ◽  
Fossil Fuel ◽  
Transport Model ◽  
Mixing Layer ◽  
Horizontal Resolution ◽  
The Other ◽  
Model Data ◽  
The City ◽  
Urban Sites

Abstract. Carbon dioxide (CO2) and methane (CH4) mole fractions were measured at four near ground sites located in and around London during the summer of 2012 in view to investigate the potential of assimilating such measurements in an atmospheric inversion system for the monitoring of the CO2 and CH4 emissions in the London area. These data were analysed and compared with simulations using a modelling framework suited to building an inversion system: a 2 km horizontal resolution South of England configuration of the transport model CHIMERE driven by European Centre for Medium-Range Weather Forecasting (ECMWF) meteorological forcing, coupled to a 1 km horizontal resolution emission inventory (the UK National Atmospheric Emission Inventory). First comparisons reveal that local sources have a large impact on measurements and these local sources cannot be represented in the model at 2 km resolution. We evaluate methods to minimise some of the other critical sources of misfits between the observation data and the model simulation that overlap the signature of the errors in the emission inventory. These methods should make it easier to identify the corrections that should be applied to the inventory. Analysis is supported by observations from meteorological sites around the city and a three-week period of atmospheric mixing layer height estimations from lidar measurements. The difficulties of modelling the mixing layer depth and thus CO2 and CH4 concentrations during the night, morning and late afternoon led us to focus on the afternoon period for all further analyses. The misfits between observations and model simulations are high for both CO2 and CH4 (i.e., their root mean square (RMS) is between 8 and 12 parts per million (ppm) for CO2 and between 30 and 55 parts per billion (ppb) for CH4 at a given site). By analysing the gradients between the urban sites and a suburban or rural reference site, we are able to decrease the impact of uncertainties in the fluxes and transport outside the London area and in the model domain boundary conditions, and to better focus attention on the signature of London urban CO2 and CH4 emissions. This considerably improves the statistical agreement between the model and observations for CO2 (model–data RMS misfit of between 3 and 7 ppm) and to a lesser degree for CH4 (model–data RMS misfit of between 29 and 38 ppb). Between one of the urban sites and either reference site, selecting the gradients during periods wherein the reference site is upwind of the urban site further decreases the statistics of the misfits in general even though not systematically. In a final attempt to focus on the signature of the city anthropogenic emission in the mole fraction measurements, we use a theoretical ratio of gradients of CO to gradients of CO2 from fossil fuel emissions in the London area to diagnose observation based fossil fuel CO2 gradients, and compare them with the modelled ones. This estimate increases the consistency between the model and the measurements when considering one of the urban sites, but not when considering the other. While this study evaluates different approaches for increasing the consistency between the mesoscale model and the near ground data, and manages to decrease the random component of the analysed model data misfits to an extent that should not be prohibitive to extracting the signal from the London urban emissions, large biases remain in the final misfits. These biases are likely to be due to local emissions, to which the urban near ground sites are highly sensitive. This questions our current ability to exploit urban near ground data for the atmospheric inversion of city emissions based on models at spatial resolution coarser than 2 km.

scholarly journals High resolution air quality simulation over Europe with the chemistry transport model CHIMERE

2013 ◽  
Vol 6 (3) ◽  
pp. 4137-4187 ◽  
Author(s):  
E. Terrenoire ◽  
B. Bessagnet ◽  
L. Rouïl ◽  
F. Tognet ◽  
G. Pirovano ◽  
...  
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Mean Squared Error ◽  
Transport Model ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Eastern European ◽  
Rural And Urban ◽  
Good Reproduction ◽  
Eastern European Countries

Abstract. A high resolution air quality simulation (0.125° × 0.0625° horizontal resolution) performed over Europe for the year 2009 has been evaluated using both rural and urban background stations available over most of the domain. Using seasonal and yearly mean statistical indicators such as the correlation index, the fractional bias and the root mean squared error; we interpret objectively the performance of the simulation. Positive outcomes are: a very good reproduction of the daily variability at UB sites for O3 (R =0.73) as well as for NO2 (R =0.61); a very low bias calculated at UB stations for PM2.5 (FB = −6.4%) and PM10 concentrations (FB = −20.1%). Conversely, main weaknesses in model performance include: the underestimation of the NO2 daily maxima at UB site (FB = −53.6%); an overall underestimation of PM10 and PM2.5 concentrations observed over Eastern European countries (e.g. Poland); the overestimation of sulphates concentrations at spring time (FB = 53.7%); finally, over the year, total nitrate and ammonia concentrations are better reproduced than nitrate and ammonium aerosol phase compounds. Obtained results suggest that, in order to improve the model performances, efforts should focus on the improvement of the emission inventory quality for Eastern Europeans countries and the improvement of a specific parameterisation in the model to better account for the urban effect on meteorology and air pollutants concentrations.

scholarly journals Simulating CH<sub>4</sub> and CO<sub>2</sub> over South and East Asia using the zoomed chemistry transport model LMDzINCA

2017 ◽  
Author(s):  
Xin Lin ◽  
Philippe Ciais ◽  
Philippe Bousquet ◽  
Michel Ramonet ◽  
Yi Yin ◽  
...  
Keyword(s):  
East Asia ◽  
Transport Model ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Surface Fluxes ◽  
Vertical Resolution ◽  
Monitoring Networks ◽  
Atmospheric Measurements ◽  
Monsoon Period ◽  
Chemistry Transport Model

Abstract. The increasing availability of atmospheric measurements of greenhouse gases (GHGs) from surface stations can improve the retrieval of their fluxes at higher spatial and temporal resolutions by inversions, provided that chemistry transport models are able to properly represent the variability of concentrations observed at different stations. South and East Asia (SEA) is a region with large and very uncertain emissions of carbon dioxide (CO2) and methane (CH4), the most potent anthropogenic GHGs. Monitoring networks have expanded greatly during the past decade in this region, which should contribute to reducing uncertainties in estimates of regional GHG budgets. In this study, we simulate concentrations of CH4 and CO2 using a zoomed version of the global chemistry transport model LMDzINCA during the period 2006–2013. The zoomed version has a fine horizontal resolution of ~ 0.66° in longitude and ~0.51° in latitude over SEA and a coarser resolution elsewhere. The concentrations of CH4 and CO2 simulated from the zoomed model (abbreviated as ‘ZASIA’) are compared to those from the same model but with a uniform regular grid of 2.50° in longitude and 1.27° in latitude (abbreviated as ‘REG’), both having the same vertical 19 sigma pressure levels and prescribed with the same biogenic and anthropogenic fluxes. Model performance is evaluated for annual gradients between sites, seasonal, synoptic and diurnal variations, against a new dataset including 30 surface stations over SEA and adjacent regions. Our results show that, when prescribed with identical surface fluxes, compared to REG, the ZASIA version moderately improves the representation of CH4 mean annual gradients between stations as well as the seasonal and synoptic variations of this trace gas within the zoomed region. This moderate improvement probably results from reduction of representation errors and a better description of the CH4 concentration gradients related to the skewed spatial distribution of surface CH4 emissions, suggesting that the zoom transport model will be better suited for inversions of CH4 fluxes in SEA. With the relatively coarse vertical resolution and low-frequency (monthly) prescribed fluxes, the model generally does not capture the diurnal cycle of CH4 at most stations even with its zoomed configuration, emphasizing the need to increase the vertical resolution, and to improve parameterizations of turbulent diffusion in the planetary boundary layer and deep convection during the monsoon period. The model performance for CH4 is better than that for CO2 at any temporal scale, likely due to inaccuracies in the CO2 fluxes prescribed in this study.

Intercomparison of atmospheric transport models using 1 km grid meteorological data for the Fukushima Daiichi Nuclear Power Plant Accident

2020 ◽  
Author(s):  
Hiromi Yamazawa ◽  
Yousuke Sato ◽  
Tsuyoshi Sekiyama ◽  
Mizuo Kajino ◽  
Daisuke Goto ◽  
...  
Keyword(s):  
Nuclear Power ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Meteorological Data ◽  
Model Performance ◽  
Aerial Survey ◽  
Horizontal Resolution ◽  
Horizontal Distribution ◽  
Middle Part ◽  
Model Intercomparison

&lt;p&gt;&amp;#160; Following the previous atmospheric transport model intercomparison project (MIP2: Sato et al, 2018), a new project of model intercomparison (MIP3) has been conducted in which, out of 12 models in MIP2, 9 models are participating. The main aim of MIP3 is to examine the effects of using a refined meteorological data with a finer horizontal resolution of 1 km (Sekiyama et al., 2019). This paper describes outline of the preliminary results of MIP3.&lt;/p&gt;&lt;p&gt;&amp;#160; The horizontal distribution Cs-137 deposition in the eastern part of Honshu Island (the main island of Japan) calculated by the models were compared with the aerial survey results to find that the simple ensemble average of the 9 models was a little worse than that of the 12-model ensemble in MIP2 in terms of the statistical index RANK, which is the combination of the correlation coefficient, the fractional bias, the figure of merit in space and KPS. This slightly poorer performance is tentatively considered to be caused partially by the absence of three models which showed rather broad deposition patterns and by the underestimation in the Nakadori area (the middle part of Fukushima Pref.). However, in the sector in the northwestern direction from the accidental site which had the largest deposition, the deposition pattern simulated by the MIP3 ensemble, if compared with that of MIP2, is more consistent with the survey result. As for the atmospheric concentrations, although the model performance for the plumes that traveled over wider areas was found to be slightly poorer for MIP3 than MIP2, it was found that the MIP3 ensemble generally showed better performance for the plumes that affected the near area in the Hamadori area (the coastal part of Fukushima Pref.). The better performance of the MIP3 in this area can be attributed to the better representation of topography in the meteorological simulation.&lt;/p&gt;

scholarly journals Analysis of the potential of near-ground measurements of CO<sub>2</sub> and CH<sub>4</sub> in London, UK, for the monitoring of city-scale emissions using an atmospheric transport model

2016 ◽  
Vol 16 (11) ◽  
pp. 6735-6756 ◽  
Author(s):  
Alex Boon ◽  
Grégoire Broquet ◽  
Deborah J. Clifford ◽  
Frédéric Chevallier ◽  
David M. Butterfield ◽  
...  
Keyword(s):  
Reference Site ◽  
Emission Inventory ◽  
Fossil Fuel ◽  
Transport Model ◽  
Mixing Layer ◽  
Horizontal Resolution ◽  
Model Data ◽  
The Impact ◽  
The City ◽  
Urban Sites

Abstract. Carbon dioxide (CO2) and methane (CH4) mole fractions were measured at four near-ground sites located in and around London during the summer of 2012 with a view to investigating the potential of assimilating such measurements in an atmospheric inversion system for the monitoring of the CO2 and CH4 emissions in the London area. These data were analysed and compared with simulations using a modelling framework suited to building an inversion system: a 2 km horizontal resolution south of England configuration of the transport model CHIMERE driven by European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological forcing, coupled to a 1 km horizontal resolution emission inventory (the UK National Atmospheric Emission Inventory). First comparisons reveal that local sources, which cannot be represented in the model at a 2 km resolution, have a large impact on measurements. We evaluate methods to filter out the impact of some of the other critical sources of discrepancies between the measurements and the model simulation except that of the errors in the emission inventory, which we attempt to isolate. Such a separation of the impact of errors in the emission inventory should make it easier to identify the corrections that should be applied to the inventory. Analysis is supported by observations from meteorological sites around the city and a 3-week period of atmospheric mixing layer height estimations from lidar measurements. The difficulties of modelling the mixing layer depth and thus CO2 and CH4 concentrations during the night, morning and late afternoon lead to focusing on the afternoon period for all further analyses. The discrepancies between observations and model simulations are high for both CO2 and CH4 (i.e. their root mean square (RMS) is between 8 and 12 parts per million (ppm) for CO2 and between 30 and 55 parts per billion (ppb) for CH4 at a given site). By analysing the gradients between the urban sites and a suburban or rural reference site, we are able to decrease the impact of uncertainties in the fluxes and transport outside the London area and in the model domain boundary conditions. We are thus able to better focus attention on the signature of London urban CO2 and CH4 emissions in the atmospheric CO2 and CH4 concentrations. This considerably improves the statistical agreement between the model and observations for CO2 (with model–data RMS discrepancies that are between 3 and 7 ppm) and to a lesser degree for CH4 (with model–data RMS discrepancies that are between 29 and 38 ppb). Between one of the urban sites and either the rural or suburban reference site, selecting the gradients during periods wherein the reference site is upwind of the urban site further decreases the statistics of the discrepancies in general, though not systematically. In a further attempt to focus on the signature of the city anthropogenic emission in the mole fraction measurements, we use a theoretical ratio of gradients of carbon monoxide (CO) to gradients of CO2 from fossil fuel emissions in the London area to diagnose observation-based fossil fuel CO2 gradients, and compare them with the fossil fuel CO2 gradients simulated with CHIMERE. This estimate increases the consistency between the model and the measurements when considering only one of the two urban sites, even though the two sites are relatively close to each other within the city. While this study evaluates and highlights the merit of different approaches for increasing the consistency between the mesoscale model and the near-ground data, and while it manages to decrease the random component of the analysed model–data discrepancies to an extent that should not be prohibitive to extracting the signal from the London urban emissions, large biases, the sign of which depends on the measurement sites, remain in the final model–data discrepancies. Such biases are likely related to local emissions to which the urban near-ground sites are highly sensitive. This questions our current ability to exploit urban near-ground data for the atmospheric inversion of city emissions based on models at spatial resolution coarser than 2 km. Several measurement and modelling concepts are discussed to overcome this challenge.

scholarly journals Twelve-month, 12 km resolution North American WRF-Chem v3.4 air quality simulation: performance evaluation

2014 ◽  
Vol 7 (6) ◽  
pp. 8433-8476 ◽  
Author(s):  
C. W. Tessum ◽  
J. D. Hill ◽  
J. D. Marshall
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Model Performance ◽  
Predictive Performance ◽  
Horizontal Resolution ◽  
Basis Set ◽  
Chemical Transport Model ◽  
High Concentration ◽  
Annual Average ◽  
Simulation Performance

Abstract. We present results from and evaluate the performance of a 12 month, 12 km horizontal resolution air pollution simulation for the contiguous United States using the WRF-Chem (Weather Research and Forecasting with Chemistry) meteorology and chemical transport model (CTM). We employ the 2005 US National Emissions Inventory, the Regional Atmospheric Chemistry Mechanism (RACM), and the Modal Aerosol Dynamics Model for Europe (MADE) with a Volatility Basis Set (VBS) secondary aerosol module. Overall, model performance is comparable to contemporary models used for regulatory and health-effects analysis, with an annual average daytime ozone (O3) mean fractional bias (MFB) of 12% and an annual average fine particulate matter (PM2.5) MFB of −1%. WRF-Chem, as configured here, tends to overpredict total PM2.5 at some high concentration locations, and generally overpredicts average 24 h O3 concentrations, with better performance at predicting average daytime and daily peak O3 concentrations. Predictive performance for PM2.5 subspecies is mixed: the model overpredicts particulate sulfate (MFB = 65%), underpredicts particulate nitrate (MFB = −110%) and organic carbon (MFB = −65%), and relatively accurately predicts particulate ammonium (MFB = 3%) and elemental carbon (MFB = 3%), so that the accuracy in total PM2.5 predictions is to some extent a function of offsetting over- and underpredictions of PM2.5 subspecies. Model predictive performance for PM2.5 and its subspecies is in general worse in winter and in the western US than in other seasons and regions, suggesting spatial and temporal opportunities for future WRF-Chem model development and evaluation.

scholarly journals Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 91
Author(s):  
Santiago Lopez-Restrepo ◽  
Andres Yarce ◽  
Nicolás Pinel ◽  
O.L. Quintero ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Transport Model ◽  
Cost Model ◽  
Low Cost ◽  
Model Performance ◽  
Monitoring Network ◽  
Correlation Factor ◽  
Chemical Transport Model ◽  
High Quality

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.

scholarly journals The On-Line Integrated Mesoscale Chemistry Model BOLCHEM

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 192
Author(s):  
Rita Cesari ◽  
Tony Christian Landi ◽  
Massimo D’Isidoro ◽  
Mihaela Mircea ◽  
Felicita Russo ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Transport Model ◽  
Horizontal Resolution ◽  
Integration Step ◽  
Chemistry Transport Model ◽  
European Environmental Agency ◽  
On Line ◽  
One Year ◽  
Pm2.5 And Pm10 ◽  
Monitoring Service

This work presents the on-line coupled meteorology–chemistry transport model BOLCHEM, based on the hydrostatic meteorological BOLAM model, the gas chemistry module SAPRC90, and the aerosol dynamic module AERO3. It includes parameterizations to describe natural source emissions, dry and wet removal processes, as well as the transport and dispersion of air pollutants. The equations for different processes are solved on the same grid during the same integration step, by means of a time-split scheme. This paper describes the model and its performance at horizontal resolution of 0.2∘× 0.2∘ over Europe and 0.1∘× 0.1∘ in a nested configuration over Italy, for one year run (December 2009–November 2010). The model has been evaluated against the AIRBASE data of the European Environmental Agency. The basic statistics for higher resolution simulations of O3, NO2 and particulate matter concentrations (PM2.5 and PM10) have been compared with those from Copernicus Atmosphere Monitoring Service (CAMS) ensemble median. In summer, for O3 we found a correlation coefficient R of 0.72 and mean bias of 2.15 over European domain and a correlation coefficient R of 0.67 and mean bias of 2.36 over Italian domain. PM10 and PM2.5 are better reproduced in the winter, the latter with a correlation coefficient R of 0.66 and the mean bias MB of 0.35 over Italian domain.

scholarly journals Automatic transport model data assimilation in Laplace space

2012 ◽  
Vol 48 (1) ◽  
Author(s):  
K. S. Barnhart ◽  
T. H. Illangasekare
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Model Data
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