scholarly journals A field study to estimate the impact of noise barriers on mitigation of near road air pollution

2021 ◽  
Author(s):  
Ranga Rajan Thiruvenkatachari ◽  
Yifan Ding ◽  
David Pankratz ◽  
Akula Venkatram
Keyword(s):  
Air Pollution ◽  
Field Study ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Dispersion Models ◽  
Noise Barriers ◽  
Data Set ◽  
Wind Speeds ◽  
Sonic Anemometers ◽  
The Impact

AbstractAir pollution associated with vehicle emissions from roadways has been linked to a variety of adverse health effects. Wind tunnel and tracer studies show that noise barriers mitigate the impact of this pollution up to distances of 30 times the barrier height. Data from these studies have been used to formulate dispersion models that account for this mitigating effect. Before these models can be incorporated into Federal and State regulations, it is necessary to demonstrate their applicability under real-world conditions. This paper describes a comprehensive field study conducted in Riverside, CA, in 2019 to collect the data required to evaluate the performance of these models. Eight vehicles fitted with SF6 tracer release systems were driven in a loop on a 2-km stretch of Interstate 215 that had a 5-m tall noise barrier on the downwind side. The tracer, SF6, was sampled at over 40 locations at distances ranging from 5 to 200 m from the barrier. Meteorological data were measured with several 3-D sonic anemometers located upwind and downwind of the highway. The data set, corresponding to 10 h collected over 4 days, consists of information on emissions, tracer concentrations, and micrometeorological variables that can be used to evaluate barrier effects in dispersion models. An analysis of the data using a dispersion model indicates that current models are likely to overestimate concentrations, or underestimate the mitigation from barriers, at low wind speeds. We suggest an approach to correct this problem.

Assessment of the Impact of Spatial Data on the Results of Air Pollution Dispersion Modeling

2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Robert Oleniacz ◽  
Mateusz Rzeszutek
Keyword(s):  
Land Cover ◽  
Spatial Data ◽  
Spatial Databases ◽  
Dispersion Model ◽  
Ambient Air ◽  
Air Pollutant ◽  
Dispersion Models ◽  
Data Set ◽  
Pollution Dispersion ◽  
The Impact

AbstractAdvanced dispersion models, taking into account information on the relief and land cover, as well as temporal and spatial variability of meteorological conditions, are beginning to play an increasingly important role in the assessment of the impact on the air quality. There are numerous spatial databases which can be used in this type of a calculation process, however, there is no answer to the question of how the use of appropriate data set of terrain characteristics affects the results of the distribution of air pollutant concentrations at the surface of the ground. This paper presents two different sets of spatial data of the relief and land cover. Then, their impact on the results of modeling the propagation of pollutants in the ambient air was characterized, using the meteorological processor CALMET and the dispersion model CALPUFF. The obtained results of concentrations in the adopted calculation area were compared on the basis of statistical indicators used to assess pollution dispersion models contained in the statistical package BOOT Statistical Model Evaluation Software Package Version 2.0. The obtained results of calculations of the maximum 1-hour concentrations, the maximum 24-hour mean concentrations and annual mean concentrations for the prepared computational grids with a resolution of 1×1 km were analyzed.

scholarly journals The modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rui Zhang ◽  
Yujie Meng ◽  
Hejia Song ◽  
Ran Niu ◽  
Yu Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
High Temperature ◽  
Air Pollutants ◽  
Meteorological Data ◽  
Effect Of Temperature ◽  
Distributed Lag ◽  
Modification Effect ◽  
Incidence Risk ◽  
The Impact ◽  
The Relationship

Abstract Background Although exposure to air pollution has been linked to many health issues, few studies have quantified the modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China. Methods The data of daily incidence of influenza and the relevant meteorological data and air pollution data in Ningbo from 2014 to 2017 were retrieved. Low, medium and high temperature layers were stratified by the daily mean temperature with 25th and 75th percentiles. The potential modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo was investigated through analyzing the effects of air pollutants stratified by temperature stratum using distributed lag non-linear model (DLNM). Stratified analysis by sex and age were also conducted. Results Overall, a 10 μg/m3 increment of O3, PM2.5, PM10 and NO2 could increase the incidence risk of influenza with the cumulative relative risk of 1.028 (95% CI 1.007, 1.050), 1.061 (95% CI 1.004, 1.122), 1.043 (95% CI 1.003, 1.085), and 1.118 (95% CI 1.028, 1.216), respectively. Male and aged 7–17 years were more sensitive to air pollutants. Through the temperature stratification analysis, we found that temperature could modify the impacts of air pollution on daily incidence of influenza with high temperature exacerbating the impact of air pollutants. At high temperature layer, male and the groups aged 0–6 years and 18–64 years were more sensitive to air pollution. Conclusion Temperature modified the relationship between air pollution and daily incidence of influenza and high temperature would exacerbate the effects of air pollutants in Ningbo.

scholarly journals Exposure Assessment of Mercury and Its Compounds by Dispersion Modeling: A Case Study in the Sea of Japan Coastal Area

2011 ◽  
Vol 4 ◽  
pp. ASWR.S6551
Author(s):  
Khandakar Habib Al Razi ◽  
Moritomi Hiroshi ◽  
Kambara Shinji
Keyword(s):  
Air Quality ◽  
Sea Of Japan ◽  
Coastal Area ◽  
Concentration Distribution ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Background Concentration ◽  
The Sea Of Japan ◽  
Atmospheric Concentration ◽  
The Impact

In Japan, mercury and its compounds were categorized as hazardous air pollutants in 1996 and are on the list of “Substances Requiring Priority Action” published by the Central Environmental Council of Japan. The Air Quality Management Division of the Environmental Bureau, Ministry of the Environment, Japan, selected the current annual mean environmental air quality standard for mercury and its compounds of 0.04 μg/m3. Long-term exposure to mercury and its compounds can have a carcinogenic effect, inducing eg, Minamata disease. This study evaluates the impact of mercury emissions on air quality in the coastal area of the Sea of Japan. Average yearly emission of mercury from an elevated point source in this area with background concentration and one-year meteorological data were used to predict the ground level concentration of mercury. The annual mean concentration distribution of mercury and its compounds were calculated for the middle part of Honshu Island, which served as a background level of mercury concentration for the coastal are of the Sea of Japan. To estimate the concentration of mercury and its compounds in air of the local area, two different simulation models have been used. The first is the National Institute of Advanced Science and Technology Atmospheric Dispersion Model for Exposure and Risk Assessment (AIST-ADMER) that estimates regional atmospheric concentration and distribution. The second is the Ministry of Economy, Trade and Industry Low Rise Industrial Source Dispersion Model (METI-LIS) that estimates the atmospheric concentration distribution in the vicinity of facilities.

scholarly journals Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study

2019 ◽  
Vol 19 (4) ◽  
pp. 2561-2576 ◽  
Author(s):  
Anna Karion ◽  
Thomas Lauvaux ◽  
Israel Lopez Coto ◽  
Colm Sweeney ◽  
Kimberly Mueller ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Methane Emissions ◽  
Gas Production ◽  
Estimation Methods ◽  
Trace Gas ◽  
Barnett Shale ◽  
Dispersion Models ◽  
Data Set ◽  
Gas Dispersion ◽  
Tracer Dispersion

Abstract. Greenhouse gas emissions mitigation requires understanding the dominant processes controlling fluxes of these trace gases at increasingly finer spatial and temporal scales. Trace gas fluxes can be estimated using a variety of approaches that translate observed atmospheric species mole fractions into fluxes or emission rates, often identifying the spatial and temporal characteristics of the emission sources as well. Meteorological models are commonly combined with tracer dispersion models to estimate fluxes using an inverse approach that optimizes emissions to best fit the trace gas mole fraction observations. One way to evaluate the accuracy of atmospheric flux estimation methods is to compare results from independent methods, including approaches in which different meteorological and tracer dispersion models are used. In this work, we use a rich data set of atmospheric methane observations collected during an intensive airborne campaign to compare different methane emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We estimate emissions based on a variety of different meteorological and dispersion models. Previous estimates of methane emissions from this region relied on a simple model (a mass balance analysis) as well as on ground-based measurements and statistical data analysis (an inventory). We find that in addition to meteorological model choice, the choice of tracer dispersion model also has a significant impact on the predicted downwind methane concentrations given the same emissions field. The dispersion models tested often underpredicted the observed methane enhancements with significant variability (up to a factor of 3) between different models and between different days. We examine possible causes for this result and find that the models differ in their simulation of vertical dispersion, indicating that additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models commonly used in regional trace gas flux inversions.

Take one dispersing plume and add some precipitation: using ensembles to simulate deposition uncertainty

2020 ◽  
Author(s):  
Susan Leadbetter ◽  
Peter Bedwell ◽  
Gertie Geertsema ◽  
Irene Korsakissok ◽  
Jasper Tomas ◽  
...  
Keyword(s):  
High Resolution ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Radioactive Material ◽  
Positional Error ◽  
Multiple Model ◽  
Dispersion Models ◽  
Air Concentration ◽  
Initial State

<p>In the event of an accidental airborne release of radioactive material, dispersion models would be used to simulate the spread of the pollutant in the atmosphere and its subsequent deposition. Typically, meteorological information is provided to dispersion models from numerical weather prediction (NWP) models. As these NWP models have increased in resolution their ability to resolve short-lived, heavy precipitation events covering smaller areas has improved. This has led to more realistic looking precipitation forecasts. However, when traditional statistics comparing precipitation predictions to measurements at a point (e.g. an observation site) are used, these high-resolution models appear to have a lower skill in predicting precipitation due to small differences in the location and timing of the precipitation with respect to the observations. This positional error is carried through to the dispersion model resulting in predictions of high deposits where none are observed and vice versa; a problem known as the double penalty problem in meteorology.</p><p>Since observations are not available at the onset of an event, it is crucial to gain insight into the possible location and timing errors. One method to address this issue is to use ensemble meteorological data as input to the dispersion model. Meteorological ensembles are typically generated by running multiple model integrations where each model integration starts from a perturbed initial state and uses slightly different model parametrisations to represent uncertainty in the atmospheric state and its evolution. Ensemble meteorological data provide several possible predictions of the precipitation that are all considered to be equally likely and this allows the dispersion model to produce several possible predictions of the deposits of radioactive material.</p><p>As part of the Euratom funded project, CONFIDENCE, a case study involving the passage of a warm front, where the timing of the front is uncertain in relation to a hypothetical nuclear accident in Europe was examined. In this study a ten-member meteorological ensemble was generated using time lagged forecasts to simulate perturbations in the initial state and two different model parameterisations. This meteorological ensemble was used as input to a single dispersion model to generate a dispersion model ensemble. The resulting ensemble dispersion output and methods to communicate the uncertainty in the deposition and the resulting uncertainty in the air concentration predictions are presented. The results demonstrate how high-resolution meteorological ensembles can be combined with dispersion models to simulate the maximum impact of precipitation and the uncertainty in its position and timing.</p>

scholarly journals NYTEFOX – The NY-Ålesund TurbulencE Fiber Optic eXperiment investigating the Arctic boundary layer, Svalbard

2021 ◽  
Author(s):  
Marie-Louise Zeller ◽  
Jannis-Michael Huss ◽  
Lena Pfister ◽  
Karl E. Lapo ◽  
Daniela Littmann ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Field Experiment ◽  
Fiber Optic ◽  
Meteorological Data ◽  
Surface Radiation ◽  
The Arctic ◽  
Vertical Profiles ◽  
Arctic Boundary Layer ◽  
Data Set ◽  
Sonic Anemometers

Abstract. The NY-Ålesund TurbulencE Fiber Optic eXperiment, NYTEFOX, was a field experiment at the Arctic site Ny-Ålesund (11.9° E, 78.9° N) and yielded a unique meteorological data set. These data describe the distribution of heat, airflows, and exchange in the Arctic boundary layer for a period of 14 days from 26 February to 10 March 2020. NYTEFOX is the first field experiment to investigate the heterogeneity of airflow and its transport in temperatures, wind, and kinetic energy in the Arctic environment using the Fiber-Optic Distributed Sensing (FODS) technique for horizontal and vertical observations. FODS air temperature and wind speed were observed at a spatial resolution of 0.127 m and 9 s in time along a horizontal array of 700 m at 1 m height above ground level (agl) and along three 7 m vertical profiles. Ancillary data were collected from three sonic anemometers and an acoustic profiler (miniSodar, SOund Detection And Ranging) yielding turbulent flow statistics and vertical profiles in the lowest 300 m agl, respectively. The observations from this field campaign are publicly available on Zenodo (https://doi.org/10.5281/zenodo.4335461) and supplement the data set operationally collected by the Basic Surface Radiation Network (BSRN) meteorological data set at Ny-Ålesund, Svalbard.

scholarly journals The NY-Ålesund TurbulencE Fiber Optic eXperiment (NYTEFOX): investigating the Arctic boundary layer, Svalbard

2021 ◽  
Vol 13 (7) ◽  
pp. 3439-3452
Author(s):  
Marie-Louise Zeller ◽  
Jannis-Michael Huss ◽  
Lena Pfister ◽  
Karl E. Lapo ◽  
Daniela Littmann ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Field Experiment ◽  
Fiber Optic ◽  
Meteorological Data ◽  
Surface Radiation ◽  
The Arctic ◽  
Vertical Profiles ◽  
Arctic Boundary Layer ◽  
Data Set ◽  
Sonic Anemometers

Abstract. The NY-Ålesund TurbulencE Fiber Optic eXperiment (NYTEFOX) was a field experiment at the Ny-Ålesund Arctic site (78.9∘ N, 11.9∘ E) and yielded a unique meteorological data set. These data describe the distribution of heat, airflows, and exchange in the Arctic boundary layer for a period of 14 d from 26 February to 10 March 2020. NYTEFOX is the first field experiment to investigate the heterogeneity of airflow and its transport of temperature, wind, and kinetic energy in the Arctic environment using the fiber-optic distributed sensing (FODS) technique for horizontal and vertical observations. FODS air temperature and wind speed were observed at a spatial resolution of 0.127 m and a temporal resolution of 9 s along a 700 m horizontal array at 1 m above ground level (a.g.l.) and along three 7 m vertical profiles. Ancillary data were collected from three sonic anemometers and an acoustic profiler (minisodar; sodar is an acronym for “sound detection and ranging”) yielding turbulent flow statistics and vertical profiles in the lowest 300 m a.g.l., respectively. The observations from this field campaign are publicly available on Zenodo (https://doi.org/10.5281/zenodo.4756836, Huss et al., 2021) and supplement the meteorological data set operationally collected by the Baseline Surface Radiation Network (BSRN) at Ny-Ålesund, Svalbard.

scholarly journals Fine particulate pollution and asthma exacerbations

2017 ◽  
Vol 103 (9) ◽  
pp. 828-831 ◽  
Author(s):  
Naïm Bouazza ◽  
Frantz Foissac ◽  
Saik Urien ◽  
Romain Guedj ◽  
Ricardo Carbajal ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Pollutants ◽  
Asthma Exacerbation ◽  
Meteorological Data ◽  
Maximum Effect ◽  
Sigmoid Function ◽  
Asthma Exacerbations ◽  
Fine Particulate ◽  
Syncytial Virus ◽  
The Impact

ObjectiveAs the results from epidemiological studies about the impact of outdoor air pollution on asthma in children are heterogeneous, our objective was to investigate the association between asthma exacerbation in children and exposure to air pollutants.MethodsA database of 1 264 585 paediatric visits during the 2010–2015 period to the emergency rooms from 20 emergency departments (EDs) of ‘Assistance Publique Hôpitaux de Paris (APHP)’, the largest hospital group in Europe, was used. A total of 47 107 visits were classified as asthma exacerbations. Concentration of air pollutants (nitrogen dioxide, ozone, fine particulate matter (PM) with an aerodynamic diameter smaller than 10  µm (PM10) and 2.5 µm (PM2.5)), as well as meteorological data, evolution of respiratory syncytial virus infection and pollen exposition, were collected on an hourly or daily basis for the same period using institutional databases. To assess the association between air pollution and asthma, mixed-effects quasi-Poisson regression modelling was performed.ResultsThe only compound independently associated with ED visits for asthma was PM2.5 (P<10−4). The association between asthma exacerbation and PM2.5 was not linear, and a sigmoid function described the relationshipsatisfactorily. PM2.5 concentration, which gives half the maximum effect, was estimated at 13.5 µg/m3.ConclusionsWe found an association between daily asthma exacerbation in paediatric visits to the ED and fine particulate air pollutants.

scholarly journals Estimation of bubble-mediated air–sea gas exchange from concurrent DMS and CO<sub>2</sub> transfer velocities at intermediate–high wind speeds

2017 ◽  
Vol 17 (14) ◽  
pp. 9019-9033 ◽  
Author(s):  
Thomas G. Bell ◽  
Sebastian Landwehr ◽  
Scott D. Miller ◽  
Warren J. de Bruyn ◽  
Adrian H. Callaghan ◽  
...  
Keyword(s):  
Wind Speed ◽  
Gas Exchange ◽  
North Atlantic ◽  
Gas Transfer ◽  
Data Set ◽  
Wind Speeds ◽  
Wide Range ◽  
Carbon Dioxide Co2 ◽  
The Impact

Abstract. Simultaneous air–sea fluxes and concentration differences of dimethylsulfide (DMS) and carbon dioxide (CO2) were measured during a summertime North Atlantic cruise in 2011. This data set reveals significant differences between the gas transfer velocities of these two gases (Δkw) over a range of wind speeds up to 21 m s−1. These differences occur at and above the approximate wind speed threshold when waves begin breaking. Whitecap fraction (a proxy for bubbles) was also measured and has a positive relationship with Δkw, consistent with enhanced bubble-mediated transfer of the less soluble CO2 relative to that of the more soluble DMS. However, the correlation of Δkw with whitecap fraction is no stronger than with wind speed. Models used to estimate bubble-mediated transfer from in situ whitecap fraction underpredict the observations, particularly at intermediate wind speeds. Examining the differences between gas transfer velocities of gases with different solubilities is a useful way to detect the impact of bubble-mediated exchange. More simultaneous gas transfer measurements of different solubility gases across a wide range of oceanic conditions are needed to understand the factors controlling the magnitude and scaling of bubble-mediated gas exchange.

scholarly journals VINESYM: an integrated vine and grapevine mathematical model for vegetative development and production quality forecast

2019 ◽  
Vol 13 ◽  
pp. 02005
Author(s):  
Vittorio Faluomi ◽  
Iacopo Borsi
Keyword(s):  
Mathematical Model ◽  
Acid Content ◽  
Vegetative Growth ◽  
Meteorological Data ◽  
Mechanistic Model ◽  
Sugar Accumulation ◽  
Quality Model ◽  
Data Set ◽  
Carbon Demand ◽  
The Impact

The present work deal with the development of a mathematical model able to predict, using time dependent meteorological data, soil and vine characteristics, the growing of a vine and grapevine in terms of leaf area, shoot length, fruit and vegetative mass and finally sugar and acid content of the berry. The model is based upon a source-sink relationship approach, integrated with a soil-atmosphere model, where water accumulation in soil, sap flow across vine are coupled with potential carbon demand functions to directly consider possible water and temperature stresses. The model includes also a N2 sink-source approach, limiting growth rate following N2 availability. Finally, a mechanistic model to evaluate sugar accumulation and a correlation-based model for acid concentration evaluation in the berry is coupled with vegetative growth, to provide the information required to manage vineyard operations and evaluate the impact to the potential wine quality. The primary distinctive trait of this model is then the integration and feedback among prediction of grapevine quality model (sugar an acid content) and vegetative growth model, using a common initial ad boundary conditions data set.

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