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Concept: Atmospheric dispersion modeling


Concentrations of particulate emissions from a quarry located in hilly terrain were calculated by two common atmospheric dispersion models, AERMOD and CALPUFF. Evaluation of these models for emissions from quarries/open pit mines that are located in complex topography is missing from the literature. Due to severe uncertainties in the input parameters, numerous scenarios were simulated and model sensitivity was studied. Model results were compared among themselves, and to measured total suspended particulate (TSP). For a wide range of meteorological and topographical conditions studied, AERMOD predictions were in a better agreement with the measurements than those obtained by CALPUFF. The use of AERMOD’s “Open pit” tool seems unnecessary when accurate digital topographic data are available. Onsite meteorological data are shown to be crucial for reliable dispersion calculations in complex terrain.

Concepts: Particulate, Air pollution, Topography, Landform, Terrain, Atmospheric dispersion modeling


A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. A hybrid air quality modeling approach was used to estimate exposure to traffic-related air pollutants in support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) conducted in Detroit (Michigan, USA). Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) and Research LINE-source dispersion model for near-surface releases (RLINE) dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multi-scale Air Quality (CMAQ) and the Space-Time Ordinary Kriging (STOK) models. To capture the near-road pollutant gradients, refined “mini-grids” of model receptors were placed around participant homes. Exposure metrics for CO, NOx, PM2.5 and its components (elemental and organic carbon) were predicted at each home location for multiple time periods including daily and rush hours. The exposure metrics were evaluated for their ability to characterize the spatial and temporal variations of multiple ambient air pollutants compared to measurements across the study area.

Concepts: Pollution, Model, United States Environmental Protection Agency, Smog, National Ambient Air Quality Standards, Air pollution, Air dispersion modeling, Atmospheric dispersion modeling


Particulate matter is the main air pollutant in open pit mining areas. Preferred models that simulate the dispersion of the particles have been used to assess the environmental impact of the mining activities. Results obtained through simulation have been compared with the particle concentration measured in several sites and a coefficient of determination R(2)<0.78 has been reported. This result indicates that in the open pit mining areas there may be additional sources of particulate matter that have not been considered in the modeling process. This work proposes that the unconsidered sources of emissions are of regional scope such as the re-suspension particulate matter due to the wind action over uncovered surfaces. Furthermore, this work proposes to estimate the impact of such emissions on air quality as a function of the present and past meteorological conditions. A statistical multiple regression model was implemented in one of the world's largest open pit coal mining regions which is located in northern Colombia. Data from 9 particle-concentration monitoring stations and 3 meteorological stations obtained from 2009 to 2012 were statistically compared. Results confirmed the existence of a high linear relation (R(2)>0.95) between meteorological variables and particulate matter concentration being humidity, humidity of the previous day and temperature, the meteorological variables that contributed most significantly in the variance of the particulate matter concentration measured in the mining area while the contribution of the AERMOD estimations to the short term TSP (Total Suspended Particles) measured concentrations was negligible (<5%). The multiple regression model was used to identify the meteorological condition that leads to pollution episodes. It was found that conditions drier than 54% lead to pollution episodes while humidities greater than 70% maintain safe air quality conditions in the mining region in northern Colombia.

Concepts: Regression analysis, Statistics, Smog, Mining, Air pollution, Atmospheric dispersion modeling, Open-pit mining, Surface mining


Implications A new meteorological preprocessor called AERCOARE was developed for offshore source dispersion modeling using the EPA regulatory model AERMOD. The combined AERCOARE-AERMOD modeling approach allows stakeholders to use the same dispersion model for both offshore and onshore applications. This approach could replace current regulatory practices involving two completely different modeling systems. As improvements and features are added to the dispersion model component, AERMOD, such techniques can now also be applied to offshore air quality permitting.

Concepts: Model, Unified Modeling Language, Air pollution, Air dispersion modeling, Atmospheric dispersion modeling, Air pollution dispersion terminology, AERMOD


Nowadays, several dispersion models are available to simulate the transport processes of air pollutants and toxic substances including radionuclides in the atmosphere. Reliability of atmospheric transport models has been demonstrated in several recent cases from local to global scale; however, very few actual emission data are available to evaluate model results in real-life cases. In this study, the atmospheric dispersion of 131I emitted to the atmosphere during an industrial process was simulated with different models, namely the WRF-Chem Eulerian online coupled model and the HYSPLIT and the RAPTOR Lagrangian models. Although only limited data of 131I detections has been available, the accuracy of modeled plume direction could be evaluated in complex late autumn weather situations. For the studied cases, the general reliability of models has been demonstrated. However, serious uncertainties arise related to low level inversions, above all in case of an emission event on 4 November 2011, when an important wind shear caused a significant difference between simulated and real transport directions. Results underline the importance of prudent interpretation of dispersion model results and the identification of weather conditions with a potential to cause large model errors.

Concepts: Climate, Simulation, Operations research, Atmospheric pressure, Atmosphere, Wind, Air pollution, Atmospheric dispersion modeling


Qualitatively and quantitatively, we have demonstrated that airborne polychlorinated biphenyl (PCB) concentrations in the air surrounding New Bedford Harbor (NBH) are caused by its water PCB emissions. We measured airborne PCBs at 18 homes and businesses near NBH in 2015, with values ranging from 0.4 to 38 ng m(-3), with a very strong Aroclor 1242/1016 signal that is most pronounced closest to the harbor and reproducible over three sampling rounds. Using U.S. Environmental Protection Agency (U.S. EPA) water PCB data from 2015 and local meteorology, we predicted gas-phase fluxes of PCBs from 160 to 1200 μg m(-2) day(-1). Fluxes were used as emissions for AERMOD, a widely applied U.S. EPA atmospheric dispersion model, to predict airborne PCB concentrations. The AERMOD predictions were within a factor of 2 of the field measurements. PCB emission from NBH (110 kg year(-1), average 2015) is the largest reported source of airborne PCBs from natural waters in North America, and the source of high ambient air PCB concentrations in locations close to NBH. It is likely that NBH has been an important source of airborne PCBs since it was contaminated with Aroclors more than 60 years ago.

Concepts: Scientific method, United States Environmental Protection Agency, Polychlorinated biphenyl, Air pollution, Biphenyl, Polychlorinated dibenzodioxins, Air dispersion modeling, Atmospheric dispersion modeling


The Fukushima Daiichi nuclear power reactor units that generated large amounts of airborne discharges during the period of March 12-21, 2011 were identified individually by analyzing the combination of measured (134)Cs/(137)Cs depositions on ground surfaces and atmospheric transport and deposition simulations. Because the values of (134)Cs/(137)Cs are different in reactor units owing to fuel burnup differences, the (134)Cs/(137)Cs ratio measured in the environment was used to determine which reactor unit ultimately contaminated a specific area. Atmospheric dispersion model simulations were used for predicting specific areas contaminated by each dominant release. Finally, by comparing the results from both sources, the specific reactor units that yielded the most dominant atmospheric release quantities could be determined. The major source reactor units were Unit 1 in the afternoon of March 12, 2011, Unit 2 during the period from the late night of March 14 to the morning of March 15, 2011. These results corresponded to those assumed in our previous source term estimation studies. Furthermore, new findings suggested that the major source reactors from the evening of March 15, 2011 were Units 2 and 3 and that the dominant source reactor on March 20, 2011 temporally changed from Unit 3 to Unit 2.

Concepts: Atmosphere, Computer simulation, Units of measurement, Air pollution, Nuclear power, Environmental engineering, Atmospheric dispersion modeling


Abstract Case study descriptions of acute onset of respiratory, neurologic, dermal, vascular, abdominal, and gastrointestinal sequelae near natural gas facilities contrast with a subset of emissions research, which suggests that there is limited risk posed by unconventional natural gas development (UNGD). An inspection of the pathophysiological effects of acute toxic actions reveals that current environmental monitoring protocols are incompatible with the goal of protecting the health of those living and working near UNGD activities. The intensity, frequency, and duration of exposures to toxic materials in air and water determine the health risks to individuals within a population. Currently, human health risks near UNGD sites are derived from average population risks without adequate attention to the processes of toxicity to the body. The objective of this paper is to illustrate that current methods of collecting emissions data, as well as the analyses of these data, are not sufficient for accurately assessing risks to individuals or protecting the health of those near UNGD sites. Focusing on air pollution impacts, we examined data from public sources and from the published literature. We compared the methods commonly used to evaluate health safety near UNGD sites with the information that would be reasonably needed to determine plausible outcomes of actual exposures. Such outcomes must be based on the pathophysiological effects of the agents present and the susceptibility of residents near these sites. Our study has several findings. First, current protocols used for assessing compliance with ambient air standards do not adequately determine the intensity, frequency or durations of the actual human exposures to the mixtures of toxic materials released regularly at UNGD sites. Second, the typically used periodic 24-h average measures can underestimate actual exposures by an order of magnitude. Third, reference standards are set in a form that inaccurately determines health risk because they do not fully consider the potential synergistic combinations of toxic air emissions. Finally, air dispersion modeling shows that local weather conditions are strong determinates of individual exposures. Appropriate estimation of safety requires nested protocols that measure real time exposures. New protocols are needed to provide 1) continuous measures of a surrogate compound to show periods of extreme exposure; 2) a continuous screening model based on local weather conditions to warn of periodic high exposures; and 3) comprehensive detection of chemical mixtures using canisters or other devices that capture the major components of the mixtures.

Concepts: Toxicity, Natural gas, National Ambient Air Quality Standards, Air pollution, Air dispersion modeling, Atmospheric dispersion modeling


Urban form controls the overall aerodynamic roughness of a city, and hence plays a significant role in how air flow interacts with the urban landscape. This paper reports improved model performance resulting from the introduction of variable surface roughness in the operational air-quality model ADMS-Urban (v3.1). We then assess to what extent pollutant concentrations can be reduced solely through local reductions in roughness. The model results suggest that reducing surface roughness in a city centre can increase ground-level pollutant concentrations, both locally in the area of reduced roughness and downwind of that area. The unexpected simulation of increased ground-level pollutant concentrations implies that this type of modelling should be used with caution for urban planning and design studies looking at ventilation of pollution. We expect the results from this study to be relevant for all atmospheric dispersion models with urban-surface parameterisations based on roughness.

Concepts: Electrochemistry, City, Model, Atmosphere, Urban planning, Air pollution, Urban design, Atmospheric dispersion modeling


Air pollution is a significant public health issue all over the world, especially in urban areas where a large number of inhabitants are affected. In this study, we quantify the health burden due to local air pollution for Warsaw, Poland. The health impact of the main air pollutants, PM, NOX, SO₂, CO, C₆H₆, BaP and heavy metals is considered. The annual mean concentrations are predicted with the CALPUFF air quality modeling system using the year 2012 emission and meteorological data. The emission field comprises point, mobile and area sources. The exposure to these pollutants was estimated using population data with a spatial resolution of 0.5 × 0.5 km². Changes in mortality and in disability-adjusted life-years (DALYs) were estimated with relative risk functions obtained from literature. It has been predicted that local emissions cause approximately 1600 attributable deaths and 29,000 DALYs per year. About 80% of the health burden was due to exposure to fine particulate matter (PM2.5). Mobile and area sources contributed 46% and 52% of total DALYs, respectively. When the inflow from outside was included, the burden nearly doubled to 51,000 DALYs. These results indicate that local decisions can potentially reduce associated negative health effects, but a national-level policy is required for reducing the strong environmental impact of PM emissions.

Concepts: Epidemiology, Pollution, United States Environmental Protection Agency, Particulate, Smog, Air pollution, Air dispersion modeling, Atmospheric dispersion modeling