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A simple analytical model, the zero‐buoyancy plume (ZBP) model, has been proposed to understand how small‐scale processes such as plume‐environment mixing and evaporation affect the steady‐state structure of the atmosphere. In this study, we refine the ZBP model to achieve self‐consistent analytical solutions for convective mass flux, addressing the inconsistencies in previous solutions. Our refined ZBP model reveals that increasing plume‐environment mixing can increase upper‐troposphere mass flux through two pathways: increased cloud evaporation or reduced atmospheric stability. To validate these findings, we conducted small‐domain convection‐permitting Radiative‐Convective Equilibrium simulations with horizontal resolutions ranging from 4 km to 125 m. As a proxy for plume‐environment mixing strength, the diagnosed entrainment rate increases with finer resolution. Consistent with a previous study, we observed that both anvil cloud fraction and upper‐troposphere mass flux increase with higher resolution. Analysis of the clear‐sky energy balance in the simulations with two different microphysics schemes identified both pathways proposed by the ZBP model. The dominant pathway depends on the relative strengths of evaporation cooling and radiative cooling in the environment. Our work provides a refined simple framework for understanding the interaction between small‐scale convective processes and large‐scale atmospheric structure. Plain Language Summary: High, anvil‐shaped clouds in the tropics significantly impact our climate, but simulating them accurately is challenging. Our study investigates how small‐scale mixing affects anvil clouds and vertical air movement in the upper atmosphere. We refined a simple analytical model, which treats convection as a single plume, to better understand these processes. Our results show that stronger mixing increases the amount of air moving upward, either through increased cloud evaporation or reduced atmospheric stability. We confirmed these findings with km‐scale numerical simulations at various grid sizes. Finer resolutions, indicating stronger mixing, led to more anvil clouds and greater upward air movement, supporting our simple plume model's predictions. These insights improve our understanding of how small‐scale processes influence the large‐scale atmosphere. Key Points: We derived a self‐consistent analytical solution for a zero‐buoyancy plume model to understand the steady‐state tropical atmosphereThe plume model suggests that increased mixing enhances convective mass flux via greater cloud evaporation or reduced atmospheric stabilitySteady‐state simulations with finer grids, indicating stronger mixing, show increased anvil cloud amount and upper‐troposphere mass flux [ABSTRACT FROM AUTHOR]

Abstract A simple analytical model, the zero‐buoyancy plume (ZBP) model, has been proposed to understand how small‐scale processes such as plume‐environment mixing and evaporation affect the steady‐state structure of the atmosphere. In this study, we refine the ZBP model to achieve self‐consistent analytical solutions for convective mass flux, addressing the inconsistencies in previous solutions. Our refined ZBP model reveals that increasing plume‐environment mixing can increase upper‐troposphere mass flux through two pathways: increased cloud evaporation or reduced atmospheric stability. To validate these findings, we conducted small‐domain convection‐permitting Radiative‐Convective Equilibrium simulations with horizontal resolutions ranging from 4 km to 125 m. As a proxy for plume‐environment mixing strength, the diagnosed entrainment rate increases with finer resolution. Consistent with a previous study, we observed that both anvil cloud fraction and upper‐troposphere mass flux increase with higher resolution. Analysis of the clear‐sky energy balance in the simulations with two different microphysics schemes identified both pathways proposed by the ZBP model. The dominant pathway depends on the relative strengths of evaporation cooling and radiative cooling in the environment. Our work provides a refined simple framework for understanding the interaction between small‐scale convective processes and large‐scale atmospheric structure.

Lake-terminating glaciers are widely distributed in the Himalayas, and their rapid melting and terminal calving are the most significant triggering and influencing factors of glacial lake outburst floods in the region. In recent years, the lake- terminating glaciers have experienced continuous and accelerating mass loss. From 1975 to 2000, the mass loss of lake- terminating glaciers was -0.33 ± 0.07 m w.e. ·a-1. In the past 10 years, it has reached -0.56±0.08 m w.e.·a-1, and its average mass loss rate was -0.45±0.08 m w.e.·a-1. The mass loss rate of lake-terminating glaciers is significantly higher than that of others, and terminal melting and calving are the primary reasons. The subaqueous mass loss of lake- terminating glaciers terminus cannot be accurately estimated. The plume model is widely used to simulate the melting of tidewater glaciers, providing a feasible method for determining the lake-ice mass/heat exchange process at the lake-terminating glaciers terminus. The amount of subglacial meltwater runoff, the cross-section shape of the glacier terminal, and the temperature and density of lake water significantly affect the estimation results of the plume model. Evaluating the underwater melting characteristics of glacier terminals based on the plume model will lay the foundation for accurately estimating future glacier mass changes. [ABSTRACT FROM AUTHOR]

The atmospheric convection is a phenomenon that has a length scale smaller than the resolution at which the state‐of‐the‐art general circulation numerical models are running, and thus the convection needs to be parametrized. In this work, a theoretical formulation for the parametrization of subgrid‐scale convection based on subgrid averaging that represents a generalized eddy‐diffusivity mass‐flux formulation is presented. The subgrid fluxes are derived by considering a decomposition of subgrid variables into convective and turbulent variables, and by assuming that the convection is modeled by round convective plumes with generic radial profiles. The main difference between our formulation and the mass‐flux formulations is that the condition of a very small fractional area occupied by the convection is replaced with the condition that the convective vertical velocity goes to the mean state far from the updraft region of the plume. The plume model can also be generalized by considering that the convective elements are energy‐consistent plumes, governed by the conservation of mass, momentum, kinetic energy, and buoyancy, which provides a physical‐based closure for the entrainment. Therefore, the closing problem of our formulation consists of the specification of the convective radial profiles and the boundary conditions at the initial vertical level. Furthermore, our formulation allows one to consider more realistic profiles for the convective variables, making the formulation suitable for the parametrization of atmospheric convection at the convective gray zone. This aspect is discussed in the last part of this work, where it is showed how the formulation can be implemented at any resolution. Moreover, in the present framework, no distinct assumptions are required for each convective type, thus facilitating the parametrization of convection in a unified way. [ABSTRACT FROM AUTHOR]

Gaussian dispersion modeling has implemented significant developments in the description of the planetary boundary layer characteristics along with research work, particularly on plume buoyancy and momentum, as well as airflow in complex terrain. Advanced Gaussian models show a remarkable performance in validation studies, providing sophisticated algorithms to take into account building downwash, deposition, chemical reactions, and so forth. This work aims to essentially validate the SYMOS model, currently referenced in the Czech Republic, and comparatively evaluate further modeling approaches applied to emissions from a stationary source in the suburban background of Prague. Sulfur dioxide was targeted as one of the criteria gaseous pollutants, relatively representing the sulfur content in the solid mineral fuel commonly used in local industrial facilities. Meteorological preprocessing, complex terrain, and plume rise were analyzed in-depth to determine the effect of the different algorithms in the estimation of ground-level concentrations. The obtained contour plots showed moderate similarities between SYMOS and the advanced models ADMS and AERMOD, but largely overestimated the concentrations when plume rise was considered. The descriptive statistical analysis revealed ADMS tended to predict higher hourly peak concentrations, while AERMOD estimated higher annual averages, attributed to differences in meteorological conditions and dispersion algorithms. Moreover, surface roughness was identified as a critical factor in the calculation of concentrations in complex terrain. Extensive assessment and validation of SYMOS algorithms are essential to investigate a different approach to characterize atmospheric stability and thermal lift. [ABSTRACT FROM AUTHOR]

The Green Ocean Amazon (GoAmazon) 2014/5 field campaign data are used to study the diurnal cycle of clouds and precipitation. Through a careful classification of days with shallow cumulus, congestus and deep convection, we investigate the major differences among locally generated convection regimes and the most important environmental factors governing the shallow‐to‐deep convection transition. On shallow cumulus days, a greater sensible heat flux drives deeper boundary layer growth, which entrains drier free‐tropospheric air and lowers the relative humidity, thus leading to a significantly higher cloud base than those on days with deeper convection. Congestus and deep convection regimes exhibit distinct cloud top height distributions with noticeable differences in the vertical wind shear in the mid‐troposphere, suggesting an important role of wind shear in limiting the vertical extent of convection. On deep convection days, with preexisting nocturnal convection or cold‐pools from external disturbances, the timing of peak surface precipitation (12:00–13:00 LST) tends to be in‐phase with the diurnal variation in surface fluxes. However, it takes longer for local deep convection to develop without these disturbances. A plume model with thermodynamic and dynamical constraints is developed to explore the relative importance of various convection‐controlling factors. Initial cloud‐base vertical velocity and buoyancy are important in helping parcels ascend to the level of free convection (LFC). After parcels reach the LFC, entrainment of environmental air and lower free troposphere humidity become crucial in determining cloud top. Entrainment rate differentiates among convection regimes, which may be tied to the cloud size distribution at cloud base. Key Points: Greater surface sensible heat flux on shallow cumulus days leads to higher cloud bases than on deeper convection daysDays with external disturbances trigger earlier convection, making the peak rainfall timing more in phase with surface fluxesEntrainment of environmental air and free tropospheric humidity play crucial roles in determining the shallow to deep convection transition [ABSTRACT FROM AUTHOR]

Volcanic plumes from small and moderate eruptions represent a challenge in the study of plume morphology due to eruption source parameter uncertainties and atmospheric influence. Sakurajima volcano, Japan, features such activity and due to its continuous eruptions in the recent years provides an ideal natural laboratory. A data set of 896 eruptions between 2009 and 2016 with well‐constrained plume heights, estimated erupted mass, and associated atmospheric conditions has been compiled. Plume heights ranged between 1,500 and 5,000 m and mainly developed under stable atmospheric stratification and low background wind speeds. The eruptions presented in the database were used to drive FPLUME, a 1‐D integral volcanic plume model, to study the simulated plume morphology. FPLUME was seen to provide consistent results under stable atmospheric stratification. A method for the real‐time monitoring of erupted mass used in the Sakurajima observatory was seen to provide appropriate first guess estimates for the eruptions, showing agreement with analytical and simulated mass flow rate calculations. Volcanic plumes from Sakurajima show significant influence by the atmospheric environment. The plume scaling parameter (Π) was used to characterize the expected degree of plume bending with results correlating well against modeled plume angles. The vertical wind profile was seen to have a significant impact on the resolved plume. Wind shear characteristics were seen to have a mechanical effect on the plume, aiding or inhibiting bending. Finally, potential issues were identified in simulations under unstable atmospheric conditions as the model either failed to provide a solution or overestimated the plume height. Key Points: A database of 896 eruptions from Sakurajima with associated atmospheric profiles is presentedDifferent plume bending regimes are quantitatively evaluated using the FPLUME modelVertical wind shear mechanically affects plume morphology by aiding or inhibiting plume bending [ABSTRACT FROM AUTHOR]

Smoke plume rise is critically dependent on plume updraft structure. Smoke plumes from landscape burns (forest and agricultural burns) are typically structured into “sub-plumes” or multiple-core updrafts with the number of updraft cores depending on characteristics of the landscape, fire, fuels, and weather. The number of updraft cores determines the efficiency of vertical transport of heat and particulate matter and therefore plume rise. Daysmoke, an empirical-stochastic plume rise model designed for simulating wildland fire plumes, requires updraft core number as an input. In this study, updraft core number was gained via a cellular automata fire model applied to an aerial ignition prescribed burn conducted at Eglin AFB on 6 February 2011. Typically four updraft cores were simulated in agreement with a photo-image of the plume showing three/four distinct sub-plumes. Other Daysmoke input variables were calculated including maximum initial updraft core diameter, updraft core vertical velocity, and relative emissions production. Daysmoke simulated a vertical tower that mushroomed 1,000 m above the mixing height. Plume rise was validated by ceilometer. Simulations with two temperature profiles found 89–93 percent of the PM2.5 released during the flaming phase was transported into the free atmosphere above the mixing layer. The minimal ground-level smoke concentrations were verified by a small network of particulate samplers. Implications of these results for inclusion of wildland fire smoke in air quality models are discussed.

We present Daysmoke, an empirical-statistical plume rise and dispersion model for simulating smoke from prescribed burns. Prescribed fires are characterized by complex plume structure including multiple-core updrafts which makes modeling with simple plume models difficult. Daysmoke accounts for plume structure in a three-dimensional veering/sheering atmospheric environment, multiple-core updrafts, and detrainment of particulate matter. The number of empirical coefficients appearing in the model theory is reduced through a sensitivity analysis with the Fourier Amplitude Sensitivity Test (FAST). Daysmoke simulations for “bent-over” plumes compare closely with Briggs theory although the two-thirds law is not explicit in Daysmoke. However, the solutions for the “highly-tilted” plume characterized by weak buoyancy, low initial vertical velocity, and large initial plume diameter depart considerably from Briggs theory. Results from a study of weak plumes from prescribed burns at Fort Benning GA showed simulated ground-level PM2.5 comparing favorably with observations taken within the first eight kilometers of eleven prescribed burns. Daysmoke placed plume tops near the lower end of the range of observed plume tops for six prescribed burns. Daysmoke provides the levels and amounts of smoke injected into regional scale air quality models. Results from CMAQ with and without an adaptive grid are presented.

Solar Chimney is a potentially effective low carbon technique that uses solar energy to heat and cool buildings or to enhance ventilation. Proper design of a solar chimney requires a reliable model to estimate the airflow rate generated by the heat of solar irradiation. Existing analytical models ignore density variations either for the whole channel or across the channel gap. This paper presents a plume model based on energy balances and the thermal boundary theory and thus considered density variations in both horizontal and vertical directions. This plume model, expressed implicitly as a function of heat flux, can be solved easily through simple iterations. The performance of the model was verified by using experimental data in the literature. Results show that the plume model outperformed existing analytical models. Recognizing the challenges in airflow measurement, we suggest that further tests and calibrations of this plume model be done by using more concrete and accurate experimental data. Simple in form, the plume model has its potential in building simulation programs. [ABSTRACT FROM AUTHOR]

The volcanic plume-rise model of Devenish (2013) is applied to the duration of the 39-day eruption of Eyjafjallajökull in 2010 to produce a time series of the estimated source mass flux. This in turn is integrated to give the total emitted mass, which is found to lie within the error bounds of an observational estimate made by Gudmundsson et al. (2012). The calculation uses realistic profiles of key atmospheric variables such as wind speed, temperature, and humidity taken from a numerical weather prediction model and appropriate to the time of the eruption. The sensitivity of the model results to changes in the values of the entrainment coefficients is discussed. It is shown that including the radius of the plume (when it is strongly affected by the wind) in the comparison of the modelled and observed rise heights not only improves the accuracy of the estimated total emitted mass (compared with neglecting the radius) but also reduces the sensitivity of this estimate to the value of the entrainment coefficient associated with velocity differences normal to the plume axis. [ABSTRACT FROM AUTHOR]

Mathematical models of natural processes can be used as inversion tools to predict unobserved properties from measured quantities. Uncertainty in observations and model formulation impact on the efficacy of inverse modelling. We present a general methodology, history matching, that can be used to investigate the effect of observational and model uncertainty on inverse modelling studies. We demonstrate history matching on an integral model of volcanic plumes that is used to estimate source conditions from observations of the rise height of plumes during the eruptions of Eyjafjallajökull, Iceland, in 2010 and Grímsvötn, Iceland, in 2011. Sources of uncertainty are identified and quantified, and propagated through the integral plume model. A preliminary sensitivity analysis is performed to identify the uncertain model parameters that strongly influence model predictions. Model predictions are assessed against observations through an implausibility measure that rules out model inputs that are considered implausible given the quantified uncertainty. We demonstrate that the source mass flux at the volcano can be estimated from plume height observations, but the magmatic temperature, exit velocity and exsolved gas mass fraction cannot be accurately determined. Uncertainty in plume height observations and entrainment coefficients results in a large range of plausible values of the source mass flux. Our analysis shows that better constraints on entrainment coefficients for volcanic plumes and more precise observations of plume height are required to obtain tightly constrained estimates of the source mass flux. [ABSTRACT FROM AUTHOR]

Fast fluid dynamics (FFD) is an intermediate model between multi-zone models and computational fluid dynamics (CFD) models for indoor airflow simulations. The use of coarse grids is preferred with FFD in order to increase computing speed. However, by using a very large mesh cell to represent a heat source that could have a much smaller physical size than the cell, coarse-grid FFD would under-predict the thermal plume and thermal stratification. This investigation integrated a thermal plume model into coarse-grid FFD. The integration first used the plume model to calculate a source for the momentum equations and then corrected the temperature at the plume cell. The integration enabled coarse-grid FFD to correctly predict the plumes. When applied to displacement ventilation, coarse-grid FFD with the plume model can accurately predict the mean air temperature stratification in rooms as compared with experimental data from the literature. The improved model has also been used to calculate the ventilation rate for buoyancy-driven natural ventilation. The calculated ventilation rates agree well with the experimental data or predictions by CFD and analytical models. Coarse-grid FFD with the plume model used only a small fraction of the computing time required by fine-grid FFD, while the associated errors for the two grid sizes were comparable. [ABSTRACT FROM AUTHOR]

To analyze the deterrent effect and level of traffic electronic enforcement on inhibition of traffic violation, on the basis of the plume model, this paper built a quantitative analysis model of traffic electronic enforcement deterrence level. This model corrected and redefined the factor meaning and expression form of plume model, and calibrated constant values with data from traffic survey to analyze the characteristics of related factors which can influence the traffic electronic enforcement deterrence effect on the scope of time and space. The case studies showed that the calculation results of the model was consistent with the survey results of traffic violation rate, which indicated that this model can quantify the contribution degree of electronic enforcement on inhibition of traffic violation. By reasonable layout of location, direction and quantity of traffic electronic enforcement facilities, the traffic violation rate of the layout area can be effectively reduced. [ABSTRACT FROM AUTHOR]

Observations of volcanic lightning made using a lightning mapping array during the 2010 eruption of Eyjafjallajökull allow the trajectory and growth of the volcanic plume to be determined. The lightning observations are compared with predictions of an integral model of volcanic plumes that includes descriptions of the interaction with wind and the effects of moisture. We show that the trajectory predicted by the integral model closely matches the observational data and the model well describes the growth of the plume downwind of the vent. Analysis of the lightning signals reveals information on the dominant charge structure within the volcanic plume. During the Eyjafjallajökull eruption both monopole and dipole charge structures were observed in the plume. By using the integral plume model, we propose the varying charge structure is connected to the availability of condensed water and low temperatures at high altitudes in the plume, suggesting ice formation may have contributed to the generation of a dipole charge structure via thunderstorm-style ice-based charging mechanisms, though overall this charging mechanism is believed to have had only a weak influence on the production of lightning. [ABSTRACT FROM AUTHOR]

Abstract: A simple three-dimensional volcanic plume model that incorporates the effects of moisture and ambient wind is presented and used iteratively to refine the source mass flux, obtained from an empirical relationship between the plume rise height and source mass flux, according to the prevailing atmospheric conditions. It is applied to the eruption of Eyjafjallajökull in May 2010 using realistic atmospheric profiles appropriate to the time of the eruption. It is shown that the ambient wind has the largest effect on the refined source mass flux with moisture playing a secondary though still important role. It is also shown that significant differences in the values of the revised source mass fluxes can arise when the realistic atmospheric profiles are approximated by idealised profiles. The revised source mass flux is used to initialise a long-range dispersion model of ash in the atmosphere. [Copyright &y& Elsevier]

Smoke plume rise is critically dependent on plume updraft structure. Smoke plumes from landscape burns (forest and agricultural burns) are typically structured into "sub-plumes" or multiple-core updrafts with the number of updraft cores depending on characteristics of the landscape, fire, fuels, and weather. The number of updraft cores determines the efficiency of vertical transport of heat and particulate matter and therefore plume rise. Daysmoke, an empirical-stochastic plume rise model designed for simulating wildland fire plumes, requires updraft core number as an input. In this study, updraft core number was gained via a cellular automata fire model applied to an aerial ignition prescribed burn conducted at Eglin AFB on 6 February 2011. Typically four updraft cores were simulated in agreement with a photo-image of the plume showing three/four distinct sub-plumes. Other Daysmoke input variables were calculated including maximum initial updraft core diameter, updraft core vertical velocity, and relative emissions production. Daysmoke simulated a vertical tower that mushroomed 1,000 m above the mixing height. Plume rise was validated by ceilometer. Simulations with two temperature profiles found 89-93 percent of the PM2.5 released during the flaming phase was transported into the free atmosphere above the mixing layer. The minimal ground-level smoke concentrations were verified by a small network of particulate samplers. Implications of these results for inclusion of wildland fire smoke in air quality models are discussed. [ABSTRACT FROM AUTHOR]

We present Daysmoke, an empirical-statistical plume rise and dispersion model for simulating smoke from prescribed burns. Prescribed fires are characterized by complex plume structure including multiple-core updrafts which makes modeling with simple plume models difficult. Daysmoke accounts for plume structure in a three-dimensional veering/sheering atmospheric environment, multiple-core updrafts, and detrainment of particulate matter. The number of empirical coefficients appearing in the model theory is reduced through a sensitivity analysis with the Fourier Amplitude Sensitivity Test (FAST). Daysmoke simulations for "bent-over" plumes compare closely with Briggs theory although the two-thirds law is not explicit in Daysmoke. However, the solutions for the "highly-tilted" plume characterized by weak buoyancy, low initial vertical velocity, and large initial plume diameter depart considerably from Briggs theory. Results from a study of weak plumes from prescribed burns at Fort Benning GA showed simulated ground-level PM2.5 comparing favorably with observations taken within the first eight kilometers of eleven prescribed burns. Daysmoke placed plume tops near the lower end of the range of observed plume tops for six prescribed burns. Daysmoke provides the levels and amounts of smoke injected into regional scale air quality models. Results from CMAQ with and without an adaptive grid are presented. [ABSTRACT FROM AUTHOR]

We consider a network of sensors that measure the intensities of a complex plume composed of multiple absorption–diffusion source components. We address the problem of estimating the plume parameters, including the spatial and temporal source origins and the parameters of the diffusion model for each source, based on a sequence of sensor measurements. The approach not only leads to multiple-source detection, but also the characterization and prediction of the combined plume in space and time. The parameter estimation is formulated as a Bayesian inference problem, and the solution is obtained using a Markov chain Monte Carlo algorithm. The approach is applied to a simulation study, which shows that an accurate parameter estimation is achievable. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In July 2002, a toxic gas release from a waste stack affected a large number of people in one of South Africa's key industrial zones. An Investigation Panel was set up by the relevant Provincial authorities to determine the cause of the accident. The findings suggested that a combination of technical and managerial shortcomings may have given rise to the accident. A Regression Model was developed in order to determine the degree of exposure. The concentration of Sulphur Dioxide (SO2) gas at the top of the stack was calculated as 3300 ppm with a ground-level concentration of 1000 - 2000 ppb. A more thorough investigation was commissioned by National Government. The technical investigation provided the basis for the work covered in this paper. The regression model was re-examined employing two different techniques to mitigate the effect of model disposition. An area of maximum exposure was defined based on the direction in which the plume traveled in order to determine the inhalation dosage at the point of greatest contact. The findings suggest that the levels of SO2 inhaled exceeded the National Institute for Occupational Health (NIOSH), World Health Organisation (WHO) and Department of Environmental Affairs and Tourism (DEAT) IDLH exposure limits. This prompted more exhaustive analysis of the event. Since insufficient data was available to pursue the scientific route further, a cause-effect relationship was established between the calculated level of exposure and the injuries sustained by some of the victims. This study suggests that despite our scientific advances, the adverse impact that technology may have on society such as in the case of industrial catastrophes can be minimized when knowledge is more effectively employed in the workplace in trying to avert the occurrence or when dealing with the after-effects. [ABSTRACT FROM AUTHOR]

The sources of groundwater pollution such as, industrial effluents, sewage and extensive farming have lead to agrochemical pollution. Mathematical modeling helps to analyze the existing situation, allows forecasting, and to evaluate the effects of changes in the surrounding water quality. The present research has been focused mainly towards understanding the various processes affecting the transport of chemicals in soils. Dispersion coefficient for the sandy loam soil was found to be 0.247 m²/d, 0.150 m²/d and 0.01 m²/d for nitrates, phosphates and Chlorpyriphos through column, and 0.3 37 m²/d, 0.217 m²/d and 0.077 m²/d for nitrates, phosphates and Chiorpyriphos through channel studies, respectively. For similar analysis of the breakthrough curves, dispersion coefficient for the clay soil was found to be 0.0835 m²/d, 0.0632 m²/d and 0.008 m²/d for nitrates, phosphates and Chlorpyriphos through column and 0.147 m²/d , 0.0848m²/d and 0.022 m²/d for nitrates, phosphates and Chlorpyriphos through channel studies, respectively. The one-dimensional analytical model has been used and validated with the experimental data obtained from column and channel studies in sandy loam and clay soils and compared with model output (in which total elimination rate "K" is considered as zero). From this a variation of about 40-60 percent in the leaching characteristics of pollutants was being observed (nitrates, phosphates and chlorpyriphos). [ABSTRACT FROM AUTHOR]

Air pollution emissions from ports are major sources of contaminant exposures to downwind communities. Elevated pollutant concentrations relate to emissions from port activities and nearby heavy industries including refining. Methane (CH 4) in the 66 Refinery plume, located west of the Los Angeles Port, provided a real-world validation opportunity for in situ -derived emissions in comparison with imaging spectroscopy-derived emissions. Airborne remote sensing data were acquired by the airborne thermal infrared Mako imaging spectrometer, while contemporaneous in situ meteorology and trace gas measurements and air samples were collected using a ground based mobile system, SISTER™ (Standard Instrumentation Suite: Truck Enabled for Response). SISTER measures 13 trace gases, meteorology, aerosol size distributions, and vertical aerosol profiles at up to highway speeds. Real-time data visualization is used to target sample collection. SISTER & Mako data were collected 19 June 2020 with additional SISTER data including air samples collected 16 July 2020. In situ CH 4 emissions were derived from two series of inversion plume models with different numbers of plumes for comparison with Mako reference emissions. The informed series used Mako spatial data, whereas the uninformed series did not. In situ survey data and air samples also were collected for two nearby oil wells and found significantly elevated alkanes through undecane and aromatics in the refinery and oil well plumes compared to nearby reference air. Remote sensing CH 4 emissions were 69 g s−1 (2.18 Gg yr−1), within 20% of the informed in situ emissions of 87 g s−1 (2.73 Gg yr−1) and within 10% of four-plume uninformed emissions of 80 g s−1 (2.51 Gg yr−1). On an annualized basis, this is 10% of estimated US refining CH 4 emissions. Derived emissions were robust – agreeing within 10–20% for the various models; however, partitioning between plumes was very poor for the uninformed plumes because neglecting wind veering caused emissions mis-assignment. Monte Carlo simulation emission uncertainties were 12–13% for 19 June and 24–25% for 16 July when emissions were much lower, 0.25 Gg CH 4 yr−1. This study emphasized the importance of fine-scale structure in winds with respect to characterizing emissions at the sub-facility (kilometer) scale, while also showing robust estimation of emissions at the facility scale by in situ survey for a wide range of models. Wind structure on kilometer and smaller scales plays a key role in understanding the fate of emissions. • Concurrent in situ and airborne remote sensing CH 4 plume data were collected. • Very good agreement (<10%) between remote sensing and in situ derived emissions. • Kilometer-scale wind structure (particularly veering) was critical in the agreement. • Plume was significantly elevated over ambient for a wide range of alkanes and aromatics. [ABSTRACT FROM AUTHOR]

The National Atmospheric Release Advisory Center (NARAC) serves as a national resource for the United States, providing tools and services to quickly predict the environmental contamination and health effects caused by airborne radionuclides, and to provide scientifically based guidance to emergency managers for the protection of human life. NARAC''s scientists have developed a diverse tool kit of numerical modeling capabilities to respond to different types of release events, distance scales (local, regional, continental, and global), and response times. [Copyright &y& Elsevier]