Pollutant dispersion over Industrial Sub-urban area (Helwan)

The concentration of pollutants released from one chimney of the National Company for cement production in Helwan industrial area has been calculated; The calculations are based on the Gaussian plume model covering the period June 1988-May .1989. A method has been presented to calculate the dispersion parameters ay and az in horizontal and vertical directions respectively. The method rely on two-level observation of both wind velocity and temperature. The plume rise correction recommended by Briggs has been adopted to calculate the effective release height (stack height~ plus the plume rise).. The maximum concentration values for different heights and their1otations have been calculated.

Calculation of crosswind integrated concentration by using different dispersion schemes

The Gaussian model is the most extensively used model for local dispersion. The Gaussian formula for a continuous release from a point source (GPM) is integrated to get crosswind integrated concentration. Different schemes such as Irwin, power law, Briggs, Standard method, and split sigma theta method can be used to obtain integrated concentration. Also downwind speed in power law, plume rise and Statistical measures are used in the model to know which is the best scheme agrees with the observed concentration data obtained from Copenhagen, Denmark.

Integration of a Coupled Fire-Atmosphere Model Into a Regional Air Quality Forecasting System for Wildfire Events

The objective of this study was to assess feasibility of integrating a coupled fire-atmosphere model within an air-quality forecast system to create a multiscale air-quality modeling framework designed to simulate wildfire smoke. For this study, a coupled fire-atmosphere model, WRF-SFIRE, was integrated, one-way, with the AIRPACT air-quality modeling system. WRF-SFIRE resolved local meteorology, fire growth, the fire plume rise, and smoke dispersion, and provided AIRPACT with fire inputs. The WRF-SFIRE-forecasted fire area and the explicitly resolved vertical smoke distribution replaced the parameterized BlueSky fire inputs used by AIRPACT. The WRF-SFIRE/AIRPACT integrated framework was successfully tested for two separate wildfire events (2015 Cougar Creek and 2016 Pioneer fires). The execution time for the WRF-SFIRE simulations was <3 h for a 48 h-long forecast, suggesting that integrating coupled fire-atmosphere simulations within the daily AIRPACT cycle is feasible. While the WRF-SFIRE forecasts realistically captured fire growth 2 days in advance, the largest improvements in the air quality simulations were associated with the wildfire plume rise. WRF-SFIRE-estimated plume tops were within 300-m of satellite-estimated plume top heights for both case studies analyzed in this study. Air quality simulations produced by AIRPACT with and without WRF-SFIRE inputs were evaluated with nearby PM2.5 measurement sites to assess the performance of our multiscale smoke modeling framework. The largest improvements when coupling WRF-SFIRE with AIRPACT were observed for the Cougar Creek Fire where model errors were reduced by ∼50%. For the second case (Pioneer fire), the most notable change with WRF-SFIRE coupling was that the probability of detection increased from 16 to 52%.

Improving prediction of trans-boundary biomass burning plume dispersion: from northern peninsular Southeast Asia to downwind western North Pacific Ocean

Plumes from the boreal spring biomass burning (BB) in northern peninsular Southeast Asia (nPSEA) are lifted into the subtropical jet stream and transported and deposited across nPSEA, South China, Taiwan and even the western North Pacific Ocean. This paper as part of the Seven SouthEast Asian Studies (7-SEAS) project effort attempts to improve the chemical weather prediction capability of the Weather Research and Forecasting coupled with the Community Multiscale for Air Quality (WRF–CMAQ) model over a vast region, from the mountainous near-source burning sites at nPSEA to its downwind region. Several sensitivity analyses of plume rise are compared in the paper, and it is discovered that the initial vertical allocation profile of BB plumes and the plume rise module (PLMRIM) are the main reasons causing the inaccuracies of the WRF–CMAQ simulations. The smoldering emission from the Western Regional Air Partnership (WRAP) empirical algorithm included has improved the accuracies of PM10, O3 and CO at the source. The best performance at the downwind sites is achieved with the inline PLMRIM, which accounts for the atmospheric stratification at the mountainous source region with the FINN burning emission dataset. Such a setup greatly improves not only the BB aerosol concentration prediction over near-source and receptor ground-based measurement sites but also the aerosol vertical distribution and column aerosol optical depth of the BB aerosol along the transport route. The BB aerosols from nPSEA are carried by the subtropical westerlies in the free troposphere to the western North Pacific, while BB aerosol has been found to interact with the local pollutants in the Taiwan region through three conditions: (a) overpassing western Taiwan and entering the central mountain area, (b) mixing down to western Taiwan, (c) transport of local pollutants upwards and mixing with a BB plume on higher ground. The second condition, which involves the prevailing high-pressure system from Asian cold surge, is able to impact most of the population in Taiwan.

Forest-fire aerosol–weather feedbacks over western North America using a high-resolution, online coupled air-quality model

The influence of both anthropogenic and forest-fire emissions, and their subsequent chemical and physical processing, on the accuracy of weather and air-quality forecasts, was studied using a high-resolution, online coupled air-quality model. Simulations were carried out for the period 4 July through 5 August 2019, at 2.5 km horizontal grid cell size, over a 2250×3425 km2 domain covering western Canada and USA, prior to the use of the forecast system as part of the FIREX-AQ ensemble forecast. Several large forest fires took place in the Canadian portion of the domain during the study period. A feature of the implementation was the incorporation of a new online version of the Canadian Forest Fire Emissions Prediction System (CFFEPSv4.0). This inclusion of thermodynamic forest-fire plume-rise calculations directly into the online air-quality model allowed us to simulate the interactions between forest-fire plume development and weather. Incorporating feedbacks resulted in weather forecast performance that exceeded or matched the no-feedback forecast, at greater than 90 % confidence, at most times and heights in the atmosphere. The feedback forecast outperformed the feedback forecast at 35 out of 48 statistical evaluation scores, for PM2.5, NO2, and O3. Relative to the climatological cloud condensation nuclei (CCN) and aerosol optical properties used in the no-feedback simulations, the online coupled model's aerosol indirect and direct effects were shown to result in feedback loops characterized by decreased surface temperatures in regions affected by forest-fire plumes, decreases in stability within the smoke plume, increases in stability further aloft, and increased lower troposphere cloud droplet and raindrop number densities. The aerosol direct and indirect effect reduced oceanic cloud droplet number densities and increased oceanic raindrop number densities, relative to the no-feedback climatological simulation. The aerosol direct and indirect effects were responsible for changes to the near-surface PM2.5 and NO2 concentrations at greater than the 90 % confidence level near the forest fires, with O3 changes remaining below the 90 % confidence level. The simulations show that incorporating aerosol direct and indirect effect feedbacks can significantly improve the accuracy of weather and air-quality forecasts and that forest-fire plume-rise calculations within an online coupled model change the predicted fire plume dispersion and emissions, the latter through changing the meteorology driving fire intensity and fuel consumption.

An emergency response model for evaluating the formation and dispersion of plumes originating from major fires (BUOYANT v4.20)

A mathematical model called BUOYANT has previously been developed for the evaluation of the dispersion of positively buoyant plumes originating from major warehouse fires. The model addresses the variations of the cross-plume integrated properties of a rising plume in a vertically varying atmosphere and the atmospheric dispersion after the plume rise regime. We have described in this article an extension of the BUOYANT model to include a detailed treatment of the early evolution of the fire plumes, before the plume rise and atmospheric dispersion regimes. The model input and output consist of selected characteristics of forest or pool fires, and the properties of a source term for the plume rise module, respectively. The main model structure of this source term model is based on the differential equations for low-momentum releases of buoyant material, which govern the evolution of the plume radius, velocity and density differences. The model is also partially based on various experimental results on fire plumes. We have evaluated the refined BUOYANT model by comparing the model predictions against the experimental field-scale data of the Prescribed Fire Combustion and Atmospheric Dynamics Research Experiment, RxCADRE. The predicted concentrations of CO2 agreed fairly well with the aircraft measurements conducted in the RxCADRE campaign. We have also compiled an operational version of the model. The operational model can be used for emergency contingency planning and for the training of emergency personnel, in case of major forest and pool fires.

Cooling tower plume abatement and plume modeling: a review

Visible plumes above wet cooling towers are of great concern due to the associated aesthetic and environmental impacts. The parallel path wet/dry cooling tower is one of the most commonly used approaches for plume abatement, however, the associated capital cost is usually high due to the addition of the dry coils. Recently, passive technologies, which make use of free solar energy or the latent heat of the hot, moist air rising through the cooling tower fill, have been proposed to minimize or abate the visible plume and/or conserve water. In this review, we contrast established versus novel technologies and give a perspective on the relative merits and demerits of each. Of course, no assessment of the severity of a visible plume can be made without first understanding its atmospheric trajectory. To this end, numerous attempts, being either theoretical or numerical or experimental, have been proposed to predict plume behavior in atmospheres that are either uniform versus density-stratified or still versus windy (whether highly-turbulent or not). Problems of particular interests are plume rise/deflection, condensation and drift deposition, the latter consideration being a concern of public health due to the possible transport and spread of Legionella bacteria.

In-situ characterization of layered pollution in the wintertime Arctic atmosphere by small sensors

<p>During the Arctic winter, local emissions (e.g. from home-heating, traffic, power station or industry plumes) coupled to poor dispersion caused by strong temperature inversions can lead to severe air pollution events. For example, each winter, Fairbanks (Alaska) experiences high abundances of gaseous pollutants and particulate matter (PM), leading to air-quality exceedances. However, there is still limited knowledge on the coupled physico-chemical and dynamical processes that cause wintertime Arctic pollution and aerosol formation under the very cold and low light conditions, and where levels of oxidants such as ozone at the surface can become depleted under limited vertical mixing. Here, we demonstrate novel deployment of low cost small sensors measuring PM2.5, gases (CO, NO, NO2, O3) and meteorological parameters (P, T, RH) to characterize Arctic atmospheric composition and properties, including mapping vertical distributions.</p><p>Our three-week pre-ALPACA (Alaskan Layered Pollution and Chemical Analysis) intensive field-campaign took place in downtown Fairbanks in Nov-Dec 2019. Small sensor temperature-dependencies were characterized by instrument cross-comparisons and correction-algorithms developed. Sensors were then deployed near-ground, on the roof of a 19 m building, and on a vertical pulley system set-up along the side of the building for vertical profiling. The small sensors show a strong capability to capture temporal variations in PM2.5, CO, NO and NO<sub>2</sub> and O<sub>3</sub>, across a wide temperature range: surface gas and particle abundances became elevated during a cold-polluted period (temperatures as low as -30 C) and again became elevated during a subsequent warm-polluted period (temperatures around -3 C). Vertical profiling during the warm-polluted period identified strong temperature inversions associated with near-surface layers of high PM2.5 and CO that are distinct from an overlying clean, warm, humid air-mass. During the cold-polluted period, temperature inversions were present but less strong, there was little vertical structure in composition, and PM2.5 was often greater at 20m than at the surface. This finding contrasts with a full winter-season analysis that shows cold surface temperatures typically associated with strong inversions and PM highest at the surface. We invoke plume-rise modelling to show how buoyant plumes from local emissions (e.g. home-heating) can reach heights of about 10-20 m, allowing polluted emissions to rise and accumulate at altitude unless inversions are sufficiently strong to constrain the plume-rise. Causes of the temperature inversions include radiative cooling and advection of overlying warm-air. Our study highlights how small sensor measurements and vertical profiling can help elucidate the coupled processes of atmospheric chemistry, physics, dynamics and emissions that lead to surface air pollution episodes at high latitudes.</p><p>This study forms part of the Alaskan Layered Pollution and Chemical Analysis (ALPACA) project https://alpaca.community.uaf.edu/. We are grateful for technical support from Alaska-DEC, LPC2E, UAF, SEOSS, Alphasense and SouthCoastScience.</p>