Assessing the Impact of Fugitive Dust Emissions from Cement Silos at Cluster of Concrete Batching Facilities Using Air Dispersion Modeling

This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM10) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM10 released from the cement silos into the air. Simulations were carried out for PM10 emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM10 emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m3, and the highest daily emission value is 0.6 μg/m3;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m3. The highest daily emission average value was 1250.09 μg/m3;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM10 pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.

Comparison between the Chinese EIA Guidelines for Air Dispersion Modelling and the Advanced Air Dispersion Model ADMS

This paper makes comparisons between Chinese Environmental Impact Assessment (EIA) Guidelines for Air dispersion modelling and the advanced air dispersion model ADMS. Since 2001 the ADMS model has been the first and only foreign model that has been approved by the Appraisal Center for Environment and Engineering (ACEE) to be used in EIA projects in China (http://www.china-eia. com/inden_content/rjrz/ rjrz_ADMS/htm). In the paper the following sections provide brief descriptions of the main features of the Chinese Guidelines for Air Dispersion (Section 2) and ADMS (Section 3); Section 4 provides a comparison of the two modelling methods for some simple cases and conclusions and discussion are given in Section 5.

Unified Data Model of Urban Air Pollution Dispersion and 3D Spatial City Model:Groundwork Assessment towards Sustainable Urban Development for Malaysia

Understanding the behavior of urban air pollution is important en route for sustainable urban development (SUD). Malaysia is on its mission to be a developed country by year 2020 comprehends dealing with air pollution is one of the indicators headed towards it. At present monitoring and managing air pollution in urban areas encompasses sophisticated air quality modeling and data acquisition. However, rapid developments in major cities cause difficulties in acquiring the city geometries. The existing method in acquiring city geometries data via ground or space measurement inspection such as field survey, photogrammetry, laser scanning, remote sensing or using architectural plans appears not to be practical because of its cost and efforts. Moreover, air monitoring stations deployed are intended for regional to global scale model whereby it is not accurate for urban areas with typical resolution of less than 2 km. Furthermore in urban areas, the pollutant dispersion movements are trapped between buildings initiating it to move vertically causing visualization complications which imply the limitations of existing visualization scheme that is based on two-dimensional (2D) framework. Therefore this paper aims is to perform groundwork assessment and discuss on the current scenario in Malaysia in the aspect of current policies towards SUD, air quality monitoring stations, scale model and detail discussion on air pollution dispersion model used called the Operational Street Pollution Model (OSPM). This research proposed the implementation of three-dimensional (3D) spatial city model as a new physical data input for OSPM. The five Level of Details (LOD) of 3D spatial city model shows the scale applicability for the dispersion model implementtation. Subsequently 3D spatial city model data commonly available on the web, by having a unified data model shows the advantages in easy data acquisition, 3D visualization of air pollution dispersion and improves visual analysis of air quality monitoring in urban areas.

Using ADMS models for Air Quality Assessment and Management in China

ADMS-Urban is the most widely used advanced dispersion model for urban areas, being used extensively in China and worldwide, providing a practical tool for assessing and managing urban air quality. In this paper we briefly describe the ADMS dispersion models and give an overview of their use in China. And it describes in more detail the use of ADMS-Urban in Fushun in Liaoning province and in Jinan in Shangdong province respectively, for studies of urban air quality. Finally the conclusions are presented.

Improving modeling of low-altitude particulate matter emission and dispersion:A cotton gin case study

Monitoring and modeling of airborne particulate matter(PM)from low-altitude sources is becoming an important regulatory target as the adverse health consequences of PM become better understood.However,application of models not specifically designed for simulation of PM from low-altitude emissions may bias predictions.To address this problem,we describe the modification and validation of an air dispersion model for the simulation of lowaltitude PM dispersion from a typical cotton ginning facility.We found that the regulatory recommended model(AERMOD)overestimated pollutant concentrations by factors of 64.7,6.97 and 7.44 on average for PM 2.5,PM 10,and TSP,respectively.Pollutant concentrations were negatively correlated with height(p<0.05),distance from source(p<0.05)and standard deviation of wind direction(p<0.001),and positively correlated with average wind speed(p<0.001).Based on these results,we developed dispersion correction factors for AERMOD and cross-validated the revised model against independent observations,reducing overestimation factors to 3.75,1.52 and 1.44 for PM 2.5,PM 10 and TSP,respectively.Further reductions in model error may be obtained from use of additional observations and refinement of dispersive correction factors.More generally,the correction permits the validated adjustment and application of pre-existing models for risk assessment and development of remediation techniques.The same approach may also be applied to improve simulations of other air pollutants and environmental conditions of concern.