Application of a prognostic model TAPM to sea-breeze flows, surface concentrations, and fumigating plumes

doi:10.1016/j.envsoft.2003.08.011

Environmental Modelling & Software

Volume 19, Issue 6, June 2004, Pages 591-601

https://doi.org/10.1016/j.envsoft.2003.08.011 Get rights and content

Abstract

We apply The Air Pollution Model (TAPM) (version 2.0), a three-dimensional prognostic model developed as a tool to predict both meteorological and air pollution fields for environmental impact assessments and related air pollution studies, to data from the 1995 Kwinana Coastal Fumigation Study. The field study was conducted over a 12-day summer period in the coastal region of Kwinana in Western Australia in order to investigate the local sea-breeze meteorology, the footprint of SO₂ concentration due to industrial sources, and the behaviour of fumigating plumes from power plant stacks. The National Centers for Environmental Prediction meteorological analyses are used as input synoptic fields in the model, multi-level nesting is applied, and the model is run both with and without assimilation of local surface wind measurements. The results show that TAPM simulates the onset of sea breezes, and their magnitude and decay with time, reasonably accurately. As regards to the plume footprint, TAPM performs as well as a specialised regulatory model driven by observed meteorology in Kwinana. As expected, TAPM gives better predictions when the wind data are assimilated, but the results without data assimilation are also good. Comparison with the hourly-averaged dispersion moments (i.e., the mean plume height, standard deviations and skewness values), obtained using a limited number of lidar plume scans both before and after fumigation, demonstrates that TAPM is capable of realistically simulating the observed fumigation characteristics (e.g., negative vertical skewness) and the influence of vertical wind direction shear (i.e., positive lateral skewness).

Introduction

Coastal regions are often preferred sites for industrial development. However, the complex meteorology of such regions can adversely affect transport and dispersion of air pollutants. On the regional scale (≈100 km), the daytime sea-breeze or the nighttime land-breeze circulations, caused by the differences in thermal properties of land and water surfaces, can potentially limit the net ventilation of an air shed by recirculating contaminants. On the local (or small) scale (≈10 km), fumigation of elevated plumes into the spatially growing thermal internal boundary layer (TIBL) or trapping of plumes released within the TIBL can lead to localised spots of high ground-level concentrations (GLCs) of pollutants. Mathematical modelling serves as an important tool for the determination of the air pollution footprint for coastal air quality management. Normally, coastal air pollution modelling is done at regional or local scale, or both, depending on the type of application being considered. In the former, numerical prognostic models that solve the fundamental fluid dynamics and scalar transport equations are used to calculate the flow and pollution transport (e.g., Koo and Reible, 1995). In the latter, plumes from individual point sources and their interaction with the TIBL are modelled explicitly using simple, analytical techniques (e.g., Hibberd and Luhar, 1996, Luhar, 2002) with input meteorological information typically derived from local surface-based observations. These analytical models are computationally efficient, but the required meteorological information is not always available. With ever increasing computer power, the prognostic modelling approach is increasingly becoming feasible for use even down to local scale for routine air pollution applications. This approach does not require site-specific meteorological data to drive the model, while still offering the option of assimilating any observed meteorological data that are available.

The Air Pollution Model (TAPM) developed by CSIRO Atmospheric Research is a prognostic model (Hurley, 2002), developed as a tool to predict both meteorological and air pollution fields for environmental impact assessments and related air pollution studies. The model is designed for operation on a personal computer, and is capable of being applied to both regional- and local-scale cases. Previous variants of this model have been used to compare various turbulence closure schemes (Hurley, 1997), to model sea-breeze structure in Kwinana in Western Australia (Hurley and Luhar, 2000), and to model year-long meteorology and air pollution for the industrial area of Kwinana (Hurley et al., 2001). The current version (2.0) of TAPM has been used by Hurley et al. (2003) to model year-long urban meteorology and photochemical smog and particles in Melbourne (Australia) and by Luhar and Hurley (2003) to simulate meteorological and concentration data from the Indianapolis (urban) and Kincaid (rural) field experiments in flat terrain. In this paper, we apply TAPM to simulate the sea-breeze flows, surface concentrations of sulfur dioxide (SO₂) due to industrial point sources, and dispersion characteristics of fumigating point-source plumes observed during the 1995 Kwinana Coastal Fumigation Study conducted in Kwinana (see Sawford et al., 1998 for more information about the study).

We also compare the TAPM predictions of the GLC of SO₂ with those predicted by DISPMOD (version 6.03), a short-range, state-of-the-art analytical model driven by observed meteorology (Rayner, 1987, Rayner, 1998, Luhar, 2002). DISPMOD is primarily a coastal dispersion model, and was developed specifically for air pollution regulation in the Kwinana industrial area. Although it is based on the Gaussian plume approach, some of its components include advanced techniques that account for the complex meteorological and dispersion processes observed in the area. For example, it uses a skewed probability density function (PDF) approach for both fumigation and dispersion within the convective boundary layer, incorporates the turning of the wind with height (i.e., wind direction shear) under daytime onshore flow conditions, and includes the growth of the TIBL for multi-layered onshore flows with a neutral layer, given the onshore flow stability (see Luhar, 2002). Such processes are generally not accounted for in other analytical fumigation or coastal dispersion models (e.g., EPA, 1988). However, DISPMOD needs appropriate input data, which may be difficult to obtain, to invoke these advanced options. TAPM implicitly accounts for complex processes through the controlling meteorological and turbulence predictions and their coupling with a comprehensive dispersion module. TAPM is much more general and portable than DISPMOD, with minimal, if any, local meteorological data requirement. DISPMOD is heavily parameterised based on results from the 1995 Kwinana study (see Section 3), and is, therefore, expected to perform well in Kwinana.

Section snippets

The Air Pollution Model

TAPM is a three-dimensional (3D), nestable, prognostic meteorological and air pollution model, controlled by a graphical user interface. The model can be used in one-way nestable mode to improve efficiency and resolution. It uses global input databases of terrain height, land use, sea-surface temperature (SST), and synoptic meteorological analyses. A complete description of version 2.0 of the model used in the present study is given by Hurley (2002). The meteorological component of TAPM

The Kwinana data

Coastal fumigation is a daytime turbulent dispersion phenomenon in which an elevated, relatively narrow plume travelling in a stable or neutral onshore flow, which is driven by sea breezes or synoptic conditions, is intercepted by the spatially growing TIBL over land, and is subsequently mixed down to the ground by the convective eddies generated within the boundary layer (see Fig. 1). Fumigation under south-westerly sea breezes is a major feature of the summertime air pollution meteorology in

Input synoptic meteorological fields

Since the dates of the Kwinana dataset precede the synoptic meteorological data supplied with TAPM (1997 to present), we used the US National Centers for Environmental Prediction (NCEP) fields (Kalnay et al., 1996) of horizontal wind components, temperature and moisture, to generate the required synoptic fields in TAPM. The NCEP operational model assimilates meteorological observations from a global network of stations and the model output is then calibrated so as to minimize the model’s errors

Model application

To simulate the ground-level SO₂ data, TAPM was run for the entire Kwinana study period, including two extra spin-up days at the start. Four nested domains of 30×30 horizontal grid points at 30-, 10-, 3- and 1-km spacing for the meteorology, and 81×81 horizontal grid points at 7.5-, 2.5-, 0.75- and 0.25-km spacing for the pollution, both centred on coordinates AMG-E 384.5 km (115° 46.5′ E, longitude) and AMG-N 6437.6 km (32° 11.5′ S, latitude), were used. There were 25 vertical levels, with the

Surface meteorology

The time series of the hourly-averaged wind speed, wind direction and temperature observed at 10 m AGL at the Hope Valley station over the 12-day experiment period between 26 January and 6 February 1995, and the corresponding predictions by the model at the same level with (TAPM-A) and without (TAPM-NA) wind data assimilation, are shown in Fig. 4a–c. The variation of the observed wind speed and wind direction over the entire sampling period is cyclic on a daily basis as a result of the regular

Summary and conclusions

With ever increasing computer power, the prognostic modelling approach is increasingly becoming feasible for routine air pollution management applications. An intelligently formulated prognostic model can potentially eliminate the need for local meteorological measurements because the meteorology is predicted. Moreover, under complex flow and diffusion conditions, prognostic models are more generally applicable and more robust than those based on analytical techniques normally used in

Acknowledgements

The authors wish to thank Mr. Mark Collier and Ms. Mary Edwards for generating the NCEP fields in TAPM format, Dr. Martin Cope for providing a helpful review of the manuscript, and the three anonymous referees for their useful remarks.

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Application of a prognostic model TAPM to sea-breeze flows, surface concentrations, and fumigating plumes

Abstract

Introduction

Section snippets

The Air Pollution Model

The Kwinana data

Input synoptic meteorological fields

Model application

Surface meteorology

Summary and conclusions

Acknowledgements

Atmospheric Environment

Atmospheric Environment

Atmospheric Environment

Atmospheric Environment

Atmospheric Environment

PARTPUFF—a Lagrangian particle/puff approach for plume dispersion modelling applications

Journal of Applied Meteorology

An evaluation of several turbulence schemes for the prediction of mean and turbulent fields in complex terrain

Boundary-Layer Meteorology

The Kwinana Coastal Fumigation Study: III—meteorological and turbulence modelling on selected days

Boundary-Layer Meteorology