Appendix A-1

 

Guidelines on Choice of Models and Model Parameters

 

[The information contained in this Appendix is only meant to assist the Applicant in performing the air quality assessment.  The Applicant must exercise professional judgment in applying this general information for the Project.]

 

 

1.    Introduction

 

1.1       To expedite the review process by the Authority and to assist project proponents or environmental consultants with the conduct of air quality modelling exercise which are frequently called for as part of environmental impact assessment studies, this paper describes the usage and requirements of a few commonly used air quality models.

 

2.                  Choice of Models

 

2.1       The models which have been most commonly used in air quality impact assessments, due partly to their ease of use and partly to the quick turn-around time for results, are of Gaussian type and designed for use in simple terrain under uniform wind flow. There are circumstances when these models are not suitable for ambient concentration estimates and other types of models such as physical, numerical or mesoscale models will have to be used. In situations where topographic, terrain or obstruction effects are minimal between source and receptor, the following Gaussian models can be used to estimate the near-field impacts of a number of source types including dust, traffic and industrial emissions.

 

            Model  Applications

            FDMfor evaluating fugitive and open dust source impacts (point, line and area sources)

            CALINE4for evaluating mobile traffic emission impacts (line sources)

            ISCST3for evaluating industrial chimney releases as well as area and volumetric sources (point, area and volume sources); line sources can be approximated by a number of volume sources.

 

            These frequently used models are also referred to as Schedule 1 models (see attached list).

 

2.2              Note that both FDM and CALINE4 have a height limit on elevated sources (20 m and 10m, respectively). Source of elevation above these limits will have to be modelled using the ISCST3 model or suitable alternative models. In using the latter, reference should be made to the 'Guidelines on the Use of Alternative Computer Models in Air Quality Assessment' in Appendix B-3.

 

2.3              The models can be used to estimate both short-term (hourly and daily average) and long-term (annual average) ambient concentrations of air pollutants. The model results, obtained using appropriate model parameters (refer to Section 3) and assumptions, allow direct comparison with the relevant air quality standards such as the Air Quality Objectives (AQOs) for the relevant pollutant and time averaging period.

 

3.         Model Input Requirements

 

3.1            Meteorological Data

 

3.1.1    At least 1 year of recent meteorological data (including wind speed, wind direction, stability class, ambient temperature and mixing height) from a weather station either closest to or having similar characteristics as the study site should be used to determine the highest short-term (hourly, daily) and long-term (annual) impacts at identified air sensitive receivers in that period. The amount of valid data for the period should be no less than 90 percent.

 

3.1.2    Alternatively, the meteorological conditions as listed below can be used to examine the worst case short-term impacts:

 

            Day time:

            stability class D; wind speed 1 m/s (at 10m height); worst-case wind angle; mixing height 500 m

 

            Night time:

            stability class F; wind speed 1 m/s (at 10m height); worst case wind angle; mixing height 500 m

           

            This is a common practice with using the CALINE4 model due to its inability to handle lengthy data set.

 

3.1.3    For situations where, for example, (i) the model (such as CALINE4) does not allow easy handling of one full year of meteorological data; or (ii) model run time is a concern, the followings can be adopted in order to determine the daily and annual average impacts:

 

(i)                 perform a frequency occurrence analysis of one year of meteorological data to determine the actual wind speed (to the nearest unit of m/s), wind direction (to the nearest 10^o) and stability (classes A to F) combinations and their frequency of occurrence;

(ii)                determine the short term hourly impact under all of the identified wind speed, wind direction and stability combinations; and

(iii)              apply the frequency data with the short term results to determine the long term (daily / annual) impacts.

 

Apart from the above, any alternative approach that will capture the worst possible impact values (both short term and long term) may also be considered.

 

3.1.4    Note that the anemometer height (relative to a datum same for the sources and receptors) at which wind speed measurements were taken at a selected station should be correctly entered in the model. These measuring positions can vary greatly from station to station and the vertical wind profile employed in the model can be grossly distorted from the real case if incorrect anemometer height is used. This will lead to unreliable concentration estimates.

 

3.1.5    An additional parameter, namely, the standard deviation of wind direction,  σ_Θ, needs to be provided as input to the CALINE4 model. Typical values ofσ_Θrange from 12^o for rural areas to 24^o for highly urbanised areas under 'D' class stability. For semi-rural such as new development areas, 18^o is more appropriate under the same stability condition. The following reference can be consulted for typical ranges of standard deviation of wind direction under different stability categories and surface roughness conditions.

 

Ref.(1): Guideline On Air Quality Models (Revised), EPA-450/2-78-027R, United States Environmental Protection Agency, July 1986.

 

3.2    Emission Sources

 

            All the identified sources relevant to a process plant or a study site should be entered in the model and the emission estimated based on emission factors compiled in the AP-42 (Ref. 2) or other suitable references. The relevant sections of AP-42 and any parameters or assumptions used in deriving the emission rates (in units g/s, g/s/m or g/s/m²) as required by the model should be clearly stated for verification. The physical dimensions, location, release height and any other emission characteristics such as efflux conditions and emission pattern of the sources input to the model should also correspond to site data.

 

            If the emission of a source varies with wind speed, the wind speed-dependent factor should be entered.

 

Ref.(2): Compilation of Air Pollutant Emission Factors, AP-42, 5^th Edition, United States Environmental Protection Agency, January 1995.

 

3.3            Urban/Rural Classification

 

            Emission sources may be located in a variety of settings. For modelling purposes these are classed as either rural or urban so as to reflect the enhanced mixing that occurs over urban areas due to the presence of buildings and urban heat effects. The selection of either rural or urban dispersion coefficients in a specific application should follow a land use classification procedure. If the land use types including industrial, commercial and residential uses account for 50% or more of an area within 3 km radius from the source, the site is classified as urban; otherwise, it is classed as rural.

 

3.4       Surface Roughness Height

 

            This parameter is closely related to the land use characteristics of a study area and associated with the roughness element height. As a first approximation, the surface roughness can be estimated as 3 to 10 percent of the average height of physical structures. Typical values used for urban and new development areas are 370 cm and 100 cm, respectively.

 

 

3.5    Receptors

 

            These include discrete receptors representing all the identified air sensitive receivers at their appropriate locations and elevations and any other discrete or grid receptors for supplementary information. A receptor grid, whether Cartesian or Polar, may be used to generate results for contour outputs.

 

3.6       Particle Size Classes

 

            In evaluating the impacts of dust-emitting activities, suitable dust size categories relevant to the dust sources concerned with reasonable breakdown in TSP (< 30 μm) and RSP (< 10 μm) compositions should be used.

 

3.7       NO₂ to NO_x Ratio

 

            The conversion of NO_x to NO₂ is a result of a series of complex photochemical reactions and has implications on the prediction of near field impacts of traffic emissions. Until further data are available, three approaches are currently acceptable in the determination of NO₂:

 

(a)               Ambient Ratio Method (ARM) - assuming 20% of NO_x to be NO₂; or

(b)               Discrete Parcel Method (DPM, available in the CALINE4 model); or

(c)               Ozone Limiting Method (OLM) - assuming the tailpipe NO₂ emission to be 7.5% of NO_x and the background ozone concentration to be in the range of 57 to 68 μg/m³ depending on the land use type (see also the EPD reference paper 'Guidelines on Assessing the 'TOTAL' Air Quality Impacts' in Appendix B-2).

 

3.8       Odour Impact

 

            In assessing odour impacts, a much shorter time-averaging period of 5 seconds is required due to the shorter exposure period tolerable by human receptors. Conversion of model computed hourly average results to 5-second values is therefore necessary to enable comparison against recommended standard. The hourly concentration is first converted to 3-minute average value according to a power law relationship which is stability dependent (Ref. 3) and a result of the statistical nature of atmospheric turbulence. Another conversion factor (10 for unstable conditions and 5 for neutral to stable conditions) is then applied to convert the 3-minute average to 5-second average (Ref. 4). In summary, to convert the hourly results to 5-second averages, the following factors can be applied:

 

                Stability Category    1-hour to 5-sec Conversion Factor

A & B45

        C                                     27

D9

E & F8

 

Under ‘D’ class stability, the 5-second concentration is approximately 10 times the hourly average result. Note, however, that the combined use of such conversion factors together with the ISCST results may not be suitable for assessing the extreme close-up impacts of odour sources.

 

Ref.(3): Richard A. Duffee, Martha A. O’Brien and Ned Ostojic, ‘Odor Modeling – Why and How’, Recent Developments and Current Practices in Odor Regulations, Controls and Technology, Air & Waste Management Association, 1991.

 

Ref.(4): A.W.C. Keddie, ‘Dispersion of Odours’, Odour Control – A Concise Guide, Warren Spring Laboratory, 1980.

 

3.9       Plume Rise Options

 

            The ISCST3 model provides by default a list of the U.S. regulatory options for concentration calculations. These are all applicable to the Hong Kong situations except for the 'Final Plume Rise' option. As the distance between sources and receptors are generally fairly close, the non-regulatory option of  'Gradual Plume Rise' should be used instead to give more accurate estimate of near-field impacts due to plume emission. However, the 'Final Plume Rise' option may still be used for assessing the impacts of distant sources.

 

3.10     Portal Emissions

 

            These include traffic emissions from tunnel portals and any other similar openings and are generally modelled as volume sources according to the PIARC 91 (or more up-to-date version) recommendations (Ref. 5, section III.2). For emissions arising from underpasses or any horizontal openings of the like, these are treated as area or point sources depending on the source physical dimensions. In all these situations, the ISCST3 model or more sophisticated models will have to be used instead of the CALINE4 model. In the case of portal emissions with significant horizontal exit velocity which cannot be handled by the ISCST3 model, the impacts may be estimated by the TOP model (Ref. 6) or any other suitable models subject to prior agreement with EPD.  The EPD’s 'Guidelines on the Use of Alternative Computer Models in Air Quality Assessment' should also be referred to in Appendix B-3.

 

Ref.(5): XIXth World Road Congress Report, Permanent International Association of Road Congresses (PIARC), 1991.

 

Ref.(6): N. Ukegunchi, H. Okamoto and Y. Ide "Prediction of vehicular emission pollution around a tunnel mouth", Proceedings 4th International Clean Air Congress, pp. 205-207, Tokyo, 1977.

 

3.10            Background Concentrations

 

            Background concentrations are required to account for far-field sources which cannot be estimated by the model. These values, to be used in conjunction with model results for assessing the total impacts, should be based on long term average of monitoring data at location representative of the study site. Please make reference to the paper 'Guidelines on Assessing the 'TOTAL' Air Quality Impacts' in Appendix B-2 for further information.

 

3.11     Output

 

            The highest short-term and long-term averages of pollutant concentrations at prescribed receptor locations are output by the model and to be compared against the relevant air quality standards specified for the relevant pollutant. Contours of pollutant concentration are also required for indicating the general impacts of emissions over a study area.

 

            Copies of model files in electronic format should also be provided for EPD's reference.

 

 

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Schedule 1

 

Air Quality Models Generally Accepted by

Hong Kong Environmental Protection Department for

Regulatory Applications as at 1 July 1998*

 

Industrial Source Complex Dispersion Model - Short Term Version 3 (ISCST3) or the latest version developed by U.S. Environmental Protection Agency

 

California Line Source Dispersion Model Version 4 (CALINE4) or the latest version developed by Department of Transportation, State of California, U.S.A.

 

Fugitive Dust Model (FDM) or the latest version developed by U.S. Environmental Protection Agency

 

 

 

 

 

*      EPD is continually reviewing the latest development in air quality models and will update this Schedule accordingly.