Encyclopedia of Environmental Science and Engineering, Volume I and II

1163

U

URBAN AIR POLLUTION MODELING^

INTRODUCTION

Urban air pollution models permit the quantitative estimation

of air pollutant concentrations by relating changes in the rate

of emission of pollutants from different sources and meteo-

rological conditions to observed concentrations of these pol-

lutants. Many models are used to evaluate the attainment and

maintenance of air quality standards, urban planning, impact

analysis of existing or new sources, and forecasting of air

pollution episodes in urban areas.

A mathematical air pollution model may serve to gain

insight into the relation between meteorological elements and

air pollution. It may be likened to a transfer function where

the input consists of both the combination of weather condi-

tions and the total emission from sources of pollution, and

the output is the level of pollutant concentration observed in

time and space. The mathematical model takes into consid-

eration not only the nature of the source (whether distributed

or point sources) and concentrations at the receptors, but also

the atmospheric processes that take place in transforming the

concentrations at the source of emission into those observed

at the receptor or monitoring station. Among such processes

are: photochemical action, adsorption both on aerosols and

ground objects, and of course, eddy diffusion.

There are a number of areas in which a valid and practi-

cal model may be of considerable value. For example, the

operators of an industrial plant that will emit sulfur diox-

ide want to locate it in a particular community. Knowing the

emission rate as a function of time; the distribution of wind

speeds, wind direction, and atmospheric stability; the loca-

tion of SO 2 -sensitive industrial plants; and the spatial dis-

tribution of residential areas, it is possible to calculate the

effect the new plant will have on the community.

In large cities, such as Chicago, Los Angeles, or New York,

during strong anticyclonic conditions with light winds and

low dispersion rates, pollution levels may rise to a point

where health becomes affected; hospital admissions for

respiratory ailments increase, and in some cases even deaths

occur. To minimize the effects of air pollution episodes,

advisories or warnings are issued by government officials.

Tools for determining, even only a few hours in advance,

that unusually severe air pollution conditions will arise are

invaluable. The availability of a workable urban air pollution

model plus a forecast of the wind and stability conditions

could provide the necessary information.

In long-range planning for an expanding community it

may be desirable to zone some areas for industrial activity

and others for residential use in order to minimize the effects

of air pollution. Not only the average-sized community, but

also the larger megalopolis could profitably utilize the abil-

ity to compute concentrations resulting from given emis-

sions using a model and suitable weather data. In addition,

the establishment of an air pollution climatology for a city or

state, which can be used in the application of a model, would

represent a step forward in assuring clean air.

For all these reasons, a number of groups have been

devoting their attention to the development of mathematical

models for determining how the atmosphere disperses mate-

rials. This chapter focuses on the efforts made, the necessary

tools and parameters, and the models used to improve living

conditions in urban areas.

COMPONENTS OF AN URBAN AIR POLLUTION

MODEL

A mathematical urban air pollution model comprises four

essential components. The first is the source inventory. One

must know the materials, their quantities, and from what

location and at what rate they are being injected into the

atmosphere, as well as the amounts being brought into a

community across the boundaries. The second involves the

measurement of contaminant concentration at representative

parts of the city, sampled properly in time as well as space.

The third is the meteorological network, and the fourth is

the meteorological algorithm or mathematical formula that

describes how the source input is transformed into observed

values of concentration at the receptors (see Figure 1). The

difference between what is actually happening in the atmo-

sphere and what we think happens, based on our measured

C021_001_r03.indd 1163C021_001_r03.indd 1163 11/18/2005 1:31:34 PM11/18/2005 1:31:34 PM