3. Duration of Sampling
The duration of sampling needs to be considered for precise sampling. Since the activities vary with land-use pattern one has to decide the duration accordingly.

4. Collection Limitations
The collection efficiency of the medium used for sampling should be atleast 75% or more throughout the sampling period.

5. Analytical Limitations
These limitations can be over-come considerably by stringent analytical quality control and selection of analytical techniques.

6. Alteration of Constitutents
This is one of the most important factors that adversely affect the precision and accuracy of AAQM. For example, the oxides of nitrogen undergo photochemical reactions and in the presence of the relatively high cencentrations of olefinic hydrocarbons emitted from automobiles, they are readily converted to the irritants known as peroxyacetyl nitrates, before being collected as nitrogen oxides. Similarly, sulphur dioxide can undergo chain of reactions under specific climatic conditions and there can be alteration of its constitution before it is trapped in absorbant.

7. Effect of storage
There can be error in the values of AAQM measurements when the storage of samples is not proper.

8. Interpretation of Data
The AAQ data interpretation demands the comprehensive multidisciplinary training and work experience in field conditions. In the absence of suitably trained manpower this can also be the limitation. Thus, the air quality surveys have become quite complex and therefore detail planning is also necessary as regards the number and locations (configuration) of air quality monitors is achieving the monitoring objectives.

Biomonitoring of Air Quality in Delhi

(a) During winter of 1982 seven traffic intersections were selected from where plant-leaf samples were collected and analysed for Lead (Pb) content using AAS method. It was found that with the increase in the traffic volume during IX Asian Games, the lead content in the leaves increased too. (Boralkar et al, 1986).

(b) In summer of 1983, one month old plants of Alfalta (Medicago Sativa L.) were exposed in different parts of Delhi and their responses were correlated with known levels of air pollution in the city (Table 1). The inter-relationship between the Air Pollution Index (calculated on the basis of plant responses) and atmospheric sulphation rate and between the sulphate in leaves and sulphur dioxide in air proved the usefulness of Alfalfa plants as suitable indicator plant for the general air quality in the city (Boralkar and Mukherjee, 1991).

Experimental Design, Field Studies & Data Analysis

The air quality sampling has several objectives. Sampling is designed to achieve specific objectives. There could be wide variety for different type of sampling systems depending on the objectives and 'other constraints. Sampling station density depends on type of data needed, population density and distritution, meteorology and climatology of the area and distribution of industrial areas. Automatic continuous sampling equipment in general

Table 1 : Characters of plant species and parameters of ambient air quality at different location in the city of Delhi, (after Boralkar & Mukherjee, 1991)

Location	Plant characters				Air quality parameters
	% decrease    % increase API Shoot    Shoot    Soluble     SO4 D= length biomass in leaves    A+B+C				Microgram per cubic mg SO3/100 meter, 4th average    cm2/day   SO2  NO2  SPM  Sulphation  rate
	(A)	(B)	(C)	3
D.S.I.D.C. Wazirpur     (Roadside-industrial area)	13	36	203	84	48	29	414	0.83
Najafgarh (Industrial area)	35	44	291	123	128	36	600	1.91
I.T.C. (Roadside)	27	36	187	83	62	56	454	1.14
Dr. Mukherjee Nager     (Residential & Commercial)	+2	22	156	59	335	20	304	0.25
J.N.U. Campus     (Clean, Control Location)	0	0	0	0	17	16	150	0.03

involve fewer stations than an integrated sampling device. Use of dispersion models is very important tool in designing sampling network. In a topographically complex area with hills, valleys, lakes, mountains, etc., where local spatial and temporal variations of the meteorological parameters are high, comparatively large number of stations are required than plain areas. Sampling site selection and use of dispersion model for this purpose is required to be considered. Sampling time and frequency, sampling system and selection, data analysis, aif quality statistics and meterology should also figure prominantly.

Air Quality Assessment & Surveillance Programme

This should include area and land use description, emission inventories, air quality measurements, meteorological measurements, development and use of dispersion models and evaluation of the effects of pollution. Specific data format for area and land use description, well designed inventory forms for collecting emission data, proper records of air quality measurements and meteorological and climtological data record, are required to be described in detail. Effect assessment, population exposure and material damage are also needed to be discussed.

Classification of Air Pollutants

As a part of the air quality management a project with the purpose of classifying the urban and industrial areas with regard to air pollution is desirable. The basis of the classification should be air quality goals proposed. Further, available information on ambient air concentrations, emissions, traffic land, topography, climate and population size and density has to be used to estimate the geographical extent of areas with concentrations or depositions exceeding the air quality goals. For example the pollutants that are included for the classification of the air polluntants that are included for classification of the air pollutants in Norway are given in the table 2.