The wide dissemination of air pollutants in the environment is generating increasing international concern. A variety of air pollutants have known or suspected harmful effects on human health and wildlife. They pollutants may not only prove a problem in the immediate vicinity of these sources but can travel long distances, chemically reacting in the atmosphere to produce secondary pollutants. In both developed and developing countries, the major threat to clean air is now posed by Combustion Contaminants (CC) and Persistent Organic Pollutants (POPs). The conventional procedure in assessing pollutants to the environment is time consuming and expensive to carry out. Furthermore, selective sampling does not describe the variation of the pollutants in space and time. Our project suggests some alternative approaches to overcome these disadvantages. Principal activity is therefore being devoted to developing the smart sensor system (electronic nose) with long-time operational capability in the field. This proposal explores one approach that uses array of intelligent acoustic platform with self-controlled autonomy for the operation in variable environment. A successful outcome will identify an array of intelligent SAW platform with corresponding sensitive layers and self-adaptation procedures for providing the adequate identification of air pollutants in the variable environment.

The key objectives of the programme are:

General:
Two types of analytes are to be investigated as representative examples of air pollutants with greatest impact on health for humans and wildlife. These are CCs (e.g. CO, CO2, NOx) and POPs (e.g. PolyChlorinated Biphenyls (PCBs) and hydrocarbons).

Specific:

1) To develop multi-directional/multi-mode integrated SAW platform (i-SAW-p) included several individual acoustic transducers (4) with single sensing layer;
2) To elaborate the neural algorithms for self-adaptation of the i-SAW-p from 1) using self-sensing procedures and creation of intelligent SAW platform (i-SAW-p);
3) To design and development sensing array using i-SAW-ps from 2); to optimise array configuration and operation conditions;
4) To synthesize the components of the receptor centers for CCs and POPs; to elaborate self-assembled/self-limiting approaches for formation of sensitive layers in two-dimensional framework on the surface of i-SAW-ps of array from 3);
5) To use massifs from 3) with sensitive coatings from 4) to design and develop prototype of smart sensing instrument; to elaborate the associative memory neural algorithms for analysis of complex mixtures;
6) To develop approaches for detection of small concentration (up to ppb level) of air pollutants in variable environment using smart sensors from 5); to optimise analytical procedures for CCs and POPs listed above and prepare a methodological guide for their monitoring;
7) To publish the validated analytical methods in a leading international journal such as Sensors and Actuators, Analytical Chemistry and IEEE Sensor Journal.

The seven partners in the consortium are leading experts in their own countries in the fields of analytical science, nanochemistry, neurocomputing and physics and represent a strong and comprehensive range of skills for all facets of the programme.