Fuzzy pattern recognition for atmospheric quality in original location of Capital Iron and Steel Company

The total suspended particulate (TSP), sulfur dioxide (SO₂), nitrogen oxides (NO_x) and carbon monoxide (CO) are common monitoring factors of atmospheric environmental quality. Considering the air pollution control and activity policy, the atmospheric environmental quality must be identified based on the actual data about above pollution factors. Based on F.H. measure, a class of similarity measure function (SMF) was presented in this paper. The SMF was applied to atmosphere quality recognition in the original location of Capital Iron and Steel Company (CISC) by using the actual data measured by Beijing Environmental Impact Assessment Association Incorporation. The regularity, symmetry, and inequality of the SMF were proved. The result showed that the atmospheric quality of the location is better in summer, and bad in winter. The recognition is realistic due to the consumption of the bunker coal is large in winter. Being able to evaluate the environmental background value effectively, the SMF presented in this paper can applied to recognize other environment factors such as water, noise.