天然气大气式灶具的CO排放特性预测

CO是城市燃气燃烧过程中生成的主要污染物之一,必须对其排放量进行严格的控制。随着我国气源多样化格局的形成,不同组分的天然气在同一管网中运输,可能会引发末端设备的互换性问题,造成CO排放量的不稳定。为此,通过实验分析了天然气组分与大气式灶具CO排放特性之间的关系,并提出CO排放特性的预测公式。实验分为3个阶段:(1)在设计的大气式基准燃烧器上,测试了2 kPa条件下CH_4掺混单一组分时CO的排放特性,确定了C_2H_6、C_3H_8、C_4H_(10)、N_2和H_2各自对CO排放量的影响;(2)进行以CH_4为主要成分的多组分随机掺混配气CO的排放实验测试,并对实验结果进行多元线性回归分析,确定CO排放量与天然气各组分含量之间的数学关系;(3)选取3台结构型式具有代表性的实际天然气灶具,进行不同组分天然气的CO排放特性测试,验证提出的数学关系式的通用性。实验验证结果表明:实验回归得到的计算公式具有一定的通用性,可以很好地预测天然气组分变化时燃烧器的CO排放性能。

Prediction on CO emission performance of atmospheric gas cookers

CO is one of the main pollutants generated during the combustion of city gas, so its emission must be controlled strictly. As gas sources are diversified in China, natural gas with different compositions is transported in the same pipeline network. Consequently, interchangeability problem may occur in terminal equipments and CO emission is unstable. In view of this, the relationship between natural gas composition and CO emission performance of atmospheric gas cookers was experimentally analyzed, and then a formula for predicting CO emission performance was developed. The experiment was conducted in three stages. First, the CO emission performance was tested under 2 kPa at a designed partially premixed burner when CH4 was blended with a single composition. Thus, the influences ofC₂H₆、C₃H₈、C₄H₁₀、N₂, and H2 on CO emission were determined, respectively. Second, CO emission of randomly blended multi-composition gas with CH₄ as the dominant composition was experimentally tested and the experimental results were analyzed by means of multivariate linear regression to set up the relationship between CO emission and the content of each gas composition. Third, three actual gas cookers with typical structures were selected for CO emission performance test of natural gas with different compositions, and the universality of the proposed mathematical equation was verified. It is shown that the calculation formula established by means of regression is, to some extent, universal, and can be applied to effectively predict CO emission performance of burners with different gas compositions.