Negative effects of haze risk can easily spread faster and more widely, however, existing studies rarely investigate the whole period or cycle of diffusion events, which leads to lowered public knowledge, often resulting in exaggerated negative effects. In this paper, the diffusion simulation model based on cellular automata is used to evaluate the diffusion of haze risk information. Firstly, according to the whole-life cycle of emergencies, the public affected by haze risk information is classified by resembling the SEIR infectious disease model. Secondly, a diffusion rule from unknown to exposed individuals is developed based on the theory of cellular automata. Then, according to the individual state transformation at different stages, a whole-life cycle model regarding haze risk information diffusion and propagation model is constructed. Finally, appropriate parameters are selected to calculate the results without intervention. The results show that during the whole evolution process, the unknowns continue to decrease, and the lurkers continue to increase. Due to the existence of the immunization period, the immunized persons reach their maximum number before they are about to lose immunity, and the number of communicators reaches their minimum. Afterward, the number of immunized persons reduced to a stable level, and the number of communicators continues to increase toward an agglomeration benefit. Therefore, in order to achieve effective control of the spread of haze risk information, strong and weak control measures are taken for each type of individuals, and the immunity of unknowns and lurkers is increased for individual type control. For the entire information diffusion control, increase communicator immunity and reduce immunization conversion rate. The study of the spread of haze risk information helps to increase the public's sense of responsibility, helps to improve the government's credibility, and contributes to the establishment of a harmonious society.

雾霾风险的负面影响很容易更快，更广泛地传播，但是，现有研究很少研究扩散事件的整个周期或周期，这导致公众知识降低，常常导致夸大的负面影响。本文利用基于元胞自动机的扩散模拟模型对雾霾风险信息的扩散进行评估。首先，根据紧急情况的整个生命周期，通过类似于SEIR传染病模型对受霾风险信息影响的公众进行分类。其次，基于细胞自动机理论，建立了从未知个体到暴露个体的扩散规则。然后，根据不同阶段的个体状态转换，构建了关于霾风险信息扩散和传播模型的全生命周期模型。最后，选择适当的参数以计算结果而无需干预。结果表明，在整个演化过程中，未知数不断减少，潜伏者不断增加。由于存在免疫期，被免疫者将在失去免疫力之前达到最大数量，而传播者的数量达到最小。之后，被免疫者的数量减少到稳定的水平，而传播者的数量继续增加，以实现集聚收益。因此，为了有效地控制雾霾风险信息的传播，对每种类型的个体都采取强而弱的控制措施，并且对于个体类型的控制，增加了未知数和潜伏者的免疫力。对于整个信息传播控制，增加传播者免疫力并降低免疫转化率。对霾风险信息传播的研究有助于提高公众的责任感，有助于提高政府的信誉，并有助于建立和谐社会。