Given its serious impacts on the public’s health, air pollution in China is a matter of strong public concern, particularly in reference to malodorous waste gas. Petition letters related to atmospheric pollution accounted for about 40% of the total petition cases. However, scholarly views differ on whether the Chinese government responds to public opinion on the environment and seeks to improve its environmental governance behavior. For this study, data from national surveys on the public’s environmental satisfaction administered during the period 2011–2015 were analyzed to determine whether the public’s dissatisfaction with the state of the environment in a given year resulted in increased investments by provincial governments in pollution governance during the following year. The study’s findings revealed that governmental behavior in response to public opinion on the environment was selective within the field of environmental governance, with provincial governments being inclined to invest more in waste gas pollution control than in water pollution control. Furthermore, results from this study show that the Chinese government tends to put more efforts into the environmental field where it could more easily achieve short-term benefits.

It is a critical question for environmental governance to examine whether the administrative award and punishment measures are effective in promoting environmental governance performance. Choosing the implementation of a mandatory target system (MTS) as the subject, this paper employs a fixed-effect panel data model and regression discontinuity design to test whether the MTS has improved the environmental governance performance of local governments in China. The results of this research demonstrate that the MTS has a positive effect on environmental performance, however the regression discontinuity design illustrates that the reward and punishment measures in the MTS have no significant effects on the provincial environmental performance. The results of this research provide a reasonable explanation to the existing gaps among the studies on the effectiveness of the MTS. This study has profound policy implications for the design and implementation of the environmental governance system in China.

The concern for workers’ safety in construction industry is reflected in many studies focusing on static safety risk identification and assessment. However, studies on real-time safety risk assessment aimed at reducing uncertainty and supporting quick response are rare. A method for real-time safety risk assessment (RTSRA) to implement a dynamic evaluation of worker safety states on construction site has been proposed in this paper. The method provides construction managers who are in charge of safety with more abundant information to reduce the uncertainty of the site. A quantitative calculation formula, integrating the influence of static and dynamic hazards and that of safety supervisors, is established to link the safety risk of workers with the locations of on-site assets. By employing the hidden Markov model (HMM), the RTSRA provides a mechanism for processing location data provided by the real-time location system (RTLS) and analyzing the probability distributions of different states in terms of false positives and negatives. Simulation analysis demonstrated the logic of the proposed method and how it works. Application case shows that the proposed RTSRA is both feasible and effective in managing construction project safety concerns.