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In recent years, social media has had a crucial role in promoting governments to act more responsibly. However, few studies have investigated whether social media use actually leads to increased disclosure during environmental incidents, or how social media influences regional governments’ information disclosure, even though delayed and insufficient disclosure on relevant incidents is often widespread in China. In this article, we model information disclosure during environmental incidents as an evolutionary game process between the central government and local governments, and examine the role of social media on game participants’ strategy selections in the information disclosure game. The results indicate that social media plays an active role in promoting the regional government to proactively disclose information during environmental incidents through two mechanisms: the top–down intervention mechanism, and the bottom–up reputation mechanism. More specifically, social media can provide efficient information channels for the central government to supervise local officials’ limited disclosure during environmental incidents, essentially sharing the central government’s supervision costs, and thus improving its supervision and intervention efficiency. Social media helps focus the public’s attention on the limited disclosure of local officials in environmental incidents, and actively mobilizes citizens to protest to maintain their interests, placing considerable pressure on the reputation of local governments.

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Integration of observations of the coastal ocean continuum, from regional oceans to shelf seas and estuaries/deltas with models, can substantially increase the value of observations and enable a wealth of applications. In particular, models can play a critical role at connecting sparse observations, synthesizing them, and assisting the design of observational networks; in turn, whenever available, observations can guide coastal model development. Coastal observations should sample the two-way interactions between nearshore, estuarine and shelf processes and open ocean processes, while accounting for the different pace of circulation drivers, such as the fast atmospheric, hydrological and tidal processes and the slower general ocean circulation and climate scales. Because of these challenges, high-resolution models can serve as connectors and integrators of coastal continuum observations. Data assimilation approaches can provide quantitative, validated estimates of Essential Ocean Variables in the coastal continuum, adding scientific and socioeconomic value to observations through applications (e.g., sea-level rise monitoring, coastal management under a sustainable ecosystem approach, aquaculture, dredging, transport and fate of pollutants, maritime safety, hazards under natural variability or climate change). We strongly recommend an internationally coordinated approach in support of the proper integration of global and coastal continuum scales, as well as for critical tasks such as community-agreed bathymetry and coastline products.

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We consider an M/G/1 retrial queue with general retrial times, and introduce working vacations and vacation interruption policy into the retrial queue. During the working vacation period, customers can be served at a lower rate. If there are customers in the system at a service completion instant, the vacation will be interrupted and the server will come back to the normal working level. Using supplementary variable method, we obtain the stationary probability distribution and some performance measures. Furthermore, we carry out the waiting time distribution and prove the conditional stochastic decomposition for the queue length in orbit. Finally, some numerical examples are presented.

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