Existing fire smoke detectors use the intensity of scattering light or the light extinction coefficient as the indicator of fire smoke to trigger fire alarms. However, false fire alarms could be triggered by dust and water fog. Achieving reliable early fire detection with minimal false alarms is a challenge. Based on the Mie scattering theory of spherical particles, it is derived that the ratio of scattering intensity and the ratio of optical extinction of two incident lights with different wavelengths only depends on the intrinsic properties of the aerosol (the average particle size and refractive index). This paper then presents an improved dual-wavelength smoke detection by measuring scattering light and extinction simultaneously to reduce false alarms. Simulations and verification with test fires of European Standard EN 54 were performed, demonstrating that fires can be distinguished from nuisance sources without complicated calculations. These results indicate that the improved detection system can be applied for smoke monitoring and fire protection.

It has been demonstrated that climate change is an established fact. A good comprehension of climate and extreme weather variation characteristics on a temporal and a spatial scale is important for adaptation and response. In this work, the characteristics of temperature, precipitation, and extreme weather distribution and variation is summarized for a period of 60 years and the seasonal fluctuation of temperature and precipitation is also analyzed. The results illustrate the reduction in daily and annual temperature divergence on both temporal and spatial scales. However, the gaps remain relatively significant. Furthermore, the disparity in daily and annual precipitation are found to be increasing on both temporal and spatial scales. The findings indicate that climate change, to a certain extent, narrowed the temperature gap while widening the precipitation gap on temporal and spatial scales in China.

Earthquakes are one type of natural disaster that causes serious economic loss, deaths, and homelessness, and providing shelters is vital to evacuees who have been affected by an earthquake. Constructing shelters with reasonable capacity in the right locations and allocating evacuees to them in a reasonable time period is one disaster management method. This study proposes a multi-objective hierarchical model with three stages, i.e., an immediate shelter (IS) stage, a short-term shelter (STS) stage, and a long-term shelter (LTS) stage. According to the requirements of evacuees of IS, STS, and LTS, the objective of both the IS and STS stages is to minimize total evacuation time and the objectives of the LTS are to minimize total evacuation time and to minimize total shelter area. A modified particle swarm optimization (MPSO) algorithm is used to solve the IS and STS stages and an interleaved modified particle swarm optimization algorithm and genetic algorithm (MPSO-GA) is applied to solve the LTS stage. Taking Chaoyang District, Beijing, China as a case study, the results generated using the model present the government with a set of options. Thus, according to the preferences of the government, the determination can be made regarding where to construct ISs, STSs, and LTSs, and how to allocate the evacuees to them.

Acoustic emission (AE) monitoring has become an optional technology to quantify slope deformation. However, there are still challenges in developing generic AE interpretation strategies. Dynamics and kinematics models are two physical methods for analysing slope stability, which appear to improve the interpretability of AE monitoring data. The aim of this study is to explore the change patterns and interrelations of dynamics, kinematics, and AE measurements using a model test and physical analysis, to further understand the development process of a progressive landslide. A model test is designed based on the kinematics model of landslide three-stage deformation. An equation between factor of safety (FoS) and thrust is proposed based on the mechanical model of a landslide test. There is a clear correspondence between the displacement and inverse velocity during the deformation-controlled process. Relationships are uncovered between the thrust and FoS as well as the thrust and acceleration. As a characteristic parameter of AE, ring down count (RDC) is able to quantify the deformation process of the soil slope. Moreover, acceleration and RDC can reflect the sudden change of the slope state and, hence, can be effective indicators for the early warning in a progressive landslide.