In recent years, vehicle emissions have become one of the important pollutant sources of the urban atmosphere. Scholars and decision-makers are constantly expected to accurately grasp the dispersion of vehicle pollutants to formulate a series of policies and strategies which can facilitate a friendly and sustainable urban environment, such as controlling the total number of vehicles, requiring higher emission standards, promoting new energy vehicles, improving public transit service, and optimizing non-motorized transportation systems. This paper provides a review of the mechanism research methods and mathematical modeling approaches for urban vehicle pollutant dispersion. The mechanism research methods reviewed include field measurements, wind tunnel experiments, and numerical simulations. The modeling approaches involve two kinds of popular models: Box models (STREET, CPBM, AURORA, PBM) and Gaussian models (CALINE, HIWAY, OSPM, CALPUFF, R-LINE, ADMS series, EPISODE, CityChem, SIRANE, MUNICH). Moreover, this paper clarifies the basic assumption, fundamental principle, related research, applicable conditions, and limitations of these mechanism research methods and modeling approaches.

With the help of smart grid technologies, a lot of electrical loads can provide demand response to support the active power balance of the grid. Compared with centralized control methods, decentralized methods reduce the computational burden of the control center and enhance the reliability of the communication. In this paper, a novel second-order multi-agent consensus control method is proposed for load control problem. By introducing the velocity state into the model, the proposed method achieves better performance than traditional ones. Simulation results verify the effectiveness of the proposed method.