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With the depletion of oil resources and the aggravation of environmental pollution, electric vehicles have a growing future and will be more popular as the main force of new energy consumption. They have attracted greater attention from various countries. The sizing and location problem for charging stations has been a hot point of global research, and these issues are important for government planning for electric vehicles. In this paper, we first built a BASS model to predict the total number of electric vehicles and calculate the size of charging stations in the coming years. Moreover, we also developed a queuing model to optimize the location of charging stations and solved this issue by using the exhaustion method, which regards minimum cost as the objective function. After that, the model was tested using data from a city in China. The results show that the model in this paper is good at predicting the number of electric vehicles in the coming years and calculating the size of charging stations. At the same time, it can also optimize the distribution of charging stations and make them more balanceable. Thus, this model is beneficial for the government in planning the development of electric vehicles in the future.

Juni 1989. Auf dem Platz des Himmlischen Friedens versammeln sich Tausende Studenten, um für mehr politische Freiheit zu kämpfen. Unter ihnen der Ex-Biologiestudent Dai Wei. Plötzlich fallen Schüsse. Dann herrscht Stille

Decades of control have killed independent thought in China, says Ma Jian

In recent years, the "coal to electricity" project (CTEP) using clean energy instead of coal for heating has been implemented by Beijing government to cope with air pollution. However, VOC pollution after CTEP was rarely studied in suburbs of Beijing. To fill this exigency, 116 volatile organic compounds (VOCs) were observed during nonheating (P1) and heating (P2) periods in suburban Beijing. The results showed that the total of VOCs (TVOCs) was positively correlated with PM2.5, PM10, NO2, CO, and SO2 but negatively correlated with O3 and wind speed. The average TVOCs concentration was 19.43 ± 12.41 ppbv in P1 and 16.25 ± 8.01 ppbv in P2. Aromatics and oxygenated VOCs (OVOCs) were the main contributors to ozone formation potential (OFP). Seven sources of VOCs identified by the positive matrix factorization (PMF) model were industrial source, coal combustion, fuel evaporation, gasoline vehicle exhaust, diesel vehicle exhaust, background and biogenic sources, and solvent usage. The contribution of coal combustion to VOCs increased significantly during P2, whereas industrial sources, fuel evaporation, and solvent usage exhibited opposite trends. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were used to analyze the source distributions. The results showed that VOC pollution was caused mainly by air mass from southern Hebei during P1 but by local emissions during P2. Therefore, although the contribution of coal combustion after heating increased, TVOCs concentration during P2 was lower than that during P1. Chronic noncarcinogenic risks of all selected VOC species were below the safe level, while the carcinogenic risks of most selected VOC species were above the acceptable risk level, especially for tetrachloromethane and 1,2-dichloroethane. The cancer risks posed by gasoline vehicle emissions, industrial enterprises, and coal combustion should be paid more attention.