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It is known that air pollution is harmful to creatures, though until now most of the human thermal comfort indices that existed were calculated only with meteorological conditions. Therefore, a new index - meteorology and environment comfort (MEC) - was given out in this paper that considers both meteorology and air pollution conditions and presents the comprehensive and synergistic effects of meteorological and air pollution. The meteorology and air pollution data were used to establish the influence function of the five air pollutants (PM2.5, PM10, O3, NO2, and SO2) according to Fechner's law; then, we calculated the somatosensory temperature (ST, a class of human thermal comfort indices) and MEC values of five typical cities (Beijing, Xining, Nanjing, Kunming, and Guangzhou). The results showed average improvements of five cities on MEC as a new comprehensive human comfort index to new ST. In spring, the MEC comfort proportion fell by 29.25%. Besides, the extreme heat discomfort ratio in Nanjing and Kunming has increased over 20%. In summer, the comfort proportion fell 12.54%; the extreme heat discomfort proportion of Beijing increased 37.86% and Kunming increased 24.09%. Air pollution significantly raised discomfort stress in Beijing. In fall, the comfort proportion fell by 20.87%; and the extreme heat discomfort of Nanjing increased 23.67% caused by poor air quality. About winter, the comfort ratio decreased 12.72%, and the cold discomfort proportion of Nanjing increased 30.30%, signifying awful air quality in winter. Air pollution levels significantly affect the comfort levels in all seasons, which is more evident with good weather patterns. MEC can offer early warnings of extreme weather events and provide a basis for the better prevention and control of air pollution to protect human health basing on the predictions of meteorological and environmental impact factors.

One year-long criteria air pollutants data collected in Beijing were analyzed in this paper, which can support the research on formation, transport and human health effects of air pollutants. This is the first time to study the spatial and temporal variations of criteria pollutants in Beijing using hourly observational data from 12 sites between June 2014 and May 2015 released by the Ministry of Environmental Protection (MEP) of China. Beijing is facing tremendous air pollution as the daily averaged PM2.5 (particulate matter with aerodynamic diameter less than 2.5 µm) concentrations in all sites exceeding the Chinese Ambient Air Quality Standards (CAAQS) Grade I & II standards (15 and 35 µg/m3). Slightly differences in PM2.5 and ozone (O3) were observed between sites at the urban and rural areas. Pearson correlation coefficients show that most pollutants are temporally correlated in Beijing except for O3. The coefficients of divergence (COD) indicate that PM2.5 is associated at most sites with only one rural site (Dingling) having observable difference and one site may be insufficient for monitoring surrounding area. The 8 h peak O3 (O3-8 h) also correlates at different sites but with one urban site (Haidianquwanliu) different from others. In addition, an extreme PM2.5 event (hourly average concentration exceeding 300 μg/m3 for ~40 h) was examined with the consideration of meteorological conditions. Southerly wind with low speed and high relative humidity allow the accumulation of pollutants while northerly wind with high speed and low relative humidity result in good air quality.

The extreme high temperature weather event caused by global warming has increased the risk of urban electric power supply. Critical risk determination method is useful to the system risk prevention and adaptive strategy formulation. Based on analyzing the failure mechanism of power supply under heat wave impact, the paper put forward the method framework of energy-flow network on electric power system risk evaluation. There are three parts in the framework including energy-flow chart analysis of power supply and consumption, establishment and network analysis of Gephi visualization network, and matrix diagram evaluation of node importance. The visualized network of power system with different years and electricity input from external area were established and compared in the case study of Beijing in China. The analysis results showed that the network structure stability of the power system decreased slightly, which was due to the node energy flow becoming high imbalance such as power input from external area, local power generation and energy consumption. For risk prevention, power infrastructures should focus on the high-voltage transmission and distribution facilities and 500 kV hub substations. Meanwhile, to electric power generation and supply, natural gas supply and power supply from Inner Mongolia Autonomous Region played the key roles. And power consumption should focus on the tertiary industry and living consumption.

Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis.

Temperature and relative humidity can simultaneously change in indoor environment, which significantly affect the emission rate of formaldehyde and volatile organic compounds (VOCs) from building materials. Prior studies generally focus on the single effect of temperature or relative humidity, and the combined effect is not considered. This paper investigates the comprehensive influence of temperature and relative humidity on the emission rate of pollutants from building materials. Correlation between the emission rate and the combined environmental factors is derived theoretically. Data in literature are applied to validate the effectiveness of the correlation. With the correlation, the indoor formaldehyde concentration in summer is predicted to be 1.63 times of that in winter in Beijing, which is approximately consistent with surveyed data. In addition, a novel approach is proposed to assess the human health impact due to pollutants emitted from building materials at varied temperature and relative humidity. An association between the human carcinogenic potential (HCP) and the environmental factors is obtained. By introducing a reference room model developed previously, it is calculated that the HCP of bedroom at high relative humidity (70%, 25°C) for formaldehyde exceeds 10-4 cases, meaning high cancer health risk. This study should prove useful for evaluating the emission behaviors and the associated exposure of pollutants from building materials at varied environmental conditions.