Search

Purpose – The purpose of this paper is to investigate how the information about haze, a term used in China to describe the air pollution problem, is portrayed on Chinese social media by different types of organizations using the theoretical framework of the health belief model (HBM). Design/methodology/approach – A content analysis was conducted based on the 756 posts retrieved from Sina Weibo, the top microbloging platform in China, following the simple random sampling method. χ2 analysis was conducted to examine the relationships across the three types of organizations (governmental organizations, non-governmental organizations, and corporations) and the use of the HBM concepts (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, self-efficacy, and cues to action) in terms of haze and its threat to health. Findings – The results of this study indicated that corporations posted more Weibo messages categorized as perceived benefit and most of these posts are related to their products, while governmental organizations posted fewer Weibo messages categorized as perceived severity. Social implications – This study provides health decision makers and media consumers with knowledge about how to use social media more effectively in terms of haze-related issues. Originality/value – Given the severity of air pollution and the influential role microblogging takes, the study aims to fill the gap in the limited literature on haze information dissemination on social media in China. In addition, this study aims to shed theoretical light on HBM as applied to a non-westernized context. [ABSTRACT FROM AUTHOR]

Firstly, based on the status quo of air pollution in Beijing, Tianjin and Hebei province, the paper summarized three basic assumptions on inter-provincial cooperative air pollution control. Secondly, the paper constructed inter-provincial cooperative air pollution control game model which included the regional optimization model and the Shapley value allocation method. By solving the regional optimization model, the paper obtained the optimal reduction and reduction cost for each province. Then applying the Shapley value allocation method, the paper achieved the relatively fair distribution of the cooperation benefit among Beijing, Tianjin and Hebei province. Finally, the paper used the SO2 reduction of Beijing, Tianjin and Hebei province in 2009 as an example to carry out the empirical analysis. The results demonstrated the effectiveness and practicability of the model, and optimized simulation results of the model can be used as a reference for regional decision-making, such a win-win model will enhance regional cooperation in air pollution control. [ABSTRACT FROM AUTHOR]

Key project of "manufacturing industry and logistics industry linkage" was proposed in the Logistics Adjustment and Revitalization Plan by the state council In 2009. However the consumption and pollution generated by manufacturing Industry and logistics Industry linkage in China are also large at present. How to conduct manufacturing Industry and logistics Industry linkage by the low-carbon manner Is one of most important issues under current low-carbon economy background. In this paper, the issue is studied and analyzed by constructing system dynamics model, which could propose suggestions for low-carbon linkage development of manufacturing industry and logistics industry. [ABSTRACT FROM AUTHOR]

This study examines the dynamic relationships among output, carbon emission, and population of China during the period of 1960 to 2009 by using auto regressive distributive lag (ARDL) model. In order to make the co-integration analysis robust, the paper applied Toda and Yamamoto causality test to understand the causal links among output, carbon emission, and population. The empirical results suggest that population significantly affect output whereas carbon emission does not affect output in the long run. The error correction model (ECM) version of ARDL model found deviations from long run equilibrium which is due to dynamics in the variables concerned. Toda and Yamamoto causality test revealed bi-directional causality between population and carbon emission and also between population and output. Empirical results signify that population can be considered as a powerful ingredient in the context of increase in carbon emission which is instrumental to environmental conservation in China. [ABSTRACT FROM AUTHOR]

Background: Research on the relationships between economic development, energy consumption, environmental pollution, and human health has tended to focus on the relationships between economic growth and air pollution, energy and air pollution, or the impact of air pollution on human health. However, there has been little past research focused on all the above associations. Methods: The few studies that have examined the interconnections between the economy, energy consumption, environmental pollution and health have tended to employ regression analyses, DEA (Data Envelopment Analysis), or DEA efficiency analyses; however, as these are static analysis tools, the analyses did not fully reveal the sustainable economic, energy, environmental or health developments over time, did not consider the regional differences, and most often ignored community health factors. To go some way to filling this gap, this paper developed a modified two stage Undesirable Meta Dynamic Network model to jointly analyze energy consumption, economic growth, air pollution and health treatment data in 31 Chinese high-income and upper-middle income cities from 2013–2016, for which the overall efficiency, production efficiency, healthcare resource utilization efficiency and technology gap ratio (TGR) for all input and output variables were calculated. Results: It was found that: (1) the annual average overall efficiency in China's eastern region was the highest; (2) the production stage efficiencies were higher than the healthcare resource utilization stage efficiencies in most cities; (3) the high-income cities had lower TGRs than the upper–middle income cities; (4) the high-income cities had higher average energy consumption efficiencies than the upper-middle income cities; (5) the health expenditure efficiencies were the lowest of all inputs; (6) the high-income cities' respiratory disease and mortality rate efficiencies were higher than in the upper–middle income cities, which had improving mortality rate efficiencies; and (7) there were significant regional differences in the annual average input and output indicator efficiencies. Conclusions: First, the high-income cities had higher average efficiencies than the upper-middle income cities. Of the ten eastern region high-income cities, Guangzhou and Shanghai had average efficiencies of 1, with the least efficient being Shijiazhuang. In the other regions, the upper-middle income cities required greater technology and health treatment investments. Second, Guangzhou, Lhasa, Nanning, and Shanghai had production efficiencies of 1, and Guangzhou, Lhasa, Nanning, Shanghai and Fuzhou had healthcare resource utilization efficiencies of 1. As the average production stage efficiencies in most cities were higher than the healthcare resource utilization stage efficiencies, greater efforts are needed to improve the healthcare resource utilization. Third, the technology gap ratios (TGRs) in the high-income cities were slightly higher than in the upper-middle income cities. Therefore, the upper-middle income cities need to learn from the high-income cities to improve their general health treatment TGRs. Fourth, while the high-income cities had higher energy consumption efficiencies than the upper-middle income cities, these were decreasing in most cities. There were few respiratory disease efficiency differences between the high-income and upper-middle income cities, the high-income cities had falling mortality rate efficiencies, and the upper-middle income cities had increasing mortality rate efficiencies. Overall, therefore, most cities needed to strengthen their health governance to balance economic growth and urban expansion. Fifth, the average AQI efficiencies in both the high-income and upper-middle income cities were higher than the average CO2 efficiencies. However, the high-income cities had lower average CO2 emissions and AQI efficiencies than the upper-middle income cities, with the AQI efficiency differences between the two city groups expanding. As most cities were focusing more on air pollution controls than carbon dioxide emissions, greater efforts were needed in coordinating the air pollution and carbon dioxide emissions treatments. Therefore, the following suggestions are given. (1) The government should reform the hospital and medical systems. (2) Local governments need to strengthen their air pollution and disease education. (3) High-income cities need to improve their healthcare governance to reduce the incidence of respiratory diseases and the associated mortality. (4) Healthcare governance efficiency needs to be prioritized in 17 upper-middle income cities, such as Hangzhou, Changchun, Harbin, Chengdu, Guiyang, Kunming and Xi'an, by establishing sound medical management systems and emergency environmental pollution treatments, and by increasing capital asset medical investments. (5) Upper-middle income cities need to adapt their treatment controls to local conditions and design medium to long-term development strategies. (6) Upper-middle income cities need to actively learn from the technological and governance experiences in the more efficient higher-income cities. [ABSTRACT FROM AUTHOR]

This paper made an overview and introduction of urban PM2.5 numerical forecast models in China, and mainly introduced air quality simulated forecast system of Beijing, Shanghai, and Nanjing. On this basis, it discussed development direction and existing problems of urban PM2.5 forecast models in China. Besides, it revealed significance of numerical models for air quality forecast. In a heavy air poUution of Beijing - Tianjin - Hebei in October 6 - 12 th of 2014, the forecast results indicated that poUutants was transported from south to north, so the regional transport exerts great influence on concentration of PM2.5. [ABSTRACT FROM AUTHOR]

Continuously monitoring surface ozone (O3) spatial distribution and forecasting its variations are beneficial to improving air quality and ensuring public health in China, although achieving this goal faces challenges from currently available observations and retrieval techniques. Hence, we introduce a coupled surface O3 estimation framework (LESO) to address these challenges by integrating ground-level observing networks and satellite remote sensing. LESO features easy-to-use deep learning algorithms, independence on chemical transportation models (CTMs), and consistent performance using data from different satellites. LESO includes a deep forest 21 (DF21) model to interpolate O3 concentration by learning spatial patterns and a long short-term memory (LSTM) model to forecast O3 concentration by learning data from the past. We used sites of city-level in situ networks as the control sites to manifest short-distance O3 transportation. Satellite-based observations of O3 precursor indicators were incorporated to capture O3 photochemical reactions. DF21 explained a larger fraction of O3 variability (90%) with a mean bias error (MBE) of smaller than $1~\mu \text {g/m}^{3}$. We also investigated the impact of the number of training sites on the DF21 performance, which suggested that five training sites could ensure a good DF21 performance for the most areas ($R^{2} > 0.85$ and bias $< 2~\mu \text {g/m}^{3}$). The forecast O3 concentration via LSTM showed a good and stable agreement ($R^{2}\approx 0.85$ and bias $< 5~\mu \text {g/m}^{3}$) with ground-based measurements for 8-, 24-, 28-, and 72-h time periods, respectively. Overall, LESO aims to bring convenient functionality and reliable surface O3 estimates for broad users. [ABSTRACT FROM AUTHOR]

Drawing lessons from the clean development mechanism (CDM), this paper developed a combined margin methodology to quantify baseline emission factors of air pollutants in China's regional power grids. The simple average of baseline emission factors of SO2, NOX, and PM2.5 in China's six power grids in 2010 were respectively 1.91 kg/MWh, 1.83 kg/MWh and 0.32 kg/MWh. Several low-efficient mitigation technologies, such as low nitrogen oxide burner (LNB), were suggested to be replaced or used together with other technologies in order to virtually decrease the grid's emission factor. The synergies between GHG and air pollution mitigation in China's power sector was also notable. It is estimated that in 2010, that every 1% CO2 reduction in China's power generation sector resulted in the respective coreduction of 1.1%, 0.5%, and 0.8% of SO2, NOX, and PM2.5. Wind is the best technology to achieve the largest amount of coabatement in most parts of China. This methodology is recommended to be used in making comprehensive air pollution control strategies and in cobenefits analysis in future CDM approval processes. [ABSTRACT FROM AUTHOR]

In this paper, a coupled MM5--CMAQ modeling system was employed to investigate the PM10 pollution issue in Beijing, China, with a focus on assessing the effects of different restriction policies implemented during and after the 2008 Olympic Games. The simulations under designed scenarios were implemented over a 2-level nested grid domain for comparing the difference of PM10 concentrations under restriction and no-restrictions situations. The restriction measures include alternate-day vehicle driving, construction activities, trans-boundary emissions from neighboring provinces, and vehicle restrictions during the post-Olympic period. Meteorological contributions to the air quality improvement were also examined. The results show that significant improvement of air quality in Beijing during the 2008 Games was attributed largely to these restriction measures, although favorable weather conditions play an important role. Also, during the post-Olympic period, daily vehicle restrictions implemented temporarily under extreme weather conditions played a crucial role in alleviating Beijing's air pollution. Beijing not only needs to take continuing efforts to addresses its own PM10 problem, but also has a clear self-interest in demanding better environmental performance from neighboring provinces. It is suggested that Beijing would work collectively with neighboring provinces to develop a long-term multi-region initiative and strategy aimed at emission reduction for providing the citizens in this region a healthy and clean air in the long run. [ABSTRACT FROM AUTHOR]

Abstract: Following model evaluation in part I, this part II paper focuses on the process analysis and chemical regime analysis for the formation of ozone (O3) and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM10) in China. The process analysis results show that horizontal transport is the main contributor to the accumulation of O3 in Jan., Apr., and Oct., and gas-phase chemistry and vertical transport contribute to the production and accumulation of O3 in Jul. Removal pathways of O3 include vertical and horizontal transport, gas-phase chemistry, and cloud processes, depending on locations and seasons. PM10 is mainly produced by primary emissions and aerosol processes and removed by horizontal transport. Cloud processes could either decrease or increase PM10 concentrations, depending on locations and seasons. Among all indicators examined, the ratio of provides the most robust indicator for O3 chemistry, indicating a VOC-limited O3 chemistry over most of the eastern China in Jan., NOx-limited in Jul., and either VOC- or NOx-limited in Apr. and Oct. O3 chemistry is NOx-limited in most central and western China and VOC-limited in major cities throughout the year. The adjusted gas ratio, AdjGR, indicates that PM formation in the eastern China is most sensitive to the emissions of SO2 and may be more sensitive to emission reductions in NOx than in NH3. These results are fairly consistent with the responses of O3 and PM2.5 to the reductions of their precursor emissions predicted from sensitivity simulations. A 50% reduction of NOx or AVOC emissions leads to a reduction of O3 over the eastern China. Unlike the reduction of emissions of SO2, NOx, and NH3 that leads to a decrease in PM10, a 50% reduction of AVOC emissions increases PM10 levels. Such results indicate the complexity of O3 and PM chemistry and a need for an integrated, region-specific emission control strategy with seasonal variations to effectively control both O3 and PM2.5 pollution in China. [Copyright &y& Elsevier]

Background: Global climate change is one of the most serious environmental issues faced by humanity, and the resultant change in frequency and intensity of heat waves and cold spells could increase mortality. The influence of temperature on human health could be immediate or delayed. Latitude, relative humidity, and air pollution may influence the temperature-mortality relationship. We studied the influence of temperature on mortality and its lag effect in four Chinese cities with a range of latitudes over 2008-2011, adjusting for relative humidity and air pollution.Methods: We recorded the city-specific distributions of temperature and mortality by month and adopted a Poisson regression model combined with a distributed lag nonlinear model to investigate the lag effect of temperature on mortality.Results: We found that the coldest months in the study area are December through March and the hottest months are June through September. The ratios of deaths during cold months to hot months were 1.43, 1.54, 1.37 and 1.12 for the cities of Wuhan, Changsha, Guilin and Haikou, respectively. The effects of extremely high temperatures generally persisted for 3 days, whereas the risk of extremely low temperatures could persist for 21 days. Compared with the optimum temperature of each city, at a lag of 21 days, the relative risks (95 % confidence interval) of extreme cold temperatures were 4.78 (3.63, 6.29), 2.38 (1.35, 4.19), 2.62 (1.15, 5.95) and 2.62 (1.44, 4.79) for Wuhan, Changsha, Guilin and Haikou, respectively. The respective risks were 1.35 (1.18, 1.55), 1.19 (0.96, 1.48), 1.22 (0.82, 1.82) and 2.47 (1.61, 3.78) for extreme hot temperatures, at a lag of 3 days.Conclusions: Temperature-mortality relationships vary among cities at different latitudes. Local governments should establish regional prevention and protection measures to more effectively confront and adapt to local climate change. The effects of hot temperatures predominantly occur over the short term, whereas those of cold temperatures can persist for an extended number of days. [ABSTRACT FROM AUTHOR]

A microscale air pollutant dispersion model system is developed for emergency response purposes. The model includes a diagnostic wind field model to simulate the wind field and a random-walk air pollutant dispersion model to simulate the pollutant concentration through consideration of the influence of urban buildings. Numerical experiments are designed to evaluate the model's performance, using CEDVAL (Compilation of Experimental Data for Validation of Microscale Dispersion Models) wind tunnel experiment data, including wind fields and air pollutant dispersion around a single building. The results show that the wind model can reproduce the vortexes triggered by urban buildings and the dispersion model simulates the pollutant concentration around buildings well. Typically, the simulation errors come from the determination of the key zones around a building or building cluster. This model has the potential for multiple applications; for example, the prediction of air pollutant dispersion and the evaluation of environmental impacts in emergency situations; urban planning scenarios; and the assessment of microscale air quality in urban areas. [ABSTRACT FROM AUTHOR]

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO2), nitrogen monoxide (NO), respirable suspended particulates (PM10), sulfur dioxide (SO2), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations ( p ≥ 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring ( p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO2, CO, PM10, NO, and NO2. The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM10 and NO2, and the air pollution index API (correlation coefficients ∣ R ∣ ≥ 0.7, p ≤ 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region. [ABSTRACT FROM AUTHOR]