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The purpose of this paper is to explore the features of health misinformation on social media sites (SMSs). The primary goal of the study is to investigate the salient features of health misinformation and to develop a tool of features to help users and social media companies identify health misinformation.

Empirical data include 1,168 pieces of health information that were collected from WeChat, a dominant SMS in China, and the obtained data were analyzed through a process of open coding, axial coding and selective coding. Then chi-square test and analysis of variance (ANOVA) were adopted to identify salient features of health misinformation.

The findings show that the features of health misinformation on SMSs involve surface features, semantic features and source features, and there are significant differences in the features of health misinformation between different topics. In addition, the list of features was developed to identify health misinformation on SMSs.

This study raises awareness of the key features of health misinformation on SMSs. It develops a list of features to help users distinguish health misinformation as well as help social media companies filter health misinformation.

Theoretically, this study contributes to the academic discourse on health misinformation on SMSs by exploring the features of health misinformation. Methodologically, the paper serves to enrich the literature around health misinformation and SMSs that have hitherto mostly drawn data from health websites.

Smoke and dust emissions from industrial furnaces can do great harm to the environment and human health. This paper aims to analyze the morphology, diameter and elements of the submicron particles from the furnace flues and the nearby ambient air by using two typical industrial furnaces, the sintering furnace and the electric furnace.

Two typical industrial furnaces, the sintering furnace and the electric furnace, were chosen in this study, to analyze the morphology, diameter and elements of the submicron particles from the furnace flues and the near-by ambient air.

The results show that the particles from the two furnaces are mainly in the small sizes of 0.3-0.6 μm. Particles from sintering plant flue are mainly spherical and rich in K and Cl, whereas those from the electric plant flue are mainly particles rich in metal elements, such as Zn and Fe, and have different morphology.

The particles in the atmosphere nearby the two furnaces contain aged particles from the flue, lots of spherical particles, rectangle particles and various aggregations. The elements of those particles are complex.

This study aims to focus on the submicron particles (with diameter of 0.2-1.0 μm) of the ambient air from a coal-fired power plant. A systematic examination of their morphology, particle size and chemical element will be analyzed, so as to provide more scientific information and theoretical basis for the formation and control method of inhalable particles, as well as data support for environmental impact and ecological effects assessments.

In this paper, the morphology, size distribution and elemental characteristics of submicron particles from ambient air of a coal-fired power plant are studied by single particle analysis.

The results show that atmospheric particles in coal-fired power plant are mainly spherical particles, and most of them are soot aggregates adhered or coated with other particles with few rectangle particles. The particles collected in the afternoon and evening are mainly of spherical particles, and small-sized particles collected in the morning are mainly spherical ones, while the overall concentration is larger than that of the spherical particles in the size range above 0.5 μm. The results indicated that the larger-sized spherical particles have a lower concentration.

Coal-fired power plants are still the main supply of electricity in China, but the inhalable particles, especially sub-micron particles (0.1-1.0 μm) cannot be effectively captured by the dust removal device from the coal-fired power plant. Thus, a large amount of inhalable particles is emitted into the atmosphere, becoming the major air pollutants in China.

Severe airborne particulate pollution frequently occurs over the North China Plain (NCP) region in recent years. To better understand the characteristics of carbonaceous components in particulate matter (PM) over the NCP region.

PM samples were collected at a typical area affected by industrial emissions in Handan, in January 2016. The concentrations of organic carbon (OC) and elemental carbon (EC) in PM of different size ranges (i.e. PM_2.5, PM₁₀ and TSP) were measured. The concentrations of secondary organic carbon (SOC) were estimated by the EC tracer method.

The results show that the concentration of OC ranged from 14.9 μg m⁻³ to 108.4 μg m⁻³, and that of EC ranged from 4.0 μg m⁻³ to 19.4μg m⁻³, when PM_2.5 changed from 58.0μg m⁻³ to 251.1μg m⁻³ during haze days, and the carbonaceous aerosols most distributed in PM_2.5 rather than large fraction. The concentrations of OC and EC PM_2.5 correlated better (r = 0.7) than in PM_2.5−10 and PM_>10, implying that primary emissions were dominant sources of OC and EC in PM_2.5. The mean ratios of OC/EC in PM_2.5, PM_2.5–10 and PM_>10 were 4.4 ± 2.1, 3.6 ± 0.9 and 1.9 ± 0.7, respectively. Based on estimation, SOC accounted for 16.3%, 22.0% and 9.1% in PM_2.5, PM_2.5–10 and PM_>10 respectively.

The ratio of SOC/OC (48.2%) in PM_2.5 was higher in Handan than those (28%–32%) in other megacities, e.g. Beijing, Tianjin and Shijiazhuang in the NCP, suggesting that the formation of SOC contributed significantly to OC. The mean mass absorption efficiencies of EC (MACEC) in PM₁₀ and TSP were 3.4 m² g⁻¹ (1.9–6.6 m² g⁻¹) and 2.9 m² g⁻¹ (1.6–5.6 m² g⁻¹), respectively, both of which had similar variation patterns to those of OC/EC and SOC/OC.