石灰湿法脱硫过程中pH条件对结垢的影响研究

针对石灰湿法脱硫中存在的结垢问题，在鼓泡床中模拟了石灰湿法脱硫过程，通过分析液相的组成，结合反应机理探讨了pH对结垢的影响。结果表明，当pH控制在6.0～4．0时，既能避免结垢，又能获得较高的脱硫率。提出了实际中预测结垢倾向的方法。     

Risk of serious injury of occupants involved in frontal crashes of cab-over-type trucks

Objectives: Truck vehicles (TVs) have a different structure and stiffness than non-TVs and are used commercially for transporting goods. This study aimed to analyze whether truck occupants have a greater risk of serious injury than those of other types of vehicles.

Methods: Crash data were obtained from the Korean In-Depth Data Analysis Study (KIDAS) for calendar years 2011–2016. Vehicles involved in frontal crash were included and classified into TVs and non-TVs (passenger cars and sports utility vehicles). We compared the demographic characteristics and serious injuries by body region between the 2 groups and analyzed factors that contributed to the serious injury severity from frontal crashes.

Results: The analysis was based on 884 occupants; 177 (20.0%) were in TVs and 707 (80.0%) were in non-TVs. Non-TVs had more frontal airbags deployments than TVs (50.9% vs. 3.4%, P <.01). TV occupants were 4.8 times more likely to have a serious lower extremity (LE) injury (adjusted odds ratio [AOR] = 4.820; 95% confidence interval [CI], 2.407–9.653) and 2.5 times to have a serious abdominal injury (AOR = 2.465; 95% CI, 1.108–5.487) compared to non-TV occupants.

Conclusions: Truck occupants had more serious LE and abdominal injuries than those of other types of vehicles in frontal crashes. Structural improvement and legislative efforts to develop safety systems are necessary to improve the safety of truck occupants.     

表面活性物质对HPMA阻垢缓蚀性能的影响

表面活性物质的加入可明显提高水解聚马来酸酐(HPMA)的阻垢、缓蚀性能,且不同表面活性物质影响程度不同,通过剩余硬度法测定阻垢性能,静态失重法测定缓蚀性能,从而比较异丙醇、葡萄糖酸钠对HPMA阻垢、缓蚀性能的影响。实验结果表明,异丙醇与HPMA复合使用时效果较好,阻垢率达到 79 0 %,缓蚀率达 70 7%,且阻垢率随Ca2 + 浓度增大而增大。     

Characterization of biological responses under different environmental conditions: A hierarchical modeling approach

A natural river system is organized as a nested hierarchy of interconnected habitats with specific environmental conditions to which the biological community has adapted. Due to this hierarchical structure, identifying the role of different stressors on the biological community is a formidable task. Efforts trying to link stressors to biological integrity have always been bound to the geographic scale of the selected study area, leading to scale-specific results. In this research, an attempt is made to lift this limitation and develop a hierarchical, scale-sensitive methodology that can identify the significant environmental stressors to the biological community at different scales. Sites with similar background environmental conditions are clustered using self-organizing maps (SOM). This is used to identify stressors which affect the biological community throughout the area of study - called environmental gradients or large-scale stressors. Subsequently, these clusters of similar observations (sampling sites) are progressively sub-divided using environmental variables with a significant but localized effect on the biological community - called small-scale stressors. A parent group of sites is split only when the resulting sub-groups have significantly different biological responses. At the end of this recursive sites decomposition procedure, the original set of observations is organized as a tree of environmentally homogeneous groups of observations characterized by unique biological responses to multiple stressors with different geographic extents. The developed hierarchical analysis methodology has been validated using a large-size dataset of environmental observations from the State of Ohio. Our results show that habitat degradation and increased nutrient loading are the large-scale stressors with a widespread impact in Ohio. Other stressors, such as heavy metals, pH or nitrate concentrations have significant albeit localized effects on biological integrity.     

规模化养猪场环境污染及防治途径

本文分析了规模化养猪场的环境污染情况,提出了规模化养猪场的污染防治途径。     

Comparative analysis of data reduction techniques for questionnaire validation using self-reported driver behaviors

Introduction: Exploratory data reduction techniques, such as Factor Analysis (FA) and Principal Component Analysis (PCA), are widely used in questionnaire validation with ordinal data, such as Likert Scale data, even though both techniques are indicated to metric measures. In this context, this study presents an e-survey, conducted to obtain self-reported behaviors between Brazilian drivers (N = 1,354, 55.2% of males) and Portuguese drivers (N = 348, 46.6% of males) based on 20 items from the Driver Behavior Questionnaire (DBQ) on a five-point Likert Scale. This paper aimed to examine DBQ validation using FA and PCA compared to Categorical Principal Component Analysis (CATPCA) which is more indicative to use with Likert Scale data. Results: The results from all techniques confirmed the most replicated factor structure of DBQ, distinguishing behaviors as errors, ordinary violations, and aggressive violation. However, after Varimax rotation, CATPCA explained 11% more variance compared to FA and 2% more than PCA. We identified cross-loadings among the component of the techniques. An item changed its dimension in the CATPCA results but did not change the structural interpretability. Individual scores from dimension 1 of CATPCA were significantly different from FA and PCA. Individual scores from factor 1 of CATPCA were significantly different from FA and PCA. Practical applications: The CATPCA seems to be more advantageous in order to represent the original data and considering data constrains. In addition to finding an interpretable factorial structure, the representation of the original data is regarded as relevant since the factor scores could be used for crash prediction in future analyses.     

What makes neighborhood different from home and city? Effects of place scale on place attachment

Several years ago Hidalgo and Hernandez reported a curvilinear, U-shaped, relationship between scale of place (apartment, neighborhood, city) and strength of attachment to the place. In this paper four studies are presented, carried out in four Central-European cities, that (1) confirmed the reported curvilinear relationship using five places (apartment, building, neighborhood, city district, city) in three out of four cities and for five items of the Place Attachment Scale, (2) revealed a consistent curvilinear, inverse U-shaped relationship between scale of place and percentage of variance of place attachment predicted by three groups of factors: physical (type of housing, size of building, upkeep and personalization of house precincts, etc.), social (neighborhood ties and sense of security in the residence place), and socio-demographic (age, education, gender, length of residence, family size), and (3) identified strength of direct and indirect effects of the three groups of predictors on attachment to the five types of places. The curvilinear relationship between place scale and place attachment was particularly strong in highly attractive cities and in those scale items that described people's emotional reactions to places whereas a linear relationship was obtained in the least attractive city and in the items that referred to sense of security, amount of control and knowledge of place. In all four cities the best predicted variable was attachment to middle ranges of the place scale (building and neighborhood). The overall best direct predictor of place attachment was neighborhood ties, followed by direct and indirect effects of length of residence, building size, and type of housing. In conclusion it is argued that the usual choice of predictors of place attachment is biased by researchers' interest in the middle scales of place (neighborhood) at the expense of other place scales. In the paper a claim is made that attachments to smaller (apartments, homes) and larger (city) scales of place along with their unique predictors deserve more attention from environmental psychologists.     

The environmental attitudes inventory: A valid and reliable measure to assess the structure of environmental attitudes

Environmental attitudes (EA), a crucial construct in environmental psychology, are a psychological tendency expressed by evaluating the natural environment with some degree of favour or disfavour. There are hundreds of EA measures available based on different conceptual and theoretical frameworks, and most researchers prefer to generate new measures rather than organize those already available. The present research provides a cumulative and theoretical approach to the measurement of EA, in which the multidimensional and hierarchical nature of EA is considered. Reported are findings from three studies on the development of a psychometrically sound, multidimensional inventory to assess EA cross-culturally, the Environmental Attitudes Inventory (EAI). The EAI has twelve specific scales that capture the main facets measured by previous research. The twelve factors were established through confirmatory factor analyses, and the EAI scales are shown to be unidimensional scales with high internal consistency, homogeneity and high test-retest reliability, and also to be largely free from social desirability.     

Terrestrial exposure of oilfield flowline additives diminish soil structural stability and remediative microbial function

Onshore oil production pipelines are major installations in the petroleum industry, stretching many thousands of kilometres worldwide which also contain flowline additives. The current study focuses on the effect of the flowline additives on soil physico-chemical and biological properties and quantified the impact using resilience and resistance indices. Our findings are the first to highlight deleterious effect of flowline additives by altering some fundamental soil properties, including a complete loss of structural integrity of the impacted soil and a reduced capacity to degrade hydrocarbons mainly due to: (i) phosphonate salts (in scale inhibitor) prevented accumulation of scale in pipelines but also disrupted soil physical structure; (ii) glutaraldehyde (in biocides) which repressed microbial activity in the pipeline and reduced hydrocarbon degradation in soil upon environmental exposure; (iii) the combinatory effects of these two chemicals synergistically caused severe soil structural collapse and disruption of microbial degradation of petroleum hydrocarbons.