Advanced oxidation/reduction technologies: a perspective from Iberoamerican countries

Environmental Science and Pollution Research -     

Understanding and addressing the environmental risk of microplastics

Over the past decades, the plastic production has been dramatically increased. Indeed, a category of small plastic particles mainly with the shapes of fragments, fibers, or spheres, called microplastics (particles smaller than 5 mm) and nanoplastics (particles smaller than 1 μm) have attracted particular attention. Because of its wide distribution in the environment and potential adverse effects to animal and human, microplastic pollution has been reported as a serious environment problem receiving increased attention in recent years. As one of the commonly detected emerging contaminants in the environment, recent evidence indicates that the concentration of microplastics show an increasing trend, for the reason that up to 12.7 million metric tons of plastic litter is released into aquatic environment from land-based sources each year. Furthermore, microplastic exposure levels of model organisms in laboratory studies are usually several orders of magnitude higher than those found in environment, and the microplastics exposure conditions are also different with those observed in the environment. Additionally, the detection of microplastics in feces indicates that they can be excreted out of the bodies of animal and human. Hence, great uncertainties might exist in microplastics exposure and health risk assessment based on current studies, which might be exaggerated. Policies reduce microplastic emission sources and hence minimize their environmental risks are determined. To promote the above policies, we must first overcome the technical obstacles of detecting microplastics in various samples.     

Molecular Detection of human Noroviruses in Influent and Effluent Samples From Two Biological Sewage Treatment Plants in the Region of Monastir,Tunisia

Noroviruses (NoVs) are responsible for numerous cases of waterborne and foodborne gastroenteritis every year. They are released in the sewage and their detection in this environment can reflect the epidemiology of the viral strains circulating in the community. A three-year (2007–2010) survey was conducted in order to evaluate the presence of human NoVs using RT-PCR in 518 sewage samples collected at the entrance and exit of two biological sewage treatment plants located in Monastir region, Tunisia. In this study, we aimed to genetically characterize the most prevalent GI and GII NoV strains, in order to obtain a rough estimate of the efficacy of disinfection treatments and to compare the results with clinical data documented in the same area during the same period. This work confirms the wide circulation and the genetic diversity of NoVs in Tunisia and the widespread distribution of NoV variants in both raw and treated wastewater. Indeed, NoV was detected in 192 (37.1 %) sewage samples, among them mixed infections with group A rotavirus were detected in 125 (65.1 %) cases. The genotypes of the GI NoVs were GI.1, GI.2, GI.4, GI.5, and GI of unassigned genotype (GI.UA), and the genotypes of the GII NoVs were all GII.12. This study enhances the currently poor environmental virological data gathered in Tunisia, demonstrates the benefit of environmental surveillance as a tool to determine the epidemiology of NoVs circulating in a given community, and underlines the need for the design and support of similar long-term studies in our country, in order to compensate for the absence of a national surveillance system for gastroenteric viruses.     

A One Year Study on the Concentrations of Norovirus and Enteric Adenoviruses in Wastewater and A Surface Drinking Water Source in Norway

Enteric viruses transmitted via the faecal-oral route occur in high concentrations in wastewater and may contaminate drinking water sources and cause disease. In order to quantify enteric adenovirus and norovirus genotypes I and II (GI and GII) impacting a drinking source in Norway, samples of surface water (52), wastewater inlet (64) and outlet (59) were collected between January 2011 and April 2012. Samples were concentrated in two steps, using an electropositive disc filter and polyethylene glycol precipitation, followed by nucleic acid extraction and analysis by quantitative polymerase chain reaction. Virus was detected in 47/52 (90.4 %) of surface water, 59/64 (92 %) of wastewater inlet and 55/59 (93 %) of wastewater outlet samples. Norovirus GI occurred in the highest concentrations in surface water (2.51e + 04) and adenovirus in wastewater (2.15e + 07). While adenovirus was the most frequently detected in all matrices, norovirus GI was more frequently detected in surface water and norovirus GII in wastewater. This study is the first in Norway to monitor both sewage and a drinking water source in parallel, and confirms the year-round presence of norovirus and adenovirus in a Norwegian drinking water source.     

危化品企业安全生产标准化与其他管理体系的对比研究

分析了安全生产标准化与其他管理体系的关系,并结合当前推进安全生产标准化工作的具体要求,阐述了安全生产标准化的作用。     

Origin of major ions in monthly rainfall events at the Bamenda Highlands, North West Cameroon

Rainwater characteristics can reveal emissions from various anthropogenic and natural sources into the atmosphere. The physico-chemical characteristics of 44 monthly rainfall events （collected between January and December 2012） from 4 weather stations （Bamenda, Ndop plain, Ndawara and Kumbo） in the Bamenda Highlands （BH） were investigated. The purpose was to determine the sources of chemical species, their seasonal inputs and suitability of the rainwater for drinking. The mean pH of 5 indicated the slightly acidic nature of the rainwater. Average total dissolved solids （TDS） were low （6.7 mg/L）, characteristic of unpolluted atmospheric moisture/air. Major ion concentrations （mg/L） were low and in the order K＋ 〉 Ca2＋ 〉 Mg2~ 〉 Na＋ for cations and NO3 〉〉 HCO3 〉 SO] 〉 CI- 〉 PO3- 〉 F- for anions. The average rainwater in the area was mixed Ca-Mg-SO4-CI water type. The CI-/Na＋ ratio （1.04） was comparable to that of seawater （1.16）, an indication that N a＋ and CI originated mainly from marine （Atlantic Ocean） aerosols. High enrichments of Ca2＋, Mg2＋ and SO2- to Na＋ ratios relative to seawater ratios （constituting 44% of the total ions） demonstrated their terrigenous origin, mainly from Saharan and Sahelian arid dusts. The K＋/Na＋ ratio （2.24）, which was similar to tropical vegetation ash （2.38）, and NO3 was essentially from biomass burning. Light （〈 100 mm） pre-monsoon and post-monsoon convective rains were enriched in major ions than the heavy （〉 100 mm） monsoon rains, indicating a high contribution of major ions during the low convective showers. Despite the acidic nature, the TDS and major ion concentrations classified the rainwater as potable based on the WHO guidelines.     

Community structure and elevational diversity patterns of soil Acidobacteria

Acidobacteria is one of the most dominant and abundant phyla in soil,and was believed to have a wide range of metabolic and genetic functions. Relatively little is known about its community structure and elevational diversity patterns. We selected four elevation gradients from 1000 to 2800 m with typical vegetation types of the northern slope of Shennongjia Mountain in central China. The vegetation types were evergreen broadleaved forest,deciduous broadleaved forest,coniferous forest and sub-alpine shrubs. We analyzed the soil acidobacterial community composition,elevational patterns and the relationship between Acidobacteria subdivisions and soil enzyme activities by using the 16 S rRNA meta-sequencing technique and multivariate statistical analysis. The result found that 19 known subdivisions as well as an unclassified phylotype were presented in these forest sites,and Subdivision 6 has the highest number of detectable operational taxonomic units(OTUs). A significant single peak distribution pattern(P 0.05) between the OTU number and the elevation was observed. The Jaccard and Bray–Curtis index analysis showed that the soil Acidobacteria compositional similarity significantly decreased(P 0.01) with the increase in elevation distance. Mantel test analysis showed the most of the soil Acidobacteria subdivisions had the significant relationship(P 0.01) with different soil enzymes. Therefore,soil Acidobacteria may be involved in different ecosystem functions in global elemental cycles. Partial Mantel tests and CCA analysis showed that soil pH,soil temperature and plant diversity may be the key factors in shaping the soil Acidobacterial community structure.     

Evaluation of accuracy of linear regression models in predicting urban stormwater discharge characteristics

Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days （ADD）, have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency＇s Storm Water Management Model （SWMM）. The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid （TSS） discharge loads and event mean concentrations （EMC） were extracted. From these data, linear regression models were developed. R2 and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data.