Pilot study of personal, indoor and outdoor exposure to benzene, formaldehyde and acetaldehyde

There is a lack of data for health risk assessment of long term personal exposure to certain ubiquitous air pollutants present particularly in urban atmospheres. The relationship between ambient background concentrations and personal exposure is often unknown. A pilot campaign to measure indoor concentrations, outdoor concentrations and personal exposure to benzene, formaldehyde and acetaldehyde was conducted in a medium sized French town. A strong contribution to total personal exposure was observed from indoor sources, especially for formaldehyde and acetaldehyde, suggesting that indoor sources are dominant for these compounds. For benzene, the average personal exposure exceeded a 10 μgm^?3 limit value, although this was not the case for the ambient background concentration. For formaldehyde, the limit level was also exceeded. Observations suggest that true personal exposure cannot be determined directly from measurements pertaining from fixed ambient background monitoring stations. It is hoped that this will be taken into consideration by the bodies responsible for monitoring air pollution and the future European Air Quality Directive.     

A roadmap for the conservation of freshwater mussels in Europe

Europe has a long history of human pressure on freshwater ecosystems. As pressure continues to grow and new threats emerge, there is an urgent need for conservation of freshwater biodiversity and its ecosystem services. However, whilst some taxonomic groups, mainly vertebrates, have received a disproportionate amount of attention and funds, other groups remain largely off the public and scientific radar. Freshwater mussels (Bivalvia, Unionida) are an alarming example of this conservation bias and here we point out six conceptual areas that need immediate and long-term attention: knowledge, threats, socioeconomics, conservation, governance and education. The proposed roadmap aims to advance research, policy and education by identifying the most pressing priorities for the short- and long-term conservation of freshwater mussels across Europe.     

Carbon dioxide separation and capture by adsorption: a review

Environmental Chemistry Letters - Rising adverse impact of climate change caused by anthropogenic activities is calling for advanced methods to reduce carbon dioxide emissions. Here, we...     

ARX modeling approach to leak detection and diagnosis

This work presents a time series strategy for detection, location and quantification of leaks in large pipeline systems. The technology has two active components, which operate sequentially: the Detector and the Localizer. The Detector continuously screens real-time data, searching for any anomalies such as leaks, which are detected (or not) depending on their size and position. The Detector is based on auto-regressive multi-input/multi-output (MIMO) ARX predictors with one input filter. Subsequent to successful leak detection, the Localizer is launched to diagnose the leak via estimation of its parameters – diameter and location – using recorded data on a Search Time Window that includes information in the neighborhood of the instant of detection. The Localizer is also an ARX predictor, but with two input processors, the first is a filter for dynamic plant inputs and the second filter processes “parameter signals” of active leaks. The Localizer is developed beforehand via model identification with plant data under the action of known, artificially simulated, leaks. It is, therefore, able to recognize an active pattern of leak parameters, by maximizing the adherence of its predictions to data in the Search Time Window. The proposed detection and location methods were successfully tested in simulated leak scenarios for an industrial naphtha pipeline.     

西安夏季大气亚微米颗粒物化学组成与来源的在线观测研究

西安作为汾渭平原地区最大的城市,大气颗粒物污染形势严峻.2017年夏季期间,在西安市浐灞生态园区运用气溶胶化学组分监测仪,对大气亚微米颗粒物中的非难挥发性组分(NR-PM1)进行了在线监测.观测期间NR-PM1的平均质量浓度为(30.1?±?15.4)μg???m?3.其中有机物含量最高,占NR-PM1总质量浓度的63...     

Do tailings from the Mariana,MG (Brazil), disaster affect the initial development of millet,maize, and sorghum?

Environmental Science and Pollution Research - The collapse of the Fundão dam in Mariana, MG, in 2015 resulted in the overflow of more than 50 million m3 of mud containing mine tailings,...     

Evolution of bacterial community during bioremediation of PAHs in a coal tar contaminated soil

The monitoring of a windrow treatment applied to soil contaminated by mostly 2-, 3- and 4-ring PAHs produced by coal tar distillation was performed by following the evolution of both PAH concentration and the bacterial community. Total and PAH-degrading bacterial community structures were followed by 16S rRNA PCR-DGGE in parallel with quantification by bacterial counts and 16 PAH measurements. Six months of biological treatment led to a strong decrease in 2-, 3- and 4-ring PAH concentrations (98, 97 and 82% respectively). This result was associated with the activity of bacterial PAH-degraders belonging mainly to the Gamma-proteobacteria, in particular, the Enterobacteria and Pseudomonas genera, which were detected over the course of the treatment. This group was considered to be a good bioindicator to determine the potential PAH biodegradation of contaminated soil. Conversely, other species, like the Beta-proteobacteria, were detected after 3months, when 2-, 3- and 4-ring PAHs were almost completely degraded. Thus, presence of the Beta-proteobacteria group could be considered a good candidate indicator to estimate the endpoint of biotreatment of this type of PAH-contaminated soil.     

Impact of the mixing boundary layer on the relationship between PM2.5 and aerosol optical thickness

The purpose of this paper is to study the relationship between columnar aerosol optical thickness and ground-level aerosol mass. A set of Sun photometer, elastic backscattering lidar and TEOM measurements were acquired during April 2007 in Lille, France. The PM2.5 in the mixed boundary layer is estimated using the lidar signal, aerosol optical thickness, or columnar integrated Sun photometer size distribution and compared to the ground-level station measurements. The lidar signal recorded in the lowest level (240 m) is well correlated to the PM2.5 (R² = 0.84). We also show that the correlation between AOT-derived and measured PM2.5 is significantly improved when considering the mixed boundary layer height derived from the lidar. The use of the Sun photometer aerosol fine fraction volume does not improve the correlation.     

Remediation of DDT‐contaminated soil using optimized mixtures of surfactants and a mixing system

Soil contaminated with persistent pesticides, such as DDT, poses a serious risk to humans and to wildlife. A surfactant‐aided soil‐washing technique was studied as an alternative method for remediation of DDT‐contaminated soil. An ex situ soil washing method was investigated using nonionic and anionic surfactants due to the clayey structure of the contaminated soil. A mixture of 1 percent nonionic surfactant (Brij 35) and 1 percent anionic surfactant (SDBS) removed more than 50 percent of DDT from soil in a flow‐through system, whereas individual surfactants or other combinations of the surfactants had a lower removal efficiency. The soil‐washing technique was improved using a mixing system. The mixture of surfactants was optimized in the mixing system, and the combination of 2 percent Brij 35 and 0.1 percent SDBS was found to be optimum, removing 70 to 80 percent of DDT. Prewashing of the soil with tap water decreased the adsorption of surfactants to soil particles by 30 to 40 percent, and postwashing recovered 90 percent of the surfactants. © 2010 Wiley Periodicals, Inc.     

Maximum power point tracking methods for photovoltaic systems operating under partially shaded or rapidly variable insolation conditions: a review paper

To increase the efficiency of photovoltaic (PV) systems, maximum power point (MPP) tracking of the solar arrays is needed. Under partially shaded conditions (PSCs), the solar arrays power–current (P–I) characteristic has multiple MPP. This paper presents various methods and approaches of tracking the MPP from a PV generator operating under PSC. Some comparisons, advantages, drawbacks and critical analysis of each method are discussed. It was found that, indirect methods use empirical data or mathematical expressions of numerical approximations to estimate the MPP from the PV generator’s voltage, current and irradiance. Direct methods offer the advantage of obtaining the actual maximum power from the PV generator’s voltage and current. Artificial intelligence methods do not need exact mathematical models. They can perform under parameter variation, load and supply voltage disturbances. Finally, novel methods require less number of iterations to converge, independent to the initial conditions. All these algorithms can be included in some of the DC/DC converters and MPP trackers for stand-alone or grid-connected systems.