Photocatalytic reduction of carbon dioxide over Cu/TiO<Subscript>2</Subscript> photocatalysts

The photocatalytic reduction of CO₂ with H₂O was investigated using Cu/TiO₂ photocatalysts in aqueous solution. For this purpose, Cu/TiO₂ photocatalysts (with 0.2, 0.9, 2, 4, and 6 wt.% of Cu) have been synthesized via sol-gel method. The photocatalysts were extensively characterized by means of inductively coupled plasma optical emission spectrometry (ICP-OES), N₂ physisorption (BET), XRD, UV-vis DRS, FT-IR, Raman spectroscopy, TEM-EDX, and photoelectrochemical measurements. The as-prepared photocatalysts contain anatase as a major crystalline phase with a crystallite size around 13 nm. By increasing the amount of Cu, specific surface area and band gap energy decreased in addition to the formation of large agglomeration of CuO. Results revealed that the photocatalytic reduction of CO₂ decreased in the presence of Cu/TiO₂ in comparison to pure TiO₂, which might be associated to the formation of CuO phase acting as a recombination center of generated electron-hole pair. Decreasing of photoactivity can also be connected with a very low position of conduction band of photocatalysts with high Cu content, which makes H₂ production necessary for CO₂ reduction more difficult.     

Pollution-induced community tolerance in benthic macroinvertebrates of a mildly lead-contaminated lake

Environmental Science and Pollution Research - Pollution-induced community tolerance (PICT) has been used to demonstrate effects of sediment contamination on microbes and meiofauna. Our study...     

Elemental and isotopic determination of lead (Pb) in particulate matter in the Brazilian city of Goiânia (GO) using ICP-MS technique

Environmental Science and Pollution Research - The toxic metal lead (Pb) can be harmful to human health in various manners, but is also considered as a distinguished tracer of environmental...     

Effect of ferrate on green algae removal

Green algae Cladophora aegagropila, present in cooling water of thermal power plants, causes many problems and complications, especially during summer. However, algae and its metabolites are rarely eliminated by common removal methods. In this work, the elimination efficiency of electrochemically prepared potassium ferrate(VI) on algae from cooling water was investigated. The influence of experimental parameters, such as Fe(VI) dosage, application time, pH of the system, temperature and hydrodynamics of the solution on removal efficiency, was optimized. This study demonstrates that algae C. aegagropila can be effectively removed from cooling water by ferrate. Application of ferrate(VI) at the optimized dosage and under the suitable conditions (temperature, pH) leads to 100% removal of green algae Cladophora from the system. Environmentally friendly reduction products (Fe(III)) and coagulation properties favour the application of ferrate for the treatment of water contaminated with studied microorganisms compared to other methods such as chlorination and use of permanganate, where harmful products are produced.

     

Overview of surface measurements and spatial characterization of submicrometer particulate matter during the DISCOVER-AQ 2013 campaign in Houston,TX

The sources of submicrometer particulate matter (PM₁) remain poorly characterized in the industrialized city of Houston, TX. A mobile sampling approach was used to characterize PM₁ composition and concentration across Houston based on high-time-resolution measurements of nonrefractory PM₁ and trace gases during the DISCOVER-AQ Texas 2013 campaign. Two pollution zones with marked differences in PM₁ levels, character, and dynamics were established based on cluster analysis of organic aerosol mass loadings sampled at 16 sites. The highest PM₁ mass concentrations (average 11.6 ± 5.7 µg/m³) were observed to the northwest of Houston (zone 1), dominated by secondary organic aerosol (SOA) mass likely driven by nighttime biogenic organonitrate formation. Zone 2, an industrial/urban area south/east of Houston, exhibited lower concentrations of PM₁ (average 4.4 ± 3.3 µg/m³), significant organic aerosol (OA) aging, and evidence of primary sulfate emissions. Diurnal patterns and backward-trajectory analyses enable the classification of airmass clusters characterized by distinct PM sources: biogenic SOA, photochemical aged SOA, and primary sulfate emissions from the Houston Ship Channel. Principal component analysis (PCA) indicates that secondary biogenic organonitrates primarily related with monoterpenes are predominant in zone 1 (accounting for 34% of the variability in the data set). The relevance of photochemical processes and industrial and traffic emission sources in zone 2 also is highlighted by PCA, which identifies three factors related with these processes/sources (~50% of the aerosol/trace gas concentration variability). PCA reveals a relatively minor contribution of isoprene to SOA formation in zone 1 and the absence of isoprene-derived aerosol in zone 2. The relevance of industrial amine emissions and the likely contribution of chloride-displaced sea salt aerosol to the observed variability in pollution levels in zone 2 also are captured by PCA.

Implications: This article describes an urban-scale mobile study to characterize spatial variations in submicrometer particulate matter (PM₁) in greater Houston. The data set indicates substantial spatial variations in PM₁ sources/chemistry and elucidates the importance of photochemistry and nighttime oxidant chemistry in producing secondary PM₁. These results emphasize the potential benefits of effective control strategies throughout the region, not only to reduce primary emissions of PM₁ from automobiles and industry but also to reduce the emissions of important secondary PM₁ precursors, including sulfur oxides, nitrogen oxides, ammonia, and volatile organic compounds. Such efforts also could aid in efforts to reduce mixing ratios of ozone.     

Composition and quantification of the anthropogenic and natural fractions of wastes collected from the stormwater drainage system for discussions about the waste management and people behavior

A study was made of the composition of wastes collected from the pipes of the stormwater drainage system of Sorocaba, SP, Brazil (600 thousand inhabitants). A total of 10 samples weighing at least 100 kg each were sorted into 19 items to determine the fraction that can be considered natural (earth/sand, stones, organic matter, and water, the latter determined after oven-drying the samples) and the anthropogenic fraction (the remaining 15 items, especially construction and demolition wastes and packaging). Soil/sand was found to be the main item collected (52.5 % dry weight), followed by the water soaked into the waste (24.3 %), which meant that all the other wastes were saturated in mud, whose contents varied from 6.4 % (glass) to 87.2 % (metalized plastics packaging). In general, 83 % of the collected wastes can be classified as “natural,” but the remaining 17 % represent 2,000 kg of the most varied types of wastes discarded improperly every day on the streets of the city. This is an alarming amount of wastes that may clog parts of the drainage systems, causing troubles for all the population (like flooding) and must be strongly considered in municipal solid wastes management and in environmental education programs.     

Application of 15N–18O double stable isotope tracer technique in an agricultural nonpoint polluted river of the Yangtze Delta Region

One strategy to combat nitrate (NO₃-N) contamination in rivers is to understand its sources. NO₃-N sources in the East Tiaoxi River of the Yangtze Delta Region were investigated by applying a ¹⁵N–¹⁸O dual isotope approach. Water samples were collected from the main channel and from the tributaries. Results show that high total N and NO₃-N are present in both the main channel and the major tributaries, and NO₃-N was one of the most important N forms in water. Analysis of isotopic compositions (δ ¹⁸O, δD) of water suggests that the river water mainly originated from three tributaries during the sampling period. There was a wide range of δ ¹⁵N-NO₃ (?1.4 to 12.4 ‰) and a narrow range of δ ¹⁸O-NO₃ (3.7 to 9.0 ‰) in the main channel waters. The δ ¹⁵N and δ ¹⁸O-NO₃ values in the upper, middle, and lower channels along the river were shifted as 8.2, 3.5, and 9.5 ‰, and 9.0, 4.2, and 6.0 ‰, respectively. In the tributary South Tiao, the δ ¹⁵N and δ ¹⁸O-NO₃ values were as high as 9.5 and 7.0 ‰, while in the tributaries Mid Tiao and North Tiao, NO₃-N in most of the samples had relatively low δ ¹⁵N and δ ¹⁸O-NO₃ values from 2.3 to 7.5 ‰ and 4.7 to 7.0 ‰, separately. Our results also suggest that the dual isotope approach can help us develop the best management practice for relieving NO₃-N pollution in the rivers at the tributary scale.     

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis.