A novel application of concentrated solar thermal energy in foundries

Scrap preheating in foundries is a technology that saves melting energy, leading to economic and environmental benefits. The proposed method in this paper utilizes solar thermal energy for preheating scrap, effected through a parabolic trough concentrator that focuses sunlight onto a receiver which carries the metallic scrap. Scraps of various thicknesses were placed on the receiver to study the heat absorption by them. Experimental results revealed the pattern with which heat is gained by the scrap, the efficiency of the process and how it is affected as the scrap gains heat. The inferences from them gave practical guidelines on handling scraps for best possible energy savings. Based on the experiments conducted, preheat of up to 160 °C and a maximum efficiency of 70 % and a minimum efficiency of 40 % could be achieved across the time elapsed and heat gained by the scrap. Calculations show that this technology has the potential to save around 8 % of the energy consumption in foundries. Cumulative benefits are very encouraging: 180.45 million kWh of energy savings and 203,905 t of carbon emissions cut per year across the globe. This research reveals immense scope for this technology to be adopted by foundries throughout the world.     

Phytoplankton dynamics with a special emphasis on harmful algal blooms in the Mar Piccolo of Taranto (Ionian Sea,Italy)

The response of phytoplankton assemblages to the closure of urban sewage outfalls (USOs) was examined for the Mar Piccolo of Taranto (Mediterranean Sea), a productive semi-enclosed coastal marine ecosystem devoted to shellfish farming. Phytoplankton dynamics were investigated in relation to environmental variables, with a particular emphasis on harmful algal blooms (HABs). Recent analyses evidenced a general reduction of the inorganic nutrient loads, except for nitrates and silicates. Also phytoplankton biomass (chlorophyll a) and abundances were characterized by a decrease of the values, except for the inner area of the basin (second inlet). The phytoplankton composition changed, with nano-sized species, indicators of oligotrophic conditions, becoming dominant over micro-sized species. If the closure of the USOs affected phytoplankton dynamics, however, it did not preserve the Mar Piccolo from HABs and anoxia crises. About 25 harmful species have been detected throughout the years, such as the potentially domoic acid producers Pseudo-nitzschia cf. galaxiae and P seudo-nitzschia cf. multistriata, identified for the first time in these waters. The presence of HABs represents a threat for human health and aquaculture. Urgent initiatives are needed to improve the communication with authorities responsible for environmental protection, economic development, and public health for a sustainable mussel culture in the Mar Piccolo.     

Emerging trends in photodegradation of petrochemical wastes: a review

Various human activities like mining and extraction of mineral oils have been used for the modernization of society and well-beings. However, the by-products such as petrochemical wastes generated from such industries are carcinogenic and toxic, which had increased environmental pollution and risks to human health several folds. Various methods such as physical, chemical and biological methods have been used to degrade these pollutants from wastewater. Advance oxidation processes (AOPs) are evolving techniques for efficient sequestration of chemically stable and less biodegradable organic pollutants. In the present review, photocatalytic degradation of petrochemical wastes containing monoaromatic and poly-aromatic hydrocarbons has been studied using various heterogeneous photocatalysts (such as TiO₂, ZnO and CdS. The present article seeks to offer a scientific and technical overview of the current trend in the use of the photocatalyst for remediation and degradation of petrochemical waste depending upon the recent advances in photodegradation of petrochemical research using bibliometric analysis. We further outlined the effect of various heterogeneous catalysts and their ecotoxicity, various degradation pathways of petrochemical wastes, the key regulatory parameters and the reactors used. A critical analysis of the available literature revealed that TiO₂ is widely reported in the degradation processes along with other semiconductors/nanomaterials in visible and UV light irradiation. Further, various degradation studies have been carried out at laboratory scale in the presence of UV light. However, further elaborative research is needed for successful application of the laboratory scale techniques to pilot-scale operation and to develop environmental friendly catalysts which support the sustainable treatment technology with the “zero concept” of industrial wastewater. Nevertheless, there is a need to develop more effective methods which consume less energy and are more efficient in pilot scale for the demineralization of pollutant.     

The influence of the scale of mining activity and mine site remediation on the contamination legacy of historical metal mining activity

Globally, thousands of kilometres of rivers are degraded due to the presence of elevated concentrations of potentially harmful elements (PHEs) sourced from historical metal mining activity. In many countries, the presence of contaminated water and river sediment creates a legal requirement to address such problems. Remediation of mining-associated point sources has often been focused upon improving river water quality; however, this study evaluates the contaminant legacy present within river sediments and attempts to assess the influence of the scale of mining activity and post-mining remediation upon the magnitude of PHE contamination found within contemporary river sediments. Data collected from four exemplar catchments indicates a strong relationship between the scale of historical mining, as measured by ore output, and maximum PHE enrichment factors, calculated versus environmental quality guidelines. The use of channel slope as a proxy measure for the degree of channel-floodplain coupling indicates that enrichment factors for PHEs in contemporary river sediments may also be the highest where channel-floodplain coupling is the greatest. Calculation of a metric score for mine remediation activity indicates no clear influence of the scale of remediation activity and PHE enrichment factors for river sediments. It is suggested that whilst exemplars of significant successes at improving post-remediation river water quality can be identified; river sediment quality is a much more long-lasting environmental problem. In addition, it is suggested that improvements to river sediment quality do not occur quickly or easily as a result of remediation actions focused a specific mining point sources. Data indicate that PHEs continue to be episodically dispersed through river catchments hundreds of years after the cessation of mining activity, especially during flood flows. The high PHE loads of flood sediments in mining-affected river catchments and the predicted changes to flood frequency, especially, in many river catchments, provides further evidence of the need to enact effective mine remediation strategies and to fully consider the role of river sediments in prolonging the environmental legacy of historical mine sites.     

Depth-dependence and monthly variability of charophyte biomass production: consequences for the precipitation of calcium carbonate in a shallow <Emphasis Type="Italic">Chara</Emphasis>-lake

The month-to-month variability of biomass and CaCO₃ precipitation by dense charophyte beds was studied in a shallow Chara-lake at two depths, 1 and 3 m. Charophyte dry weights (d.w.), the percentage contribution of calcium carbonate to the dry weight and the precipitation of CaCO₃ per 1 m² were analysed from May to October 2011. Physical-chemical parameters of water were also measured for the same sample locations. The mean dry weight and calcium carbonate precipitation were significantly higher at 1 m than at 3 m. The highest measured charophyte dry weight (exceeding 2000 g m^?2) was noted at 1 m depth in September, and the highest CaCO₃ content in the d.w. (exceeding 80 % of d.w.) was observed at 3 m depth in August. The highest CaCO₃ precipitation per 1 m² exceeded 1695 g at 1 m depth in August. Significant differences in photosynthetically active radiation (PAR) were found between 1 and 3 m depths; there were no significant differences between depths for other water properties. At both sampling depths, there were distinct correlations between the d.w., CaCO₃ content and precipitation and water properties. In addition to PAR, the water temperature and magnesium and calcium ion concentrations were among the most significant determinants of CaCO₃ content and d.w. The results show that light availability seems to be the major factor in determining charophyte biomass in a typical, undisturbed Chara-lake. The study results are discussed in light of the role of charophyte vegetation in whole ecosystem functioning, with a particular focus on sedimentary processes and the biogeochemical cycle within the littoral zone.     

Assessment of trace metal air pollution in Paris using slurry-TXRF analysis on cemetery mosses

Mosses are useful, ubiquitous accumulation biomonitors and as such can be used for biomonitoring surveys. However, the biomonitoring of atmospheric pollution can be compromised in urban contexts if the targeted biomonitors are regularly disturbed, irregularly distributed, or are difficult to access. Here, we test the hypothesis that cemeteries are appropriate moss sampling sites for the evaluation of air pollution in urban areas. We sampled mosses growing on gravestones in 21 urban and peri-urban cemeteries in the Paris metropolitan area. We focused on Grimmia pulvinata (Hedwig) Smith, a species abundantly found in all studied cemeteries and very common in Europe. The concentration of Al, As, Br, Ca, Ce, Cl, Cr, Cu, Fe, K, Mn, Ni, V, P, Pb, Rb, S, Sr, Ti, and Zn was determined by a total reflection X-ray fluorescence technique coupled with a slurry sampling method (slurry-TXRF). This method avoids a digestion step, reduces the risk of sample contamination, and works even at low sample quantities. Elemental markers of road traffic indicated that the highest polluted cemeteries were located near the highly frequented Parisian ring road and under the influence of prevailing winds. The sites with the lowest pollution were found not only in the peri-urban cemeteries, adjoining forest or farming landscapes, but also in the large and relatively wooded cemeteries located in the center of Paris. Our results suggest that (1) slurry-TXRF might be successfully used with moss material, (2) G. pulvinata might be a good biomonitor of trace metals air pollution in urban context, and (3) cemetery moss sampling could be a useful complement for monitoring urban areas.

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Graphical abstract We tested the hypothesis that cemeteries are appropriate moss sampling sites for the evaluation of air pollution in urban areas. We sampled 110 moss cushions (Grimmia pulvinata) growing on gravestones in 21 urban and peri-urban cemeteries in the Paris metropolitan area. The concentration of 20 elements in mosses was determined by a total reflection X-ray fluorescence technique coupled with a slurry sampling method. Statistical analysis revealed that: - Urbanized Parisian areas crossed by traffic roads have the highest polluted cemeteries with a strong influence of main wind direction on the distribution of air pollutants - As expected, small cemeteries with low tree density were heavily polluted - Less obvious, large green spaces such as large cemeteries (Père Lachaise, Montmartre, Montparnasse) in the center of a dense metropolis like Paris present the same level of atmospheric trace metal pollution as cemeteries in less urbanized areas or nearing a very large forest. This suggests that even in densely urbanized areas, there is more spatial variability in pollution distribution than usually assumed and that large urban areas with low traffic and green filters such as trees are likely to intercept air pollutants

     

Research and application of method of oxygen isotope of inorganic phosphate in Beijing agricultural soils

Phosphorus (P) in agricultural ecosystems is an essential and limited element for plants and microorganisms. However, environmental problems caused by P accumulation as well as by P loss have become more and more serious. Oxygen isotopes of phosphate can trace the sources, migration, and transformation of P in agricultural soils. In order to use the isotopes of phosphate oxygen, appropriate extraction and purification methods for inorganic phosphate from soils are necessary. Here, we combined two different methods to analyze the oxygen isotopic composition of inorganic phosphate (δ¹⁸O_P) from chemical fertilizers and different fractions (Milli-Q water, 0.5 mol L^?1 NaHCO₃ (pH = 8.5), 0.1 mol L^?1 NaOH and 1 mol L^?1 HCl) of agricultural soils from the Beijing area. The δ¹⁸O_P results of the water extracts and NaHCO₃ extracts in most samples were close to the calculated equilibrium value. These phenomena can be explained by rapid P cycling in soils and the influence of chemical fertilizers. The δ¹⁸O_P value of the water extracts and NaHCO₃ extracts in some soil samples below the equilibrium value may be caused by the hydrolysis of organic P fractions mediated by extracellular enzymes. The δ¹⁸O_P values of the NaOH extracts were above the calculated equilibrium value reflecting the balance state between microbial uptake of phosphate and the release of intracellular phosphate back to the soil. The HCl extracts with the lowest δ¹⁸O_P values and highest phosphate concentrations indicated that the HCl fraction was affected by microbial activity. Hence, these δ¹⁸O_p values likely reflected the oxygen isotopic values of the parent materials. The results suggested that phosphate oxygen isotope analyses could be an effective tool in order to trace phosphate sources, transformation processes, and its utilization by microorganisms in agricultural soils.     

Toward better understanding and feasibility of controlling greenhouse gas emissions from treatment of industrial wastewater with activated sludge

Wastewater treatment plants (WWTPs) have been recognized as important sources for anthropogenic greenhouse gas (GHG) emission. The objective of the study was to thoroughly investigate a typical industrial WWTP in southern Taiwan in winter and summer which possesses the emission factors close to those reported values, with the analyses of emission factors, mass fluxes, fugacity, lab-scale in situ experiments, and impact assessment. The activated sludge was the important source in winter and summer, and nitrous oxide (N₂O) was the main contributor (e.g., 57 to 91 % of total GHG emission in a unit of kg carbon dioxide-equivalent/kg chemical oxygen demand). Albeit important for the GHGs in the atmosphere, the fractional contribution of the GHG emission to the carbon or nitrogen removal in wastewater treatment was negligible (e.g., less than 1.5 %). In comparison with the sludge concentration or retention time, adjusting the aeration rate was more effective to diminish the GHG emission in the activated sludge without significantly affecting the treated water quality. When the aeration rate in the activated sludge simulation was reduced by 75 %, the mass flux of N₂O could be diminished by up to 53 % (from 9.6 to 4.5 mg/m²-day). The total emission in the WWTP (including carbon dioxide, methane, and N₂O) would decrease by 46 % (from 0.67 to 0.36 kg CO₂-equiv/kg COD). However, the more important benefit of changing the aeration rate was lowering the energy consumption in operation of the WWTP, as the fractional contribution of pumping to the total emission from the WWTP ranged from 46 to 93 % within the range of the aeration rate tested. Under the circumstance in which reducing the burden of climate change is a global campaign, the findings provide insight regarding the GHG emission from treatment of industrial wastewater and the associated impact on the treatment performance and possible mitigation strategies by operational modifications.

     

Wastewater reuse: modeling chloroform formation

The chloroform is a substance that presents a significant risk to or via the aquatic environment. Thus, the emissions, discharges and losses of this substance need to be controlled during wastewater disinfection for reclamation and reuse purposes. Due to its carcinogenetic potential, multiple studies have been carried out on drinking and surface/natural waters but less consideration has been directed to the wastewater disinfection. The focus of this work studied the formation of chloroform during chlorination in prepared waters or artificial matrices that intended to simulate wastewaters stored in landscape ponds for green areas irrigation. The relation between reaction time, chlorine dose, and chloroform formation and the variation of the dissolved organic carbon (DOC) content during the reaction was assessed. A two-variant model was proposed to simulate breakpoint chlorination practices (when chlorine dose is equal or lower than chlorine demand) and super chlorination techniques (when chlorine dose tends to surpass chlorine demand). The model was validated by the application of actual data from working conditions of six wastewater treatment plants located in Algarve, Portugal, including other data obtained in previous research studies that were not used in the model development, and by comparing the predicted values with real measured ones.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.