This study was conducted to acquire novel insight into differences between bulk (16S rDNA) and metabolically active (16S rRNA) prokaryotic communities in the sediment of a hypereutrophic lake (Japan). In the bulk communities, the class Deltaproteobacteria and the order Methanomicrobiales were dominant among bacteria and methanogens. In the metabolically active communities, the class Alphaproteobacteria and the order Methanomicrobiales and the family Methanosaetaceae were frequently found among bacteria and methanogens. Unlike the bulk communities of prokaryotes, the composition of the metabolically active communities varied remarkably vertically, and their diversities greatly decreased in the lower 20 cm of sediment. The metabolically active prokaryotic community in the sediment core was divided into three sections based on their similarity: 0–6 cm (section 1), 9–18 cm (section 2), and 21–42 cm (section 3). This sectional distribution was consistent with the vertical pattern of the sedimentary stable carbon and nitrogen isotope ratios and oxidation–reduction potential in the porewater. These results suggest that vertical disturbance of the sediment may influence the communities and functions of metabolically active prokaryotes in freshwater lake sediments. Overall, our results indicate that rRNA analysis may be more effective than rDNA analysis for evaluation of relationships between actual microbial processes and material cycling in lake sediments.

The olive mill wastewater (OMW) properties impose substantial practical and fiscal difficulties for effective management and dumping. A feasible and practical option is a regulated spreading of OMW into the soil. This study aimed to investigate the sustainable reuse of OMW through land application to enhance soil quality and wheat growth performance under rain-fed conditions. OMW was spread at 20, 40, 60, 80, and 120 m³ ha⁻¹ at two sites. Soil physical and chemical properties were measured after OMW application and after harvest. Wheat growth performance and leaf nutrient content were determined. This study revealed no deleterious influence of OMW application on soil properties and wheat growth at the two locations for all OMW application doses. The OMW land spreading improved significantly wheat growth by increasing the biological yield (BYLD) (8.4 to 36.5%), grain yield (GYLD) (20.1 to 79.4%), and harvest index (HI) (4.2 to 60.2%). Based on the measured soil chemical parameters and wheat grain yield, we can suggest that OMW application rate at 60 m³ ha⁻¹ could improve significantly wheat growth without significant negative impact on soil properties. In conclusion, we recommend using OMW as suggested in this study for wheat. However, still the long-term application of OMW assessment and local legislative adaptation of saving use are necessary.

A comparative experiment was conducted based on a non-road diesel engine to investigate the effects of two after-treatment devices on the engine’s emission characteristics as well as their power and fuel consumption performances. The first after-treatment device is a combination of a diesel oxidation catalyst (DOC) and a catalytic diesel particulate filter (CDPF). The second device is a single CDPF-coated improved noble metal catalyst. Results showed that the two after-treatment devices had almost no effect on the power and fuel consumption performance. The gaseous and particulate emissions of the engine depended on the operation conditions including the speed and load. However, the dual DOC+CDPF system and the single CDPF reduced more than 81% of the carbon monoxide (CO) and 73% of the hydrocarbon (HC) emissions. Notably, the reduction efficiency by the single CDPF was higher than that of the DOC+CDPF system. In terms of the particulate emissions, both after-treatment devices achieved more than 96% reduction of the particle number (PN) and up to 88% reduction of the particulate mass (PM). Similarly, the single CDPF outperformed the dual DOC+CDPF system in reducing particle emissions. Although no changes occurred in the bimodal particle size distribution of the engine after the installation of the two after-treatment devices, they performed differently in reducing particles with different sizes. The particles reduction efficiency of the DOC+CDPF system was higher than that of the single CDPF for the particles smaller than 14.3 nm, and this trend converted for particles larger than 14.3 nm. Improving the noble metal catalyst load in the CDPF ensured a performance that rivaled the DOC+CDPF system. Apart from the NOx emissions, the installation of a single CDPF with an improved noble metal catalyst load can make the non-road diesel engine meet the limits of the China IV emission regulations.

Commercial department assumes the vital part in energy conservation and carbon dioxide emission mitigation of China. This paper applies the time-series data covering 2001–2015 and introduces the STIRPAT method to research the factors of commercial department’s carbon dioxide emissions in China. The combination of STIRPAT method and ridge regression is first adopted to research carbon dioxide emissions of commercial department in China. Potential influencing factors of carbon dioxide emission, including economic growth, level of urbanization, aggregate population, energy intensity, energy structure and foreign direct investment, are selected to establish the extended stochastic impacts by regression on population, affluence and technology (STIRPAT) model, where ridge regression is adopted to eliminate multicollinearity. The estimation consequences show that all forces were positively related to carbon dioxide emissions in China’s commercial department except for energy structure. Energy structure is the only negative factor and aggregate population is the maximal influencing factor of carbon dioxide emissions. The economic growth, urbanization level, energy intensity and foreign direct investment all positively contribute to carbon dioxide emissions of commercial department. The findings have significant implications for policy-makers to enact emission reduction policies in commercial sector. Therefore, the paper ought to take into full consideration these different impacts of above influencing factors to abate carbon dioxide emissions of commercial sector.

A novel furnace throat structure was designed to reduce dust particle concentration in the flue gas emitted from the copper smelting industry. A two-stage turbulence model of the furnace throat based on the RNG k-ε model combined with the stochastic trajectory model was developed to analyze the gas flow and particle trajectories in this furnace throat structure. The resulting turbulent flow fields and particle trajectories under different operating conditions were shown and discussed. It indicates that the furnace throat plays an important role in separating the dust particles from the flue gas by applying centrifugal force and subsequent resistance force. Moreover, the effects of the radius of the inner flue, the number of the spiral plate, and the number of the spiral plate turns on the particle collection efficiency were analyzed to optimize the throat structure. The simulation results show that the furnace throat with inner flue radius of 0.05 m, two spiral plates, and two spiral plate turns has the highest particle collection efficiency. Furthermore, a series of experimental tests were conducted to validate the accuracy of the simulation results, and the measured experimental data show a good correlation with the numerical results.

One of the most common anthropogenic impacts on river ecosystems is the effluent discharge from wastewater treatment plants. The effects of this contamination on stream biota may be intensified in Mediterranean climate regions, which comprise a drought period that leads to flow reduction, and ultimately to stagnant pools. To assess individual and combined effects of flow stagnation and sewage contamination, biofilm and gastropod grazers were used in a 5-week experiment with artificial channels to test two flow velocity treatments (stagnant flow/basal flow) and two levels of organic contamination using artificial sewage (no sewage input/sewage input). Stressors’ effects were determined on biofilm total biomass and chlorophyll (Chl) content, on oxygen consumption and growth rate of the grazers (Theodoxus fluviatilis), and on the interaction grazer-biofilm given by grazer’s feeding activity (i.e., biofilm consumption rate). The single effect of sewage induced an increase in biofilm biomass and Chl-a content, simultaneously increasing both grazers’ oxygen consumption and their feeding activity. Diatoms showed a higher sensitivity to flow stagnation, resulting in a lower content of Chl-c. Combined stressors interacted antagonistically for biofilm total biomass, Chl-b contents, and grazers’s feeding rate. The effect of sewage increasing biofilm biomass and grazing activity was reduced by the presence of flow stagnation (antagonist factor). Our findings suggest that sewage contamination has a direct effect on the functional response of primary producers and an indirect effect on primary consumers, and this effect is influenced by water flow stagnation.

Carboxymethyl cellulose–stabilized sulfidated nano zerovalent iron (CMC-S-nZVI) was tested for its capacity to the removal of Cr(VI) in this study. The effect of synthesis approaches on morphology and properties of CMC-S-nZVI was studied. Results revealed CMC-S-nZVI prepared by the surface corrosion method had favorable homogeneity and corrosion resistance. The structure and morphology of CMC-S-nZVI particles were investigated by transmission electron microscopy, X-ray powder diffraction, and Fourier-transform infrared spectrometry. Batch experiments showed that the removal efficiency of Cr(VI) by the CMC-S-nZVI particles was influenced by the S/Fe molar ratio, initial pH, initial Cr(VI) concentration, and the reaction temperature. Increasing S/Fe molar ratio from 0 to 0.35 enhanced Cr(VI) removal efficiency from 65.37 to 85.08%. Reducing pH value and improving the reaction temperature have a positive impact on Cr(VI) removal. The removal amount was 535 mg/g (total iron) CMC-S-nZVI with initial Cr(VI) concentration of 50 mg/L. Compared with CMC-nZVI, CMC-S-nZVI had better performance in Cr(VI) removal in a simulated groundwater system. The results indicated that CMC-S-nZVI might be applicable for in situ treatment of the Cr(VI)-containing groundwater.

Triclosan (TCS) is a potential endocrine-disrupting compound (EDC), which produces an adverse impact on aquatic life and human beings. Wastewater discharge is considered as the primary source of triclosan in water bodies. The study is aimed to investigate the occurrence and environmental risk of triclosan released by municipal wastewater treatment plants (WWTP). An analytical protocol was developed and validated to determine the presence of TCS in the samples through offline solid-phase extraction (SPE) and liquid chromatography - electron spray ionization (ESI)—quadrupole mass spectrum (LC/ESI/MS). The limit of detection and quantification of protocol was estimated as 2.8 ng/L and 6.25 ng/L, respectively. The season-wise influent and effluent samples from two WWTP in Chennai, India, were monitored. The TCS concentrations in samples were found in the range of 443 to 1757 ng/L. The Risk Quotient (RQ) method was performed to evaluate the environmental (ecotoxicological and human health) risk associated with the exposure of TCS-containing wastewater. The results of the study revealed that primary producer (algae) was highly vulnerable to exposure of TCS in the aquatic environment. The estimated daily intake of TCS was much lower than the reference dosage, and this indicates that TCS did not produce any considerable risk to human health. Also, it suggested that additional treatment was required for complete removal of triclosan residues.

As we all know, geochemical data usually contain outliers and they are heterogeneous, which will severely affect the use of receptor models based on classical estimates. In this paper, an advanced modified RAPCS-RGWR (robust absolute principal component scores-robust geographically weighted regression) receptor model was introduced to analyze the pollution sources of eight heavy metals (Cd, Hg, As, Pb, Ni, Cu, Zn) in a city of southern China. The results showed that source identification and source apportionment are more consistent by this advanced model even though the soil types and farming patterns are diverse. Moreover, this model decreased the occurrence of negative values of the source contribution. For these reasons, the pollution sources were classified into five types by the new model in the study area: agricultural sources, industrial sources, traffic sources, comprehensive sources, and natural sources. (1) The contributions of agricultural sources to Cr and Ni were 243.36% and 242.61%, respectively; (2) the contribution of industrial sources to Cd was 79.25%; (3) the contribution of traffic sources to Cu was 100.31%; (4) the contributions of comprehensive sources to Hg, Pb, and Zn were 253.90%, 242.31%, and 93.32%, respectively; and (5) the contribution of natural sources to As was 208.21%. Overall, the RAPCS-RGWR receptor model improved the validity of the receptor models. It is of great realistic significance to understand and popularize the advanced model in soil source apportionment in agricultural land.