Given the prevalence of nitrate and phosphate in surface and groundwater, it is important to develop technology for the simultaneous removal of nitrate and phosphate. In this study, we prepared the bimetallic nanoparticles of Fe coupled with copper or nickel supported on chelating resin DOW 3N (D-Fe/Ni and D-Fe/Cu) for removing nitrate and phosphate simultaneously. XPS profiles revealed that Cu has better ability than Ni to increase the stability of Fe nanoparticles and prevent nZVI from oxidation. The results showed that nitrate removal efficiencies by D-Fe/Ni and D-Fe/Cu were 98.7% and 95.5%, respectively and the phosphate removal efficiencies of D-Fe/Cu and D-Fe/Ni were 99.0% and 93.0%, respectively. Besides adsorption and coprecipitation as reported in previous studies, the mechanism of phosphate removal also includes the adsorption of the newly formed polymeric ligand exchanger (PLE). Moreover, in previous studies, the presence of phosphate had significant negative effects on the reduction of nitrate. However, in this study, the removal efficiency of nitrate was less affected with the increasing concentration of phosphate for D-Fe/Cu. This was mainly because D-Fe/Cu had higher adsorption capacity of phosphate due to the newly formed PLE according to the XPS depth profile analysis.

This paper investigates the motives behind corporate giving and determines whether perceived risk plays a major role in corporate surplus food donation intention. A conceptual model is developed from the perspectives of perceived risk, economic concern, past behavior, and moral motives. A questionnaire survey is conducted among food manufacturers and retailers in the Sichuan Province in China. A total of 143 valid observations are used to conduct structural equation modeling analysis. The results show that corporate reputation, legislation, and business risks are the main sub dimensions of risks that corporations perceive. Perceived risk, past behavior, environmental concern, and altruism affect corporate donation intention significantly. Implications of the findings for promoting surplus food donation are also discussed.

The paper reviews the existing applications of sensing technologies for measuring construction off-road vehicle emissions (COVE) such as earthmoving equipment. The current literature presented different measurement methods and reported the results of utilisation of new technologies for measuring COVE. However, previous papers used different technology applications covering only a part of the monitoring process with its own limitations. Since technologies are advancing and offering novel solutions, there is an urgent need to identify the gaps, re-evaluate the current methods, and develop a critical agenda for automating the entire process of collecting emissions data from construction sites, and monitoring the emission contributors across cities. This paper systematically identifies relevant papers through a search of three key databases—Web of Science, Engineering Valley and Scopus—covering the publications in the last decade from 2008 to 2017. An innovative robust research method was designed to select and analyse the relevant papers. The identified papers were stored in a data set, and a thematic algorithm employed to find the clusters of papers which might be potentially relevant. The selected papers were used for further micro-thematic analysis to find key relevant papers on COVE, and the gap in the literature. A sample of relevant papers was found relevant to COVE and critically reviewed by coding and content analysis. This paper critically reviews the selected papers and also shows that there is a considerable gap in the applications of new technologies for measuring in-use COVE in real time based on real activities toward automated methods. This review enables practitioners and scholars to gain a concrete understanding of the gap in measuring COVE and to provide a significant agenda for future technology applications.

In this study, a chabazite-rich tuff (CHA) from the Bala deposit of Ankara region (Turkey) and its modified forms (CuCHA, AgCHA, FeCHA, and HCHA samples) were investigated at 273 and 298 K using volumetric apparatus up to 100 kPa. The chabazite samples were characterized by using thermal analysis (TG-DTG-DTA), X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy with detector X-ray energy dispersive (SEM-EDX), Fourier transform infrared (FT-IR), and N₂ adsorption methods. It was found that natural chabazite is composed of predominantly chabazite with small amounts of clinoptilolite and erionite. XRD showed that there are major structural changes to Fe- and H-exchanged chabazite samples. Capacity of chabazites for CH₄ ranged from 0.168 and 1.341 mmol/g. Among all the modified forms, it was observed that Ag form of chabazite zeolite had the greatest methane adsorption capacity at both temperatures.

The use of bioscrubber is attracting increasing attention for exhaust gas treatment in intensive pig farming. However, the challenge is to improve the methane (CH₄) removal efficiency as well as the possibility of pig house wastewater treatment. Three laboratory-scale bioscrubbers, each equipped with different recirculation water types, livestock wastewater (10-times-diluted pig house wastewater supernatant), a methanotroph growth medium (10-times-diluted), and tap water, were established to evaluate the performance of CH₄ removal and wastewater treatment. The results showed that enhanced CH₄ removal efficiency (25%) can be rapidly achieved with improved methanotrophic activity due to extra nutrient support from the wastewater. The majority of the CH₄ was removed in the middle to end part of the bioscrubbers, which indicated that CH₄ removal could be potentially optimised by extending the length of the reactor. Moreover, 52–86% of the ammonium (NH₄⁺-N), total organic carbon (TOC), and phosphate (PO₄³⁻-P) removal were simultaneously achieved with CH₄ removal in the present study. Based on these results, this study introduces a low-cost and simple-to-operate method to improve CH₄ removal and simultaneously treat pig farm wastewater in bioscrubbers.

Water pollution is one of the main threats to public health in Pakistan. The watchdogs for drinking water quality are toothless, hence Pakistan’s ranking in maintaining water quality standards is 80th out of 122 nations. Despite such alarming situation coupled with violation of various drinking water quality parameters set by WHO, the risk perception of people remains an unfolded area of research. This paper examines the risk perception of household regarding water pollution in Pakistan and its potential effect on human health. In this way, we present a more analytical interpretation of the subject by collecting data from a survey questionnaire from one of the largest urban cities of Pakistan. Conclusions are drawn which stress that education, income, and knowledge of water pollution have higher impact on risk perception. From this position, and with the development of implications for policy, we demonstrate the need of a systematic quantification of various uncertainties that can provide more realistic support for remediation-related decisions to policy makers.

The purpose of this study was to investigate the aqueous phase photochemical behavior of enoxacin (ENO), an antibiotic selected as a model pollutant of emerging concern. The second-order reaction rate constants of ENO with hydroxyl radicals (HO●) and singlet oxygen (¹O₂) were determined at pH 3, 7, and 9. Also, the rate constants of the electron transfer reaction between ENO and triplet states of chromophoric dissolved organic matter (³CDOM*) are reported for the first time, based on anthraquinone-2-sulfonate (AQ2S) as CDOM proxy. The sunlight-driven direct and indirect ENO degradation in the presence of dissolved organic matter (DOM) is also discussed. The results show that direct photolysis, which occurs more rapidly at higher pH, along with the reactions with HO● and ³AQ2S*, is the key pathway involved in ENO degradation. The ENO zwitterions, prevailing at pH 7, show kENO, HO●, kENO,₁O₂, and kENO,₃AQ₂S* of (14.0 ± 0.8) × 10¹⁰, (3.9 ± 0.2) × 10⁶, and (61.5 ± 0.7) × 10⁸ L mol⁻¹ s⁻¹, respectively, whose differences at pH 3, 7, and 9 are due to ENO pH-dependent speciation and reactivity. These k values, along with the experimental ENO photolysis quantum yield, were used in mathematical simulations for predicting ENO persistence in sunlit natural waters. According to the simulations, dissolved organic matter and water depth are expected to have the highest impacts on ENO half-life, varying from a few hours to days in summertime, depending on the concentrations of relevant waterborne species (organic matter, NO₃⁻, NO₂⁻, HCO₃⁻).

This study applies asymmetric causality to renewable energy (REC), carbon dioxide emissions (CE), and real GDP using non-linear broadcasting between these variables through the non-linear autoregressive distributed lag model (NARDL) to examine the short- and long-run asymmetries in the inconsistency of greenhouse gas emissions among the variables and to unpack the asymmetric causality of selective variables through positive and negative shocks for time series data from the Kingdom of Saudi Arabia between 1990 and 2014. The bounds cointegration test shows the existence of long-term dealings among all considered variables in the presence of asymmetry. The non-linear asymmetric causality test shows that negative shocks in carbon dioxide emissions had only positive impacts on real GDP in the long-term but are unobservable in the short-term. Additionally, the short- and the long-term incidences of positive shocks on real GDP are not similar to the negative shock to REC, implying the existence of asymmetric impacts on REC in both short- and long-term forms. Finally, the asymmetric causal relationship from carbon dioxide emissions to REC is neutral in the long-term. Both positive and negative shocks to REC consistently had an adverse effect on CE in the long-term. The presence of asymmetry between economic growth, CE, and REC could be of major substantial for more helpful policymakers and the action plan of sustainable development goals (SDGs) in Saudi Arabia.

Biosurfactants are promising substitutes for chemical surfactants during polycyclic aromatic hydrocarbon (PAH) bioremediation. However, recent studies have revealed contrasting findings and critical knowledge gaps regarding the impacts of biosurfactants on the soil PAH biodegradation efficiency and microbial community. Here, a laboratory study was conducted to evaluate the impact of rhamnolipid on the PAH dissipation efficiency and microbial community structure during the time-course incubation. The data showed that the contribution ratio of biotic loss and abiotic loss depended on the ring number of PAH. In the microcosms supplemented with 20 μg g⁻¹ rhamnolipid, the biodegradation efficiencies of phenanthrene, fluoranthene, and pyrene increased by 10.1%, 12.3%, and 22.0%, respectively, compared to those in the rhamnolipid-free treatment after incubation for 7 days. In contrast, rhamnolipid either had no impact on or inhibited PAH degradation in the later time points (21–35 days). The abundance of bacterial 16S rRNA and phnAc genes showed significant increase in soil amended of both PAH and rhamnolipid. MiSeq sequencing results revealed that potential PAHs-degrading Massilia, Bacillus, Lysobacter, Archrobacter, and Phenylobacterium became dominant genera in PAH treatment, irrespective of the rhamnolipid added. Nevertheless, PAH addition in the presence of rhamnolipid also significantly stimulated the growth of Delftia, Brevundimonas, Tumebacillus, and Geobacillus. In contrast, the rhamnolipid altered the microbial community composition through the selection of Gaiella, Solirubrobacter, Nocardioides, and Bacillus. The results reveal the intensive selectivity effect of PAH and rhamnolipid on the soil microbes that are involved in bioremediation, and highlight the positive effect on PAHs biodegradation.

In northern countries, the climate, and consequently the use of studded tyres and winter traction sanding, causes accumulation of road dust over winter and spring, resulting in high PM₁₀ concentrations during springtime dusting events. To quantify the dust at the road surface, a method—the wet dust sampler (WDS)—was developed allowing repeatable sampling also under wet and snowy conditions. The principle of operation is flushing high-pressurised water over a defined surface area and transferring the dust laden water into a container for further analyses. The WDS has been used for some time and is presented in detail to the international scientific community as reported by Jonsson et al. (2008) and Gustafsson et al. (2019), and in this paper, the latest version is presented together with an evaluation of its performance. To evaluate the WDS, the ejected water amount was measured, as well as water losses in different parts of the sampling system, together with indicative dust measurement using turbidity as a proxy for dust concentration. The results show that the WDS, when accounting for all losses, have a predictable and repeatable water performance, with no impact on performance based on the variety of asphalt surface types included in this study, given undamaged surfaces. The largest loss was found to be water retained on the surface, and the dust measurements imply that this might not have as large impact on the sampled dust as could be expected. A theoretical particle mass balance shows small particle losses, while field measurements show higher losses. Several tests are suggested to validate and improve on the mass balances. Finally, the WDS is found to perform well and is able to contribute to further knowledge regarding road dust implications for air pollution.