The aim of the present study was to investigate biosurfactant production ability of five different polyaromatic hydrocarbon (PAH)-metabolizing bacteria, such as Ochrobactrum anthropi IITR07, Pseudomonas mendocina IITR46, Microbacterium esteraromaticum IITR47, Pseudomonas aeruginosa IITR48, and Stenotrophomonas maltophilia IITR87. These bacteria showed biosurfactant production using 2% glucose as rich substrate; strain IITR47 yielded the highest with 906 and 534 mg/L biosurfactant in the presence of naphthalene and crude oil as the unique carbon sources. P. aeruginosa IITR48 showed the least surface tension at 29 N/m and the highest emulsification index at 63%. The biosurfactants produced were identified as glycolipid and rhamnolipid based on Fourier transform infrared spectroscopy analysis. In particular, the biosurfactant produced by bacteria S. maltophilia IITR87 efficiently emulsified mustard oil with an E24 value of 56%. It was observed that, all five biosurfactants from these degrader strains removed 2.4-, 1.7-, 0.9-, 3.8-, and 8.3-fold, respectively, crude oil from contaminated cotton cloth. Rhamnolipid derived from IITR87 was most efficient, exhibiting highest desorption of crude oil. These biosurfactants exhibited good stability without significantly losing its emulsification ability under extreme conditions, thus can be employed for bioremediation of PAHs from diverse contaminated ecosystem. Graphical Abstract

The objective of this study was to predict the competitive adsorption of As(III), As(V), and PO₄ by an iron oxide impregnated carbon (L-Act, 9% Fe(III) amorphous iron oxide) over a range of environmental conditions using the surface complexation modeling (SCM) approach. L-Act surface complexation constants determined from a single pH-adsorption edge were used to predict pH-dependent competitive removal in singular, binary, and tertiary adsorbate systems. As(III), As(V), and PO₄ complexes were modeled as bidentate binuclear species at low pH and monodentate species at high pH using the two monoprotic surface site/diffuse electric double layer model (2MDLM). F values determined based on 2MDLM predictions were close to those calculated by FITEQL (a statistical optimization program) demonstrating the effectiveness of the 2MDLM in describing adsorption behavior. F values were generally in the recommended range of 0.1–20 indicating a good fit between the data and the model. The 2MDLM also successfully predicted As(III)/As(V)/PO₄ adsorption data of hydrous ferric oxide and goethite adsorbents from the literature.

The influence of biochar on the soil structure and aggregate stability has been debated in previous studies. To probe the action of biochar on soil aggregates, a 5-year field experiment was implemented in the brown earth soil of northeastern China. We determined the aggregate distribution (> 2000 μm, 250–2000 μm, 53–250 μm, and < 53 μm) and organic carbon (OC) and organo-mineral complex contents both in the topsoil (0–20 cm) and within the soil aggregates. Three treatments were studied as follows: control (basal application of mineral NPK fertilizer), biochar (biochar applied at a rate of 2.625 t ha⁻¹), and stover (maize stover applied at a rate of 7.5 t ha⁻¹), and all treatments received the same fertilization. The biochar and stover applications decreased the soil bulk and particle densities significantly (p < 0.05) and enhanced the soil total porosity. Both amendments significantly (p < 0.05) enhanced the total OC, heavy OC fractions, and organo-mineral complex quantities in the bulk soil as well as in all the studied aggregate fractions. Biochar and stover applications promoted the formation of small macroaggregates. A greater amount of organic matter was contained in the macroaggregates, which led to the formation of more organo-mineral complexes, thereby improving soil aggregate stability. However, the different mechanisms underlying the effect of biochar and stover on organo-mineral complexes need further research. Biochar and stover applications are both effective methods of improving the soil structure in Northeast China.

In the present study, millimeter CS-TPP@MnFe₂O₄ gel beads (particle size 3–4 mm) were prepared by the sol-gel process using the embedding method, and its performance of Cu(II) and influence factors were studied. The effect of various parameters such as the gel bead addition amount, adsorption time, temperature, pH, and competitive substances (anion and cationic) was studied. The surface and properties of gel beads were characterized by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR), and transmission electron microscopy (TEM). The experimental results showed that the optimal pH for adsorption of Cu(II) by CS-TPP@MnFe₂O₄ was 5–7, the adsorption of Cu(II) reached equilibrium at 24 h, and the maximum adsorption capacity could reach 125.70 mg g⁻¹ at 298.15 K by Langmuir isotherm model. K⁺, Na⁺, Cl⁻, NO₃⁻, and SO₄²⁻ had little effect on the adsorption, and Ca²⁺, Mg²⁺, and H₂PO₄⁻ inhibited the adsorption, and SiO₃²⁻ and humic acid (HA) promoted the adsorption of Cu(II) by the adsorbent. After five adsorption-desorption experiments, the desorption rate of gel beads reached 89.3%, and the adsorption capacity of Cu(II) was still high. In conclusion, the CS-TPP@MnFe₂O₄ gel beads are a type of stable and effective materials to remove Cu(II) from water.

Air pollution can significantly accelerate the process of material corrosion, which may cause significant economic losses and serious safety incidents. Atmospheric corrosion maps provide atmospheric corrosivity in a given geographic scope, which can guide the designers to select the most suitable anti-corrosion materials for outdoor projects, also provide useful information for maintenance. This article investigated mapping of atmospheric corrosivity in Shandong Province, China. In order to obtain atmospheric corrosivity data, 100 exposure corrosion test sites were established in Shandong according to International Standard Organization (ISO) 8565. Hot-dip galvanized steel samples were exposed for 1 year in the test sites. Taking the results of exposure corrosion test as the data, inverse distance weighting (IDW) and ordinary kriging (OK) interpolation algorithm were used to estimate the atmospheric corrosivity of Shandong Province according to ISO 9223. The validity of OK and IDW was compared in developing atmospheric corrosion maps of Shandong Province on a 1 × 1 km resolution. The cross-validation results showed that OK interpolation algorithm with Gaussian semivariogram model get the best result in the prediction of corrosion rate. When the corrosion category was used as the criterion, the IDW interpolation algorithm of power 4 performed best, predicted results of 74 sites (n = 100) were consistent with observed. However, high mean relative errors (MRE more than 37%) and relatively low correlation (R² about 24%) indicated that the prediction results of the two interpolation algorithms had a large error, which was caused by the low data density and the complicated corrosive factors of the atmosphere.

Sulfamethoxazole (SMX), a representative sulfonamide antibiotic, has been identified as a new kind of persistent pollutant with property of hard biodegradation and hydrolyzation. Conventional methods cannot remove it well. In this study, the performances and mechanisms for SMX degradation were examined by persulfate (PS) activation with nanoscale zero-valent iron (nZVI) at various conditions including dosages of nZVI and PS, pH value, and initial SMX concentration. Results showed that about 88.4% SMX (10 mg/L) was removed by nZVI/PS system (0.10 g/L nZVI, 1.0 mM PS) within 120 min compared to 63.1% by nZVI alone system under room temperature. Lower initial SMX concentration and higher PS concentration were beneficial to the degradation of SMX, while pH (from 3.11 to 9.33) and nZVI dosage (from 0.05 to 0.30 g/L) had little effect. Radical quenching experiment and electron spin resonance test demonstrated that the degradation of SMX was attributed to sulfate radicals (SO₄·⁻) and hydroxyl radicals (·OH) produced in this system. SMX reduction reaction by nZVI in nZVI/PS process was proved by reductive-oxidative degradation experiment and HPLC test, and the reduction product could be oxidized by SO₄·⁻ and ∙OH to other products even to H₂O and CO₂. Further, probable removal mechanisms have also been proposed. This study manifests that nZVI/PS system is effective for SMX removal and may provide some ideas for understanding the transformation process of antibiotic in iron-based advanced oxidation processes.

Over the past 40 years since China’s reform and opening up, the industrial structure has undergone tremendous changes. The rapid development of the economy has been accompanied by a surge in carbon emissions. How to achieve a win-win situation for economic growth and carbon emissions reduction has aroused widespread concern from all sectors of society. Here, this paper discusses the dynamic relationship of industrial structure upgrading, economic growth, and carbon emission reduction. Results show that there is a long-term equilibrium relationship among industrial structure upgrading, economic growth, and carbon emissions. In the short term, when the three variables deviate from the long-term equilibrium state, the non-equilibrium state will be pulled back to equilibrium with the adjustment strength of − 0.0633, − 0.0097, and 0.0013. Carbon emission reduction promotes industrial structure upgrading. Industrial structure upgrading has a greater positive impact on economic growth. Industrial structure upgrading and economic growth have a negative impact on carbon emissions, thereby promoting emission reduction. And at the 10% significance level, there is a one-way Granger causality from carbon emissions to industrial structure upgrading, economic growth can cause one-way changes in carbon emissions, and industrial structure upgrading is a one-way Granger cause of economic growth. Finally, several carbon emission reduction policies are proposed promote industrial restructuring and sustainable economic development.

In this paper, folic acid–coated graphene oxide nanocomposite (FA-GO) is used as an adsorbent for the treatment of heavy metals including cadmium (Cd²⁺) and copper (Cu²⁺) ions. As such, graphene oxide (GO) is modified by folic acid (FA) to synthesize FA-GO nanocomposite and characterized by the atomic force microscopy (AFM), Fourier transform-infrared (FT-IR) spectrophotometry, scanning electron microscopy (SEM), and C/H/N elemental analyses. Also, computational intelligence tests are used to study the mechanism of the interaction of FA molecules with GO. Based on the results, FA molecules formed a strong π-π stacking, chemical, and hydrogen bond interactions with functional groups of GO. Main parameters including pH of the sample solution, amounts of adsorbent, and contact time are studied and optimized by the Response Surface Methodology Based on Central Composite Design (RSM-CCD). In this study, the equilibrium of adsorption is appraised by two (Langmuir and Freundlich and Temkin and D-R models) and three parameter (Sips, Toth, and Khan models) isotherms. Based on the two parameter evaluations, Langmuir and Freundlich models have high accuracy according to the R² coefficient (more than 0.9) in experimental curve fittings of each pollutant adsorption. But, multilayer adsorption of each contaminant onto the FA-GO adsorbent (Freundlich equation) is demonstrated by three parameter isotherm analysis. Also, isotherm calculations express maximum computational adsorption capacities of 103.1 and 116.3 mg g⁻¹ for Cd²⁺ and Cu²⁺ ions, correspondingly. Kinetic models are scrutinized and the outcomes depict the adsorption of both Cd²⁺ and Cu²⁺ followed by the pseudo-second-order equation. Meanwhile, the results of the geometric model illustrate that the variation of adsorption and desorption rates do not have any interfering during the adsorption process. Finally, thermodynamic studies show that the adsorption of Cu²⁺ and Cd²⁺ onto the FA-GO nanocomposite is an endothermic and spontaneous process.

The green tide in the Yellow Sea is the world’s largest macroalgal bloom. The maximum area affected by green tide can reach tens of thousands of square kilometers. Previous studies have shown that green tide drifts northward during the outbreak, yet the location of its northernmost drift and the characteristics of interannual variations have not been explored in detail. In this paper, we use the Moderate Resolution Imaging Spectrometer (MODIS) data, GaoFen-1 (GF-1) satellite data, unmanned aerial vehicle (UAV) aerial data, and field trips for extraction and monitoring of green tide and then analyze the emergence, development, and dissipation of the green tide in Rongcheng coastal waters and the change of the northernmost drift position and its related factors from the year of 2013 to 2018. The results show that green tide have drifted to the Rongcheng coastal area over the years and the northernmost drift position can reach 37.662° N in 2014. Interannual difference of the northernmost position of the drift of the green tide is obvious, it is mainly affected by the wind, and there is no certain connection with the maximum coverage area, the coverage area when reaching the northernmost position, and the existence days of the green tide. These results can help to understand the drift range and dissipation process of green tide in the Yellow Sea.

Foreign direct investment (FDI) and the consumption of non-renewable energy have been on the increase in the coastal Mediterranean countries (CMCs) over the last few decades. Both trigger growth, but the environmental impact could be far-reaching as environmental distortions are mainly human-induced. This study examines the environmental issues facing CMCs. Specifically, we investigate whether the pollution haven hypothesis holds for CMCs. We employ a quantile panel data analysis for CMCs to account for heterogeneity and distributional effects of socioeconomic factors. The result reveals that the influence of FDI on environmental degradation is a function of the indicators utilized and also depends on the initial levels of environmental degradation. The results suggest that the pollution haven hypothesis does not hold for CMCs. However, we also find that energy consumption significantly increases environmental degradation for all indicators and across the observed quantiles. The effects of economic growth and urbanization on the environment were mixed for the different indicators and across quantiles. We recommend that it is pertinent for CMCs to limit their “dirty” energy sources and substitute them with renewables to promote environmental sustainability.