Radionuclides ¹³⁷Cs and ⁹⁰Sr and total beta activity were determined from air filters collected in Rovaniemi (Finnish Lapland) in 1965–2011. Nuclear contamination sources present in the air filter samples as well as temporal changes in radionuclide concentrations were examined. Ozone observations and meteorological modeling were used in combination with radionuclide analyses to study the reasons behind the observed seasonal concentration variation. In general, the magnitude and variation in activity concentrations of ¹³⁷Cs and ⁹⁰Sr and total beta activity in the surface air of Rovaniemi in 1965–2011 corresponded well with values from other countries. However, the obtained results prove in practice that hardly any refractory or intermediate radionuclides from the destroyed Chernobyl reactor fuel were introduced to Finnish Lapland. The main source of ¹³⁷Cs and ⁹⁰Sr and total beta activity in the surface air of Rovaniemi in 1965–2011 has been intense atmospheric nuclear weapon testing in 1950s–1960s and later tests performed in 1965–1980, as well as leakages from underground nuclear tests in Semipalatinsk, 1966, and Novaya Zemlya, 1987. For ¹³⁷Cs and total beta activity, the influence of Chernobyl and Fukushima accidents was detected.

The removal of 17β-estradiol (E2) from contaminated water on nanoscale Fe–Mn binary oxide-loaded multiwalled carbon nanotubes (MWCNTs/FMBO) was evaluated in this work. The characterizations of the mesoporous adsorbent were analyzed by using SEM, TEM, VSM, XRD, XPS, and FTIR measurements. The effects of experimental conditions in E2 removal, including stabilizer additional level, adsorption time, initial E2 concentration, solution pH, reaction temperature, and foreign ions, were examined. The maximum monolayer adsorption capacity (qₘ) of MWCNTs/FMBO for E2 in the experiment was 47.25 mg/g as verified by the Langmuir sorption isotherm study. The adsorption process was pH-sensitive with an optimum pH of 7.0. On the kinetics study, the adsorption data could be satisfactorily fitted by the pseudo-second-order kinetics. Thermodynamic parameters indicated that the adsorption process was spontaneous and exothermal. In addition, the foreign ions did not show any noticeable inhibition for E2 removal from the water solution except for PO₄³⁻ that was adversely affected for E2 uptake than other anions in a certain concentration. The adsorption capacities of the mesoporous adsorbent remained at 86.16% even after five adsorption–desorption cycles without significant loss of capacity, which demonstrated the stability and reusability for further removal of E2. Moreover, both hydrogen bond and π–π interaction might be the dominating adsorption mechanisms for E2 adsorption onto MWCNTs/FMBO.

Exposure to environmental endocrine disruptors (EEDs) has been linked to adverse health outcomes. The vast majority of studies examined one class of EEDs at a time but humans often are exposed to multiple EEDs at the same time. It is, therefore, important to know the co-exposure status of multiple EEDs in an individual, to preclude and control for potential confounding effects posed by co-exposed EEDs. This study examined the concentrations of seven classes of EEDs in the US population utilizing the data from the National Health and Nutrition Examination Survey (NHANES), 2009–2014 survey cycles. We applied linear correlation and cluster analysis to characterize the correlation profile and cluster patterns of these EEDs. We found that EEDs with a similar structure are often highly correlated. Among between-class correlations, mercury and perfluoroalkyl substances (PFAS) and cadmium and polycyclic aromatic hydrocarbons (PAHs) were two significantly correlated EEDs. In epidemiologic studies, measurement and control for co-exposure to pollutants, especially those with similar biological effects, are critical when attempting to make causal inferences. Appropriate statistical methods to handle within- and between-class correlations are needed.

Acid mine discharge (AMD) has been demonstrated to have significant impacts on microbial community composition in the surrounding soil environment. However, their effect on adjacent soil has not been extensively studied. In this study, microbial community composition of 20 AMD-contaminated soil samples collected from an abandoned coal mine along an AMD creek was characterized using high-throughput sequencing. All samples were characterized as extremely low in pH (< 3) and relatively enriched in HCl-extractable Fe species. The dominant phylotypes were belonging to genera Ochrobactrum, Acidiphilium, Staphylococcus, Brevibacterium, and Corynebacterium. Canonical correspondence analysis results revealed that the HCl-extractable Fe(III) had a strong impact on the soil microbial assemblage. Co-occurrence network analysis revealed that Aquicella, Acidobacteriaceae, Ochrobactrum, Enhydrobacter, Sphingomonas, and Legionellales were actively correlated with other taxa. As expected, most of the abundant taxa have been reported as acidophilic Fe-metabolizing bacteria. Hence, a co-occurring sub-network and a phylogenetic tree related to microbial taxa responsible for Fe metabolism were constructed and described. The biotic interaction showed that Dechloromonas exhibited densely connections with Fe(III)-reducing bacteria of Comamonas, Burkholderia, Shewanella, Stenotrophomonas, Acidithiobacillus, and Pseudomonas. These results demonstrated that Fe-metabolizing bacteria could have an important role in the Fe biogeochemical cycling.

In order to explore the research trends and hotspots related to the treatment of heavy metals in wastewater by graphene and its composites, this study collected information on 511 publications from the Science Citation Index-Expanded (SCIE) and conducted a quantitative and visual analysis. The article on the adsorption of heavy metals in wastewater by graphene and its composites first appeared in 2006 and continued to grow since 2011. It broke through 100 articles for the first time in 2016 and the overall trend is on the rise. The 511 articles were published in 185 journals, of which RSC Advances is the most dynamic journal, and Journal of Materials Chemistry A is the most authoritative journal. Asian authors published about 87.14% of papers, and China, Iran, and India played a leading role compared with other countries. The University of Chinese Academy of Sciences is the largest research institution for the adsorption of heavy metals in wastewater by graphene and its composites. Hot keywords are “heavy metal removal,” “water sample,” “recent advance,” “reusable adsorbent,” “graphene-based material,” and “composite nanosheet.” Combined with keywords and cluster analysis, the chemical modification of graphene oxide has become a hot research direction for graphene materials to remove heavy metals from wastewater. Among them, MnFe₂O₄-graphene composite is a hot spot for graphene modification. In general, HNO₃, HCl, and EDTA are desorption reagents for graphene and its composites.

Copper (Cu) and norfloxacin (Nor) are frequently used as feed additives for animal growth promotion, which results in a great probability of Cu²⁺ and Nor coexisting in animal excretion and in soils. Sorption of Cu²⁺ and Nor on soil organic matter (SOM) can markedly affect their environmental fate. Thus, humic acid (HA), a major fraction of SOM, was chosen to investigate the cosorption behaviors of Cu²⁺ and Nor on HA under different solution chemistry conditions (pHs, ionic strengths, and foreign ions). The addition of Nor decreased the maximum adsorption capacity (Qₘ) of Cu²⁺ and an increasing effect was observed with increasing Nor concentration. Meanwhile, the addition of Cu²⁺ also markedly inhibited the sorption of Nor on HA. The Qₘ of Cu²⁺ increased with increasing pH from 3.0 to 5.0 whether Nor was present or not, but more addition of Nor led to less increment in Qₘ of Cu²⁺ at the same pH. The Qₘ of Nor was observed at pH 4.0 without Cu²⁺, but that was found at pH 5.0 and 3.0 with the addition of 20 and 100 mg L⁻¹ Cu²⁺, respectively. The sorption of Cu²⁺ on HA decreased with increasing ionic strength and followed an order of NaH₂PO₄ > Na₂SO₄ ≈ NaNO₃ at pH 5.0 whether Nor was present or not. Additionally, the higher valence cation had a stronger inhibition effect on Cu²⁺ sorption. The competition between Cu²⁺ and Nor for sorption on HA under the same conditions indicated that the coexistence of Cu²⁺ and Nor may enhance the feasibility of their mobility and environmental risk.

A novel magnetic ion-imprinted polymer with high accessibility to palladium ions was synthesized via co-precipitation polymerization. Accordingly, a ternary complex composed of PdCl₂ as an imprinting ion, 8-aminoquinoline (AQ) as a ligand, and 4-vinyl pyridine (4-VP) as a complexing monomer was applied to Fe₃O₄@SiO₂ as magnetic core, followed by precipitation polymerization using 2-hydroxyethyl methacrylate (2-HEMA) as a co-monomer, ethylene glycol dimethacrylate (EGDMA) as the crosslinker, and 2,2-azobisisobutyronitrile (AIBN) as an initiator in the presence of 2-methoxyethanol as a solvent. The palladium ions were leached out by a solution containing 50% (v/v) HCl. The synthesized polymer was characterized physically and morphologically using different techniques. In order to assess the conditions required for adsorption, as well as the selectivity and reusability, batch adsorption experiments were carried out. The experiments exhibited that the maximum adsorption capacity was about 65.75 mg g⁻¹ at 25 °C, while the pH solution and the adsorbent dose were 4 and 1 g L⁻¹, respectively. Kinetic studies of experimental data demonstrated that they correspond very much to the pseudo-second-order kinetic model. The development of the Langmuir and Freundlich isothermal models on the equilibrium data proved to correspond well to the Langmuir isotherm model. Interferences studies of the magnetic polymer demonstrated higher affinity and discernment for palladium ions than other co-existing ions in the solutions. Spontaneous (ΔG < 0) and exothermic (ΔH < 0) behavior of the adsorption process is confirmed by thermodynamic studies. In addition, the affinity of the spent polymer has not been dramatically reduced over at least five regeneration cycles.

This paper considers a problem of how to allocate resource effectively and equitably among provinces. To address the problem, a total factor resource input-oriented data envelopment analysis (DEA) model is used to evaluate the energy and environmental efficiency for 30 provinces in China during 2009–2013 in this paper. Based on the evaluation results, from efficient and fair perspective, a revised DEA-based resource allocation model is established. It is worth pointing out that the model takes the input orientation and output orientation into account at the same time and can be used to allocate coal consumption and carbon emission by 2020 for 30 provinces in China. Results indicate that if the Chinese government wants to fulfill the CO₂ emission reduction targets of 40–45% by 2020, and coal consumption intensity reduction target during 13th Five-Year Plan, inefficient provinces will undertake more coal consumption and carbon emission intensity reduction obligation share. And provinces with historical high coal consumption and high CO₂ emission intensity will have greater potential of coal consumption and carbon emission intensity reduction. In addition, this paper set several scenarios of gross domestic product (GDP) growth rate, under the scenarios analysis, finds the growth rate of GDP has negative effect on reduction of coal consumption and carbon dioxide emissions intensity. This research provides more realistic practical significance for achieving sustainable economic development.

In the present study, a detailed investigation was carried out on MoO₃ alumina-supported catalysts behavior in selective catalytic reduction of SO₂ to sulfur with CH₄. At first, four different molybdenum catalysts with weight rates of 0, 5, 10, and 15 were impregnated on γ-alumina to be characterized using XRD, SEM, BET, BJH, and N₂ adsorption. Then, to find the most active catalyst, temperature dependency test was performed on all of the prepared catalysts and the result representing Al2O3-Mo10 as the best catalyst. In next step, the effects of feed gas composition, space velocity, and long-term activity, as an important industrial factor, were tested on Al₂O₃-Mo10. It was revealed instantaneously from the beginning, MoO₃ specie started to convert mainly into MoS₂ and MoO₂, and a minor part into Mo₂C, which is terminated after 750 min achieving a stable condition. Thereafter, SO₂ conversion and sulfur selectivity increased from 85.8 to 89.4% and 99.4 to 99.7%, respectively. XRD graph of the used catalyst and TPO thermogravimetric/mass-spectra proved possible happening of the proposed mechanism in long-term activity. At the end, mean activation energy was determined based on Arrhenius model in temperature range of 550 to 800 °C, with a value of 0.33 eV for Al₂O₃-Mo10.

This study aims to provide an overview of human studies on the association of exposure to phthalates and insulin resistance. We systematically searched human studies available until 15 January 2018.We conducted a literature search in Scopus, ISI Web of Science, PubMed, Google Scholar, and Cochrane Collaboration. We used the following keywords to identify relevant articles: “phthalate”, “phthalate ester”, “metabolic syndrome”, “insulin resistance”, “glucose intolerance”, and “diabetes”. For analyzing data, we conducted meta-analysis using the Stata software. We appraised each study to examine the sources of heterogeneity, including difference in clinical outcomes and exposure measurements. To determine the robustness and whether some of the factors have the highest impact on the results of the present meta-analysis, several sensitivity analyses were conducted. Sensitivity analysis showed that by removing studies with the highest weight and age groups, no change was observed in heterogeneity. Moreover, with excluding the study conducted in Europe, the results remained unchanged and constant. In addition, the funnel plot and Egger’s tests were executed to access publication bias. Both the funnel plots and Egger’s test did not show any evidence of publication bias (P = 0.31). In the random effects meta-analysis of all studies (n = 8), the pooled correlation coefficient between phthalate exposure and HOMA-IR was 0.10 (95% CI; 0.07–0.12, P < 0.001), with significant heterogeneity (P < 0.001, I² = 85.5%). Our findings revealed positive association between exposure to phthalate metabolites and increased HOMA-IR; this association remained significant even after adjusting the analysis for multiple confounding variables.