The antibiotic distributions, partitioning, and migration pathways in river basins have withdrawn great attention in the past decades. This study investigates 26 antibiotics of five classifications in surface water and sediment samples at 23 sites in Fenhe River, a typical tributary of Yellow River. There are 21 antibiotics found in the water samples at the concentration from 113.8 to 1106.0 ng/L, in the decreasing order of SAs > QNs > MLs > TCs > CAs. Fifteen antibiotics were detected in the sediment at the concentrations from 25.11 to 73.22 μg/kg following the decreasing order of SAs > MLs > TCs > QNs > CAs. The antibiotic concentrations vary greatly in surface water, generally lower in upstream and in reservoirs, and reaching highest in the midstream of the Fenhe River after passing Taiyuan and Jinzhong, and then lower again in the downstream. The antibiotic concentrations in sediment have a less variation in the entire river basin, but become high in the downstream. The results show the water-sediment partitioning coefficients of antibiotics generally were lower than those in other areas, having a migration path from the water to suspended solids, and then accumulated in sediment. The water-sediment partitioning coefficients also vary across the basin. The water-sediment partitioning coefficients of sulfacetamide and tetracycline are higher than the water-sediment partitioning coefficients of other antibiotics, with less variation across the basin, the water-sediment partitioning coefficients of azithromycin, enrofloxacin, and roxithromycin are low in the midstream of the river, and high at the river source and downstream. The water-sediment partitioning coefficients are significantly affected by the pH of sediment and the particle size of sediment. The prediction models of water-sediment partitioning coefficients for antibiotics are constructed with the selected effecting factors. The simulation values of antibiotics except chlortetracycline and erythromycin are highly consistent with the observed values, indicating that the prediction model is reliable.

With per capita water resources at only around a quarter of the world average, China’s water resources are limited and unevenly distributed. Past research on water resource utilization has mainly focused on industrial water use (agriculture and industry), water plant ownership efficiencies (private or public operation), or water resources and economic production; however, there have been few studies focused on water supply livelihood. Therefore, this paper considered both industrial production water services, non-production water services (public sector and residential water use), and water leakage losses, which is a water supply problem seldom mentioned in other studies. An undesirable directional distance function (DDF) dynamic data envelopment analysis (DEA) model was employed for the dynamic analysis as it was able to deal with both desirable and undesirable outputs at the same time. The model examined collected water supply and water leak efficiency data from 30 Chinese provinces/municipalities from 2007 to 2018, from which it was found that (1) Beijing, Gansu, Guangdong, and Ningxia had efficient water supply and water leak losses from 2007 to 2018 and the most improved province was Jiangxi; (2) the eastern provinces, in general, had better water efficiencies and the central and western provinces needed greater improvements; and (3) the lowest water leakage loss efficiencies were in Inner Mongolia, Jiangxi, and Heilongjiang, all of which required significant improvements.

This research aims to reveal the premature deaths caused by long-term exposure to PM₂.₅ in 2018 in Turkey utilizing the AirQ+ program developed by the World Health Organization. Calculation of yearly average PM₂.₅ concentration in provinces, acreage of provinces, and the mortality rate of the at-risk population was the data required for the operation of the AirQ+ program. With the help of the AirQ+ program, the results revealed that a total of 44,617 people (95% CI 29.882–57.709) died prematurely due to sustained exposure to PM₂.₅ in Turkey in 2018. The highest estimated mortality proportion attributable to PM₂.₅ pollution was in the provinces of Igdir and Kahramanmaras. The highest estimated number of mortality cases per 100,000 population attributable to PM₂.₅ pollution was in the provinces of Manisa and Afyonkarahisar. This research points out that reaching the PM₂.₅ limits specified by the WHO could have prevented 44,617 premature deaths in the year 2018 in Turkey.

Sustainable management of groundwater resources requires detailed basin-wide water assessments. Semi-urbanized areas surrounding metropolitan cities in the western part of India were assessed for their suitability for domestic, irrigation, and industrial purposes. These study areas reflect rapid urban growth with residential complexes, combined with agricultural, horticultural, and industrial uses. Therefore, 68 representative groundwater samples were collected during the pre-monsoon (PRM) and post-monsoon (POM) seasons of 2015 and analyzed for major ions. According to the World Health Organization (WHO) drinking standards, parameters like EC, TDS, TH, HCO₃, Ca, and Mg were found to exceed the desirable maximum limits, and the B and F content exceeded the permissible limits. The drinking suitability was studied using the modified water quality index (MWQI). The irrigation suitability was assessed using indices such as sodium adsorption ratio (SAR), percent sodium (%Na), and permeability index (PI). The industrial suitability was evaluated based on Langelier saturation index (LSI), saturation index (SI), Ryznar stability index (RSI), etc. MWQI results corroborate that 52.94 and 70% samples fall in no pollution category, and 47% and 30% samples were identified to be in the moderate category of pollution in the PRM season and POM season, respectively. The spatial variation maps of LSI, SI, RSI, Puckorius scaling index (PSI) and Larson–Skold index (LaI) show that the majority of the samples in the PRM season have low to insignificant scaling and corrosive potentials as compared to POM samples. The study results provide reliable information for water reserve managers to prepare the sustainable and more accurate basin management plans.

Toxic effects of industrial emissions on vegetation have been extensively studied, and at the same time indirect effects of pollution are less known. In 2011 and 2015, we studied temperature regime and leaf growth for Betula pubescens and B. pendula in deciduous forests near the Middle Ural copper smelter (MUCS). At two polluted sites (1 and 2 km from the smelter) and two unpolluted sites (16 and 27 km), we logged continuously air temperatures during the growing season (May–August) and measured leaves until completion of growth (May–June). Near MUCS, daily mean air temperatures were 0.7–1.0 °C higher with daily temperature range 2.2–2.7 °C greater than at distant sites. Daily air temperature range decreased from spring to midsummer, suggesting that the ability of vegetation to mitigate temperature variations increases with plant biomass, which peaks in midsummer. Growth of birch leaves near MUCS began 4–10 days earlier and completed 3–7 days earlier than far away. Thermal sum over the leaf growth period did not differ between areas in 2011, and in 2015 was lower in the polluted than in the unpolluted area. The earlier leaf growth completion near MUCS can be attributed to higher air temperatures and more rapid accumulation of required thermal sums.

The paper aims to investigate the influencing factors that drive the temporal and spatial differences of CO₂ emissions for the transportation sector in China. For this purpose, this study adopts a Logistic Mean Division Index (LMDI) model to explore the driving forces of the changes for the transport sector’s CO₂ emissions from a temporal perspective during 2000–2017 and identifies the key factors of differences in the transport sector’s CO₂ emissions of China’s 15 cities in four key years (i.e., 2000, 2005, 2010, and 2017) using a multi-regional spatial decomposition model (M-R). Based on the empirical results, it was found that the main forces for affecting CO₂ emissions of the transport sector are not the same as those from temporal and spatial perspectives. Temporal decomposition results show that the income effect is the dominant factor inducing the increase of CO₂ emissions in the transport sector, while the transportation intensity effect is the main factor for curbing the CO₂ emissions. Spatial decomposition results demonstrate that income effect, energy intensity effect, transportation intensity effect, and transportation structure effect are important factors which result in enlarging the differences in city-level CO₂ emissions. In addition, the less-developed cities and lower energy efficiency cities have greater potential to reduce CO₂ emissions of the transport sector. Understanding the feature of CO₂ emissions and the influencing factors of cities is critical for formulating city-level mitigation strategies of the transport sector in China. Overall, it is expected that the level of economic development is the main factor leading to the differences in CO₂ emissions from a spatial-temporal perspective.

The wasted sludge from ferrous ion-dependent nitrate removal (FeNiR) process is potential to be re-used as adsorbent to remove industrial pollutants. After pretreatment, the adsorption efficiency of FeNiR wasted sludge to reactive red X-3B, minocycline hydrochloride and Cr⁶⁺ was 88.95%, 90.08%, and 95.97%. The optimal initial pH to adsorb reactive red X-3B, minocycline hydrochloride, and Cr⁶⁺ was 2, 4, 2, while the optimal adsorbent dosage was 0.3 g, 0.8 g, and 1.0 g, and the optimal temperature was 50 °C, 30 °C, and 50 °C. The adsorption process follows the pseudo-secondary adsorption kinetics model, indicating the chemical adsorption dominates the adsorption process. The analysis of adsorption thermodynamic shows that all three adsorption reactions proceed spontaneously. From the results of the scanning electron microscope (SEM) and Brunner-Emmett-Teller (BET) analysis, the FeNiR wasted sludge after pretreatment is porous that endows the wasted sludge physical adsorption ability. The Fourier transform infrared (FTIR) analysis shows that the chemical bonds, including the hydroxyl group of Fe₃O₄, the Fe-O, and the α-FeOOH in the iron encrustation play more important roles in the adsorption process. Being used as adsorbent to treat industrial wastewater is a promising way to re-use the wasted sludge and decreases the cost of FeNiR process.

Microcosms are used experimentally to simulate ecosystems. This technology has received increasing attention and is widely used for environmental research. This review briefly introduces the origin and development of microcosm theory, summarizes classification and applications of microcosms across decades, and describes the advantages and limitations of microcosm technology in comparison with other methods. Finally, trends in the development of microcosm models are discussed.

Metal contamination is a threat to estuarine environments. They can accumulate in the food chain and cause toxic effects on aquatic organisms and human health. This study evaluated the concentrations of metals (Cd, Cr, Cu, Fe, Ni, Pb, and Zn) in aquatic organisms of Antonina Bay (southern Brazil) to analyze whether the metal concentrations were in accordance with Brazilian food legislation and estimate the human risk of local seafood consumption. All analyzed organisms (Centropomus parallelus, Mugil curema, Genidens genidens, Crassostrea brasiliana, and Xiphopenaeus kroyeri) showed traces of metals in their tissues with different metal concentrations among species. Metal concentrations were generally higher in oyster C. brasiliana, and biomagnification was not observed. Cr and Zn concentrations were above the limits established by legislation for all species in at least one sample. The concentrations of the other metals were within permitted levels. However, concentrations of Cd, Cr, Fe, and Zn posed a human consumption risk. In general, the C. brasiliana oyster presented the highest risk for human consumption, probably due to its filtering habit. Thus, the results indicated that metal concentrations in the tissues of the Antonina Bay seafood can pose a risk to human health, and this chronic exposure to metals also can cause toxic effects on local aquatic biota.

This research was designed to experimentally study the influence of using three metal oxide nanofluids at different high flow rates with various mass concentration of nanoparticles as the working fluid, on the thermal efficiency and pumping power of heat pipe solar collector (HPSC). The volume flow rate of the working fluid was 5, 8, 11, and 14 L/min. Also, mass concentration of nanoparticles was 0.5 and 1.167 g/L. Co-precipitation technique was employed to prepare CuO, Al₂O₃, and MgO nanoparticles. The optical and structural characterization of the nanostructure were considered by using X-ray diffraction (XRD), Fourier transform infrared (FT-IR), scanning electron microscopy (SEM), and UV-visible analysis. The thermal performance of the HPSC using metal oxide nanofluids and water was compared with the volume flow rate that varied from 5 to 14 L/min. It was observed that nanofluids improved the collector efficiency between 9 and 20% compared with deionized water. The present results revealed that the maximum efficiency was found to be 83% for a mass concentration of 1.167 g/L of CuO nanofluids and volume flow rate of 14 L/min. The HPSC efficiency shows better improvement with the increasing mass concentration of metal oxide nanoparticles and volume flow rate. Also, the increase rate of the pumping power and pressure drop is less than 0.9% for all of the nanofluids that were used as the working fluids. Results showed that the metal oxide nanofluids are appropriate for increasing the efficiency of HPSC.