Previous studies have primarily targeted at positive causal linkages between the logistics industry and economic benefits, resulting in biased findings without the consideration of undesirable social and environmental problems. Therefore, this paper aims to develop a holistic approach to the assessment of logistics efficiency, through considering comprehensive inputs and desirable and undesirable outputs. In specific, contextualized in China, this paper comprehensively examined the spatiotemporal variations of China logistics efficiency and further investigated the impact of some exogenous factors. Results indicate that the overall logistics efficiency of China was low, but temporally showed a trend of increase. Spatially, the logistics efficiency followed the pattern of Eastern > Central > Western > Northeastern. Moreover, for the spatial interaction among adjacent provinces, there occurred high–high patterns in the Eastern, and low–low aggregation in the Western and Northeastern regions. However, along with time, the spatial interaction among adjacent provinces was weakening. For exogenous factors, level of economic development, urbanization level, utilization rate of logistics resources, and location advantage had a significant positive impact on SLE, while the effect of labor quality was not significant. Overall, this paper enriches the theoretical understandings of sustainable logistics efficiency evaluation and unbiasedly inform central and local governments with approaches to optimizing logistics efficiency.

This study analysed the scale of bisphenol S (BPS) toxicity to the soil biochemical activity and is part of a wider effort to find solutions to restore the global soil environment balance, including elimination of the effects of ecosystem pollution with BPA, of which BPS is a significant analogue. However, since there has been no research on the effect of BPS on soil health, the objective of the study was pursued based on increasing the levels of soil contamination with the bisphenol 0, 5, 50 and 500 mg BPS kg⁻¹ DM of soil and by observing the response of seven soil enzymes: dehydrogenases, catalase, urease, acid phosphatase, alkaline phosphatase, arylsulphatase and β-glucosidase to the growing BPS pressure. The potential negative effect of bisphenol S was offset by bioaugmentation with a bacteria consortium—Pseudomonas umsongensis, Bacillus mycoides, Bacillus weihenstephanensis and Bacillus subtilis—and a fungi consortium Mucor circinelloides, Penicillium daleae, Penicillium chrysogenum and Aspergillus niger. BPS was found to be a significant inhibitor of the soil enzymatic activity and, in consequence, its fertility. Dehydrogenases and acid phosphatase proved to be the most susceptible to BPS pressure. Bioaugmentation with a bacteria consortium offset the negative effect of 500 mg BPS kg⁻¹ DM of soil by inducing an increase in the activity of acid phosphatase and alkaline phosphatase, whereas the fungi consortium stimulated the activity of β-glucosidase and acid phosphatase. A spectacular dimension of bisphenol S inhibition corresponded with both the spring rape above-ground parts and root development disorders and the content of Ca and K in them. The BPS level in soil on day 5 of the experiment decreased by 61% and by another 19% on day 60.

This study critically evaluates two COP proposals on Malaysia that have been under consideration to reduce climate damage. A top-down disaggregation framework deploying an “Empirical Regional Downscaling Dynamic Integrated Model of Climate and the Economy” is used to evaluate the local government climate roadmap and Malaysia’s emissions reduction agendas under COP21 and subsequently COP22 proposals. The findings show that the costs from climate damage over the period 2010–2110 under the Malaysian Optimal Climate Action scenario will amount to MYR5,483 (US$1589) billion. The commensurate climate damage costs under the COP21 and COP22 scenario would be MYR5, 264 (US$1526) billion. Thus, the effective proposal for reducing climate damage in Malaysia over the period 2010–2110 is the COP22 time-adjusted COP21 proposal but there are a number of macroeconomic cost implications for savings and consumption that policy makers must address before acting.

This study empirically investigates the role of eco-innovation on the reduction of carbon dioxide emissions (CO₂) in an extended version of the environmental Kuznets curve (EKC). Under dynamic framework, second-generation panel econometric techniques such as the CADF and the CIPS unit root tests, DSUR cointegrating test, and DH panel causality test are employed over the period 2007–2016 for the case of top 20 refined oil exporting countries. Results reveal that eco-innovation (i.e. research and development) exerts a negative and significant long-term effect on carbon emissions (CO₂). This result indicates that the extended version of EKC and the Porter hypotheses are validated for the selected countries. The findings, which show heterogeneity and cross-sectionally dependence in the panel time-series framework, suggest that rising levels of carbon emissions and real income may encourage more research and development (i.e. eco innovation) and lower energy consumption.

The simulation of snowmelt runoff in alpine mountainous areas is of great significance not only for the risk assessment of snowmelt flood in spring and summer, but also for the development and management of water resources in the basin. An improved snowmelt runoff model (SRM) is constructed based on the analysis of change characteristics of climate, runoff, and snow and ice cover in the middle and upper reaches of the Taxkorgan River in Xinjiang Province, China. Because of the large evaporation in the study basin, the evaporation loss is added to the model. The SRM and the improved SRM are calibrated and verified by using data such as temperature, precipitation, water vapor pressure, and snow-covered area (SCA) ratio in the study basin from 2002 to 2012. The results show that, compared with the SRM, the average Nash–Sutcliffe coefficient (NSE) of annual runoff simulation increases from 0.80 to 0.86 in the calibration and increases from 0.74 to 0.83 in the validation through the improved model, and the average runoff error reduces from − 12.8 to 1.32% in the calibration and reduces from − 20.0 to − 11.51% in the validation. After adding the measured flow rate for real-time correction, the average NSE of annual runoff simulation increases from 0.91 to 0.93 and the average annual runoff error reduces from − 7.76 to − 3.91% in the calibration. The average NSE increases from 0.85 to 0.89 and the average runoff error reduces from − 12.35 to − 2.76% in the validation. It indicates that the SRM structure with increased evaporation loss is more in line with the actual situation. The short-term simulation effect of the model is greatly improved by adding the measured flow rate for real-time correction. At the same time, the improved SRM and the hypothetical climate change scenario are used to analyze the impact analysis of the snowmelt runoff simulation in the partial wet year. The results show that in the case of rising temperature, the ice and snow ablation period is prolonged, and the annual runoff also changes significantly in time distribution. It is of guiding significance for the influence of climate change on the runoff of recharged rivers with ice–snow meltwater in the other alpine regions.

Agriculture P management practices elevate the level of inorganic phosphates in soil that results in phosphorous (P) seepage into water-bodies. This is one of the key factors that have accelerated the menace of eutrophication. Phytic acid (phytate)-P-rich plant metabolite is infamous for its anti-nutrient activity and regularly oozing in to environment though discharge of mono-gastric animals. That has amplified the magnitudes of eutrophication. In this work, for catalysis of phytate-P, the metal-organic framework fabricated towards metal oxides (Fe₃O₄) and phytase in highly ordered microcosms of silica was employed. The synthesized framework was characterized through transmission electron microscopy (TEM) and nitrogen isotherm analysis. Average pore diameter of synthesized bisect oval shaped structures was measured around ≈200 nm. Herein, phytase and Fe₃O₄ nanoparticles were loaded to the cavities of microcosms through glutaraldehyde-mediated crosslinking. Whereas Fe₃O₄ nanoparticles act as nano-absorbents that adsorb P liberated from phytase-mediated catalysis of phytate. Kinetic analysis of free and loaded phytase has shown relatively small reduction in catalytic efficiency. These loaded microcosms have removed 60–80% of phytate-phosphate. The optimized process has reduced the growth of photoautotrophs by 50%. Additionally the magnet-assisted separation of loaded microcosms eased the reapplication of loaded microcosms tested for six independent instances. The primary studies conducted to evaluate the geno-toxicity of loaded microcosms have not shown any harmful effect on the process like cell division and seed germination. The efficacy of this method has evaluated towards on-field testing in Changa (Gujarat, India) lake.

To efficiently separate photoexcited electron/hole pairs is one of the key points for achieving excellent photocatalysts with high photocatalytic performances. To achieve this aim, here we have assembled CaTiO₃ (CTO) nanoparticles onto BiOBr microplates, thus constructing novel Z-scheme CTO@BiOBr heterojunction composite photocatalysts. Observation by scanning/transmission electron microscopy confirms the good decoration of CTO nanoparticles (15–50 nm) on the surface of BiOBr microplates (diameter 0.7–2.2 μm, thickness 70–110 nm). Simulated sunlight was used as the light source, and rhodamine B (RhB) in aqueous solution was used as the model pollutant to assess the photodegradation activity of the samples. It is demonstrated that the CTO@BiOBr composites with an appropriate CTO content exhibit much enhanced photodegradation performances. In particular, the 10%CTO@BiOBr composite with a CTO mass fraction of 10%, which photocatalyzes 99.9% degradation of RhB at 30 min of photocatalysis, has a photocatalytic activity which is about 1.8 and 23.6 times larger than that of bare BiOBr microplates and CTO nanoparticles, respectively. This can be explained as the result of the Z-scheme electron transfer and efficient separation of photoexcited electron/hole pairs, as evidenced by photoluminescence, photocurrent response, and electrochemical impedance spectroscopy investigations.

In this work, three polymer suspensions were used for coating glass beads (GB), porcelain beads (PB), and polyethylene pellets (PP) in spouted bed. Subsequently, the continuous adsorption assays of the food dye Brilliant Blue FCF in a fixed bed column were performed, which was packed with the covered particles. Also, the static adsorption assays were carried out. The adsorption equilibrium isotherms were fitted by Freundlich, Langmuir, and Temkin models, being that the Temkin model was the most suitable to represent the equilibrium data. The particle coating in the spouted bed showed promising results due to the high efficiency of the process. The PB, GB, and PP obtained coating efficiency values in the range to 92–96% when using the suspension of chitosan and hydroxyethyl cellulose. However, only the polyethylene particles coated with the chitosan suspension maintained its coating efficiency (95%). The maximum adsorption capacities at equilibrium of the coated particles of PP and GB were achieved with the chitosan suspension, being the values of around 800 mg g⁻¹. Thus, the chitosan-coated polyethylene particles showed to be a promising adsorbent for fixed bed column. Graphical abstract

River water temperature (RWT) forecasting is important for the management of stream ecology. In this paper, a new method based on coupling of wavelet transformation (WT) and artificial intelligence (AI) techniques, including multilayer perceptron neural network (MLPNN) and adaptive neural-fuzzy inference system (ANFIS) for RWT prediction is proposed. The performances of the hybrid models are compared with regular MLPNN and ANFIS models and multiple linear regression (MLR) models for RWT forecasting in two river stations in the Drava River, Croatia. Model performance was evaluated using the coefficient of correlation (R), the Willmott index of agreement (d), the root mean squared error (RMSE), and the mean absolute error (MAE). Results indicate that the combination of WT and AI models (WTMLPNN and WTANFIS) yield better models than the conventional forecasting models for RWT simulation for both regular periods and heatwave events. The MLPNN and ANFIS models outperform the MLR models for RWT simulation for the studied river stations. RMSE values of WTMLPNN2 and WTANFIS2 models range from 1.127 to 1.286 °C, and 1.216 to 1.491 °C for the Botovo and Donji Miholjac stations respectively. Additionally, modeling results further confirm the importance of the day of year (DOY) on the thermal dynamics of the river. The results of this study indicate the potential of coupling of WT and MLPNN, ANFIS models in forecasting RWT.

In this study, health risk of human exposure to organohalogenated pollutants (OHPs) through milk consumption was determined. Conventionally produced, unprocessed cow’s milk samples taken from Konya District, in Turkey, and 15 different brand ultra-high-temperature (UHT) processed cow’s milk samples taken from supermarkets of Turkey were analyzed for organochlorine pesticides (OCPs, α-, β-, γ-, and δ-HCHs, p,p’-DDE, p,p’-DDD, and p,p’-DDT, heptachlor, heptachlor epoxide, endosulfan I, endosulfan II, endosulfan sulfate, endrin, endrin aldehyde, endrin ketone, aldrin + dieldrin, methoxychlor), polychlorinated biphenyls (PCBs, PCB 28, 52, 101, 153, 138, and 180), and polybrominated diphenyl ethers (PBDEs, PBDE 47, 99, 100, 153, and 154 congeners). Estimated daily intake (EDI) values calculated for both adults and children consuming raw or UHT milk were determined to exceed maximum residue limits (MRLs) set for γ-HCH, ∑Heptachlor, and endrin. EDI values also exceeded admissible daily intake (ADI) values given for ∑HCH, ∑Heptachlor, ∑Endrin aldrin + dieldrin, and ∑PCBs. p,p’-DDT/p,p’-DDE ratio was 1 or higher for 66% of the milk samples, which is an indication of sustaining illegal use of DDT. A health risk is determined for dietary intake of OHPs via consumption of milk.