Based on the idea of a “Community of Human Destiny,” the Chinese government proposed the “Belt and Road” initiative, and clearly proposed to promote green development and strengthen ecological environmental protection. However, a considerable number of countries are resource-rich economies with serious market misallocations. Using the stochastic frontier analysis (SFA) combined with the directional distance function (DDF) framework, this paper measures the green total factor productivity (GTFP) and its items (i.e., technical change and efficiency change) of 33 countries along the Belt and Road in 1995–2012, and then the impact of market misallocations on GTFP is analyzed. The following conclusions are drawn: (1) The main driving force for GTFP promotion in Asian countries came from technical change, while in European countries, it came from efficiency change. (2) Market misallocations had significantly hindered the GTFP of these economies. Countries with greater market misallocations have smaller GTFP. (3) Results based on counterfactual measures showed that GTFP could be increased by up to 4.04% and the average can be increased by 1.24% after eliminating market misallocations.

Neural network models have been used to predict chlorophyll-a concentration dynamics. However, as model generalization ability decreases, (i) the performance of the models gradually decreases over time; (ii) the accuracy and performance of the models need to be improved. In this study, Transfer learning (TL) is employed to optimize neural network models (including feedforward neural networks (FNN), recurrent neural networks (RNN) and long short-term memory (LTSM)) and overcome these problems. Models using TL are able to reduce the influence of mutable data distribution and enhance generalization ability. Thus, it can improve the accuracy of prediction and maintain high performance in long-term applications. Also, TL is compared with parameter norm penalties (PNP) and dropout—two other methods used to improve model generalization ability. In general, TL has a better prediction effect than PNP and dropout. All the models, including FNN with different architectures, RNN and LSTM, as well as models optimized by PNP, dropout, and TL, are applied to an estuary reservoir in eastern China to predict chlorophyll-a dynamics at 5-min intervals. According to the results of this study, (i) models with TL produce the best prediction results; (ii) the original models and the models with PNP and dropout lose their ability to predict within 3 months, while TL models retain a high prediction accuracy.

The issue of recycling waste solar cells is critical with regard to the expanded use of these cells, which increases waste production. Technology establishment for this recycling process is essential with respect to the valuable and hazardous metals present therein. In the present study, the leaching potentials of Acidithiobacillus thiooxidans, Acidithiobacillus ferrooxidans, Penicillium chrysogenum, and Penicillium simplicissimum were assessed for the recovery of metals from spent solar cells, with a focus on retrieval of the valuable metal Te. Batch experiments were performed to explore and compare the metal removal efficiencies of the aforementioned microorganisms using spent media. P. chrysogenum spent medium was found to be most effective, recovering 100% of B, Mg, Si, V, Ni, Zn, and Sr along with 93% of Te at 30 °C, 150 rpm and 1% (w/v) pulp density. Further optimization of the process parameters increased the leaching efficiency, and 100% of Te was recovered at the optimum conditions of 20 °C, 200 rpm shaking speed and 1% (w/v) pulp density. In addition, the recovery of aluminum increased from 31 to 89% upon process optimization. Thus, the process has considerable potential for metal recovery and is environmentally beneficial.

Gaseous fuel as a combustion enhancer with a pilot fuel offers significant benefits in improving engine efficiency. Hydrogen and hydroxy are the two most common gaseous fuels that have been widely investigated in the CI engine but which one performs best is still inconvenient. In this study, hydrogen and hydroxy were injected with BD40 (v/v) separately in a common diesel engine to compare the performance and emission characteristics of these fuels. Engine performance parameters include brake thermal efficiency (BTE) and brake-specific energy consumption (BSEC), and exhaust emissions include hydrocarbon (HC), CO, CO₂, NOx, and smoke opacity. The induction of both hydroxy and hydrogen with BD40 has a positive effect on engine performance and emissions except NOx when compared to neat diesel fuel and BD40. The BTE of hydroxy-rich BD40 increased by 7.2% while BSEC reduced by 7.6% as compared to BD40 with hydrogen. The CO, HC, and smoke opacity of hydroxy-operated engine was found to be better than hydrogen-inducted engine. The NOx emission increased with the induction of both gaseous fuels and hydroxy-enriched BD40 produced 12.5% more emission than hydrogen-operated BD40 engine. Thus, more concisely, hydroxy-operated biodiesel engine performed better than hydrogen engine in terms of BTE, BSEC, CO, HC, and smoke opacity.

Agricultural farmers in developing countries are at high risk of pesticide exposure and adverse effects because of unsafe practices and inappropriate legislation. Biological monitoring is considered a useful tool for pesticide exposure assessment; however, its use is limited in developing countries due to a lack of techniques and resources such as laboratory analysis, trained staff and budgets. This study examines whether the World Health Organization predicted exposure assessment model (WHO-PEAM) is a suitable alternative tool for assessing insecticide exposure among agricultural farmers. WHO-PEAM was used to predict daily doses (PDD) of chlorpyrifos for a group of Vietnamese rice farmers using a set of exposure parameters obtained from a questionnaire survey of participant famers during a field study. These results were compared to absorbed daily doses (ADD) of chlorpyrifos for the farmers measured using a biological monitoring program, in which 24-h urine samples were collected and analysed for the chlorpyrifos metabolite, 3,5,6-trichloro-2-pyridinol (TCP) using LC/MS. Validation of the model results was tested using the Wilcoxon signed-rank test (WSR) and two-way mixed-model intraclass correlation coefficient (ICC). The mean of total ADD was 20 μg/kg/day while that of total PDD was 22 μg/kg/day. The WSR test revealed no statistically significant difference in the average values of ADDT and PDDT. ICC indicated substantial agreement for both single and average measures between ADDT and PDDT (ICC, 0.62 and 0.77, respectively). The results demonstrate that a refined WHO-PEAM model can be readily used as a field method, without biological monitoring, to evaluate chlorpyrifos exposure among agricultural farmers in Vietnam and similar developing countries.

Meta-analysis with high-quality studies can provide superior evidence. In this paper, we use meta-analysis to analyze the relationship between cadmium (Cd) content in semen and male infertility, and then objectively evaluate the effect of Cd on sperm quality. The objectives of this study were to update our understanding of infertility and to provide evidence to treat and prevent the infertility. We searched potentially relevant studies that were published from establishing database data to April 2018. Articles came from the databases of CNKI, Wanfang, VIP, PubMed, CMCI, and EMBASE. A total of 11 articles were included. We gathered the mean and variance of the infertility group and the control group to compare the Cd content in two groups. In total, the 11 studies include 1707 subjects, 1093 of which were in the infertility group and 614 of which were in the control group. We can get some information from this meta-analysis: SMD = 0.50 (95% Cl 0.39–0.61), Z = 8.92, P < 0.05; the funnel plot of the meta-analysis shows incomplete symmetry, which may have the publication bias. Therefore, the high content of Cd in semen is a causative factor of infertility. The Cd content in semen can be used as an indicator of sperm quality.

The effects of different concentrations of phosphorus (P) on absorption and transfer of selenium (Se) in rice seedlings were studied by hydroponics experiment. The interaction between iron plaque and phosphorus on absorption and transport of selenium were studied by adding a large amount of iron-induced iron plaque, to provide a theoretical basis for rational application of phosphate fertilizer in the selenium bio-strengthening process of rice. The results showed that phosphorus deficiency may result in the formation of reddish brown iron oxide coating on the root surface of rice. The formation of root iron plaque of rice is related to concentration of phosphorus, and low concentration of phosphorus (0–1.5 mmol L⁻¹) can increase the amount of root iron plaque. Compared P deficiency culture and 2 mmol L⁻¹ P culture, Se content in the shoots and roots decreased by 76 and 47%, respectively. Addition of Fe²⁺ significantly reduced biomass of shoot and had no significant effect on the roots; when the P concentration increased from 0.1 to 0.3 mmol L⁻¹, transfer coefficient of Se decreased. Therefore, both root iron plaques induced by phosphorus deficiency and iron addition have a strong adsorption effect on selenium, which reduces the transport of selenium from the rice roots to the shoots. In the lower range of phosphorus concentration, low phosphorus can promote selenium content of rice shoot, while higher on the contrary. In the practice of rice production, proper management of phosphorus nutrient is of great significance to control selenium content in rice grain.

China is the largest cement producer and carbon dioxide (CO₂) emitter in the world. The country has attracted too much attention in calculating and comparing its CO₂ emissions. However, as the second largest CO₂ emitter after the fire power industry, China’s long-term cement demand and cement-related CO₂ emission projections were not fully studied. The Chinese government, however, committed that by 2020 and 2030, China’s per capita GDP of CO₂ emissions would be lower than that in 2005 by 40–45% and 60–65%, respectively. In this paper, China’s cement demand in 2030 was projected based on the population size, urbanization rate, fixed assets investment, and per capita GDP. Furthermore, decoupling study in China’s cement industry was also involved based on the GDP and CO₂ emissions during 2001–2015. We also used the diffusion rate of 12 types of CO₂ reduction measures and two changed scenarios of clinker-to-cement ratio, to project the cement CO₂ emission factors toward 2030 after determining the accounting scope. Meanwhile, the CO₂ emissions of China’s cement industry through 2030 were projected naturally. The results showed that China’s cement output in 2030 will be approximately 2000, 1650, and 937 Mt. based on the fixed assets investment, urbanization rate, and per capita GDP respectively. The projected two scenarios cement CO₂ emission factors were resp. 407.83 and 390.02 kg CO₂/t of cement which were 42.6 and 45.1% lower than that in 2005. The cement CO₂ emissions were projected to be in the range of 366 to 818 Mt. in 2030. Additionally, China’s total cement output value has been decoupling from cement CO₂ emissions from 2012, which is mainly attributed to eliminating backward capacity, reducing excess capacity or the declining cement output. And decoupling economic from China’s cement CO₂ emissions may change to be strong or weak decoupling in the near future. As cement production is one of the factors effecting cement CO₂ emissions, the most important measure for controlling cement CO₂ emissions is a reasonable capacity utilization rate. It is therefore important to control the growth of cement CO₂ emissions by regulating the capacity utilization rate within a reasonable range. Eliminating backward capacity, removing excess capacity, controlling new capacity, staggered production, and the “going global” of cement equipment can have great impacts in controlling the total amount of cement output and CO₂ emissions.

The potential of raw date pits as a natural, widely available and low-cost agricultural waste has been studied in order to adsorb cationic dyes from an aqueous solution. Date pits were characterized by FTIR, SEM, BET, and XRD analysis. To optimize removal of two industrial dyes, basic red 2 (BR2) and methyl violet (MV), from aqueous solution using date pits, response surface methodology (RSM) is employed. Tests were carried out as per central composite design (CCD) with four input parameters namely contact time, temperature, initial concentration of adsorbate, and pH. Second-order polynomial model better fits experimental data for BR2 and MV and optimum values were then determined. In the optimum conditions, kinetic study was conducted and the pseudo-second-order model was found the best fitted model compared to pseudo-first-order model. Moreover, it was shown that intraparticle diffusion was not the sole controlling step and could be associated with other transfer resistance. On other hand, equilibrium isotherms were obtained for BR2 and MV and their maximum adsorption capacities were 92 and 136 mg g⁻¹ respectively. Two-parameter isotherm models like Langmuir, Temkin, Freundlich, Dubinin–Radushkevich, and Halsay were investigated to fit equilibrium data. Three error functions of residual root mean square error, chi-square statistic, and average relative error were used to comfort us in the selected models, which were actually Dubinin–Radushkevich and Langmuir for BR2 and Frendlich, Temkin, and Halsay for MV.

Recycling sewage sludge by applying it to agricultural land is strategically important in the European Union and is regulated by Directive 86/278/EEC, aimed at protecting the soil and humans from the presence of unwanted substances. However, because of the ruminant feeding habits, there is a risk that animals grazed on pasture or fed crops grown on land treated in this way may ingest biosolids adhered to foliage and/or on the top soil. This paper describes an episode of toxicity in a dairy herd consuming silage from a field fertilized with sewage sludge produced in a wastewater treatment plant. The affected cows were recumbent, unable to rise and suffered diarrhoea. Analysis of tissues (fresh weight) from a cow that subsequently died revealed severe hepatic iron loading (6720 mg/kg) and secondary multi-trace element hepatic deficiency, particularly of copper (0.812 mg/kg) and manganese (0.436 mg/kg), but also selenium (0.164 mg/kg) and zinc (19.9 mg/kg). The study findings indicate that the use of sewage sludge in agriculture can cause secondary multi-trace element deficiencies in ruminants. Careful attention should be taken when crops are ensilaged avoiding top-soil sewage sludge contamination, since the acidification process may greatly increase Fe bioavailability.