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91.
In this study, a rapid, specific and sensitive multi-residue method based on acetonitrile extraction followed by dispersive solid-phase extraction (d-SPE) clean-up was implemented and validated for multi-class pesticide residues determination in palm oil for the first time. Liquid-liquid extraction followed by low-temperature precipitation procedure was evaluated in order to study the freezing-out clean-up efficiency to obtain high recovery yield and low co-extract fat residue in the final extract. For clean-up step, d-SPE was carried out using a combination of anhydrous magnesium sulphate (MgSO(4)), primary secondary amine, octadecyl (C(18)) and graphitized carbon black. Recovery study was performed at two concentration levels (10 and 100 ng g(-1)), yielding recovery rates between 74.52% and 97.1% with relative standard deviation values below 10% (n?=?6) except diuron. Detection and quantification limits were lower than 5 and 9 ng g(-1), respectively. In addition, soft matrix effects (≤±20%) were observed for most of the studied pesticides except malathion that indicated medium (20-50%) matrix effects. The proposed method was successfully applied to the analysis of suspected palm oil samples.  相似文献   
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93.
Empirically based models are used worldwide to estimate soil erosion. The Revised Universal Soil Loss Equation (RUSLE) is one such model that has been intensively tested and validated under conditions in the United States. RUSLE estimates average soil loss as a function of five main factors: rainfall erosivity (R), soil erodibility (K), crop management (C), support practice (P), and topographic (LS) factors. This study investigated the application of RUSLE to Mediterranean conditions. The validation and calibration of RUSLE in the study area utilized field plots soil erosion measurements. The results found the RUSLE soil loss estimation to be three times the actual soil loss (7.8 and 2.6 Mg/ha, for RUSLE and actual measured soil loss, respectively). The difference between the RUSLE factors and the measured factors were responsible for the differences between the soil loss estimation by RUSLE and the measured soil loss. Specifically, the RUSLE K-factor showed three times the magnitude of the measured K-factor, the RUSLE C-factor underestimated the measured C-factor, and the RUSLE P-factor overestimated the measured P-factor by three times. Adjusting the RUSLE factors according to the measured ones increased the models predictability, whereas the adjusted-RUSLE soil loss estimation underestimated the measured soil loss by 14%. The adjustment of RUSLE, according to the prevailing conditions of the study area, increased the model efficiency three times (0.26 and 0.86 before and after adjustment of the mode,l respectively). For more accurate and reliable validation of the RUSLE under the Mediterranean conditions, it is advisable to conduct long-term soil loss experimentation and measurements.  相似文献   
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Environmental Science and Pollution Research - This study uses a consumer-based accounting approach to evaluate the CO2 emission factors of 17 countries in Asia and the Pacific region by including...  相似文献   
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Environmental Science and Pollution Research - Effective design of ultrafast new-generation photocatalysts is a challenging task that requires highly dedicated efforts. This research focused on the...  相似文献   
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Environmental Science and Pollution Research - The coastal zone of Bangladesh, with a population density of 1278 people per square kilometer, is under serious threat due to heavy metal pollution....  相似文献   
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Environmental Science and Pollution Research - During the past few decades, the treatment of hazardous waste and toxic phenolic compounds has become a major issue in the pharmaceutical, gas/oil,...  相似文献   
98.
Global warming and greenhouse gas emissions pose severe threats to environmental sustainability. A sustainable environment is a prerequisite for long-term socioeconomic growth and human survival. Green technology is brought about by a country's economic and financial openness, and education provides knowledge to the public and labor, contributing to environmental sustainability. Thus, this research aims to unveil the liaison between human capital, trade openness, and environmental quality for Russia, Brazil, India, China, and South Africa (BRICS) countries from 1998 to 2018. Several econometric methods, including the Driscoll–Kraay standard errors and the Dumitrescu–Hurlin causality approaches, reveal long-run and causal relationships among the modelled indicators. The Driscoll–Kraay standard error results show that human capital is negatively related to carbon dioxide emissions (CO2 emissions). Imposing high tariffs and excise duties, changing tax structures, discouraging the inflow of polluted commodities, and encouraging green trade can help BRICS combat high environmental pollution. The results show that a one-point increase in human capital in models 1 and 2 can reduce CO2 emissions by 1.5279 and 0.1538 points, respectively. In contrast, a 1% growth in trade can lead to a rise in CO2 emissions of 0.3731% and 0.2384%, respectively. Similarly, financial development and energy consumption result in high CO2 emissions in the long run. Moreover, a feedback effect of the human capital index on CO2 emissions is discovered. As a result of the findings, the government and responsible authorities should provide financial support and encourage investments in the region's energy-resourceful and sustainable green projects.  相似文献   
99.
Environmental Science and Pollution Research - Lithium (Li) exploitation for industrial and domestic use is resulting in a buildup of the element in various environmental components that results in...  相似文献   
100.
Environmental Science and Pollution Research - TiO2-based heterogeneous photocatalysis systems have been reported with remarkable efficiency to decontaminate and mineralize a range of pollutants...  相似文献   
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