Study of factors affecting on the extraction efficiency of polycyclic aromatic hydrocarbons from soils using open-vessel focused microwave-assisted extraction

As part of an evaluation of focused microwave-assisted extraction (FMAE) using an open-vessel system, the effects of matrix, moisture content, ageing, and solvent have been studied on the extraction efficiency of polycyclic aromatic hydrocarbons (PAHs) from spiked soils. PAHs were spiked onto three different uncontaminated air dried and originally wet soil matrices with 1- and 20-day ageing periods. Solvents used were hexane–acetone (1:1), cyclohexane–acetone (1:1) and dichloromethane. FMAE only required a small amount of solvent (20 ml) and short extraction time (10 min) in the open cell under 90 W of microwave power. The results revealed that the extraction efficiency strongly depends on the nature of soil matrix; moisture content may enhance the recoveries of PAHs for many cases; and, the influence of the type of solvent is not significant. A comparison between microwave extraction and 16-h Soxhlet extraction has been made on spiked soils. It evidenced that the microwave method under ambient pressure is a suitable alternative to Soxhlet method for the analysis of PAHs in soils. For the evaluation of the developed FMAE method, three reference materials were used. The PAHs recovered from three reference materials were in a good agreement with reference values.     

Nitrogen nutrition in cotton and control strategies for greenhouse gas emissions: a review

Cotton (Gossypium hirustum L.) is grown globally as a major source of natural fiber. Nitrogen (N) management is cumbersome in cotton production systems; it has more impacts on yield, maturity, and lint quality of a cotton crop than other primary plant nutrient. Application and production of N fertilizers consume large amounts of energy, and excess application can cause environmental concerns, i.e., nitrate in ground water, and the production of nitrous oxide a highly potent greenhouse gas (GHG) to the atmosphere, which is a global concern. Therefore, improving nitrogen use efficiency (NUE) of cotton plant is critical in this context. Slow-release fertilizers (e.g., polymer-coated urea) have the potential to increase cotton yield and reduce environmental pollution due to more efficient use of nutrients. Limited literature is available on the mitigation of GHG emissions for cotton production. Therefore, this review focuses on the role of N fertilization, in cotton growth and GHG emission management strategies, and will assess, justify, and organize the researchable priorities. Nitrate and ammonium nitrogen are essential nutrients for successful crop production. Ammonia (NH₃) is a central intermediate in plant N metabolism. NH₃ is assimilated in cotton by the mediation of glutamine synthetase, glutamine (z-) oxoglutarate amino-transferase enzyme systems in two steps: the first step requires adenosine triphosphate (ATP) to add NH₃ to glutamate to form glutamine (Gln), and the second step transfers the NH₃ from glutamine (Gln) to α-ketoglutarate to form two glutamates. Once NH₃ has been incorporated into glutamate, it can be transferred to other carbon skeletons by various transaminases to form additional amino acids. The glutamate and glutamine formed can rapidly be used for the synthesis of low-molecular-weight organic N compounds (LMWONCs) such as amides, amino acids, ureides, amines, and peptides that are further synthesized into high-molecular-weight organic N compounds (HMWONCs) such as proteins and nucleic acids.     

Putting vulnerability to climate change on the map: a review of approaches, benefits, and risks

There is growing demand among stakeholders across public and private institutions for spatially-explicit information regarding vulnerability to climate change at the local scale. However, the challenges associated with mapping the geography of climate change vulnerability are non-trivial, both conceptually and technically, suggesting the need for more critical evaluation of this practice. Here, we review climate change vulnerability mapping in the context of four key questions that are fundamental to assessment design. First, what are the goals of the assessment? A review of published assessments yields a range of objective statements that emphasize problem orientation or decision-making about adaptation actions. Second, how is the assessment of vulnerability framed? Assessments vary with respect to what values are assessed (vulnerability of what) and the underlying determinants of vulnerability that are considered (vulnerability to what). The selected frame ultimately influences perceptions of the primary driving forces of vulnerability as well as preferences regarding management alternatives. Third, what are the technical methods by which an assessment is conducted? The integration of vulnerability determinants into a common map remains an emergent and subjective practice associated with a number of methodological challenges. Fourth, who participates in the assessment and how will it be used to facilitate change? Assessments are often conducted under the auspices of benefiting stakeholders, yet many lack direct engagement with stakeholders. Each of these questions is reviewed in turn by drawing on an illustrative set of 45 vulnerability mapping studies appearing in the literature. A number of pathways for placing vulnerability mapping on a more robust footing are also identified.     

The Role of Climate and Human Influences in the Dry‐Up of the Jinci Springs,China1

Abstract: One of the largest karst springs in North China, the Jinci Springs, dried up and has remained dry since 1994. We develop a correlation analysis with time‐lag and a regression analysis with time‐lag to study the relation between spring flow and precipitation. This allows us to obtain a better understanding of karst hydrological processes by differentiating the contribution of variation in precipitation from anthropogenic impacts on the dry‐up of Jinci Springs. We divided the karstic hydrological processes into two phases: pre‐1961 and post‐1961. In the first phase (i.e., 1954‐1960) the groundwater recharge was affected by precipitation alone, and in the second phase (i.e., 1961‐1994) the groundwater recharge was influenced by both precipitation and human activities. Using precipitation and groundwater recharge data in the first phase, we set up a groundwater recharge model with time‐lags. By running the time‐lags model, we acquired the groundwater recharge likely to occur under the sole effect of precipitation in the second phase. Using a water‐balance calculation, we conclude that the groundwater recharge exhibited statistical stationarity, and the Jinci Springs dry‐up was the result of anthropogenic activities. At least three specific types of anthropogenic activities contributed to the drying‐up of Jinci Springs: (1) groundwater pumping accounts for 51%, (2) the dewatering from coal mining accounts for 33%, (3) and dam‐building 14%. The drying‐up of Jinci Springs meant that the groundwater drained from the aquifer’s fractures, and subsequently changed the structure of the karst aquifer. Although groundwater exploitation has been reduced, the flow at Jinci Springs has not reoccurred.     

改性生物炭负载nZVI对土壤Cr(VI)的修复差异研究

考察了生物炭(BC)、酸洗生物炭(HCl-BC)和纳米零价铁负载生物炭(n ZVI-HCl-BC)对土壤中Cr(VI)还原和总Cr形态转化的影响.结果表明,生物炭对Cr(VI)还原率随土壤含水率的升高而显著提高.在较高土壤含水率(70%)条件下,各生物炭对Cr(VI)的最高还原率排序为:HCl-BC(97.26%)n ZVI-HCl-BC(88.36%)BC(87.61%).在不同Cr(VI)污染水平下(150、300、600和900 mg·kg~(-1)),HCl-BC对土壤中Cr(VI)的还原率最高.随Cr(VI)含量升高,BC和HCl-BC对Cr(VI)的还原率呈降低趋势,而n ZVI-HCl-BC对Cr(VI)的还原率为先降低后升高.形态分析表明,生物炭在不同程度上增加了土壤中Cr残渣态的比例:n ZVI-HCl-BC(11.58%)HCl-BC(9.53%)BC(1.42%),表明生物炭对土壤Cr起到稳定作用.综上,改性生物炭显著促进Cr(VI)还原及总Cr向残渣态转化,表明其具有修复Cr污染土壤的潜力.     

Prediction of daily averaged PM10 concentrations by statistical time-varying model

In this study, a time-varying statistical model, TVAREX, was proposed for daily averaged PM₁₀ concentrations forecasting of coastal cities. It is a Kalman filter based autoregressive model with exogenous inputs depending on selected meteorological properties on the day of prediction. The TVAREX model was evaluated and compared to an ANN model, trained with the Levenberg–Marquardt backpropagation algorithm subjected to the same set of inputs. It was found that the error statistics of the TVAREX model in general were comparable to those of the ANN model, but the TVAREX model was more efficient in capturing the PM₁₀ pollution episodes due to its online nature, therefore having an appealing advantage for implementation.