Experimental study on soil CO2 emission in the alpine grassland ecosystem on Tibetan Plateau

The Tibetan Plateau, the Roof of the World, is the highest plateau with a mean elevation of 4000 m. It is characterized by high levels of solar radiation, low air temperature and low air pressure compared to other regions around the world. The alpine grassland, a typical ecosystem in the Tibetan Plateau, is distributed across regions over the elevation of 4500 m. Few studies for carbon flux in alpine grassland on the Tibetan Plateau were conducted due to rigorous natural conditions. A study of soil respiration under alpine grassland ecosystem on the Tibetan Plateau from October 1999 to October 2001 was conducted at Pangkog County, Tibetan Plateau (31.23°N, 90.01°E, elevation 4800 m). The measurements were taken using a static closed chamber technique, usually every two weeks during the summer and at other times at monthly intervals. The obvious diurnal variation of CO2 emissions from soil with higher emission during daytime and lower emission during nighttime was discovered. Diurnal CO2 flux fluctuated from minimum at 05:00 to maximum at 14:00 in local time. Seasonal CO2 fluxes increased in summer and decreased in winter, representing a great variation of seasonal soil respiration. The mean soil CO2 fluxes in the alpine grassland ecosystem were 21.39 mgCO2 · m-2 · h-1, with an average annual amount of soil respiration of 187.46 gCO2 · m-2 · a-1. Net ecosystem productivity is also estimated, which indicated that the alpine grassland ecosystem is a carbon sink.     

Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".     

Direct Current Plasma Emission Spectrometric Determination of Major, Minor and Trace Elements in Microwave Oven Acid Leachates of Powdered Whole Coal Samples

Major concentrations of Al₂O₃, Fe₂O₃, MgO, CaO, Na₂O and K₂O, minor levels of TiO₂, P₂O₅ and thirty petrologically, geochemically and environmentally significant trace elements have been determined in microwave oven acid leachates of whole powdered coal samples by direct current plasma‐atomic emission spectrometry (DCP‐AES). A single sample preparation procedure was suitable for all the determinations with no additional dilution step for major elements solution. Dried samples (0.5 g) were treated in low‐pressure PFA digestion vessels with HF/HCl/HNO₃/HClO₄ acids to quantitatively extract the analytes from the bulk material, while leaving the major part of organic matrix as a residue. The major constituents of geological samples, in particular the easily ionised elements (EIEs) such as alkali and alkaline earths, may complicate the instrumental determinations in DCP‐AES because of differential enhancements of elemental emission intensities and stray light interferences. Taking account of these factors, the coal matrix is considered to have very low major oxide totals as compared to many other common geo‐environmental and related materials (rocks, sediments, soil, ashes etc.). The sample size employed here, while yielding a relatively concentrated solution to cover a wide range of elemental determinations, provided a sample matrix that significantly diminished interferences for DCP measurements. The need for closely matching the unknowns and calibrators was eliminated except for overall acidity and an excess quantity of caesium for EIE buffering. Calibration of the spectrometer was accomplished by simple aqueous single element solutions as high concentration calibrators in addition to a reagent blank as a low concentration calibrator. Two point working curves were established to allow for the maximum concentrations of each element expected in the unknowns. The precision of determinations under routine conditions as well as the reproducibility of the leaching and precision of instrumental measurements have been evaluated. Relative standard deviations (RSD) were of 1–2% for those elements whose concentrations in solid samples were well above the limits of quantification. Method detection limits in the buffered solutions were also evaluated. To evaluate the accuracy of the microwave oven‐DCP method a suite of eight certified coal reference materials of differing rank, were analysed with good agreement with the certified and/or available published data. Results are presented for the uncertified major oxides in the AR series reference materials.     

Localization of mining-induced horizontal fractures along rock layer interfaces in overburden: field measurements and prediction

The locations of mining-induced horizontal fractures along rock interfaces in the overburden of Donetsk Coal Basin were identified using an original experimental device. The device traps methane from horizontal fracture zone (100–fold coal seam thickness) over an active longwall mining excavation. Presence or absence of horizontal fractures along rock layer interfaces is correlated with physical characteristics of the overburden, such as thickness, uniaxial compressive strength of overburden rock layers, location of rock layer interfaces and thickness of extracted coal seams. As a result, a combined criterion based on these physical characteristics is proposed to predict the presence of overburden horizontal fracturing in coal mine operations.     

On Tension Failure of 2-D Rock Specimens and Associated Acoustic Emission

Summary To understand the failure mechanism of quasi-brittle materials like rock under tensile stress, observations on the failure process of granite and marble plate specimens under tension are summarized and presented. Micro- and macro-failure properties of rock plates under uniaxial tension have been characterized by using an acoustic emission technique. Acoustic emission signals associated with micro-fractures are captured to locate the sources. An algorithm based on arrival time difference is developed for this purpose. The results reveal clearly the failure processes of rock which include initiation, nucleation and propagation of micro-fractures when the axial stress is close to the peak strength of rock. It is believed that the difference in heterogeneity between granite and marble specimens leads to different fracture shapes and different behaviors of associated acoustic emissions. Numerical simulation of acoustic emissions for two-dimensional tensile test is also carried out. The simulated characteristics are in good agreement with the experimental results.     

Development of a rain‐on‐snow detection algorithm using passive microwave radiometry

Currently observed climate warming in the Arctic has numerous consequences. Of particular relevance, the precipitation regime is modified where mixed and liquid precipitation can occur during the winter season leading to rain‐on‐snow (ROS) events. This phenomenon is responsible for ice crust formation, which has a significant impact on ecosystems (such as biological, hydrological, ecological and physical processes). The spatially and temporally sporadic nature of ROS events makes the phenomenon difficult to monitor using meteorological observations. This paper focuses on the detection of ROS events using passive microwave (PMW) data from a modified brightness temperature (T_B) gradient approach at 19 and 37 GHz. The approach presented here was developed empirically for observed ROS events with coincident ground‐based PMW measurements in Sherbrooke, Quebec, Canada. It was then tested in Nunavik, Quebec, with the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E). We obtained a detection accuracy of 57, 71 and 89% for ROS detection for three AMSR‐E grid cells with a maximum error of 7% when considering all omissions and commissions with regard to the total number of AMSR‐E passes throughout the winter period. Copyright © 2016 John Wiley & Sons, Ltd.     

Climate change mitigation scenarios and policies and measures: the case of Kazakhstan

This article illustrates the main difficulties encountered in the preparation of GHG emission projections and climate change mitigation policies and measures (P&M) for Kazakhstan. Difficulties in representing the system with an economic model have been overcome by representing the energy system with a technical-economic growth model (MARKAL-TIMES) based on the stock of existing plants, transformation processes, and end-use devices. GHG emission scenarios depend mainly on the pace of transition in Kazakhstan from a planned economy to a market economy. Three scenarios are portrayed: an incomplete transition, a fast and successful one, and even more advanced participation in global climate change mitigation, including participation in some emission trading schemes. If the transition to a market economy is completed by 2020, P&M already adopted may reduce emissions of CO₂ from combustion by about 85 MtCO₂ by 2030 – 17% of the emissions in the baseline (WOM) scenario. One-third of these reductions are likely to be obtained from the demand sectors, and two-thirds from the supply sectors. If every tonne of CO₂ not emitted is valued up to US$10 in 2020 and $20 in 2030, additional P&M may further reduce emissions by 110 MtCO₂ by 2030.     

Impact of sub-pixel heterogeneity on modelled brightness temperature for an agricultural region

Knowledge of sub-pixel heterogeneity, particularly at the passive microwave scale, can improve the brightness temperature (and ultimately the soil moisture) estimation. However, the impact of surface heterogeneity (in terms of soil moisture, soil temperature and vegetation water content) on brightness temperature in an agricultural setting is relatively unknown. The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) provided an opportunity to evaluate sub-pixel heterogeneity at the scale of a Soil Moisture Ocean Salinity (SMOS) or the Soil Moisture Active Passive (SMAP) radiometer footprint using field measured data. The first objective of this study was to determine if accounting for surface heterogeneity reduced the error between estimated brightness temperature (T_b) and T_b measured by SMOS. It was found that when accounting for variation in surface soil moisture, temperature and vegetation water content within the pixel footprint, the error between the modelled T_b and the measured T_b was less than if a homogeneous pixel were modelled. The correlation between the surface parameters and the error associated with not accounting for surface heterogeneity were investigated. It was found that there was low to moderate correlation between the error and the coefficient of variance associated with the measured soil moisture, soil temperature and vegetation volumetric water content during the field campaign. However, it was found that the correlations changed depending on the stage of vegetation growth and the amount of time following a precipitation event. At the start of the field campaign (following a precipitation event), there was strong correlation between the error and all three surface parameters (r ≥ 0.75). Following a precipitation event close to the middle of the field campaign (during which there was rapid growth in vegetation), there was strong correlation between the error and the variability in vegetation water content (r = 0.89), moderate correlation with soil moisture (r = 0.61) and low correlation with soil temperature (r = 0.26).     

同步辐射软X射线吸收谱与发射谱测定天然针铁矿能带结构

天然半导体矿物由于成分、缺陷复杂,传统测试方法如紫外可见漫反射等难以准确测定其禁带宽度.本文以针铁矿为例,通过第一性原理计算得到纯针铁矿及掺Al针铁矿的电子结构.计算结果显示,纯针铁矿导带底与价带顶均由Fe3d与O2p轨道组成,而当含杂质Al时,Al2p与O2p发生杂化参与了价带组成.在此基础上,利用同步辐射X射线氧的K边吸收谱与发射谱对纯针铁矿及天然针铁矿的能带结构进行了测定.结果表明,天然含Al的针铁矿禁带宽度为2.30eV,小于纯针铁矿(2.57eV).本研究提供了一种测定天然氧化物矿物禁带宽度的新方法,为深入研究天然半导体可见光催化活性产生机制提供了理论依据.     

Coastal aquaculture,mangrove deforestation and blue carbon emissions: Is REDD+ a solution?

Globally, coastal aquaculture particularly shrimp farming has been under huge criticism because of its environmental impacts including devastating effects on mangrove forests. However, mangroves are ecologically and economically important forests, and the most carbon-rich forests in the tropics that provide a wide range of ecosystem services and biodiversity conservation. Carbon emissions are likely to have been the dominant cause of climate change and blue carbon emissions are being critically augmented through mangrove deforestation. Because of mangrove deforestation, different climatic variables including coastal flooding, cyclone, drought, rainfall, salinity, sea-level rise, and sea surface temperature have dramatic effects on coastal aquaculture. Mangrove forests have been instrumental in augmenting resilience to climate change. The “Reducing Emissions from Deforestation and forest Degradation (REDD)” program can help to restore mangroves which in turn increases options for adaptation to climate change. However, technical and financial assistance with institutional support are needed to implement REDD+.