Does the Temporal Resolution of Precipitation Input Influence the Simulated Hydrological Components Employing the SWAT Model?

This study aimed to evaluate the influence of sub‐daily precipitation time steps on model performance and hydrological components by applying the Green and Ampt infiltration method using the Soil and Water Assessment Tool (SWAT). Precipitation was measured at a resolution of 0.1 mm and aggregated to 5‐, 15‐, 30‐, and 60‐min time steps. Daily discharge data over a 10‐year period were used to calibrate and validate the model. Following a global sensitivity analysis, relevant parameters were optimized through an automatic calibration procedure using SWAT‐CUP for each time step. Daily performance statistics were almost equal among all four time steps (NSE ≈ 0.47). Discharge mainly consisted of groundwater flow (55%) and tile flow (42%), in reasonable proportions for the investigated catchment. In conclusion, model outputs were almost identical, showing simulations responded nearly independently of the chosen precipitation time step. This held true for (1) the selection of sensitive parameters, (2) performance statistics, (3) the shape of the hydrographs, and (4) flow components. However, a scenario analysis revealed that the precipitation time step becomes important when saturated hydraulic conductivities are low and curve numbers are high. The study suggests that there is no need in using precipitation time steps <1 h for lowland catchments dominated by soils with a low surface runoff potential if daily flow values are being considered. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

A case study of an isolated wind powered electricity system meeting 100% of local demand

Using meteorological and electricity demand data for a 4-year period, electricity demand in Shetland was modeled to provide an estimate of the demand over a 30-year period from 1 January 1981. That modeled demand was then compared to estimated wind power output over the same period using the WAsP model. The wind farm output was estimated for a range of sizes of wind farm up to the consented 370 MW Viking Wind Farm in Shetland. Some wind power was available for 94% of the time and the 370 MW wind farm would meet 100% of demand for nearly 80% of the time. The statistics of single and accumulated deficits were calculated for a range of wind farms and estimates of the amount of additional generation capacity and additional power requirements were assessed. The study suggests that with storage, wind power in Shetland could meet all electricity demand in Shetland at around £130 to £150/MWh (excluding subsidy) and with a grid connection allowing the sale of excess power, those costs could be reduced.     

中国2030年CO2排放总量预测研究

我国2005年和2010年CO2排放总量分别为55亿t和81.52亿t,“十五”和“十一五”期间年均增长率分别为11.0％和8.0％.中国2011-2015年、2016-2020年、2021-2025年和2026-2030年GDP年均增长率分别为8％、7％、6％、5％的经济发展模式与对应的能源消费弹性系数分别为0.5、0.5、0.4和0.3的能源发展模式,预测2030年燃煤、燃油和天然气CO2排放量及全国CO2排放总量.提出减少CO2排放总量对策,主要包括：调整能源结构,尽量减少煤炭消费量占能源消费总量的比例,增加石油、天然气和新能源的比例,提高CO2综合利用率,完善CO2管理政策与法律法规等.     

微囊藻毒素-LR的全内反射荧光免疫传感器研究

在开发全内反射荧光免疫传感器的基础上,研究水中微囊藻毒素-LR(MC-LR)的检测方法。建立了基于MC-LR平面波导免疫芯片的制备方法,并结合流动分析和荧光检测开发检测系统,针对MC-LR的免疫检测条件进行优化。结果表明,全内反射荧光免疫传感器对MC-LR抗体的检测限为0.001μg/mL;在间接竞争免疫检测模式下,最优检测条件是预反应时间5min、预反应温度37℃、进样停留时间500s;在最优检测条件下,对MC-LR的检测限为0.100μg/L,线性区间为0.200~4.000μg/L;全内反射荧光免疫传感器检测MC-LR的加标回收率均在100.0%±20.0%,平行测定的相对标准偏差小于5%。     

浙江省工业烟粉尘总量控制研究

通过对浙江省工业烟粉尘排放总量和排放源现状进行分析,提出工业烟粉尘减排治理对策,对工业烟粉尘4个重点行业(水泥制造行业、火力发电行业、钢铁行业(包括炼钢、钢压延加工和黑色金属铸造行业)、纺织染整行业(包括棉印染精加工、化纤织物染整精加工和棉织造加工行业)排放源的烟粉尘减排途径和潜力进行分析测算,研究提出工业烟粉尘总量控制措施和建议。     

陕北能源化工基地某工业园区水污染物排放总量控制研究

基于水污染物总量控制思路,以陕北能源化工基地某工业园区为研究对象,分析工业园区主要水环境问题及原因,分别对园区企业和集中污水处理厂提出排水水量、水质控制要求,从工程技术措施和管理手段上提出了明确的解决方案和要求。结果表明,各项减排措施实施后,COD、氨氮、石油类物质分别削减49.4%、71.0%、72.6%,园区排水总量控制在1.18万t/d,最终保证园区水污染物总量控制目标的实现。     

北京市“十三五”大气污染物排放总量控制基本思路探讨

随着各项环保措施的深入实施,北京市大气环境质量进一步改善的难度逐渐加大。对北京市"十二五"时期的大气污染物排放总量控制工作进行了经验总结,并分析了"十三五"时期大气污染物的排放形势和减排压力。在此基础上,从6个方面提出了北京市"十三五"期间大气污染物排放总量控制的基本思路。     

湖库型水体总氮总量控制目标的区域分配研究

基于层次分析法原理,以资源禀赋、社会经济、农业生产生活、污染治理水平为主要考虑因素设计指标体系和层次结构,建立了湖库型水体总氮总量控制目标分配方法,并在石头口门水库流域进行了应用,为湖库型水体总氮总量控制目标分配及石头口门水库流域总氮总量控制提供借鉴。     

烟气脱硫溶液中硫酸根的去除

分别采用石灰乳化学沉淀法和低温结晶法去除烟气脱硫溶液中的SO42-。实验结果表明：在室温、CaO溶液质量分数25%的条件下,石灰乳化学沉淀法对SO42-的去除率仅为59.51%,且向溶液中引入了Ca2+,产生的硫酸钙固体废物难以再生利用;采用低温结晶法处理烟气脱硫溶液,在结晶温度7 ℃、结晶时间3 h、NaOH加入量34.8 g/L的条件下,SO42-的去除率为82.04%、滤液中的ρ（Na+）为3.88 g/L。在现场工业应用试验中,采用低温结晶法去除烟气脱硫溶液中的SO42-,平均SO42-的去除率可达70.00%以上,滤液中的ρ（Na+）小于15.00 g/L。该法可有效抑制烟气脱硫溶液中SO42-含量的增加。     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.