A directional passive air sampler for monitoring polycyclic aromatic hydrocarbons (PAHs) in air mass

A passive air sampler was developed for collecting polycyclic aromatic hydrocarbons (PAHs) in air mass from various directions. The airflow velocity within the sampler was assessed for its responses to ambient wind speed and direction. The sampler was examined for trapped particles, evaluated quantitatively for influence of airflow velocity and temperature on PAH uptake, examined for PAH uptake kinetics, calibrated against active sampling, and finally tested in the field. The airflow volume passing the sampler was linearly proportional to ambient wind speed and sensitive to wind direction. The uptake rate for an individual PAH was a function of airflow velocity, temperature and the octanol-air partitioning coefficient of the PAH. For all PAHs with more than two rings, the passive sampler operated in a linear uptake phase for three weeks. Different PAH concentrations were obtained in air masses from different directions in the field test.     

Seasonal and spatial occurrence and distribution of atmospheric polycyclic aromatic hydrocarbons (PAHs) in rural and urban areas of the North Chinese Plain

Passive air sampling (PAS) was employed to study the occurrence of gaseous and particle-bound PAHs in the North Chinese Plain. The averaged concentrations of gaseous and particle-bound PAHs were 485 ± 209 ng/m³ and 267 ± 161 ng/m³, respectively. The PAHs concentrations at urban sites were generally higher than those at rural ones with ratios <1.5 in spring, summer and fall, but differences between them were not significant for the wintertime and annually averaged concentrations. This urban-rural distribution pattern was related to the PAHs emission sources. PAHs spatial variation can be partially (49%) explained by emission with a simple linear regression method. Both the gaseous and particle-bound PAHs were highest in winter and lowest in summer, with winter/summer ratios of 1.8 and 8, respectively. Emission strength was the most important factor for the seasonality.     

Evaluation of ogawa passive sampling devices as an alternative measurement method for the nitrogen dioxide annual standard in El Paso, Texas

Nitrogen Dioxide (NO₂) is a common urban air pollutant that results from the combustion of fossil fuels. It causes serious human health effects, is a precursor to the formation of ground level ozone, another serious air pollutant, and is one of the six criteria air pollutants established by the United States (U.S.) Clean Air Act (CAA). Ogawa Passive Sampling Devices (PSDs) for NO₂ were collocated and operated at six NO₂ Federal Reference Method (FRM) monitor locations in the El Paso, Texas area for the 2004 calendar year. Passive samples were taken at 2-week, 3-week, and 4-week intervals and compared against the continuously operating FRM monitors. Results showed that the collective NO₂ annual arithmetic mean for all passive monitors was identical to the NO₂ mean for all FRM monitors. Of the individual locations, three passive annual NO₂ means were identical to their corresponding FRM means, and three passive annual NO₂ means differed from their corresponding FRM means by only one part per billion (ppb). Linear correlation analysis between all readings of the individual NO₂ PSDs and FRM values showed an average absolute difference of 1.2 ppb with an r ² of 0.95. Paired comparison between high and low concentration annual NO₂ sites, seasonal considerations, and interlab quality control comparisons all showed excellent results. The ease of deployment, reliability, and the cost-savings that can be realized with NO₂ PSDs could make them an attractive alternative to FRM monitors for screening purposes, and even possibly an equivalent method for annual NO₂ monitoring. More tests of the Ogawa NO₂ PSD are recommended for different ecosystem and climate regimes.     

中国煤电和核电的环境影响与健康风险比较

将煤电与核电的环境影响和健康风险从全燃料链角度进行比较 ,结果表明 ,煤电燃料链的环境影响和健康风险比核电燃料链大。     

Two-echelon closed-loop supply chain deterministic inventory models in a batch production environment

This paper considers a two-echelon closed-loop supply chain consisting of a manufacturer and a remanufacturer at the upper echelon and a retailer at the lower echelon. The retailer faces a constant demand from customers, which is satisfied through recovered and new products received from the remanufacturer and the manufacturer, respectively. The manufacturer produces the product with finite rate, whereas the recovery of returned product is instantaneous at the remanufacturer. We develop three models to determine the optimal production-inventory policy of the players for minimizing the joint total cost of the system. In the first model, the retailer receives the product in batches from the manufacturer and the remanufacture simultaneously, whereas in the second and third models, the batches are received alternatively. In the third model, however, the procurement of raw material at the manufacturer is also considered. Numerical illustration is presented to examine the impact of certain key parameters.     

Temporal and Spatial Trends in Nutrient and Sediment Loading to Lake Tahoe,California‐Nevada,USA

Since 1980, the Lake Tahoe Interagency Monitoring Program (LTIMP) has provided stream‐discharge and water quality data—nitrogen (N), phosphorus (P), and suspended sediment—at more than 20 stations in Lake Tahoe Basin streams. To characterize the temporal and spatial patterns in nutrient and sediment loading to the lake, and improve the usefulness of the program and the existing database, we have (1) identified and corrected for sources of bias in the water quality database; (2) generated synthetic datasets for sediments and nutrients, and resampled to compare the accuracy and precision of different load calculation models; (3) using the best models, recalculated total annual loads over the period of record; (4) regressed total loads against total annual and annual maximum daily discharge, and tested for time trends in the residuals; (5) compared loads for different forms of N and P; and (6) tested constituent loads against land use‐land cover (LULC) variables using multiple regression. The results show (1) N and P loads are dominated by organic N and particulate P; (2) there are significant long‐term downward trends in some constituent loads of some streams; and (3) anthropogenic impervious surface is the most important LULC variable influencing water quality in basin streams. Many of our recommendations for changes in water quality monitoring and load calculation methods have been adopted by the LTIMP.     

Evaluating the impact of uncertainty and variability on the value chain optimization of a forest biomass power plant using Monte Carlo Simulation

Mathematical programming models have been used to optimize the design and management of forest bioenergy supply chains. A deterministic mathematical model is beneficial for making optimum decisions; however, its applicability to real-world problems may be limited because it does not capture all the complexities, including uncertainties in the parameters, in the supply chain. In this paper, a combination of Monte Carlo Simulation and optimization model is used to evaluate the impact of uncertainty in biomass quality, availability and cost, and electricity prices on the supply chain of a forest biomass power plant. The optimization model is a deterministic mixed integer non-linear model with monthly time steps over a 1-year planning horizon. Variability in biomass quality, i.e. moisture content (MC) and higher heating value (HHV), based on the historical data of a real case study is studied in detail and fitted probability distributions are used in the model, while for electricity prices different scenarios are considered. The results show that the impact of variability in the MC on profit is higher than that of uncertainty in HHV. It is observed that the annual profit ranges between $13.3 million and $17.9 million in the presence of all possible uncertainties while its average is $15.5 million. Uncertainty in biomass availability and cost and electricity price results in the risks of having annual profit of less than $14 million and low monthly storage levels.     

复合链式结构下中国林业碳库系统测度模型构建

温室气体上升导致的全球气候变暖问题不容忽视,增加森林碳汇和木质林产品碳储是缓解温室效应的有效途径。根据森林碳汇功能与林产品碳储功能的关联理论与模型,推导和改进包括森林子碳库、土壤子碳库及木质林产品子碳库在内的林业碳库核算模型及方法,以实现目标碳从森林碳库向木质林产品碳库的过渡与转移。基于气候变化背景下森林-林产品产业链的发展现状,构建包括森林子碳库和林产品子碳库的复合一体化林业碳库模型,使之为中国林业碳库的计量与评价提供判据。首先,对包含森林子碳库和木质林产品子碳库在内的世界林业碳库的发展现状进行探讨,归纳和比较国内外主流的关联林业碳库评估方法模型,从而对中国林业碳库模型的构建提供理论背景支持和逻辑方法支撑。其次,分析现有中国林业碳库评估存在的优势和弊端,找出适合中国林业特点的国家碳库创新评估路径,运用政府间气候变化专门委员会指定的生产法的思路,通过分析目标碳在林产品产业链生产、加工等过程中的流入和支出,提出创新中国林业碳库的模型构想并对其系统内涵进行分析。最后,赋予中国林业碳库系统模型数学表达,分析其数理结构并进行逻辑演绎,在森林子碳库和木质林产品子碳库两个复合链式体系下构建中国林业碳库系统测度模型(ForestProducts Carbon Model/FPCM)。     

中国农业现代化发展水平的空间非均衡及动态演进

研究中国农业现代化发展水平的地区差距以及内部动态分布特征对于制定农业现代化发展的相关政策具有重要意义。本文利用1997-2013年中国31个省、市(自治区)的面板数据,构建了农业现代化发展水平的指标体系,进而采用熵权综合指数法测算出中国农业现代化发展水平的综合指数,同时借助Dagum基尼系数和Markov链估计方法对中国农业现代化发展水平的地区差距及其分布动态进行了实证研究,得到如下结论:1Dagum基尼系数及分解结果表明,中国农业现代化发展水平的总体差距在样本考察期内呈现出先上升、后下降的演变趋势。从三大地区来看,东部地区内差距呈现出上升趋势,而中部和西部地区内差距则呈现出下降趋势。地区间差距是造成中国农业现代化发展水平空间非均衡的首要原因,并且其对总体差距的贡献率呈波动上升趋势;地区内差距对总体差距的贡献率变化较小,而超变密度对总体差距的贡献率呈现出先上升、再下降的演变趋势。2Markov链分析表明,中国农业现代化发展水平状态流动性较低。从整体来看,中国农业现代化发展水平存在较为明显的上升趋势,并且农业现代化发展的低水平省份将逐步减少,总体向中等以上水平发展。针对本文实证结果,由此得到如下政策建议:首先,加大国家对西部地区农业基础设施建设的投入,引导农业科技人才回归;其次,加强区域间农业现代化发展全方位的交流与合作,发挥省区之间的协同效应;最后,因地制宜,充分利用资源禀赋,推动农业现代化发展。