基于高频AQI数据的关中城市群空气污染规律探索

基于高频分时AQI及各污染物浓度数据,本文使用"AQI小时指数"、首要污染物等进行统计分析并建立VAR模型对关中城市群空气污染的总体情况、日内波动规律以及城市间空气污染的关联规律做了不同层次的挖掘。研究结果表明:(1)关中城市群的空气质量整体较差,春、冬季空气污染程度明显大于夏季,空气污染的"季节效应"和"集簇性"明显,且主要表现为颗粒物污染。(2)空气质量的日内波动规律在春、冬两季表现为下半天优于上半天,夏季夜间优于白天。但在不考虑四季AQI小时指数图"相位"差异的情况下,四季空气污染的日内波动呈现出明显的相似性。(3)各城市空气污染存在明显的关联规律。城市群内一个城市空气污染的恶化会加剧其他城市的空气污染,并且对其他城市空气污染的影响峰值会在24小时之内出现,且该影响会随着空间和时间尺度的增大而逐步衰减。     

Modeling potential herbicide loss to surface waters on the Swiss plateau

Lack of sufficiently detailed data often limits the applicability of complex transport-reaction models for estimating potential herbicide loss to surface waters. Therefore, there is also a need for simple models that are easy to apply but still capture the main features of the underlying processes.In this study, a simple regression model was developed to assess the vulnerability of catchments in the Swiss Plateau to diffuse herbicide loss to surface waters. The model is designed as a screening tool to rank the catchments in a relative sense and not to calculate Predicted Environmental Concentrations (PEC) of pesticides. The main goal is to capture two dominating factors controlling diffuse herbicide transport into streams and rivers. These factors are herbicide application and fast flow processes that are mainly responsible for herbicide transport. In a first step vulnerability of sites to herbicide loss is estimated based on site-specific conditions irrespective of actual herbicide application. In the second step, this vulnerability assessment is combined with actual herbicide application data to estimate the potential herbicide loss.The fast flow index (FFI), derived from discharge data using a base flow separation method, was applied as a proxy for the amount of fast flow occurring. The influence of catchment attributes (including topographic, climatic and soil data) on the FFI was analyzed using a multiple regression approach based on data from 57 catchments of the Swiss Plateau. By combining regression analysis with mechanistic knowledge, a two factor non-linear model based on river density and soil permeability as dominant input factors was selected as the best model for FFI prediction given the available data. Higher dimensional models had to be excluded because the strong correlation between the potential input factors led to unrealistic dependences while only minimally improving the quality of the fit.The spatial pattern of the predicted FFI as a measure for the vulnerability to diffuse herbicide losses shows a clearly increasing trend from the western to the eastern part of the Swiss Plateau and towards the pre-alpine/alpine regions in the south.In general the pattern of herbicide use corresponds to site conditions typical of a low FFI. However, the spatial analysis revealed exceptions, namely areas in which high actual herbicide use coincides with a high FFI.Despite the uncertainties in the model, this simple approach seems to be useful for supporting site-adapted agricultural practice whenever the higher accuracy of more detailed models is not required or too expensive to achieve. In addition, in combination with data on actual herbicide application, it can support the design of monitoring strategies by identifying critical areas of actual herbicide loss.     

The reliability of experts' opinions in constructing a composite environmental index: The case of ESI 2005

The complexity of the environment demands a well-constructed composite environmental index (CEI) to provide a useful tool to draw attention to environmental conditions and trends for policy purposes. Among the common difficulties in constructing a proper CEI are uncertainties due to the selection of the most representative underlying variables or indicators. A degree of uncertainty accompanies experts' judgments, and to deal with vague, subjective or inconsistent information, logic other than classic is required. This study analyzes a procedure that uses different experts' opinions in constructing a CEI, with the use of paraconsistent annotated logic. For this, a sensitivity analysis of the Environmental Sustainability Index (ESI 2005) was used as an example to assess the reliability of experts' opinions. The uncertainty due to the disagreement in experts' opinions clearly indicates that the forms we presently use to measure and monitor the actual environment are insufficient, that is, there is a lack of a “science of sustainability”.     

Landfill site selection using spatial information technologies and AHP: A case study in Beijing,China

Site selection is an important and necessary issue for waste management in fast-growing regions. Because of the complexity of waste management systems, the selection of the appropriate solid waste landfill site requires consideration of multiple alternative solutions and evaluation criteria. Based on actual conditions of the study area, we considered economic factors, calculated criteria weights using the analytical hierarchy process (AHP), and built a hierarchy model for solving the solid waste landfill site-selection problem in Beijing, China. A geographic information system (GIS) was used to manipulate and present spatial data. All maps are graded from 1 (lowest suitability) to 5 (highest suitability) using spatial information technologies. The candidate sites were determined by aggregation based on the criteria weights. The candidate sites are divided by ‘best’, ‘good’ and ‘unsuitable’ landfill areas. Best landfill areas represent optimal sites; good landfill areas can be used as back-up candidate sites. Our work offers a siting methodology and provides essential support for decision-makers in the assessment of waste management problems in Beijing and other rapidly developing cities in developing countries.     

Convergence or divergence in desertification risk? Scale-based assessment and policy implications in a Mediterranean country

This paper explores changes (1990–2000) in two environmental indexes with the aim of providing empirical evidence on regional and local convergence in an increasing-impact phenomenon such as Land Degradation (LD) in Italy. Convergence analysis for ESAI (Environmental Sensitive Area Index) and LVI (Land Vulnerability Index) was developed at five different geographical scales. Results indicate that territorial disparities in land vulnerability tend to increase during the investigated period following a defined spatial pattern that depends on land quality, the environmental context and the economic performance of regional systems. Finally, the implications this process has on policy strategies aimed at mitigating desertification risk are discussed.     

Evolution Rules of Urban-rural Development and Inspiration for China’s Agriculture

Based on urban-rural contrast coefficient,this article designs the agriculture relative development index(ARDI) as indicators measuring the intensity of urban-rural dual structure which is comparable among the countries of the world.This article calculates ARDI of 40 countries from 1980 to 2004.The result shows that ARDI in the developed countries and most of the middle-income countries are rising and yet there are declines in most of the low-income countries.The result also showed that most countries’ ARDI...     

利用中巴地球资源卫星数据反演武汉市湖泊营养状态指数

以武汉市主要湖泊为例,研究了利用中巴地球资源卫星（CBERS2）数据反演水体营养状态指数（TLI）。研究旨在评估利用中巴地球资源卫星数据来估算内陆水体富营养化程度的可能性。首先利用地面水质监测数据计算武汉市某些湖泊监测点的“真实的”营养状态指数（包括综合营养状态指数和修正的Carlson营养状态指数）,同时,在事先经过辐射校正和几何校正的CBERS2图像上,以9×9像元为采样窗口,提取各个对应地点的灰度值均值（从波段1至波段4）;然后,采用多元逐步回归分析,以各波段灰度值均值为自变量,建立营养状态指数经验遥感反演模型;最后,利用模型对整个湖泊水体的营养化状态指数进行反演,并绘制了其空间分布图。 结果显示,营养状态指数的自然对数值与CBERS2图像各波段灰度值之间存在较好相关关系,回归系数平方值(R²)为0.51。利用反演模型反演得到的湖区水质分布与实际情况基本相符。由于CBERS2图像数据可以从我国许多数据分发中心免费获取,这为低成本的水质遥感监测提供了一条途径。     

Sustainability of silicon feedstock for a low-carbon society

We need to ensure the sustainable management of advanced materials, such as purified silicon, that contribute to a low-carbon society. Because a drastic increase in the demand for photovoltaic (PV) systems is tightening the supply of silicon for PV cells, the sustainability of silicon feedstock needs to be explored. For this purpose, a material flow analysis of silicon in Japan from 1996 to 2006 is presented in this paper. Our analysis finds that rapid growth in demand for polycrystalline silicon (pc-silicon) and single crystalline silicon (sc-silicon) has changed the structure of the purified silicon supply. The strong demand for purified silicon for solar cells is responsible for this change. While off-grade silicon obtained as a by-product of electronic-grade silicon (EG-Si) covered the demand for solar sells before 2000, pc-silicon is currently produced independently for solar cells via an energy-intensive process. Analysis of the resource effective-use index (REI), which indicates how effectively purified silicon is used, shows progress in the effective use of pc- and sc-silicon. REI analysis indicates that the effective use of pc-silicon is reaching a maximum, while the effective use of sc-silicon is advancing, with a corresponding increase in price. To ensure a sustainable supply of silicon feedstock, this paper proposes four solutions: (1) production of solar-grade pc-silicon by a less costly and less energy-consuming method; (2) reduction in the amount of crystalline silicon per watt in solar cells; (3) acceleration of the development and deployment of other solar cell types; and (4) reuse and recycling of solar cells in the future.     

Octanol–air partition coefficients of polybrominated biphenyls

The octanol–air partition coefficients (K_OA) for PBB15, PBB26, PBB31, PBB49, PBB103 and PBB153 were determined as a function of temperature using a gas chromatographic retention time technique with 1,1,1-trichloro-2,2-bis (4-chlorophenyl) ethane (p,p′-DDT) as a reference substance. The internal energies of phase change from octanol to air (Δ_OAU) were calculated for the six compounds and were in the range from 74 to 116 kJ mol⁻¹. Simple regression equations of log K_OA versus relative retention times (RRTs) on gas chromatography (GC), and log K_OA versus molecular connectivity indexes (MCI) were obtained, for which the correlation coefficients (r²) were greater than 0.985 at 283.15 K and 298.15 K. Thus the K_OA values of the remaining PBBs can be predicted by using their RRTs and MCI according to these relationships.