基于产业链的区域环境污染物排放的产业贡献

区域经济增长与环境质量之间的关系研究是目前学者们探讨的重要学术议题之一.其中较多的是对EKC曲线的验证,近几年部分学者从国民经济各部门中的产业自身特征、产业结构、技术进步、FDI效应等方面考察产业发展对污染物排放的影响.然而以上研究议题中学者均没有讨论污染物的发生主体-各产业部门与排污的直接关系.故本文将从宏观尺度下的综合水平测度区域经济发展与环境质量关系、中观尺度下的产业属性特征与排污关系的研究视角转移至分析具体产业部门的污染物排放效应,同时将产业置于产业链的结构形式中,研究产业链上产业发展与污染物排放的关系.发现:第一,通过借助复杂网络思想的社区划分方法,将山东省39个产业部门分为3个社团.其中社团I主要由制造业部门组成,共有18个产业部门,社团II包括了15个部门,主要是第三产业,杜团III由6个产业部门组成且内部异质性高.第二,选择其中以制造业为主的社团I,并在社团I内识别出一条彼此间联系最为紧密的产业链,包括农林牧渔业、食品制造及烟草加工业、化学工业、纺织工业、服装皮革羽绒及其制品业、通用/专用设备制造业和交通运输设备制造业.以一种定量的方法获取了通过价值流传递而串在一起的产业链条.该产业链的经济规模、污染物规模在山东省均有重要地位.第三,采用岭回归分析方法,构建了6个制造业与产业链工业废水、固体废弃物排放的关系模型,6个制造业中对工业废水、固体废弃物排放相对贡献度最大的部门分别为服装皮革羽绒及其制品业、食品制造及烟草加工业.这是由于上游产业排污的链式传递效应与产业自身污染物排放效应的共同叠加作用.     

Survivor needs or logistical convenience? Factors shaping decisions to deliver relief to earthquake‐affected communities,Pakistan 2005–06

In Bureaucratizing the Good Samaritan , Waters (2001) argues that bureaucratic rationality distracts humanitarian agencies from the needs of the people they are supposed to assist, in favour of other values that their institutional frameworks dictate. We test his claim by investigating the response to the Pakistan 2005 earthquake. One of us (Dittemore) worked with the United Nations Joint Logistics Centre in the theatre, managing a relief cargo shipment database. The response, known as 'Operation Winter Race', was hampered by extreme logistical challenges, but ultimately succeeded in averting a second disaster resulting from cold and starvation. We use statistical models to probe whether survivor needs significantly guided decisions to deliver relief to affected communities. Needs assessments remained incomplete and incoherent. We measure needs through proxy indicators and integrate them, on a Geographic Information System (GIS) platform, with logistics and relief delivery data. We find that, despite strong logistics effects, needs orientations were significant. However, the strength of decision factors varies between commodity types (food versus clothing and shelter versus reconstruction materials) as well as over the different phases of the response. This study confirms Thomas's observation that logistics databases are rich 'repositories of data that can be analyzed to provide post-event learning' (Thomas, 2003, p. 4). This article is an invitation for others to engage in creative humanitarian data management.     

基于社会科学统计程序(SPSS)回归性分析的尾矿库事故预测模型

基于社会科学统计程序(SPSS)软件的分析功能,对调查研究中获取的尾矿库案例进行数据提炼和分类编码,找出相关因子并进行回归性分析。最终目的是找出尾矿库各个因素的内在联系,建立简单的尾矿库事故模型,从而可以初步预测尾矿库事故发生的可能性。该预测模型为尾矿库事故的研究提出了新方法,对于防灾减灾以及保护人民生命财产安全起到了积极作用。     

Modelling vegetation greenness responses to climate variability in a Mediterranean terrestrial ecosystem

Accurate knowledge of the quality and environmental impact of the highway runoff in Pear River Delta, South China is required to assess this important non-point pollution source. This paper presents the quality characterization and environmental impact assessment of rainfall runoff from highways in urban and rural area of Guangzhou, the largest city of Pear River Delta over 1 year’s investigation. Multiple regression and Pearson correlation analysis were used to determine influence of the rainfall characteristics on water quality and correlations among the constituents in highway runoff. The results and analysis indicates that the runoff water is nearly neutral with low biodegradability. Oil and grease (O&G), suspended solids (SS) and heavy metals are the dominant pollutants in contrast to the low level of nutrient constituents in runoff. Quality of highway runoff at rural site is better than that of at urban site for most constituents. Depth and antecedent dry period are the main rainfall factors influencing quality of highway runoff. The correlation patterns among constituents in highway runoff at urban site are consistent with their dominant phases in water. Strong correlations (r ≥ 0.80) are found among chemical oxygen demand (COD), total phosphorus, Cu and Zn as well as conductivity, nitrate nitrogen and total nitrogen. O&G, COD, SS and Pb in highway runoff at urban site substantially exceed their concentrations in receiving water of Pear River. The soil directly discharged by highway runoff at rural site has contaminated seriously by heavy metals in surface layer accompanying with pH conversion from original acidic to alkaline at present.     

Estimation of Nonpoint Source Nitrate Concentrations in Indiana Rivers Based on Agricultural Drainage in the Watershed

Subsurface tile‐drained agricultural fields are known to be important contributors to nitrate in surface water in the Midwest, but the effect of these fields on nitrate at the watershed scale is difficult to quantify. Data for 25 watersheds monitored by the Indiana Department of Environmental Management and located near a U.S. Geological Survey stream gage were used to investigate the relationship between flow‐weighted mean concentration (FWMC) of nitrate‐N and the subsurface tile‐drained area (DA) of the watershed. The tile DA was estimated from soil drainage class, land use, and slope. Nitrate loads from point sources were estimated based on reported flows of major permitted facilities with mean nitrate‐N concentrations from published sources. Linear regression models exhibited a statistically significant relationship between annual/monthly nonpoint source (NPS) nitrate‐N and DA percentage. The annual model explained 71% of the variation in FWMC of nitrate‐N. The annual and monthly models were tested in 10 additional watersheds, most with absolute errors within 1 mg/l in the predicted FWMC. These models can be used to estimate NPS nitrate for unmonitored watersheds in similar areas, especially for drained agricultural areas where model performance was strongest, and to predict the nitrate reduction when various tile drainage management techniques are employed.     

区域环境--经济协调发展定量分析方法研究

本文对目前常用的环境与经济协调发展分析方法的优劣和特点进行了具体分析，指出现在常用的进行可持续发展水平定量分析的层次分析法存在明显的缺陷，以及现有的几种评价环境与经济之间协调程度的方法的局限性。提出了较为客观实用的评估方法，即依据系统分析和数理统计的原理利用主成分分析进行环境——经济协调度分析，并对环境——经济协调度定量评估的步骤、方法包括测算方法的选择、数学模型的建构进行深入的探讨和研究，以南阳市为例对该方法进行了验证。     

ANALYZING CORRELATIONS BETWEEN STREAM AND WATERSHED ATTRIBUTES1

ABSTRACT: Bivariate correlation analysis has been widely used to explore relationships between stream and watershed attributes that have all been measured on the same set of watersheds or sampling locations. Researchers routinely test H₀: ρ= 0 for each correlation in a large table and then go on to discuss only those that are declared “significant.” Such test results are inaccurate because no allowance is made for multiple testing, and also because the tests are not mutually independent. This paper reviews the Bonferroni approach to controlling the overall error rate in multiple testing and shows how the approach becomes impractical for large correlation tables. The Hotelling/Williams test is introduced for comparing two dependent correlations that share a variable, and numerical constraints for two such correlations are illustrated. References are also given for testing other hypothesized patterns among dependent correlations, and links to dependent correlation software are provided. The methods are illustrated for watershed and stream variables sampled in 23 small agricultural watersheds of the Willamette Valley, Oregon.     

For what it's worth: evaluating revealed preferences for green certification

In a case study that examines the outcomes of a flexible information-based policy, we observe how organizations obtain Leadership in Energy and Environmental Design certification. We use a regression discontinuity analysis to identify practices used to upgrade certification tiers. This analysis reveals preferences for green certification strategies and, we argue, intimates the perceived motivations for green certification. We distinguish practices that potentially confer private gains through returns to efficiency and productivity investments, from practices that only provide public benefits. Data show that organizations strategically certify to avoid high-cost resource use, appeal to key stakeholders, and communicate building and organization quality. Builders upgrading to the highest tiers are more likely to deploy practices with private gains. Results suggest a willingness to extend short time horizons associated with energy-efficiency investments in exchange for marketing benefits. Our discussion notes the capacity for certifications to mitigate market barriers associated with the energy-efficiency gap.     

我国区域空气污染治理效率及其影响机制——基于超效率SBM模型和门槛回归模型

随着人民对美好生活需求的日益增长,政府空气污染治理的效率问题日益得到重视。本文从地方政府空气污染治理效率及其影响因素的视角入手,以全国30个省份为研究对象,运用超效率SBM模型测算2003—2015年各省级区域的空气污染治理效率。在此基础上,运用门槛回归模型分析政府空气污染治理效率的影响机制。研究表明:①地区间空气污染治理效率差异性较为显著。中部、西部空气污染治理效率整体呈下降趋势。东部和东北地区空气污染治理效率则上升比较平稳。②政策规划、碳源、污染物排放和环境治理投入表现出双重门槛特征,其中碳源对空气污染治理效率影响显著,而以碳为首的能源消费结构则主要对中部和西部空气污染治理效率产生影响。落后地区政府应注重产业升级,财政上应对碳税等税目进行征收,产业上应鼓励企业创新,并对落后企业进行倒逼升级。     

Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.