基于面板数据的土地投入对经济增长的影响-以浙江省为例

采用生产函数与面板数据回归模型相结合的研究手段,以地处经济发达地区的浙江省为实证研究区域对土地要素投入对经济增长的影响进行了定量的研究。研究结果表明：(1)就规模效应而言,浙江省的经济增长处于规模报酬不变的发展阶段;(2)浙江省经济增长对劳动力要素的投入最为敏感,其中土地要素、劳动力要素和资本要素增加1个单位的投入量对经济增长的推动为 0.247 3、0.538 5 和 0.321 6;（3）固定资产投入在研究期间是浙江省经济增长的主要推动力,其贡献率达到6823%,而劳动力要素与土地要素则分别为2346%和625%;(4)浙江省土地利用不够集约,在研究期间土地要素对经济增长的影响能被资本要素与劳动力要素有效替代,而劳动力要素则难以被资本投入与土地投入有效替代,劳动集约型产业应该成为浙江省未来发展方向之一。     

A new direct thermal desorption-GC/MS method: Organic speciation of ambient particulate matter collected in Golden, BC

Particulate matter having an aerodynamic diameter less than 2.5 μm (PM2.5) is thought to be implicated in a number of medical conditions, including cancer, rheumatoid arthritis, heart attack, and aging. However, very little chemical speciation data is available for the organic fraction of ambient aerosols. A new direct thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS) method was developed for the analysis of the organic fraction of PM2.5. Samples were collected in Golden, British Columbia, over a 15-month period. n-Alkanes constituted 33–98% by mass of the organic compounds identified. PAHs accounted for 1–65% and biomarkers (hopanes and steranes) 1–8% of the organic mass. Annual mean concentrations were: n-alkanes (0.07–1.55 ng m⁻³), 16 PAHs (0.02–1.83 ng m⁻³), and biomarkers (0.02–0.18 ng m⁻³). Daily levels of these organics were 4.89–74.38 ng m⁻³, 0.27–100.24 ng m⁻³, 0.14–4.39 ng m⁻³, respectively. Ratios of organic carbon to elemental carbon (OC/EC) and trends over time were similar to those observed for PM2.5. There was no clear seasonal variation in the distribution of petroleum biomarkers, but elevated levels of other organic species were observed during the winter. Strong correlations between PAHs and EC, and between petroleum biomarkers and EC, suggest a common emission source – most likely motor vehicles and space heating.     

Health benefits valuation of regulatory intervention for air pollution control in thermal power plants in Delhi,India

This study estimates minimum marginal health benefits (morbidity reduction only) of air pollution control and total health benefits arising from regulatory intervention regarding the adoption of the World Bank emission guidelines (WBEG) for thermal power plants (TPPs) in Delhi. The Industrial Source Complex-Short-Term Version–3 (ISCST3) model has been used to estimate the contribution to air pollution from TPPs. The household health production function (avertive behaviour) has been used to value health benefits of air pollution control. The study revealed that the ambient air pollution due to TPPs is reduced by between 62.17% to 83.45% by adopting the WBEG. Annual marginal benefit due to reduction in exposure to air pollution by 1 μg m^?3 is estimated to be US$0.353 per person. Total annual health benefits for adopting the WBEG for TPPs are estimated at US$235.19 million. This study provides a novel methodology to evaluate health benefits of regulatory intervention.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

复杂社会技术系统安全事故的成因结构敏感性及预防对策研究

简要回顾现有复杂社会技术系统安全事故的成因理论存在的局限性,根据大量统计资料和经验总结构建事故成因理论的缺陷。该研究试图从分析和推理入手,根据复杂社会技术系统运行机制及事故成因结构敏感性特征,探索由于新技术快速普及应用而不断涌现的复杂社会技术系统的失效机制及事故的成因理论;解释复杂社会技术系统安全事故的严重程度差异性、时间方向性及情境依赖性;为任何因新技术普及应用而产生的人造系统的安全分析及事故预防提供理论和方法支撑。     

Spatial modelling of the probability of obtaining a detectable concentration of ammonia in Moreton Bay, Australia

Ammonia is an important water quality variable, which in excess, can be detrimental to waterways and their ecosystems. In the Ecosystem Health Monitoring Program in South-east Queensland ammonia is monitored monthly, however, often more than 50% of the ammonia observations in Moreton Bay are below detection limit, making it difficult to draw useful inferences. In this paper a clipped Gaussian random field is used to spatially model and map the probability of detectable concentration of ammonia. The methodology is applied to the Moreton Bay samples collected in February 2005. The results suggest that for this month the oceanic impacted areas have higher probability of detectable ammonia concentration than the areas closer to the main sources of anthropogenic inputs.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

浅淡监测数据的共享与社会效应

结合工作实际对如何有效利用监测数据进行了探讨 ,并引申出监测数据的 4种效应 ,即信息效应、价值效应、广告效应和政治效应。     

煤的低温氧化实验研究及红外光谱分析

对不同温度下的氧化煤样通过红外光谱分析其微观结构及特征,得到煤样在不同低温氧化阶段的基团变化,从微观角度掌握煤样氧化过程的变化规律.通过对唐口煤矿1302工作面煤样的低温氧化和红外光谱分析,得到唐口煤矿煤样在低温氧化阶段的自燃倾向性和氧化过程中微观结构的变化规律,该成果为制定矿井内火灾的防治技术提供了科学依据.     

四川省空气自动监测数据采集系统建设

介绍了四川省空气质量监测工作的现状和存在的问题,提出了建设四川省空气自动监测数据采集系统的技术路线,建设完成了全省空气监测数据的统一采集。