黑龙江省农村垃圾现状分析及对策

黑龙江省作为中国东北方的农业大省,农村所占比例较大。随着农村经济的快速增长,所产生的垃圾也逐年增多,加之基础设施建设薄弱,缺乏成熟的垃圾处理技术,农村的垃圾问题已经成为我省"农村环境连片整治"必须要解决的一个重点问题。     

火电行业清洁生产评价与体会

研究并分析了火电行业清洁生产评价方法及指标体系,通过工程实例,探讨如何运用清洁生产指标体系,并对其存在的不足及评价过程中可能产生的问题,提出见解和建议。     

县级城市人居环境主客观指标体系与评价模型对比研究

本文对人居环境相关研究进行了阐述,并就城市人居环境指标体系与评价模型进行了分析研究。提出了人居环境质量主客观评价结合模型,其中指标体系包括四个一级指标和18个单项指标,并依据我国黄河三角洲高效经济区内14个县级城市2007年的调查统计资料,对人居环境客观建设水平和居民满意度进行了对比评价。运用因子分析法处理指标数据,问卷调查的方法进行满意度评价。评价结果科学可行,并揭示出影响县级城市人居环境的根本因素。     

国内首个MW级分布式能源系统烟囱合理性分析

介绍了分布式能源系统的构成、运行特点及技术发展情况,研究了国内首个MW级分布式供能系统工程的烟囱高度和形式,预测和分析了项目大气污染物对环境的影响,证明了该项目烟囱选择的合理性,为下阶段国内分布式能源系统烟囱选型奠定技术基础。     

Comparative analysis of data reduction techniques for questionnaire validation using self-reported driver behaviors

Introduction: Exploratory data reduction techniques, such as Factor Analysis (FA) and Principal Component Analysis (PCA), are widely used in questionnaire validation with ordinal data, such as Likert Scale data, even though both techniques are indicated to metric measures. In this context, this study presents an e-survey, conducted to obtain self-reported behaviors between Brazilian drivers (N = 1,354, 55.2% of males) and Portuguese drivers (N = 348, 46.6% of males) based on 20 items from the Driver Behavior Questionnaire (DBQ) on a five-point Likert Scale. This paper aimed to examine DBQ validation using FA and PCA compared to Categorical Principal Component Analysis (CATPCA) which is more indicative to use with Likert Scale data. Results: The results from all techniques confirmed the most replicated factor structure of DBQ, distinguishing behaviors as errors, ordinary violations, and aggressive violation. However, after Varimax rotation, CATPCA explained 11% more variance compared to FA and 2% more than PCA. We identified cross-loadings among the component of the techniques. An item changed its dimension in the CATPCA results but did not change the structural interpretability. Individual scores from dimension 1 of CATPCA were significantly different from FA and PCA. Individual scores from factor 1 of CATPCA were significantly different from FA and PCA. Practical applications: The CATPCA seems to be more advantageous in order to represent the original data and considering data constrains. In addition to finding an interpretable factorial structure, the representation of the original data is regarded as relevant since the factor scores could be used for crash prediction in future analyses.     

地表水环境遥感监测关键技术与系统

本文主要是围绕地表水环境遥感检测展开讨论,全面介绍了水环境检测的关键技术和系统,建立改进双峰法的水体分布遥感提取方法,并以具体地区为例进行分析,采用不同方法建立解析方法,从根本上提升反演方法的区域和积极适用性,希望能够对相关人员起到参考性价值。     

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.     

Modeling Postfire Response and Recovery using the Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS)1

Abstract: This paper investigates application of the Army Corps of Engineers’ Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS) to a burned watershed in San Bernardino County, California. We evaluate the HEC‐HMS’ ability to simulate discharge in prefire and postfire conditions in a semi arid watershed and the necessary parameterizations for modeling hydrologic response during the immediate, and subsequent recovery, period after a wildfire. The model is applied to City Creek watershed, which was 90% burned during the Old Fire of October 2003. An optimal spatial resolution for the HEC‐HMS model was chosen based on an initial sensitivity analysis of subbasin configurations and related model performance. Five prefire storms were calibrated for the selected model resolution, defining a set of parameters that reasonably simulate prefire conditions. Six postfire storms, two from each of the following rainy (winter) seasons were then selected to simulate postfire response and evaluate relative changes in parameter values and model behavior. There were clear trends in the postfire parameters [initial abstractions (I_a), curve number (CN), and lag time] that reveal significant (and expected) changes in watershed behavior. CN returns to prefire (baseline) values by the end of Year 2, while I_a approaches baseline by the end of the third rainy season. However, lag time remains significantly lower than prefire values throughout the three‐year study period. Our results indicate that recovery of soil conditions and related runoff response is not entirely evidenced by the end of the study period (three rainy seasons postfire). Understanding the evolution of the land surface and related hydrologic properties during the highly dynamic postfire period, and accounting for these changes in model parameterizations, will allow for more accurate and reliable discharge simulations in both the immediate, and subsequent, rainy seasons following fire.     

Using data linkage to assess the impact of motorized recreational vehicle-related injuries in Ohio

Problem

Motorized recreational vehicle (MRV)-related injuries can result in severe medical and financial consequences. The objective of this study was to describe the epidemiology, and clinical and financial impact of MRV-related injuries in Ohio.

Method

Probabilistically linked statewide Emergency Medical Services (EMS) and hospital (inpatient and emergency department) data for 2003 and 2004 were examined. Record pairs with a MRV-related E-code (E821-E823, E825) were included in this study.

Results

There were 2,893 patients with MRV-related injuries, who had linked EMS and hospital records, resulting in more than $15 million in hospital charges and 1,921 inpatient days of hospitalization. The male-to-female ratio was nearly 4:1, and 19% were younger than 16. Almost 82% of cases were not wearing a helmet; there was a trend of decreasing helmet use with increasing age. Mean (SE) inpatient hospital charges and length of stay (LOS) were $22,218 ($1,290) and 3.8 (0.2) days, respectively. The mean (SE) Injury Severity Score (ISS) for inpatients was 9.2 (0.4). Individuals injured on a street/highway were 3.20 times more likely to sustain an ISS ≥ 16 (95% CI: 1.03, 9.88; p = 0.044) and 3.05 times more likely to sustain a traumatic brain injury (TBI) (95% CI: 1.17, 7.94; p = 0.024) than those who were injured at a place designated for sport or recreation. Children aged 12 to 15 and young adults aged 16 to 25 were 2.47 and 2.14 times more likely, respectively, to sustain a TBI than adults aged 36 or older (aged 12 to 15: 95% CI: 1.13, 5.38; p = 0.024; aged 16 to 25: 95% CI: 1.26, 3.64; p = 0.005). Higher ISS was associated with both higher total charges (p < 0.001) and longer LOS (p < 0.001).

Discussion

This study demonstrates that MRV-related injuries are an important public health problem in Ohio, with a substantial clinical and financial impact.

Impact on Industry

Enactment and enforcement of statewide MRV safety legislation and training of MRV users offer valuable opportunities to prevent these costly injuries.     

CO2 emission driving forces and corresponding mitigation strategies under low-carbon economy mode: evidence from China’s Beijing–Tianjin–Hebei region

On account of the background of China’s “new normal” characterized by slower economic growth, this paper analyses the low-carbon economy status quo in the Beijing–Tianjin–Hebei region and empirically investigates the relationship between carbon dioxide (CO₂) emissions and its various factors for China’s Beijing–Tianjin–Hebei region using panel data econometric technique. We find evidence of existence of Environmental Kuznets Curve. Results also show that economic scale, industrial structure, and urbanization rate are crucial factors to promote CO₂ emissions. However, technological progress, especially the domestic independent research and development, plays a key role in CO₂ emissions abatement. Next, we further analyze the correlation between each subregion and various factors according to Grey Relation Analysis. Thereby, our findings provide important implications for policymakers in air pollution control and CO₂ emissions reduction for this region.