Highway safety assessment and improvement through crash prediction by injury severity and vehicle damage using Multivariate Poisson-Lognormal model and Joint Negative Binomial-Generalized Ordered Probit Fractional Split model

Introduction: Predicting crash counts by severity plays a dominant role in identifying roadway sites that experience overrepresented crashes, or an increase in the potential for crashes with higher severity levels. Valid and reliable methodologies for predicting highway accidents by severity are necessary in assessing contributing factors to severe highway crashes, and assisting the practitioners in allocating safety improvement resources. Methods: This paper uses urban and suburban intersection data in Connecticut, along with two sophisticated modeling approaches, i.e. a Multivariate Poisson-Lognormal (MVPLN) model and a Joint Negative Binomial-Generalized Ordered Probit Fractional Split (NB-GOPFS) model to assess the methodological rationality and accuracy by accommodating for the unobserved factors in predicting crash counts by severity level. Furthermore, crash prediction models based on vehicle damage level are estimated using the same two methodologies to supplement the injury severity in estimating crashes by severity when the sample mean of severe injury crashes (e.g., fatal crashes) is very low. Results: The model estimation results highlight the presence of correlations of crash counts among severity levels, as well as the crash counts in total and crash proportions by different severity levels. A comparison of results indicates that injury severity and vehicle damage are highly consistent. Conclusions: Crash severity counts are significantly correlated and should be accommodated in crash prediction models. Practical application: The findings of this research could help select sound and reliable methodologies for predicting highway accidents by injury severity. When crash data samples have challenges associated with the low observed sampling rates for severe injury crashes, this research also confirmed that vehicle damage can be appropriate as an alternative to injury severity in crash prediction by severity.     

Biomonitoring airborne parent and alkylated three-ring PAHs in the Greater Cologne Conurbation II: Regional distribution patterns

The spatial distribution of an important air pollutant class, three-ring polycyclic aromatic hydrocarbons and their derivatives (PAH-3), has been monitored for the Greater Cologne Conurbation (GCC) using pine needle as passive samplers. The GCC comprises one of the most heavily populated, trafficked, and industrialized regions in Germany. Here, 71 locations covering 3600 km² were sampled and, for the first time, isopleths maps constructed to investigate the regional variability in PAH-3 concentration and composition. The highest PAH-3 loads on needles (1000-1500 ng g⁻¹) were detected downwind of three lignite fuelled power plants, followed by Cologne City (600-700 ng g⁻¹) and smaller towns (400-600 ng g⁻¹), whereas rural and forest regions yielded PAH-3 loads of 60-300 ng g⁻¹. PAH-3 ratios facilitated source reconciliation, with high dibenzothiophene versus retene values indicating lignite combustion and high 9/(9 + 1)-methylphenanthrene ratios depicting traffic emissions in inner cities. PAH-3 ratios depended on topography and outlined the heavily industrialized Rhine Valley, demonstrating atmospheric dispersal of PAH-3.     

中国城市人口规模、产业集聚与碳排放

基于2009~2018年中国286个地级市面板数据，构建空间计量模型，从城市人口规模和产业集聚的综合视角探讨对于人均碳排放的影响机制.结果显示：不同城市的人均CO₂排放具有显著的空间溢出效应；城市人口规模和产业集聚与人均CO₂排放之间均呈“倒U型”关系，且影响机制各不相同；产业集聚与城市人口规模在影响碳排放上具有协同效应；中国东中西地区及南北地区在碳排放及其影响机制上具有显著差异；地区差异、经济发展程度差异等一系列稳健性检验均验证了上述结论的可靠性.因此各地政府在制定可持续发展政策时要针对城市人口规模、产业集聚和低碳统筹发展，合理制定人口、产业和节能减排政策.     

Criminal directionality and the structure of urban form

Spatial criminology has three interrelated elements: place, distance, and direction. Though directionality has had theoretical support for many years, very few empirical verifications of this component of crime have emerged. In this article, we investigate the strength of directionality by comparing a simulated randomized dataset and a large incident-based dataset of repeat offenders. We find strong evidence for a strong presence of directionality in criminal spatial decision-making. This aspect of the spatiality of crime must be considered in any attempts to understand the aetiology of crime.     

Effects of interpolation and data resolution on methane emission estimates from rice paddies

Rice paddies are an important source of the greenhouse gas methane (CH₄). Global methane emission estimates are highly uncertain and do not account for effects of interpolation or data resolution errors. This paper determines such scaling effects for the influence of soil properties on calculated CH₄ emissions for the island of Java, Indonesia. The effects of different interpolation techniques, variograms and neighbor optimization were tested for soil properties by cross-validation. Interpolated organic carbon values were not significantly different from the original soil samples, in contrast to interpolated soil iron contents. Interpolation of soil properties coupled to a process-based model on CH₄emissions led to a significant change in distribution of calculated CH₄ emissions, i.e., the variance decreased. Effects of data resolution were examined by interpolating soil properties to derive data at different data resolutions and then calculating CH₄ emissions by applying the process-based model at these resolutions. The soil properties did not differ significantly for different data resolutions, in contrast to calculated CH₄ emissions. These scaling effects were caused by the combination of interpolation and a non-linear model. Real scaling effects may even be larger because small-scale variability was not accounted for. Scaling effects, including those caused by small-scale variability, have to be considered to achieve unbiased and less uncertain global CH₄emissions estimates from rice paddies.     

Spatial and temporal distribution of solute leaching in heterogeneous soils: analysis and application to multisampler lysimeter data

Accurate assessment of the fate of salts, nutrients, and pollutants in natural, heterogeneous soils requires a proper quantification of both spatial and temporal solute spreading during solute movement. The number of experiments with multisampler devices that measure solute leaching as a function of space and time is increasing. The breakthrough curve (BTC) can characterize the temporal aspect of solute leaching, and recently the spatial solute distribution curve (SSDC) was introduced to describe the spatial solute distribution. We combined and extended both concepts to develop a tool for the comprehensive analysis of the full spatio-temporal behavior of solute leaching. The sampling locations are ranked in order of descending amount of total leaching (defined as the cumulative leaching from an individual compartment at the end of the experiment), thus collapsing both spatial axes of the sampling plane into one. The leaching process can then be described by a curved surface that is a function of the single spatial coordinate and time. This leaching surface is scaled to integrate to unity, and termed S can efficiently represent data from multisampler solute transport experiments or simulation results from multidimensional solute transport models. The mathematical relationships between the scaled leaching surface S, the BTC, and the SSDC are established. Any desired characteristic of the leaching process can be derived from S. The analysis was applied to a chloride leaching experiment on a lysimeter with 300 drainage compartments of 25 cm2 each. The sandy soil monolith in the lysimeter exhibited fingered flow in the water-repellent top layer. The observed S demonstrated the absence of a sharp separation between fingers and dry areas, owing to diverging flow in the wettable soil below the fingers. Times-to-peak, maximum solute fluxes, and total leaching varied more in high-leaching than in low-leaching compartments. This suggests a stochastic-convective transport process in the high-flow streamtubes, while convection dispersion is predominant in the low-flow areas. S can be viewed as a bivariate probability density function. Its marginal distributions are the BTC of all sampling locations combined, and the SSDC of cumulative solute leaching at the end of the experiment. The observed S cannot be represented by assuming complete independence between its marginal distributions, indicating that S contains information about the leaching process that cannot be derived from the combination of the BTC and the SSDC.     

基于氨挥发因子方法的中国农田氨排放量估算

农田是氨的主要排放源,估算农田的氨挥发量可以明确其潜在的生态环境风险,为制定农田氨减排策略提供科学依据.通过文献收集,建立了包含867对观测值的中国农田氨挥发数据库,然后以氮肥施用量为自变量,氮肥施用引起的氨排放量为因变量,计算得到体现农业区、作物类型、肥料类型、土壤pH差异的氨挥发因子,采用独立样本进行验证,发现计算得到的氨挥发因子可以无偏地、较为准确地估算中国农田的氨挥发.不同区域、作物和管理措施下的氨挥发因子有显著差异,整体上,由于南方地区年均温和年降雨量均高于北方,导致南方的氨挥发因子高于北方,而碱性土壤的氨挥发因子高于中性和酸性土壤;与单施化肥相比,多数情况下施用有机肥可降低氨挥发因子,使用缓释控释肥或抑制剂可显著降低氨挥发因子;以单施化肥为例,水稻种植的氨挥发因子为9.9%~37.0%,高于蔬菜（2.2%~13.0%）和其他作物（3.3%~8.0%）.2015年中国农田由无机氮肥使用引起的氨排放总量为3.21 Tg,95%置信区间为2.92~3.46 Tg,其中,粮食作物和蔬菜占比最高,分别为66%和20%,豆科作物占比最低（0.8%）.由于气候、土壤、作物类型的差异,氨挥发呈现明显的空间异质性,长江中下游区排放量最高,而青藏区排放量最低.     

三峡水库干流沉积物及消落带土壤磷形态及其分布特征

三峡水库完全运行后,水文节律发生了变化(水位在145~175 m波动),沉积物和消落带土壤磷的空间分布也有可能发生变化.2016年6月采集了11个样点的沉积物及消落带样品,利用沉积物中磷形态的标准测试程序(SMT),对比研究了三峡水库干流表层沉积物及消落带土壤磷形态,分析了磷形态特征及其在横向(沉积物和消落带土壤)和纵向(回水区末端至三峡大坝)的空间分布特征.结果表明,三峡水库回水区末端至三峡坝前,干流沉积物样品总磷(TP)、Na OH-P含量呈增加趋势,HCl-P呈下降趋势,而消落带土壤磷的各形态含量纵向变化规律不明显.沉积物TP、有机磷(OP)、HCl-P和NaOHP均值依次为(859.6±106.8)、(224.6±113.9)、(435.3±77.7)和(101.5±31.6)mg·kg~(-1),均高于消落带土壤含量均值.HCl-P为沉积物和消落带土壤磷的主要形态,占TP的质量分数分别为51.3%和58.2%,Na OH-P占TP的质量分数分别为11.7%和8.1%.与沉积物相比,消落带土壤各形态磷含量变异系数高,具有较高的空间异质性.     

北港河流域水质特征及主要污染物通量估算研究

通过对北港河进行水文水质同步监测,采用多元统计法对26个采样点位10个监测指标进行分析,识别出流域水环境污染特征及主要影响因素,并进一步估算了主要污染物的通量,以期为有限资料条件下的河流污染治理提供依据.结果表明:北港河水系污染严重,主要污染物为氮、磷及有机污染物;表征生活污水、面源污染与畜禽养殖废水对水质影响的主成分的贡献率为47.95%,表征工业污染的主成分的贡献率为12.50%;重污染企业数、人口密度、建设用地占比与流域氮、耗氧有机物具有显著正相关性,表明重污染企业数、人口密度与建成区分布是影响水质的最重要指标;按污染轻重,可将流域划分为3类分区:上游轻污染区、谷饶溪及东寮坑重污染区、其他区域则为中度污染区.污染物通量变化趋势分析显示,COD_(Cr)、NH_4~+-N通量变化趋势基本与流量变化趋势一致,而TP通量则受上游点源排放影响出现一定差异性.通量变化趋势主要受水闸调度影响呈现开闸大幅度上升、闭闸大幅度下降的规律,在闭闸初期则受练江干流高水位顶托作用影响,流量及污染物通量为负值,练江干流水倒灌入北港河;此外,监测期间COD_(Cr)、NH_4~+-N最高日污染通量出现在第2次开闸期间,分别为39.23、4.98 t·d~(-1),TP最高日污染通量则出现在第1次开闸期间,为547.36 kg·d~(-1).污染通量贡献率分析表明,干流水质主要受谷饶溪及东寮坑影响,其中,谷饶溪COD_(Cr)、NH_4~+-N、TP污染贡献率分别达到了64%、47%、22%,东寮坑COD_(Cr)、NH_4~+-N、TP的贡献率则分别为26%、28%、25%,建议加强对该汇水区内生活污水、工业废水等点源污染控制.     

Forest and Farmland Conservation Effects of Oregon’s (USA) Land-Use Planning Program

Oregons land-use planning program is often cited as an exemplary approach to forest and farmland conservation, but analyses of its effectiveness are limited. This article examines Oregons land-use planning program using detailed spatial data describing building densities in western Oregon. An empirical model describes changes in building densities on forest and agricultural lands from 1974 to 1994, as a function of a gravity index of lands commuting distance to cities of various sizes, topographic characteristics, and zoning adopted under Oregons land-use planning program. The effectiveness of Oregons land-use planning program is evaluated based on the statistical significance of zoning variables and by computing estimated areas of forest and agricultural lands falling into undeveloped, low-density developed, and developed building density categories, with and without land-use zoning in effect. Results suggest that Oregons land-use planning program has provided a measurable degree of protection to forest and agricultural lands since its implementation.