基于AIS轨迹修复的船舶排放空间表征改进方法与应用

基于船舶自动识别系统（Automatic Identification System,AIS）数据表征船舶排放是目前船舶排放空间表征的主流方法,但AIS船舶轨迹点缺失会造成船舶排放量低估和船舶空间分布表征错误,进而影响船舶排放控制区的划分.为改进船舶排放空间表征,本研究以2013年广东省AIS船舶数据为例,采用基于时间和经纬度的三次样条方法对AIS船舶轨迹进行修复,结合动力法计算船舶排放,分析对比AIS轨迹修复前后船舶排放表征的差异,并利用空气质量模型和卫星观测评估AIS轨迹修复对船舶排放表征和广东沿海空气质量模拟的改进效果.结果表明：轨迹修复后广东省海域船舶轨迹点总数由4685773个增至5746664个,船舶NO_x排放量增加了0.6%.对于轨迹点与排放缺失集中的粤东海域,轨迹修复后船舶轨迹点数增加了88%,NO_x排放量在广东省船舶排放量的占比提升至22%,特别是在粤东重点修复海域NO_x排放量增加了2.7倍.原始轨迹在广东省海域较为稀疏,在粤东海域有明显轨迹缺失;轨迹修复后广东省海域船舶轨迹更为密集,粤东海域船舶轨迹得以补充,船舶排放空间分布更连贯.对比模拟结果与卫星观测结果,轨迹修复后粤东重点修复海域船舶模拟浓度与观测浓度的偏差由51%减至6%,总体上船舶排放模拟结果更接近卫星观测结果.     

New Methodology for an Expert-Designed Map From International Classification of Diseases (ICD) to Abbreviated Injury Scale (AIS) 3+ Severity Injury

Objective: There has been a longstanding desire for a map to convert International Classification of Diseases (ICD) injury codes to Abbreviated Injury Scale (AIS) codes to reflect the severity of those diagnoses. The Association for the Advancement of Automotive Medicine (AAAM) was tasked by European Union representatives to create a categorical map classifying diagnoses codes as serious injury (Abbreviated Injury Scale [AIS] 3+), minor/moderate injury (AIS 1/2), or indeterminate. This study's objective was to map injury-related ICD-9-CM (clinical modification) and ICD-10-CM codes to these severity categories.

Methods: Approximately 19,000 ICD codes were mapped, including injuries from the following categories: amputations, blood vessel injury, burns, crushing injury, dislocations/sprains/strains, foreign body, fractures, internal organ, nerve/spinal cord injury, intracranial, laceration, open wounds, and superficial injury/contusion. Two parallel activities were completed to create the maps: (1) An in-person expert panel and (2) an electronic survey. The panel consisted of expert users of AIS and ICD from North America, the United Kingdom, and Australia. The panel met in person for 5 days, with follow-up virtual meetings to create and revise the maps. Additional qualitative data were documented to resolve potential discrepancies in mapping. The electronic survey was completed by 95 injury coding professionals from North America, Spain, Australia, and New Zealand over 12 weeks. ICD-to-AIS maps were created for: ICD-9-CM and ICD-10-CM. Both maps indicated whether the corresponding AIS 2005/Update 2008 severity score for each ICD code was AIS 3+, 1/2, or indeterminable. Though some ICD codes could be mapped to multiple AIS codes, the maximum severity of all potentially mapped injuries determined the final severity categorization.

Results: The in-person panel consisted of 13 experts, with 11 Certified AIS specialists (CAISS) with a median of 8 years and an average of 15 years of coding experience. Consensus was reached for AIS severity categorization for all injury-related ICD codes. There were 95 survey respondents, with a median of 8 years of injury coding experience. Approximately 15 survey responses were collected per ICD code. Results from the 2 activities were compared, and any discrepancies were resolved using additional qualitative and quantitative data from the in-person panel and survey results, respectively.

Conclusions: Robust maps of ICD-9-CM and ICD-10-CM injury codes to AIS severity categories (3+ versus <3) were successfully created from an in-person panel discussion and electronic survey. These maps provide a link between the common ICD diagnostic lexicons and the AIS severity coding system and are of value to injury researchers, public health scientists, and epidemiologists using large databases without available AIS coding.     

Injuries in Full-Scale Vehicle Side Impact Moving Deformable Barrier and Pole Tests Using Postmortem Human Subjects

Objective: To conduct near-side moving deformable barrier (MDB) and pole tests with postmortem human subjects (PMHS) in full-scale modern vehicles, document and score injuries, and examine the potential for angled chest loading in these tests to serve as a data set for dummy biofidelity evaluations and computational modeling.

Methods: Two PMHS (outboard left front and rear seat occupants) for MDB and one PMHS (outboard left front seat occupant) for pole tests were used. Both tests used sedan-type vehicles from same manufacturer with side airbags. Pretest x-ray and computed tomography (CT) images were obtained. Three-point belt-restrained surrogates were positioned in respective outboard seats. Accelerometers were secured to T1, T6, and T12 spines; sternum and pelvis; seat tracks; floor; center of gravity; and MDB. Load cells were used on the pole. Biomechanical data were gathered at 20 kHz. Outboard and inboard high-speed cameras were used for kinematics. X-rays and CT images were taken and autopsy was done following the test. The Abbreviated Injury Scale (AIS) 2005 scoring scheme was used to score injuries.

Results: MDB test: male (front seat) and female (rear seat) PMHS occupant demographics: 52 and 57 years, 177 and 166 cm stature, 78 and 65 kg total body mass. Demographics of the PMHS occupant in the pole test: male, 26 years, 179 cm stature, and 84 kg total body mass. Front seat PMHS in MDB test: 6 near-side rib fractures (AIS = 3): 160–265 mm vertically from suprasternal notch and 40–80 mm circumferentially from center of sternum. Left rear seat PMHS responded with multiple bilateral rib fractures: 9 on the near side and 5 on the contralateral side (AIS = 3). One rib fractured twice. On the near and contralateral sides, fractures were 30–210 and 20–105 mm vertically from the suprasternal notch and 90–200 and 55–135 mm circumferentially from the center of sternum. A fracture of the left intertrochanteric crest occurred (AIS = 3). Pole test PMHS had one near-side third rib fracture. Thoracic accelerations of the 2 occupants were different in the MDB test. Though both occupants sustained positive and negative x-accelerations to the sternum, peak magnitudes and relative changes were greater for the rear than the front seat occupant. Magnitudes of the thoracic and sternum accelerations were lower in the pole test.

Conclusions: This is the first study to use PMHS occupants in MDB and pole tests in the same recent model year vehicles with side airbag and head curtain restraints. Injuries to the unilateral thorax for the front seat PMHS in contrast to the bilateral thorax and hip for the rear seat occupant in the MDB test indicate the effects of impact on the seating location and restraint system. Posterolateral locations of fractures to the front seat PMHS are attributed to constrained kinematics of occupant interaction with torso side airbag restraint system. Angled loading to the rear seat occupant from coupled sagittal and coronal accelerations of the sternum representing anterior thorax loading contributed to bilateral fractures. Inward bending initiated by the distal femur complex resulting in adduction of ipsilateral lower extremity resulted in intertrochanteric fracture to the rear seat occupant. These results serve as a data set for evaluating the biofidelity of the WorldSID and federalized side impact dummies and assist in validating human body computational models, which are increasingly used in crashworthiness studies.     

结合在线监测和自动识别系统分析东海沿岸船舶排放特征

海运排放大气污染物对空气质量和气候具有重要影响,但是由于船舶类型及其运行工况的复杂性,人们对船舶排放特征的认识仍然不足.东海沿岸是全球航运活动最为密集的地区之一,汇集了各种国内国际运输船只.选取宁波舟山港作为研究地点,使用在线仪器长时间测量主要的环境大气气体和颗粒污染物,并利用自动识别系统（AIS）,获得每种船舶的速度.根据后向轨迹区分出：1受船舶排放影响主导的时期（夏季风,由处于完全运行或停泊的船舶占主导地位）;2受内陆气流影响主导的时期（冬季风）.结果表明二氧化硫（SO₂）、氮氧化物（NO_x）和黑碳气溶胶（BC）的排放与高速运行的船舶相关,而一氧化碳（CO）可能与较低的运行速度的船舶有关,总颗粒物（PM）与船舶速度没有显著相关关系.主要污染物在巡航工况下的排放增强因子约为怠速工况1~4倍.研究通过对直接环境背景下船舶排放进行原位观测,为评估船舶排放清单提供重要参考.     

外部安防系统在海洋石油固定平台中的应用

为了弥补传统的海洋石油固定平台内部安防系统的不足,达到海洋石油固定平台全天候自动监测、自动报警、无人值守、主动防御、预防为主的目的,以便提早发现灾害或事故的苗头,提供及时报警,并采取适当的预防措施。根据主动防御、准确测报、防范未然和规避事故的原则方针,按区域警戒与要地防范相结合的方法,介绍了外部安防系统在海洋石油固定平台中的应用,包括六个子系统、工作流程、各个子系统在海洋石油固定平台中的应用以及特点和价值,从监控、应急、监管等多角度出发,实现了一体化的安全监控。     

一种利用AIS数据计算受限水域内航标安全距离的方法

AIS数据详细记录了特定水域的船舶位置、船首向和尺寸等数据,可用于计算受限水域内航标安全距离。按一定标准网格化目标航标附近水域,统计周围航行的他船船体出现在每一个网格中的频数,形成他船航迹的网格频数图。按长度尺寸分类,将同类他船航迹网格频数图叠加,形成特定类型船舶的航迹网格频数图。按频数大小填充颜色,可清晰地显示航标附近他船安全通行状态下与航标保持的距离。实验选取上海港航标附近水域海量AIS数据,获取了60~79m,80~99m,100~129m,130~159m船舶航迹形成的网格频数图,结果显示,四类船舶距航标的安全距离随着他船长度的增大而增加,分别为50m,70m,110m,150m。     

厦门市船舶控制区大气污染物排放清单与污染特征

以船舶自动识别系统(automatic identification system,AIS)数据,结合大量厦门港口实地调查信息,采用自下而上的动力法对在控制区内航行的船舶进行逐艘计算,得出2018年厦门市船舶控制区大气污染物排放清单,并详细分析了其污染物排放特征及时空分布.结果表明, 2018年厦门市船舶控制区内船舶污染物排放总量共16 413 t,其中进出港船舶污染物排放占82.2%,未进港船舶占17.8%,各污染物中以NO_x的排放量最大,占比达64.2%,不同航行状态下污染物排放量的顺序为停泊巡航低速巡航机动操控锚泊,控制区内船舶的主要污染来源于货船,并以集装箱船的污染物排放量为最大; 1 d中09:00～16:00处于船舶污染物排放高峰期,1 a中以2月的排放量为最低, 3月和5月出现排放峰值;空间特征上各污染物排放高值主要分布于主航道和港区海岸线.     

大连海域远洋船舶排放清单

为准确评估船用柴油机实际排放,利用船舶自动识别系统(automatic identification system,AIS)采集远洋船舶的船速、航行时间、地理位置信息等实时航行数据,采用动力法对2012年大连港远洋船舶的排放清单进行计算. 结果表明:2012年大连港远洋船舶PM₁₀、NO_x、SO_x、CO、HC、CO₂总排放量分别为5 785(包括4 628 t PM_2.5)、51 451、49 437、4 677、2 010及2 885 388 t. 在4种运行工况中系泊工况排放量最大,受船舶类型和污染物种类影响,系泊工况污染物排放所占比例有所不同,但其分担率均在75.0%左右. 船舶排放污染物的空间分析表明,船舶系泊停靠的港口区域是污染物排放最密集的区域. 从船舶类型来看,散货船、集装箱船、邮轮和油轮是污染物主要排放船型,在整个船舶排放清单中,这4类船舶对DPM(柴油机颗粒物)、NO_x、SO_x、CO、CO₂的排放分担率之和分别为90.9%、91.4%、91.9%、91.5%、91.9%. 在船舶的主机、辅机和锅炉3种排放源中,主机是主要排放源,集装箱船和滚装船的主机分担率为90.0%,货船和邮轮的辅机排放分担率达到40.0%.