Chemical contamination of the Hudson-Raritan Estuary as a result of the attack on the World Trade Center: analysis of polycyclic aromatic hydrocarbons and polychlorinated biphenyls in mussels and sediment

The September 11, 2001 attack on the World Trade Center (WTC) resulted in a massive plume of dust and smoke that blanketed lower Manhattan and part of the Hudson-Raritan Estuary (HRE). The NOAA National Status and Trends Mussel Watch Program has long-term monitoring sites in the area and thus had an opportunity to assess the effect of the WTC attack on PAH and PCB contamination of the surrounding estuary. Seven additional sites were added in the Upper HRE to attain higher sampling resolution for comparison with regularly sampled Mussel Watch Project HRE sites. Elevated background levels of PCBs and PAHs in mussel tissue and sediments were high enough before the WTC attack that concentrations were not measurably changed by WTC derived contaminant input.     

Metropolitan-scale Transport and Dispersion from the New York World Trade Center Following September 11, 2001. Part II: An Application of the CALPUFF Plume Model

Following the collapse of the New York World Trade Center (WTC) towers on September 11, 2001, Local, State, and Federal agencies initiated numerous air monitoring activities to better understand the ongoing impacts of emissions from the disaster. The collapse of the World Trade Center towers and associated fires that lasted for several weeks resulted at times in a noticeable plume of material that was dispersed around the Metropolitan New York City (NYC) area. In general, the plume was only noticeable for a short period of time following September 11, and only apparent close to the World Trade Center site. A study of the estimated pathway which the plume of WTC material would likely follow was completed to support the United States Environmental Protection Agency’s 2002 initial exposure assessments. In this study, the WTC emissions were simulated using the CALMET-CALPUFF model in order to examine the general spatial and temporal dispersion patterns over NYC. This paper presents the results of the CALPUFF plume model in terms of plume dilution and location, since the exact source strength remains unknown. Independent observations of PM_2.5 are used to support the general dispersion features calculated by the model. Results indicate that the simulated plume matched well with an abnormal increase (600–1000% of normal) in PM_2.5 two nights after the WTC collapse as the plume rotated north to southeast, towards parts of NYC. Very little if any evidence of the plume signature was noted during a similar flow scenario a week after September 11. This leads to the conclusion that other than areas within a few kilometers from the WTC site, the PM_2.5 plume was not observable over NYC’s background concentration after the first few days.     

Publications received by the Editor

Abstract

Remote sensing is the use of electromagnetic energy to measure the physical properties of distant objects. It includes photography and geophysical surveying as well as newer techniques that use other parts of the electromagnetic spectrum. The history of remote sensing begins with photography. The origin of other types of remote sensing can be traced to World War II, with the development of radar, sonar, and thermal infrared detection systems. Since the 1960s, sensors have been designed to operate in virtually all of the electromagnetic spectrum. Today a wide variety of remote sensing instruments are available for use in hydrological studies; satellite data, such as Skylab photographs and Landsat images are particularly suitable for regional problems and studies. Planned future satellites will provide a ground resolution of 10–80 m.

Remote sensing is currently used for hydrological applications in most countries of the world. The range of applications includes groundwater exploration determination of physical water quality, snowfield mapping, flood-inundation delineation, and making inventories of irrigated land. The use of remote sensing commonly results in considerable hydrological information at minimal cost. This information can be used to speed-up the development of water resources, to improve management practices, and to monitor environmental problems.     

Remote sensing application system for water environments developed for Environment Satellite 1

Remote sensing data collected by the Environment Satellite I are characterized by high temporal resolution, high spectral resolution and mid-high spatial resolution. We designed the Remote Sensing Application System for Water Environments (RSASWE) to create an integrated platform for remote sensing data processing, parameter information extraction and thematic mapping using both remote sensing and GIS technologies. This system provides support for regional water environmental monitoring, and prediction and warning of water pollution. Developed to process and apply data collected by Environment Satellite I, this system has automated procedures including clipping, observation geometry computation, radiometric calibration, 6S atmospheric correction and water quality parameter inversion. RSASWE consists of six subsystems: remote sensing image processing, basic parameter inversion, water environment remote sensing thematic outputs, application outputs, automated water environment outputs and a non-point source pollution monitoring subsystem. At present RSASWE plays an important role in operations at the Satellite Environment Center.     

Identifying and characterizing solution conduits in karst aquifers through geospatial (GIS) analysis of porosity from borehole imagery: An example from the Biscayne aquifer,South Florida (USA)

We apply geospatial analysis to borehole imagery in an effort to develop new techniques to evaluate the spatial distribution and internal structure of karst conduits. Remote sensing software is used to classify a high resolution, digital borehole image of limestone bedrock from the Biscayne aquifer (South Florida, USA) into a binary image divided into cells of rock matrix and pores. Within a GIS, 2D porosity is calculated for a series of rectangular sampling windows placed over the binary image and then plotted as a function of depth. Potential conduits that intersect the borehole are identified as peaks of high porosity. A second GIS technique identifies a conduit as a continuous object that spans the entire borehole width. According to these criteria, geospatial analysis reveals ∼10 discrete conduits along the ∼15 m borehole image. Continuous sampling of the geologic medium intersected by the borehole provides insight into the internal structure of karst aquifers and the evolution of karst features. Most importantly, this pilot study demonstrates that GIS-based techniques are capable of quantifying the depths, dimensions, shapes, apertures and connectivity of potential conduits, physical attributes that impact flow in karst aquifers.     

基于天地图的地震应急地图服务平台初步实现——以上海市为例

基于天地图和ArcGIS API建立一套地震应急地图服务模型平台,初步实现地震应急基础数据展示、地震损失预估范围发布、地震空间信息查询与定位、现场灾情反馈与标注和专题地图打印等功能。该平台以天地图为基础,利用ArcGIS API的多种模块为接口,搭建一套交互式、分布式、动态的系统构架,实现基本地震应急地图数据服务;并力求探索地震应急地图服务的初步方案,解决地震专题地图的效率和传播问题,为震时指挥决策提供辅助支撑手段,为今后多灾种信息平台融合提供了参考。     

Emergency Seismic Damage Assessment of the M_S8.0 Great Wenchuan Earthquake Based on Remote Sensing Imagery

The fast processing, seismic damage data extraction and loss evaluation from RS imagery acquired immediately after a destructive earthquake occurs, are important means for compen-sating the insufficiency of seismic damage information from ground-based investigations and provide an important basis for emergency command and rescue. The paper introduces the method of emergency seismic damage assessment using remote sensing data and its application to the great Wenchuan earthquake of magnitude 8.0 occurring in southwest Sichuan Province on May 12, 2008. The practical effectiveness of the method is also evaluated in the paper.     

Mass fraction spatiotemporal geostatistics and its application to map atmospheric polycyclic aromatic hydrocarbons after 9/11

This work proposes a space/time estimation method for atmospheric PM_2.5 components by modelling the mass fraction at a selection of space/time locations where the component is measured and applying the model to the extensive PM_2.5 monitoring network. The method we developed utilizes the nonlinear Bayesian maximum entropy framework to perform the geostatistical estimation. We implemented this approach using data from nine carcinogenic, particle-bound polycyclic aromatic hydrocarbons (PAHs) measured from archived PM_2.5 samples collected at four locations around the World Trade Center (WTC) from September 22, 2001 to March 27, 2002. The mass fraction model developed at these four sites was used to estimate PAH concentrations at additional PM_2.5 monitors. Even with limited PAH data, a spatial validation showed the application of the mass fraction model reduced the mean squared error (MSE) by 7–22%, while in the temporal validation there was an exponential improvement in MSE positively associated with the number of days of PAH data removed. Our results include space/time maps of atmospheric PAH concentrations in the New York area after 9/11.     

Metropolitan-scale Transport and Dispersion from the New York World Trade Center Following September 11, 2001. Part I: An Evaluation of the CALMET Meteorological Model

Following the collapse of the New York City World Trade Center towers on September 11, 2001, Local, State and Federal agencies initiated numerous air monitoring activities to better understand the impact of emissions from the disaster. A study of the estimated pathway that a potential plume of emissions would likely track was completed to support the U.S. EPA’s initial exposure assessments. The plume from the World Trade Center was estimated using the CALMET-CALPUFF dispersion modeling system. The following is the first of two reports that compares several meteorological models, including the CALMET diagnostic model, the Advanced Regional Prediction System (ARPS) and 5^th Generation Mesoscale Model (MM5) in the complex marine-influenced urban setting of NYC. Results indicate wind speed, in most cases, is greater in CALMET than the two mesoscale models because the CALMET micrometeorological processor does not properly adjust the wind field for surface roughness variations that exits in a major built-up urban area. Small-scale circulations, which were resolved by the mesoscale models, were not well simulated by CALMET. Independent wind observations in Lower Manhattan suggest that the wind direction estimates of CALMET possess a high degree of error because of the urban influence. Wind speed is on average 1.5 ms⁻¹ stronger in CALMET than what observations indicate. The wind direction downwind of the city is rotated 25–34 clockwise in CALMET, relative to what observations indicate.     

Chemical contamination assessment of the Hudson-Raritan Estuary as a result of the attacks on the World Trade Center: analysis of trace elements

The attack on the World Trade Center (WTC) resulted in the destruction of buildings, and the release of tons of dust and debris into the environment. As part of the effort to characterize the environmental impact of the WTC collapse, Mussel Watch Program trace element measurements from the Hudson–Raritan Estuary (HRE) were assessed for the years before (1986–2001) and after (2001–2005) the attack. Trace element measurements in the HRE were significantly higher than Mussel Watch measurements taken elsewhere in the Nation. Post-attack trace element measurements were not significantly different from pre-attack measurements. The impacts of WTC collapse may have been obscured by high ambient levels of trace elements in the HRE.     

大庆油田防震减灾信息管理系统建设

近年来，GIS技术被广泛地应用于城市或区域的防震减灾信息管理系统的建设。本文着重论述了大庆油田有限责任公司防震减灾信息管理系统的建设，以及建成后的系统所包含的主要内容和所能实现的功能。应用GIS技术建设大型企业防震减灾系统是一个新的尝试，所完成的系统不但能对企业在地震应急中起到辅助决策作用，而且对于日常管理也是十分方便的。该系统的运行为大型企业防灾系统的建设提供了思路和借鉴。     

Google Earth在地震应急中的应用

Google Earth是当前非常流行的三维虚拟地球仪软件, 以在全球范围内提供丰富的遥感影像资源而著称, 得到了许多行业的普遍应用。 我国目前地震应急指挥工作的GIS数据还是以二维展示为主, 引入新技术具有重要的意义。 Google Earth在我国的地震应急指挥工作中可以采取如下应用方案: 制作并加载行政区划图, 发布公众地震信息; 与GPS结合, 进行救援路线导航与跟踪; 根据现场资料建立三维模型, 展现地震灾区现场立体场景变化。 该应用方案对我国的地震应急指挥改革具有借鉴意义。     

Analysis and modeling of the seasonal South China Sea temperature cycle using remote sensing

The present paper describes the analysis and modeling of the South China Sea (SCS) temperature cycle on a seasonal scale. It investigates the possibility to model this cycle in a consistent way while not taking into account tidal forcing and associated tidal mixing and exchange. This is motivated by the possibility to significantly increase the model’s computational efficiency when neglecting tides. The goal is to develop a flexible and efficient tool for seasonal scenario analysis and to generate transport boundary forcing for local models. Given the significant spatial extent of the SCS basin and the focus on seasonal time scales, synoptic remote sensing is an ideal tool in this analysis. Remote sensing is used to assess the seasonal temperature cycle to identify the relevant driving forces and is a valuable source of input data for modeling. Model simulations are performed using a three-dimensional baroclinic-reduced depth model, driven by monthly mean sea surface anomaly boundary forcing, monthly mean lateral temperature, and salinity forcing obtained from the World Ocean Atlas 2001 climatology, six hourly meteorological forcing from the European Center for Medium range Weather Forecasting ERA-40 dataset, and remotely sensed sea surface temperature (SST) data. A sensitivity analysis of model forcing and coefficients is performed. The model results are quantitatively assessed against climatological temperature profiles using a goodness-of-fit norm. In the deep regions, the model results are in good agreement with this validation data. In the shallow regions, discrepancies are found. To improve the agreement there, we apply a SST nudging method at the free water surface. This considerably improves the model’s vertical temperature representation in the shallow regions. Based on the model validation against climatological in situ and SST data, we conclude that the seasonal temperature cycle for the deep SCS basin can be represented to a good degree. For shallow regions, the absence of tidal mixing and exchange has a clear impact on the model’s temperature representation. This effect on the large-scale temperature cycle can be compensated to a good degree by SST nudging for diagnostic applications.     

“REMOTE SENSING”— AN EVALUATION OF ITS IMPACT ON EARTH SCIENCE—*

“Remote sensing” techniques have been used for many years as an exploration tool; broadly speaking, any method using sensors not directly connected to the earth's surface falls into this group. It is preferable, however, to use the term solely with reference to a number of new sensors which have recently become available to earth scientists for the detection of various radiations of the electromagnetic spectrum in the wave length range from 0.1 micron (UV) to some centimeters including the visible and infrared regions. Radiations artificially induced in the earth (active sensing) or spontaneous radiations (passive sensing) can be detected. Some of the bands investigated seem promising for application to geological surveys, especially using sensors on aircraft and satellites, which allow synoptic and large scale investigations. A brief account is given of the results already achieved and of future developments such as the ERTS and manned satellite (post Apollo) “earth observation” programmes. The potential role of Europe in the field is discussed. Details are given of some applications of thermal I.R. imagery to geological and vulcanological problems, with special emphasis on the research carried out in Italy.     

利用独立分量分析进行火山灰云遥感检测

火山灰云不但引起全球气候和环境系统的重大变化,而且还会威胁航空安全。热红外遥感技术为检测火山灰云提供了新手段,但是遥感数据自身的冗余和波段相关性大大降低了火山灰云的检测精度。独立分量分析(Independent Component Analysis,ICA)能够实现遥感数据的去相关和消除冗余,在火山灰云检测中具有一定的潜力。通过探索火山灰云的物理、化学性质,文中以2010年4月19日冰岛艾雅法拉(Eyjafjallajokull)火山灰云MODIS图像为数据源,在对MODIS数据进行主成分分析处理的基础上,利用ICA进行火山灰云检测。结果表明:ICA能够较好地从MODIS图像中获取火山灰云信息,所得结果与美国地质调查局标准光谱数据库和火山灰云SO2浓度分布具有较好的一致性,取得了较好的检测效果。     

A PRELIMINARY STUDY ON THE METHOD OF SEISMIC INTENSITY ASSESSMENT BASED ON RESIDENTIAL BUILDING DATA AND HIGH RESOLUTION REMOTE SENSING IMAGES

After destructive earthquakes, the assessment result of seismic intensity is an important decision-making basis for emergency rescue, recovery and reconstruction. This job requires higher timeliness by government and society. Because remote sensing technology is not affected by the terrible traffic conditions on the ground after the earthquake, large-scale seismic damage information in the earthquake area can be collected in a short time by the remote sensing image. The remote sensing technique plays a more and more important role in rapid acquisition of seismic damage information, emergency rescue decision-making, seismic intensity assessment and other work. On the basis of previous studies, this paper proposes a new method to assess seismic intensity by using remote sensing image, i.e. to interpret the building collapse rate of a residential quarter after an earthquake by high-resolution remote sensing images. If there already are detailed building data and building structure vulnerability matrix data of a residential area, we can calculate the building collapse rate under any intensity values in this residential area by using the theory of earthquake damage prediction. Assuming that the building collapse rate interpreted by remote sensing is equal to the building collapse rate predicted by using the existing data, it will be easy to calculate the actual seismic intensity of the residential area in this earthquake event. Based on this idea, according to the relevant standard specifications issued by China Earthquake Administration, this paper puts forward some functional models, such as the calculation model of building collapse rate based on remote sensing, the data matrix model of residential building structure, the prediction function matrix model of residential building collapse rate and the prediction model of residential building collapse rate. A formula for calculating seismic intensity by using remote sensing interpretation of collapse rate is also proposed. To test and verify the proposed method, this paper takes two neighboring blocks of Jiegu Town after the Yushu M7.1 earthquake in Qinghai Province as an example. The building structure matrix of the study block was constructed by using pre-earthquake 0.6m resolution satellite remote sensing image(QuickBird, acquired on November 6, 2004), post-earthquake 0.2m aerial remote sensing image(acquired by National Bureau of Surveying and Mapping, April 15, 2010) and some field investigation data. The building collapse rate in the two blocks was calculated by using the interpretation results of seismic damage from the Remote Sensing Technology Coordinating Group of China Seismological Bureau. The seismic damage matrix of building structures in Yushu area is constructed by using the abundant scientific data of the scientific investigation team of the project “Comprehensive Scientific Investigation of the Yushu M7.1 Earthquake in Qinghai Province” of China Seismological Bureau. On this basis, the collapse rate prediction function of different structures in Yushu area is constructed. According to the prediction function of collapse rate and the building structure matrix of the two blocks, the building collapse rate under different intensity values is predicted, and the curve of intensity-collapse rate function is drawn. By comparing the building collapse rate interpreted by remote sensing and the intensity-collapse rate function curve of this two blocks, the seismic intensity of both blocks are calculated to be the same value: Ⅸ degree, which is consistent with the results of the field scientific investigation of the earthquake. The validation shows that the method proposed in this paper can effectively avoid the influence caused by the difference of seismic performance of buildings and accurately evaluate seismic intensity when using remote sensing technique. The method has certain application value for earthquake emergency work.     

Removing sun glint from optical remote sensing images of shallow rivers

Sun glint is the specular reflection of light from the water surface, which often causes unusually bright pixel values that can dominate fluvial remote sensing imagery and obscure the water‐leaving radiance signal of interest for mapping bathymetry, bottom type, or water column optical characteristics. Although sun glint is ubiquitous in fluvial remote sensing imagery, river‐specific methods for removing sun glint are not yet available. We show that existing sun glint‐removal methods developed for multispectral images of marine shallow water environments over‐correct shallow portions of fluvial remote sensing imagery resulting in regions of unreliable data along channel margins. We build on existing marine glint‐removal methods to develop a river‐specific technique that removes sun glint from shallow areas of the channel without over‐correction by accounting for non‐negligible water‐leaving near‐infrared radiance. This new sun glint‐removal method can improve the accuracy of spectrally‐based depth retrieval in cases where sun glint dominates the at‐sensor radiance. For an example image of the gravel‐bed Snake River, Wyoming, USA, observed‐versus‐predicted R² values for depth retrieval improved from 0.66 to 0.76 following sun glint removal. The methodology presented here is straightforward to implement and could be incorporated into image processing workflows for multispectral images that include a near‐infrared band. Copyright © 2016 John Wiley & Sons, Ltd.     

Land cover classification of remote sensing imagery based on interval-valued data fuzzy c-means algorithm

There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling the fuzzy nature of remote sensing data,which is caused by the uncertainty and heterogeneity in the surface spectral reflectance of ground objects.After constructing a multi-spectral interval-valued model of source data and defining a distance measure to achieve the maximum dissimilarity between intervals,an interval-valued fuzzy c-means(FCM)clustering algorithm that considers both the functional characteristics of fuzzy clustering algorithms and the interregional features of ground object spectral reflectance was applied in this study.Such a process can significantly improve the clustering effect;specifically,the process can reduce the synonym spectrum phenomenon and the misclassification caused by the overlap of spectral features between classes of clustering results.Clustering analysis experiments aimed at land cover classification using remote sensing imagery from the SPOT-5 satellite sensor for the Pearl River Delta region,China,and the TM sensor for Yushu,Qinghai,China,were conducted,as well as experiments involving the conventional FCM algorithm,the results of which were used for comparative analysis.Next,a supervised classification method was used to validate the clustering results.The final results indicate that the proposed interval-valued FCM clustering is more effective than the conventional FCM clustering method for land cover classification using multi-spectral remote sensing imagery.     

基于天地图数据平台的地震应急评估决策服务系统设计与实现

为解决现有震后灾害快速评估系统地图要素更新不及时、使用涉密等问题,研究以天地图公共数据平台为底图和数据资源、以现有计算模型为骨架、以ArcEngine为GIS开发平台、采用C/S结构开发基于天地图数据平台的地震应急评估决策综合信息系统。该系统功能主要包括地震触发、震害评估、应急辅助决策等,在系统设计上采用模块化设计,并基于通用标准和用户定制的开发思想,实现数据和应用的标准化,使其成为地震应急信息系统的重要基础和开展地震信息服务的必要支撑,更好地为各级政府及社会公众服务。     

Potential application of remote sensing systems to the African rift system

Interdisciplinary interpretation of satellite and geologic-geophysical data can be applied to East Africa as a cost-effective means of regional tectonic evaluation. All available data sources: geologic and geophysical maps and remote sensing images should be used. Remote sensing methods are very efficient for the “synoptic overlook” necessary to pinpoint areas for more detailed investigation.The use of satellite imagery is a way of applying and testing structural frameworks for mineral potential as surface reflections of deep tectonic features can be recognized. Mineralization can be correlated with tectonic lineaments that are probably related to persistent discontinuities in the upper mantle. The outlining of these discontinuities would be of value in the search for the understanding of riftogenesis and in the search for mineralization.This paper is a review of such work with a specific example from Canada, and how the approach can be applied to Africa for continuing research on recent crustal movements.