2007-10-16 ForschungsZentrum Juelich Semianr
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The document discusses global dust and smoke pollution over North America. It provides examples of large dust storms from Asia and Africa impacting air quality in North America. Satellites are able to detect most major dust and smoke emission regions by season. Fine particle composition data from sites in the eastern US show that dust in Florida originates from Africa throughout the year, while dust in other regions comes from local sources during spring and fall.
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2006-10-16 U Wisconsin Seminar
The document discusses atmospheric aerosols and their characterization. It notes that aerosols have complex physicochemical properties and their full characterization requires measuring multiple dimensions such as size, composition, shape, and mixing state. Satellite data has helped characterize the global distribution of aerosols but challenges remain in integrating different data sources. Aerosols originate from both natural sources like dust, fires and volcanoes as well as human activities and influence factors like climate, air quality and human health.
2003-12-10 Global and Local Dust/Smoke over the US
Global and local air pollution sources have changed over time. Before the 1950s, pollution was mainly from local sources like smoke and fly ash. From the 1970s-1990s, regional pollution increased due to issues like acid rain and haze. Satellite data from the 1990s onward showed evidence of global transport of pollutants like dust and smoke across vast distances. Major sources of global air pollution included dust from deserts in Africa and Asia, as well as smoke from seasonal biomass burning around the world. New monitoring capabilities revealed that global pollutant transport has significant impacts on air quality over regions far from the source.
2004-10-14 AIR-257: Satellite Detection of Aerosols
The document summarizes an air and waste management professional development course on satellite detection of aerosols. The course syllabus covers topics like satellite types and usage, detection of events like fires, dust storms and haze from satellites, and using satellite data in air quality management. It also discusses several case studies of dust and smoke transport events detected by satellites, including Asian dust storms in 1998, Central American forest fire smoke in 1998, and smoke transported from Quebec fires to the eastern US in 2002.
2004-06-24 Satellite Data Us in PM Management: A Retrospective Assessment
This document discusses how satellite data has been used to study particulate matter (PM) over time. It notes that PM is a complex phenomenon that requires characterization across multiple dimensions, and that satellites provide valuable spatial context but require integration with other data sources to fully characterize PM. The document outlines several past examples where satellite data helped detect major aerosol events like dust storms and wildfire smoke plumes, and envisions future real-time monitoring systems to aid air quality management.
2006-03-08 Intercontinental Aerosol Transport: Quantitative Tools an Results
The document discusses various tools and methods for quantifying intercontinental transport of air pollutants like dust and determining their climatic effects. It summarizes that satellite data shows Sahara desert as the largest global dust source. Transport models and analysis of chemical and temporal patterns indicate that fine dust events over the US originate from Saharan dust in summer and Gobi dust in spring. Methods like chemical fingerprinting, back trajectory analysis, and integrated chemistry-transport modeling are used to attribute the origin and quantify transport of different dust sources.
2004-06-20 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET
This document summarizes the FASTNET project which aims to better characterize natural haze conditions through the development of tools to access, archive, and analyze aerosol data. The project focuses on detailed analysis of major natural aerosol events like dust storms and wildfires. Initial efforts demonstrate the feasibility of using data on aerosol composition, transport patterns, and satellite imagery to identify the sources and pathways of dust transported from the Sahara desert to the eastern United States.
041026 Icap Transp Quant
http://capitawiki.wustl.edu/index.php/20041028_Intercontinental_Dust_and_Smoke_over_North_America:Quantitative_Tools_an_Results
2004-10-28 Intercontinental Dust and Smoke over North America:Quantitative To...
1. Various observational tools are used to establish the origin of aerosol events, including direct photographic evidence, satellite images, aerosol composition analysis, and trajectory modeling.
2. Analysis of data from 1992-2003 indicates that fine dust events over the US are mainly from intercontinental transport, with Saharan dust dominant in summer and Gobi dust in spring.
3. Apportionment of local and Saharan dust contributions on an annual and monthly basis found that Saharan dust exceeds local sources by a factor of 2-4 times in July across the southeastern US.
2003-08-27 Data Fusion for the Description and Explanation of Atmospheric Aer...
1) The document discusses combining data from multiple sensors and sources to provide a more complete description and explanation of atmospheric aerosols over space, time, and other dimensions.
2) Sensor, pixel, and feature-level data fusion techniques are used to integrate data from instruments like SeaWiFS, TOMS, and surface visibility stations.
3) Examples show how fusing these data sources provides insights into the spatial patterns, heights, and source regions of dust and smoke plumes from Asia, Africa, and Central America.
2004-09-21 Natural Aerosol Event Detection and Characterization
The document discusses analyzing natural aerosol events such as dust and smoke over the United States. It outlines using multiple data sources and analytical approaches to identify the spatial, temporal, and chemical patterns of natural aerosols. Specific analysis includes identifying the local and intercontinental origins of dust events over the US using monitoring data, satellite images, and air quality models.
2004-06-24 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET Proj...
The document discusses the FASTNET project which aims to better characterize natural haze conditions through the analysis of major natural aerosol events like forest fires and dust storms. The goal is to develop tools for data access, archiving, and analysis to describe the spatial, temporal, and compositional features of natural aerosols. This will help understand their contribution to regional haze and establish baseline natural conditions as required by the Regional Haze Rule.
2004-09-23 Eastern US Regional Haze Events: Automated Detection and Documenta...
The document summarizes the detection of seven major particulate matter (PM2.5) events that occurred in the Eastern United States from January to September 2004 using air quality monitoring data. An objective statistical approach was used to detect regional haze events based on PM2.5 concentrations exceeding a threshold. The events were then characterized using additional real-time data on meteorology and aerosol properties. This provided cursory analysis of possible causes, while more detailed investigation is required to fully interpret the events. The automated detection of events acts as a trigger and screening tool to prioritize further analysis.
2005-06-03 Aerosol Characterization and the Supporting Information Infrastruc...
The document discusses aerosol characterization and monitoring infrastructure. It describes the goal of attaining natural regional haze conditions by 2064 according to the Regional Haze Rule. It also discusses the National Ambient Air Monitoring Strategy and related initiatives like FASTNET and DataFed that pursue its recommendations around enhanced monitoring. Finally, it outlines some of the technical challenges around fully characterizing the multidimensional aerosol system.
2005-04-01 Carbonaceous Aerosol and Smoke over the Eastern US
1. The document analyzes carbonaceous aerosol and smoke patterns over eastern North America using data from surface and satellite observations.
2. Smoke from biomass burning constitutes a significant component of fine particulate matter over North America, particularly in summer, but its spatial and temporal patterns are not fully understood.
3. The analysis aims to better characterize the sources, distribution, and composition of smoke through an integrated assessment of literature and recent observation data.
A Pinatubo Climate Modeling Investigation
The document summarizes a comprehensive investigation into the climate effects of the 1991 eruption of Mount Pinatubo. Key points:
- Pinatubo produced the largest climate forcing of any 20th century volcano due to its large output of aerosols. This allows for a more quantitative analysis of climate sensitivity to a transient forcing event.
- Observations show a maximum global cooling of around 0.25°C 1-3 years after eruptions of similar size, though models typically predict around 0.5°C of cooling. Pinatubo provides an opportunity to test understanding of the climate response.
- Early predictions using a climate model matched observations reasonably well, showing peak stratospheric
Introduction & transport of air pollution. m1 pptx
History of Air pollution and episodes, Sources of air pollution and types, Introduction
to meteorology and transport of air pollution: Global winds, Headley cells, wind rose terrestrial wind profile, Effects of terrain and topography on winds, lapse rate, maximum mixing depths, plume rise
2008-04-15 EGU Mtg Vienna Exceptional Events
The document discusses methods for justifying the exclusion of air quality monitoring data influenced by exceptional events such as wildfires. It presents evidence needed to designate data as influenced by an exceptional event, including showing a likely standard exceedance, that the event was uncontrollable, a clear causal relationship between the event and the data, excess over normal values, and that the exceedance would not have occurred without the event. It then gives an example of applying these methods to analyze the influence of 2007 wildfires in Georgia on air quality data.
The Atmosphere: Climate, Climate Change and Ozone Depletion
Just want to share our report in NatSci for graduate school. I'd be happy if this could help you. Enjoy! To God be the Glory!
sulfur_signals_in_antarct-UCSD news
Sulfur isotopes trapped in Antarctic snow were found to provide clues about climate, both past and future. Measurements of sulfur in snow dating from 1984 to 2001 revealed distinctive chemical signatures from large volcanic eruptions like Pinatubo and Cerro Hudson as well as El Niño events. Unexpectedly large signals were found following extreme weather and fires caused by a super El Niño in 1997-1998. These signals were caused by reactions of sulfur compounds like carbonyl sulfide in the stratosphere, influenced by UV light. Considering these reactions could provide insight into both present and ancient climate models.
Energy Issues
The document discusses several air and energy issues including the atmosphere, the grasshopper effect of persistent organic pollutants, acidic deposition, the ozone layer, and various energy sources and their usage worldwide. It provides details on the composition and layers of the atmosphere and how human activities impact air quality. It also explains how pollutants can travel long distances and accumulate in colder regions through the grasshopper effect.
Similar to 2007-10-16 ForschungsZentrum Juelich Semianr (20)
2003-12-10 Global and Local Dust/Smoke over the US
2003-12-10 Global and Local Dust/Smoke over the US
2004-10-14 AIR-257: Satellite Detection of Aerosols
2004-10-14 AIR-257: Satellite Detection of Aerosols
2004-06-24 Satellite Data Us in PM Management: A Retrospective Assessment
2004-06-24 Satellite Data Us in PM Management: A Retrospective Assessment
2006-03-08 Intercontinental Aerosol Transport: Quantitative Tools an Results
2006-03-08 Intercontinental Aerosol Transport: Quantitative Tools an Results
2004-06-20 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET
2004-06-20 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET
2004-10-28 Intercontinental Dust and Smoke over North America:Quantitative To...
2004-10-28 Intercontinental Dust and Smoke over North America:Quantitative To...
2003-08-27 Data Fusion for the Description and Explanation of Atmospheric Aer...
2003-08-27 Data Fusion for the Description and Explanation of Atmospheric Aer...
2004-09-21 Natural Aerosol Event Detection and Characterization
2004-09-21 Natural Aerosol Event Detection and Characterization
2004-06-24 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET Proj...
2004-06-24 Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET Proj...
2004-09-23 Eastern US Regional Haze Events: Automated Detection and Documenta...
2004-09-23 Eastern US Regional Haze Events: Automated Detection and Documenta...
2005-06-03 Aerosol Characterization and the Supporting Information Infrastruc...
2005-06-03 Aerosol Characterization and the Supporting Information Infrastruc...
2005-04-01 Carbonaceous Aerosol and Smoke over the Eastern US
2005-04-01 Carbonaceous Aerosol and Smoke over the Eastern US
Introduction & transport of air pollution. m1 pptx
Introduction & transport of air pollution. m1 pptx
The Atmosphere: Climate, Climate Change and Ozone Depletion
The Atmosphere: Climate, Climate Change and Ozone Depletion
More from Rudolf Husar
100528 satellite obs_china_husar
This document discusses the challenges of characterizing air pollution using remote sensing observations over China. It describes the seven dimensions of data - spatial, height, time, particle size, composition, shape, and mixing - needed to fully characterize air pollution. While each individual observation method or data set has limitations, together they can provide consistent global-scale observations. There remain significant challenges to integrating data from multiple sensors to accurately measure air pollution. International collaboration combining global satellite data with detailed local observations in China may help advance progress in addressing this issue.
2013-04-30 EE DSS Approach and Demo
The document describes the Exceptional Event Decision Support System (EE DSS), a tool to help states and EPA regions implement the EPA's Exceptional Events Rule. The EE DSS uses air quality, meteorological, and other data to screen for exceedances and flag those likely caused by exceptional events like dust storms, wildfires, or July 4th fireworks. It aims to minimize the technical hurdles of the EE rule and provide a uniform, transparent methodology. The document outlines the EE DSS's data sources and modeling, screening approach, tools for visualizing events, and provides an example demo of the system in action.
Exceptional Event Decision Support System Description
This slideshow is a brief description of the Exceptional Event Decision Support System Description (EE DSS).
130205 epa exc_event_seminar
This document summarizes Rudolf Husar's presentation on exceptional event analysis and decision support systems. It discusses using diverse data like satellites, models, and real-time monitoring to evaluate exceptional events like wildfires, dust storms, and their impact on air quality measurements. Specific examples are presented of exceptional events from dust from Asia and Africa impacting North America, as well as wildfires in Georgia impacting ozone and PM2.5 levels. Tools like the Navy Aerosol Analysis and Prediction System model and satellite data are highlighted for their ability to analyze the transport and impact of these aerosol plumes to support regulatory decisions. The goal of reconciliation of emissions, observations, and models is discussed to improve the evaluation of exceptional events
130205 epa ee_presentation_subm
Rudolf B. Husar presented at the EPA on exceptional smoke and dust events. He discussed using diverse data like satellites, models, and real-time data in a decision support system to evaluate these events. The NAAPS aerosol model assimilates satellite data to provide the 3D structure of smoke, dust, and other aerosols. Long-term NAAPS data from 2006 to present show the vertical distribution of different aerosols. Satellite data help reduce biases between surface PM measurements and air quality models.
111018 geo sif_aq_interop
The document discusses the Air Quality Community of Practice (AQ CoP) which facilitates interoperability and data networking for air quality and health applications. The AQ CoP has developed an open-source Air Quality Data Network (ADN) consisting of 7 interoperable air quality data servers that provide access to diverse observational and model datasets using international standards. The ADN demonstrates GEO principles and infrastructure but requires further development to support real applications. The main role of the AQ CoP is to connect different initiatives and enable the ADN network.
110823 solta11 intro
The workshop will bring together practitioners from Europe and North America to discuss progress and challenges in realizing an interoperable air quality data network. Participants will assess the current state of the pilot network, address key technical issues around data standards, server implementation and maintenance, and catalog design. The goal is to advance the network from a virtual concept to an operational reality, facilitating improved access, integration and reuse of air quality observation and model data.
110823 data fed_solta11
The document describes DataFed, a federated data system that provides non-intrusive integration of diverse environmental datasets using open standards. DataFed allows users to find and access datasets through a catalog and flexible tools for processing and visualizing the data. It facilitates publishing, finding, and accessing geospatial and environmental data through loose coupling of autonomous nodes and OGC web service protocols.
110510 aq co_p_network
This document discusses the emerging pattern in the air quality information ecosystem. It notes that individual data providers, scientists, and decision supporters are being replaced by groups that facilitate access, sharing, and integration. These include data portals, science teams, and decision support systems. The ecosystem involves multiple stages from observations to decisions, with value added at each stage through activities like data aggregation, scientific collaboration, and predictive analysis. This new structure is more efficient and supports the goals of initiatives like GEOSS.
110509 aq co_p_solta
The document discusses a workshop on networking air quality observations and models to support decision making. The workshop aims to (1) introduce participants and identify shared data and applications, (2) exchange best practices for interoperability, and (3) address technical and collaboration issues. The preliminary agenda covers assessing the current state of air quality interoperability and the technical requirements for improved data sharing and integration to support applications and decision support systems.
110421 exploration of_pm_networks_and_data_over_the_us-_aqs_and_views
The document summarizes the exploration of PM networks and data over the US using two datasets: AQS and VIEWS. It presents information on the coverage and frequency of EPA monitoring data, as well as data from the VIEWS network. It also describes the user interface for the Datafed browser and schemes for processing and aggregating raw monitoring data spatially and temporally. Finally, it analyzes the spatial and temporal variation of PM levels and the correlation between continuous and EPA monitoring data in different regions of the US.
110410 aq user_req_methodology_sydney_subm
This document proposes a methodology to determine user requirements for Earth observations related to air quality management. The methodology is a bottom-up approach that (1) defines the major workflow steps of air quality management, (2) identifies the value-adding activities within each step, (3) determines the participants ("users") for each activity, and (4) establishes the Earth observation needs of each user. The methodology is intended to facilitate ongoing feedback to optimize the value of Earth observations for air quality management and reduce gaps. It provides a systematic way to account for user needs based on the specific activities and users involved in the air quality management process.
110408 aq co_p_uic_sydney_husar
This document provides a 2011 progress report for the GEOSS Air Quality Community of Practice (AQ CoP). It summarizes activities undertaken in 2011, including developing an air quality data server software to make data more accessible and interoperable, creating a user requirements registry to identify needed observations and models, and matching user needs with available data through a community catalog. It outlines ongoing projects and plans to further expand the air quality data network through coordination and workshops in 2011. The overall goal is to integrate air quality initiatives and make relevant data more findable, accessible and interoperable to support applications in air quality and health.
110105 htap pilot_aqco_p_esip_dc
The document describes the HTAP Data Network, which demonstrates a service-oriented approach to sharing atmospheric model outputs and air quality observations between various data servers using open standards. The main output is open-source WCS data server software and tools that allow different organizations to publish, find, and access distributed air quality data holdings in a interoperable way as part of the GEO Task DA-09-02d: Atmospheric Model Evaluation Network. The network aims to connect air quality data providers and users to enable effective air quality science and management.
100615 htap network_brussels
The REASoN Project will link NASA's air quality data, modeling, and systems to users in research, education, and applications. It aims to address hurdles users face in finding, accessing, evaluating, and merging relevant data. The project will utilize service orientation and interoperability standards to build an adaptable information infrastructure. This will include becoming a node on the air quality network, implementing standards for sharing data and tools, and participating in the GEOSS Architecture Implementation Pilot.
121117 eedss briefing_nasa_epa
This document summarizes the Exceptional Event Decision Support System (EE DSS) which uses NASA satellite data and the Navy Aerosol Analysis and Prediction System (NAAPS) model to help with air quality management decisions regarding exceptional events like smoke and dust events. The EE DSS has been developed since 2005 with NASA support and is now ready to serve air quality management at the federal, regional, and state levels. It can automatically detect and analyze events, display relevant data through interactive maps and cross-sections, and its tools have helped explain declines in exceptional event flags and PM2.5 concentrations from 2006-2012. Coordination is proposed with NASA and EPA for continued application of the EE DSS to smoke and dust events in
120910 nasa satellite_outline
This document discusses the usefulness of satellite observations for air quality applications and regulatory requirements. It outlines six key air quality requirements that satellites can help address, such as determining compliance with air quality standards and identifying long-range pollution transport events. The document also notes how satellites can help improve emissions estimates, characterize long-range transport of pollution, and increase interaction between air quality and remote sensing scientists. However, it cautions that relating satellite aerosol optical depth measurements directly to ground-level PM concentrations currently has too much uncertainty for regulatory or public health applications.
120612 geia closure_ofeo_ms_soa_subm
The document discusses tools for closing the gap between emissions, observations, and models of air quality. It proposes a service oriented architecture and network to integrate multiple datasets from observations, emissions, and models. This would allow iterative evaluation and improvement of models by comparing them to observations and adjusting emissions estimates to reduce biases. The end goal is to provide the best available composition of the atmosphere by integrating the best observations, emissions estimates, and models.
110414 extreme dustsmokesulfate
This proposal outlines a study on the influence of weather and climate events on air quality issues like dust, smoke, and sulfate events. The study would examine these events at both the continental/hemispherical scale and regional scale. At the continental scale, the analysis would demonstrate the role of global climate and emissions and identify tipping points for air quality regulations. At the regional scale, the study would analyze the effects of regional emissions, climate, and precipitation on air quality. The proposal describes tools and methods for conducting continental and regional air quality-climate analysis, including models, datasets, and satellite data. The goals are to support air quality management and identify implications for policy.
Aq Gci Infrastructure
The document discusses various applications of air quality data including regulatory exceptions, hemispheric transport projects, and atmospheric composition portals. It also describes the Air Quality Community of Practice's contributions to the GEOSS Common Infrastructure through developing an air quality community catalog and data finder to help users discover and access air quality data and metadata registered in the GEOSS clearinghouse and registry.
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Exceptional Event Decision Support System Description
Exceptional Event Decision Support System Description
110421 exploration of_pm_networks_and_data_over_the_us-_aqs_and_views
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Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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2007-10-16 ForschungsZentrum Juelich Semianr
- 1. Global and Global Dust and Smoke over North America Rudolf B. Husar Washington University, St. Louis, MO Seminar at Forschungszentrum Juelich, October 16, 2007 Germany
- 3. What is the magnitude of the anthropogenic perturbation of natural processes? Windblown Dust Volcanic Emissions Industrial Aerosols Aerosol are Indicators of Major Biogeochemical Processes Chistian Junge: “In the 50’s wherever you looked there was something interesting” Smoke from Fires
- 4. Early Satellite Detection of Manmade Haze, 1976 Regional Sulfate Haze over the Midwest Low Visibility Hazy ‘Blobs’ Lyons W.A., Husar R.B. Mon. Weather Rev. 1976 SMS GOES June 30 1975
- 7. US Air Pollution Control Goal: Attain natural conditions by 2064
- 10. The Asian Dust Event of April 1998 On April 19, 1998 a major dust storm occurred over the Gobi Desert The dust cloud was seen by SeaWiFS, TOMS, GMS, AVHRR satellites The transport of the dust cloud was followed on-line by an an ad-hoc international group China Mongolia Korea
- 11. Asian Dust Cloud over N. America On April 27, the dust cloud arrived in North America. Regional average PM10 concentrations increased to 65 g/m 3 Asian Dust 100 g/m 3 Hourly PM10
- 12. IMPROVE Fine Particle Dust Concentrations April 25, 1998 April 29, 1998 May 2, 1998 April 1998 Asian Dust event detection, analysis, reporting by ad-hoc international virtual (web-based) workgroup!! A driver for informatics effort on data sharing and collaboration
- 15. Seasonal Fine Aerosol Composition, E. US Upper Buffalo Smoky Mtn Everglades, FL Big Bend, TX
- 17. Satellites detect dust most storms in near real time The MODIS sensor on AQUA and Terra provides 250m resolution image s of the dust storm Visual inspection reveals the dust sources at the beginning of dust streaks. The NOAA AVHRR sensor highlights the dust by its IR sensors In the TOMS satellite image, the dust signal is conspicuously absent – too close to the ground
- 20. Origin of Fine Dust Events over the US Fine dust events over the US are mainly from intercontinental transport Dust is seasonal with noise Random short spikes added Sulfate is seasonal with noise Noise is by synoptic weather
- 25. Smoke Aerosol and Ozone During the Smoke Episode – Inverse Relationship The surface ozone is generally depressed under the smoke cloud Extinction Coefficient (visibility) Surface Ozone
- 26. May-June 2003 Siberian Fires
- 27. Aircraft Detection of Siberian Forrest Smoke near Seattle, WA Jaffe et. al., 2003
- 34. Establishing Source-Receptor Relationship Egen, 1828 Smell: [composition] Temporal Trend Decay with Distance Wind Direction Direct Evidence Trajectory