Introduction to the Sparse Matrix Operator Kernel Emissions (SMOKE) Model - Online Version
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The table below lists the dates of the upcoming Introduction to SMOKE online classes along with the enrollment status in each class.
When enrollment is full, we will no longer accept applications for the class and the status column in the table will display that the class is full.
The class is subject to cancellation if there are not enough registered students.
A minimum of 6 trainees must be registered to conduct a training.
About the Course
The online version of the Introduction to SMOKE course uses the same materials and follows the same format as our popular classroom version of the course. The online class combines pre-recorded lectures with hands-on computer exercises to teach students how to configure and run the SMOKE programs and to examine the input and output files from the software. The class introduces students to the basics of air pollutant emissions modeling and how to process emissions data through SMOKE. Students are guided through exercises to inspect the various input files for SMOKE, including emission inventory data, chemical speciation data, temporal profiles, and spatial surrogates. The hands-on exercises are structured around processing the different types of inventories with SMOKE: area/nonpoint, on-road mobile with MOVES, point, and biogenics. The hands-on exercises also include labs on merging multiple source categories together and using SMOKE to generate customized QA reports.
A live training facilitator and virtual office hours with experienced SMOKE modelers are available to provide the best possible experience to the students taking the class. The training facilitator is available throughout the course via an instant messaging chat room to help students work through technical questions with the training materials. Virtual office hours during each day of the course offer live chat and video conferencing with experienced SMOKE modelers. The office hours are a great opportunity for students to ask questions about the training, SMOKE, and emissions modeling.
Students have one week to complete the course and during that time are provided access to online and print versions of the SMOKE training manual, online lectures, and preconfigured virtual training computers. A virtual computer lab, available through Amazon AWS, gives each student a Linux box loaded with all of the data and software needed to complete this course.
The syllabus is shown below to highlight the range of topics covered during the course. After an introduction to the online training materials, including instructions and support for connecting to the virtual computing lab, the course starts with a lecture on the basics of SMOKE, including an overview of emissions modeling, an introduction to the SMOKE programs, and a description of the course structure. The Hands-on laboratories have each student working on a computer pre-loaded with the course training materials. The labs focus on configuring and running the SMOKE programs and examining the input and output files to give students practical experience using SMOKE.
At the completion of this course, students will be able to download, configure, and run the SMOKE programs. They will possess the knowledge and practical experience needed to prepare input files for SMOKE and to produce emissions input files for the CMAQ and CAMx air quality models.
Pre-course Software Needs
SMOKE is a Linux command-line based system. The CMAS Center provides pre-configured Linux images through Amazon Web Services (AWS) with all of the materials needed to complete the hands-on labs for this training. Each participant will need software on their systems to remotely access their AWS images.
You need to have an X-client (e.g. Xming) and an SSH-client (e.g. Putty) installed on your Windows machine to access remote Linux servers.
X and SSH clients are already installed on Linux and most MacOS systems. If you don't have an X client on your Mac, download and install XQuartz.
All registered students will receive additional instructions for accessing a test AWS image and the online training materials within a week of the online course start date.
Course Schedule and Syllabus
For the online training, access to Amazon AWS images and the Sakai Course Content Manager will be available during the week of the course.
One week prior to the course the students will have the opportunity to login to the Sakai Course Manager and to a test out the Amazon AWS image and test their connection to the Elluminate Live Webinar.
There are four virtual meetings when the instructor will provide live instructions to all online participants. During the first 30 minutes the instructor will give a slide presentation on the logistics and course material. The remaining time is for questions, answers and troubleshooting.
The following is a general schedule of the SMOKE Online Training interactive resources:
- Day 1 - AM Live Introduction Webinar, 9-10 am EST, Introduction to SMOKE Training Online
- Day 1 - PM Live Help Webinar, 1-2 pm EST
- Day 2 - Live Help Webinar , 1-2 pm EST
- Day 3 - Live Help Webinar, 1-2 pm EST
- Days 1-5 - Chat Room, 8 am - 5 pm, EST; CMAS Trainers will be available to moderate the course interactive discussions and answer questions
All lecture slides used during the interactive discussions will archived and available for download to the course participants.
Introduction to SMOKE Syllabus
|Introduction to the Online Training|| Live Video Conference/Chat
||Video conference with the training facilitator and CMAS emissions modelers to introduce students to the class. In this module students will learn how to navigate the online training materials and resources.
|Emissions processing basics|| Lecture
||Introduction to emissions processing concepts and terminology.
|SMOKE assigns file and scripts|| Lecture
||Introduction to the SMOKE user interface and run scripts.
|SMOKE programs and options|| Lecture
||Introduction to the SMOKE software, configuration, and run-time options.
|SMOKE problem solving|| Lecture
||Hints on troubleshooting operational issues with SMOKE.
|SMOKE and Linux Overview|| Hands-on Lab
||Hands-on introduction to the CMAS virtual training machines and the SMOKE operating environment. Includes exercises on learning about many of the SMOKE input data formats and file types.
|Area Source Processing|| Hands-on Lab
||Exercises on investigating non-point source inventory data and processing these data with SMOKE.
|Biogenic Processing|| Hands-on Lab
||Exercises on using the BEIS3 biogenic model in SMOKE to estimate biogenic emissions.
|Point Source Processing|| Hands-on Lab
||Exercises on investigating point source inventory data and processing these data with SMOKE.
|Mobile Source Processing|| Hands-on Lab
||Exercises on using the SMOKE-MOVES interface to process MOVES on-road mobile source emissions with SMOKE.
|SMOKE Merge Programs|| Hands-on Lab
||Exercises on using SMOKE to merge together multiple emissions sectors and prepare input data for CMAQ and CAMx.
|SMOKE Quality Assurance Programs|| Hands-on Lab
||Exercises on using the SMOKE program Smkreport for creating custom reports of emissions data.
Meet the Trainers
BH Baek, PhD
Research Assistant Professor, Center for Environmental Modeling for Policy Development
BH has 17 years of atmospheric chemistry experience related to emissions inventory development and processing, air quality laboratory and field monitoring, and grid-based air quality modeling applications. He is the senior software engineer for SMOKE. BH also has participated in developing several programs and tools that interface various 3rd party source-specific emissions models through the SMOKE, including the U.S. EPA MOVES model for onroad mobile sources, the U.S. EPA NONROAD model for nonroad mobile sources, the Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation (SMARTFIRE) framework for wildfire emissions, and the Federal Aviation Administration (FAA) Emissions and Dispersion Modeling System (EDMS) and Aviation Environmental Design Tool (AEDT) for airport emissions. BH is the co-developer and maintainer of the Introduction to SMOKE class.
Liz Adams, MS
Research Associate, Center for Environmental Modeling for Policy Development
Ms. Adams has over 10 years of experience in model applications, model evaluation, and debugging support to developers of air quality modeling systems. Ms. Adams prepares model documentation, and performs web-based software management, software installation and testing across multiple platforms (Linux, Mac OS X, and Windows) to support public release of the Visualization Environment for Rich Data Interpretation (VERDI) tool. Ms. Adams has installed the Sparse Matrix Operator Kernel Emissions (SMOKE) training software, data and ancillary software tools to a compute server on the Amazon Web Services (AWS) Elastic Compute Cloud (EC2) for an online SMOKE training course. Ms. Adams is experienced with using Python, QGIS, Panoply, IDV, VERDI, the Atmospheric Model Evaluation Tool (AMET), and Ncview to visualize and analyze NetCDF data from the CMAQ modeling system and comparing the results to data from the observational networks. She supports the CMAS Statistical and Graphical Analysis Tools training course by preparing, testing and porting input data and scripts for VERDI and AMET to the Virtual Computing Laboratory environment, preparing and delivering classroom lectures, and providing hands-on training support to students.
The 1-week course includes all training materials, preconfigured training machines, live techincal support, the current SMOKE Training Manual, and access to experienced SMOKE modelers.
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or purchase order. Note that you are asked to make the payment or initiate the payment
process (e.g. by providing the purchase order number) at the time of registration.
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and payment. If you find later that you are unable to attend to the class
after registration, notify the CMAS Center as soon as possible. Please see our
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A basic knowledge of emissions and air quality modeling concepts will help students to get the most out of this course. The course covers emissions modeling terminology and basic general concepts about emissions data, but the focus is mostly on the operational details of SMOKE. A background in emissions or air quality will provide context for the need for using SMOKE.
Knowledge of the Linux command line language and the C-shell are also prerequisites for this course. Students with a working understanding of navigating Linux directory structures, viewing/editing text files, and executing commands from a Linux command prompt will benefit more from this class than students with no Linux experience.
Students must have a computer connected to the Internet that includes a Secure Shell client and an X-Window client. Instructions for downloading and installing these clients for different operating systems will be provided before the class begins.
For more information on the SMOKE training, please contact Brian Naess at 919-966-9925 or email email@example.com.