Henry Magruder made a mistake—he left a CD at the coffee station. Later, when Iris Majwubu was topping off her mug with fresh tea, hoping to wrap up her work on the current SQL code module before it was time to go home, she saw the unlabeled CD on the counter. Being the helpful sort, she picked it up, intending to return it to the person who’d left it behind.

Expecting to find perhaps the latest device drivers, or someone’s work from the development team’s office, Iris slipped the disk into the drive of her computer and ran a virus scan on its contents before opening the file explorer program. She had been correct in assuming the CD contained data files, and lots of them. She opened a file at random: names, addresses, and Social Security numbers appeared on her screen. These were not the test records she expected; they looked more like critical payroll data. Concerned, she found a readme.txt file
and opened it. It read:

Jill, see files on this disc. Hope they meet your expectations. Wire money to account as arranged. Rest of data sent on payment.

Iris realized that someone was selling sensitive company data to an outside information
broker. She looked back at the directory listing and saw that the files spanned the range of every department at Sequential Label and Supply—everything from customer lists to shipping invoices. She saw one file that appeared to contain the credit card numbers of every Web customer the company supplied. She opened another file and saw that it only contained about half of the relevant data. Whoever did this had split the data into two parts.

That made sense: payment on delivery of the first half. Now, who did this belong to? She opened up the file properties option on the readme.txt file. The file owner was listed as “hmagruder.” That must be Henry Magruder, the developer two cubes over in the next aisle. Iris pondered her next action.

Iris called the company security hotline. The hotline was an anonymous way to report any
suspicious activity or abuse of company policy, although Iris chose to identify herself. The
next morning, she was called to a meeting with an investigator from corporate security,
which led to more meetings with others in corporate security, and then finally a meeting with
the director of human resources and Gladys Williams, the CIO of SLS.

Questions:
1. Why was Iris justified in determining who the owner of the CD was?
2. Should Iris have approached Henry directly, or was the hotline the most effective way
to take action? Why do you think so?
3. Should Iris have placed the CD back at the coffee station and forgotten the whole
thing? Explain why that action would have been ethical or unethical.

Two scenarios are provided for the candidates. The candidates can provide appropriate solutions for any one or both the scenarios considering all the points.

Scenario 1:

An environment is attacked by zero-day attack with users identifying a notepad with attacker details and instructions to regain access, 60% of estate/users are impacted. Every endpoint had AV & EDR tools, but the machines were infected. Environment had required security controls for network, firewall, log monitoring, nothing was detected in SIEM. Backup strategy used is snapshot back-up on the same network in the same domain.

Using threat hunting techniques can we establish how hacker could have infiltrate and,

1. How to find what are the IOC’s.
2. How do you identify if any data exfiltration has happened?
3. Approach to restrict further propagation of malicious code in estate & immediate corrective actions.
4. What will be the incident response and recovery strategy ?

Scenario 2:

When looking at any security team, one thing you might notice is that there is a tool for everything. And we do mean everything: ticketing, threat intelligence, security investigations, malware analysis, detection, incident response, advanced persistent threats, security monitoring the list goes on.

Every organization wants the best of the best to build their defenses. This can often leave their security teams and security operations centers with a tool stack of uncooperative solutions that don’t communicate with one another, with their full value remaining untapped, and they can interrupt or even cancel each other out. The team becomes paralyzed by the sheer number of alerts generated by these solutions, losing time that could be spent on contextualized investigation and response.

We often cite alert fatigue as a common challenge in SOCs, and with good reason. Nobody likes alerts, because whether it’s a fire alarm, car alarm, or alarm for any other kind of emergency, it signals to us that a real threat is present. But after hearing alerts time and time again, all we hear is the boy who cried wolf. We downplay these alerts because we’ve spent so much of our precious time combing through them, only to reveal themselves as fake. In SOC terms, this leads to real threats being missed, often to devastating consequences.

There is a solution. That solution is connecting the tools that security teams run, to communicate with each other and do away with the tedious, time-consuming tasks that have a high potential for human error. Streamlining the process with which tools are used helps to keep security professionals from losing any of their precious time.

1. What is security orchestration?
2. What can we use security orchestration for?
3. What are the benefits of security orchestration?
4. What are the key elements that are needed for SOAR to perform as desired?
5. What is Automated response and how does it work, can you give an example?

Consider the following case study: Clean Planet is a private business based in Victoria specialising in commercial cleaning supplies and business support products for organisational clients. Only a few computerized operations are in the business. In an effort to become more efficient and profitable, the vice president, Julia Thompson, has hired a systems analyst, Robert Hanover. Julia and Robert have made progress in the development of a strategic plan for Clean Planet. Robert is anxious to define the requirements for the new system. He has gathered more information and has created the following organization chart for Clean Planet. Robert: Julia, it’s time to start moving on the system investigation. The mission statement is finalized and strategic planning is well underway. I can see that the directors are beginning to think about how their departments can benefit from better information management. Julia: You’re right! Andrew McClean found out that we lost a big order the other day because the customer was able to get the estimate much more quickly from another company because of their online presence. He’s wondering just how many sales we are losing because of timeliness issues. I had Anna’s group gather numbers for the directors about how many times our profit margin has been reduced because of human error somewhere along the order process. We are profitable but could be more so by reducing error and becoming more competitive with timely information to our potential customers. Robert: Andrew’s area of sales is a logical place to start the investigation. I need to interview sales and customer service representatives to get an idea of the requirements for the new information system. What kind of information will we include? What do we want to get out? What processes need to be managed? What are our business needs? Charles Edwards President Julia Edwards Vice President Andrew McClean Director of Sales Anna McNally Director of Finance Martha Seymour Director of Operations Dennis Martin Shipping/Receiving Manager George Thompson Warehouse Manager Sales Rep (6) Accounting/Billing Clerk (2) Customer Service Rep (3) Julia: This will take some time, and a lot of information needs to be gathered. You should make sure you spend some time with the accounting clerks too because they fill in for customer service representatives. Robert: I’m ready to get started! Answer the following questions: a. Develop a fact-finding plan including interviews, documentation review, observation, questionnaires, sampling, and research. b. Review the organizational model above and list the individuals you would like to interview. Prepare a list of objectives for each of the interviews you will conduct. c. Prepare a list of specific questions for each individual you will interview.

BUSINESS PLAN ASSIGNMENT

1.      The Business Plan project (for a new business) is to be completed and submitted on Day 15. Most days will allow time for in class work plan. However, it will still be necessary to do other work on it. The assignment is worth 30% of the course grade.

2.      The Business Plan must be based on a new business you would like to establish. It should be detailed and comprehensive. You may use the sample plans provided in the Entrepreneurship textbook and in the MyEntrepreneurshipLab. You will also be provided access to the LivePlan online software for creating the business plan. Your new business could be a service, retail, or manufacturing function. It could combine 2 of these or even all 3 but remember, KEEP YOUR BUSINESS SMALL AND SIMPLE.

Instructions for your Business Plan Assignment

1.                  The plan’s maximum is 25-40 (depending on the size of the business) double-spaced pages with no more than 8-10 pages of exhibits or Appendix.

2.                  The plan must include an Executive summary, Table of Contents, Mission, Vision and Culture, Company Summary, Market Analysis Summary, Strategy and Implementation Summary, Management and Operations Summary, Financial Plan, Funding Request and Exit Strategy. Appendices including: Sales Forecast, Personnel Plan, General Assumptions, Pro Forma Profit and Loss, Pro Forma Cash flow, Pro Forma Balance Sheet, Resumes, Fact Sheet and complete list of references.

3.                  It should include a detailed marketing plan that identifies the principal target market(s), its size, location and all demographic and psychographic characteristics. Students should also identify and growth trends in the market and provide appropriate statistical information to support that conclusion. Detailed sections are required on the needs filled by the product or service offering, market research conducted, pricing methods and the proposed promotional programs and distribution system.

4.                  The plan should also include a detailed financial plan linked to the requirements and objectives of the marketing plan. This section must cover the business’ first five years and include monthly statements (income, cash flow and balance sheet for Year 1, quarterly statements for Year 2 and annual statements for Year 3-5. Optimistic and pessimistic forecasts should be included as well.

5.                  Financial methods and the scheduled amounts.

6.                  An exit or harvest strategy for the business.

7.                  Identification of the key attributes and skills brought to the business by each team member who will be active in the business and description of how these will be of benefit to the business.

8.                  Delineation of a medium to long-term growth strategy for the business, i.e., expansion and diversification plans.

9.                  A brief description of the human resources, ethical and social policies of the business.

Students will be required to make a 40-minute presentation of their plan. Students will be evaluated on their creativity, enthusiasm, use of audio-visual aids (PowerPoint is strongly recommended) and public speaking skills.

According to this article answer the following questions

A former Amazon manager alleges that her supervisor made her scour the social media accounts of applicants to determine their race and gender, and then fired her when she complained. Lisa McCarrick filed a lawsuit against an Amazon unit on Monday in the Superior Court of California, Alameda County, claiming retaliation, wrongful termination, failure to prevent discrimination and violation of the state's labor code. The 38-year-old, who lives in Rocklin, about 20 miles northeast of Sacramento, is also suing for violation of the state's Equal Pay Act, alleging that she made significantly less than her male colleagues although they were doing similar work. McCarrick joined Amazon as a loss prevention manager in July 2018 and was promoted to a regional manager five months later, the suit says. After her promotion, her supervisor instructed McCarrick to go through the social media profiles of job candidates "for the purpose of ascertaining race/ethnicity and gender," according to the lawsuit. McCarrick knew that Amazon had been criticized in the past for a lack of diversity in the workplace and thought what she was being asked to do was unlawful, according to the lawsuit. In September, she submitted a written complaint raising her concerns about being told to scour applicants' social media accounts and also the pay disparity between herself and her male coworkers. Two months later, in November, she was called into a meeting with human resources and the director of loss prevention informing her that she was fired. "During the meeting in which she was informed of her termination, it was communicated to her that her direct supervisor had admitted to utilizing social media accounts for the purpose of ascertaining race and ethnicity," the suit states. "Plaintiff's protected complaints of race/ethnicity discrimination were substantial motivating reasons for the decision to terminate her employment." The loss prevention director also told McCarrick during the meeting that her male colleagues do make more than her but "that happens all the time at Amazon," according to the lawsuit. The lawsuit claims that throughout McCarrick's employment with Amazon she always received positive performance evaluations but she was told that the reason for her termination was due to "not meeting expectations." McCarrick is seeking damages. An Amazon spokesperson said in a statement Thursday that McCarrick's claims are inaccurate. “At our core, we fundamentally believe that diversity, inclusion, equality, and equal pay for equal work are not just good for our teams and our business, it's just simply right," the statement read. "While we cannot comment on the specifics of this ongoing legal proceeding, Ms. McCarrick's allegations are just not accurate.”

1) Does this case bring about issues or Corporate Social Responsibility? How? Why?

The below test includes 10 questions, randomly selected from a large inventory. Most questions will be different each time you take the test,

You must answer at least 9 out of 10 questions correctly to receive your Certificate.

You have 40 minutes to complete each test, and you must answer all 10 questions in order to to see your results. If you do not pass this test in 40 minutes,

If the student version contains BOTH word-for-word and paraphrasing plagiarism, you should select word-for-word.

If you need help, see this document which provides criteria for determining plagiarism that are used in this test.

Privacy notice: If you pass a test, unique information displayed on your Certificate is also stored in a secure location.

Item 1

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Hints

Item 2

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Hints

Item 3

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Hints

Item 4

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Hints

Item 5

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Hints

Item 6

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Hints

Item 7

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Hints

Item 8

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Hints

Item 9

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Hints

Item 10

In the case below, the original source material is given along with a sample of student work. Determine the type of plagiarism by clicking the appropriate radio button.

Which of the following is true for the Student Version above?

Word-for-Word plagiarism

Paraphrasing plagiarism

This is not plagiarism

Can you summarize this article?

An Economic Analysis of the Intellectual Monopoly in The Lego Movie Beckett Chung

This paper aims to identify the intellectual monopoly in society. It draws inspiration from themes in The Lego Movie (2014) and examines various papers that define the causes of intellectual monopolies. Using a case study of the firm BlackBerry, this paper seeks to understand the severe consequences of an intellectual monopoly. It concludes by suggesting the market power return to the everyday worker, so society can be wholly creative.

The Lego Movie (2014) delivers an ominous warning of the darkness that lurks underneath society’s bed. The plot is structured around overcoming the antagonist, Lord Business, and his monopolistic company, Octan. Octan dominates the Lego Universe, and maintains full control over every single market. By taking advantage of key markets, such as legislation and media, Octan controls the way people think. For example, Lord Business thrusts mandatory instructions onto the laps of his citizens, ensuring everything as simple as waking up in the morning is standardized. By airing only one TV show, and playing only one song, Lord Business manipulates the people of the Lego Universe into realizing his vision of perfection. When thinking processes are monopolized, human creativity is hindered, and technological innovation will suffer.

In “The crisis of intellectual monopoly capitalism,” Pagano (2014) explored how knowledge is controlled in modern society. This paper aids in understanding what an intellectual monopoly is, and offers a socialist solution to stabilize the market for knowledge. In “Why U.S. firms are dying: Failure to innovate,” Denning (2015) presented a multitude of statistics to quantify the lack of support for creativity that workers feel. His numbers help this paper view the effect of a thought monopoly on everyday people.

Classical economics insists that a market dominated by a monopolist cannot function at maximum efficiency. Unfortunately, classical economics fails to reveal the inevitability of an intellectual monopoly as a product of competitive markets. Competition drives capitalists to maximize the efficiency in their labour power, which is rented from the workers. To maximize the efficiency of the rented labour, capitalists streamline production by dividing labour. Instead of hiring one expensive high-skilled worker to produce something, capitalists employ many cheap low-skilled workers who complete small, individual tasks to produce the same thing, at a higher volume for a lower price. Pagano (2014) argued that labour division removes the creative process from the production process (p. 1141). The division of labour represents the division of creativity from production. It is a crucial step towards creating a knowledge monopoly. Overtime, workers become entrenched in their roles, becoming mindless producers. Denning (2015) reported that a very small percentage of workers feel inclined to innovate (para. 11), which he blamed on the overwhelming focus on a firm’s stock price. This is because high production drives the stock price upwards.

The people who are creative have their ideas patented, which further boosts the stock price of the firm. However, only the few people at the head of a company are thinking, and they make it illegal for others to use their ideas. If good ideas contribute positively to stock prices, then why are firms failing to support creativity among their workers? Marxist theory dictates that the capitalist class and the working class are bound to conflict. The capitalist rents labour from the working class at a cost lower than the value of what the worker can produce. The price of labour must stay low enough for the worker to afford the cost of living, but may never grow so that the worker can begin saving. If workers begin saving, they may accrue capital, allowing them to break from the working class and become capitalists. Likewise, if workers feel pushed to innovate, they may innovate beyond the role of a mere worker. If workers begin outputting influential ideas, there is little to stop the workers from patenting their ideas, accruing capital and becoming capitalists. This threatens to dramatically shrink the workforce; which capitalists heavily rely on. So, in the name of profit, firms will continue to alienate their workers, even at the risk of falling to the intellectual monopoly they have created.

Consider the firm BlackBerry. Ten years ago, nearly everyone used their products. Now, the products are rarely seen. From 2009 to 2013, the stock price of BlackBerry plummeted by ninety percent (Gustin 2013). Using the technology industry as a model, it is possible to quantify what could happen to society should it continue under an intellectual monopoly. When Apple launched the first iPhone in 2007, they severely disrupted BlackBerry’s tight hold on the smartphone market. The iPhone emerged backed with a slew of patents, to lock in its monopoly and secure profits. Lacking the creative power to overcome the iPhone’s strengths, such as interface and internet access, BlackBerry chose to attack the iPhone’s weaknesses, such as emailing and security (Ladurantaye, McNish, & Silcoff, 2013). With only a few people in the company innovating, and intellectual property laws forbidding copying, BlackBerry was doomed. Many argue that the patent system encourages innovation because when firms race to idea A, the winner gets all of the profits. This is true, but it is risky for the losers. It hurts competing firms, and it limits true, cooperative innovation. If idea A is fruitful, then two heads are better than one. When multiple firms with diverse problemsolving skills work on an idea, they can maximize the potential of the idea at a faster rate than when one firm works alone.

At the end of The Lego Movie (2014), Lord Business discovered that the true beauty of life was not found by following the instructions, but that it lay in the individual creativity of everyday people. When the people were encouraged to live life freely, happiness blossomed. Creative freedom must return to the people if innovation is to thrive and the economy is to prosper. The intellectual monopoly must dissolve into one of perfect competition, where no one can individually influence the market, but together, everyone can work at maximum efficiency. A uniquely human gift, creativity must be shared and supported. A more diligent study would examine a case of innovation lacking on a macroeconomic scale, and would include the consideration of sociological factors such as childhood education.

A marketing company based out of New York City is doing well and is looking to expand internationally. The CEO and VP of Operations decide to enlist the help of a consulting firm that you work for, to help collect data and analyze market trends.

You work for Mercer Human Resources. The Mercer Human Resource Consulting website (www.mercer.com) lists prices of certain items in selected cities around the world. They also report an overall cost-of-living index for each city compared to the costs of hundreds of items in New York City (NYC). For example, London at 88.33 is 11.67% less expensive than NYC.

More specifically, if you choose to explore the website further you will find a lot of fun and interesting data. You can explore the website more on your own after the course concludes.

https://mobilityexchange.mercer.com/Insights/cost-of-living-rankings#rankings

In the Excel document, you will find the 2018 data for 17 cities in the data set Cost of Living. Included are the 2018 cost of living index, cost of a 3-bedroom apartment (per month), price of monthly transportation pass, price of a mid-range bottle of wine, price of a loaf of bread (1 lb.), the price of a gallon of milk and price for a 12 oz. cup of black coffee. All prices are in U.S. dollars.

You use this information to run a Multiple Linear Regression to predict Cost of living, along with calculating various descriptive statistics. This is given in the Excel output (that is, the MLR has already been calculated. Your task is to interpret the data). Based on this information, in which city should you open a second office in? You must justify your answer. If you want to recommend 2 or 3 different cities and rank them based on the data and your findings, this is fine as well. This should be ¾ to 1 page, no more than 1 single-spaced page in length, using 12-point Times New Roman font. You do not need to do any calculations, but you do need to pick a city to open a second location at and justify your answer based upon the provided results of the Multiple Linear Regression. Think of this assignment as the first page of a much longer report, known as an Executive Summary, that essentially summarizes your findings briefly and at a high level. This needs to be written up neatly and professionally. This would be something you would present at a board meeting in a corporate environment.

City Cost of Living Index Rent (in City Centre) Monthly Pubic Trans Pass Loaf of Bread Milk Bottle of Wine (mid-range) Coffee

Mumbai 31.74 $1,642.68 $7.66 $0.41 $2.93 $10.73 $1.63

Prague 50.95 $1,240.48 $25.01 $0.92 $3.14 $5.46 $2.17

Warsaw 45.45 $1,060.06 $30.09 $0.69 $2.68 $6.84 $1.98

Athens 63.06 $569.12 $35.31 $0.80 $5.35 $8.24 $2.88

Rome 78.19 $2,354.10 $41.20 $1.38 $6.82 $7.06 $1.51

Seoul 83.45 $2,370.81 $50.53 $2.44 $7.90 $17.57 $1.79

Brussels 82.2 $1,734.75 $57.68 $1.66 $4.17 $8.24 $1.51

Madrid 66.75 $1,795.10 $64.27 $1.04 $3.63 $5.89 $1.58

Vancouver 74.06 $2,937.27 $74.28 $2.28 $7.12 $14.38 $1.47

Paris 89.94 $2,701.61 $85.92 $1.56 $4.68 $8.24 $1.51

Tokyo 92.94 $2,197.03 $88.77 $1.77 $6.46 $17.75 $1.49

Berlin 71.65 $1,695.77 $95.34 $1.24 $3.52 $5.89 $1.71

Amsterdam 85.9 $2,823.28 $105.93 $1.33 $4.34 $7.06 $1.71

New York 100 $5,877.45 $121.00 $2.93 $3.98 $15.00 $0.84

Sydney 90.78 $3,777.72 $124.55 $1.94 $4.43 $14.01 $2.26

Dublin 87.93 $3,025.83 $144.78 $1.37 $4.31 $14.12 $2.06

London 88.33 $4,069.99 $173.81 $1.23 $4.63 $10.53 $1.90

mean 75.49 $2,463.12 $78.01 $1.47 $4.71 $10.41 $1.76

median 82.2 $2,354.10 $74.28 $1.37 $4.34 $8.24 $1.71

min 31.74 $569.12 $7.66 $0.41 $2.68 $5.46 $0.84

max 100 $5,877.45 $173.81 $2.93 $7.90 $17.75 $2.88

Q1 66.75 $1,695.77 $41.20 $1.04 $3.63 $7.06 $1.51

Q3 88.33 $2,937.27 $105.93 $1.77 $5.35 $14.12 $1.98

New York 100 $5,877.45 $121.00 $2.93 $3.98 $15.00 $0.84

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.935824078

R Square 0.875766706

Adjusted R Square 80.12%

Standard Error 8.30945321

Observations 17

ANOVA

df SS MS F Significance F

Regression 6 4867.380768 811.2301279 11.74895331 0.00049963

Residual 10 690.4701265 69.04701265

Total 16 5557.850894

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept  35.63950178 15.41876933 2.311436213 0.043401141 1.284342794 69.99466077 1.284342794 69.99466077

Rent (in City Centre) -0.003212852 0.003974813 -0.808302603 0.437722785 -0.012069287 0.005643584 -0.012069287 0.005643584

Monthly Pubic Trans Pass 0.299650003 0.076964051 3.89337619 0.002993072 0.128163411 0.471136595 0.128163411 0.471136595

Loaf of Bread 16.59481787 6.713301249 2.47193106 0.032995588 1.636650533 31.55298521 1.636650533 31.55298521

Milk 2.912081706 1.98941146 1.463790555 0.173964311 -1.520603261 7.344766672 -1.520603261 7.344766672

Bottle of Wine (mid-range) -0.889805486 0.740190296 -1.202130709 0.257006081 -2.539052244 0.759441271 -2.539052244 0.759441271

Coffee -2.527438053 6.484555358 -0.389762738 0.704884259 -16.97592778 11.92105168 -16.97592778 11.92105168

RESIDUAL OUTPUT

Observation Predicted Cost of Living Index Residuals Standard Residuals City

1 34.32607137 -2.586071368 -0.39366613 Mumbai

2 53.21656053 -2.266560525 -0.345028417 Prague

3 49.41436121 -3.964361215 -0.603477056 Warsaw

4 58.63611785 4.42388215 0.673427882 Athens

5 73.08449538 5.105504624 0.777188237 Rome

6 86.50256003 -3.052560026 -0.464677621 Seoul

7 75.89216916 6.307830843 0.960213003 Brussels

8 67.7257781 -0.975778105 -0.148538356 Madrid

9 90.51996071 -16.45996071 -2.50562653 Vancouver

10 81.07358731 8.866412685 1.349694525 Paris

11 83.80564633 9.134353675 1.390481989 Tokyo

12 80.02510391 -8.37510391 -1.274904778 Berlin

13 82.41624318 3.483756815 0.530316788 Amsterdam

14 97.75654811 2.243451893 0.341510693 New York

15 87.73993924 3.040060757 0.462774913 Sydney

16 86.81668291 1.11331709 0.169475303 Dublin

17 94.36817468 -6.038174677 -0.919164446 London

I want to paraphrase for this papers.

The purpose of this report introduces a useful tool, which estimates dust emission and dispersion. DUSTRAN is dust emission and transport model developed by Pacific Northwest National Laboratory. According to Shaw (2008), “(DUSTRAN), which calculates atmospheric dust concentrations that result from both natural and human activity.” We show three examples that it was applied to actual situations: dust concentration with observations of wind erosion in southeastern Washington, contaminated dust emission during high winds in southern Iraq, and transport of sea salt aerosols.

          First, a research group (Shaw, et al., 2008) shows both the DUSTRAN algorithm and the comparison of simulated dust concentration with data at the site. The measurements were made in southeastern Washington to monitor site recovering after a fire that occurred in 2001.The DUSTRAN has a dust emissions model for calculating emissions due to both natural and human activity. Moreover, it makes possible to get dust emission for specific particle size such as PM2.5, PM10, and so on. They also explain (Shaw, et al., 2008) the calculation of the atmospheric concentration of particulate matter caused by wind erosion, and it requires soil composition, characteristics of the soil crust vegetation cover, and soil moisture. They concluded that the comparisons had provided availability of the DUSTRAN as to estimate dust emission, however, they also suggested the importance of soil moisture data and the weakness of the DUSTRAN that it tends to overestimate PM10 when dust concentrations are low.

         Second, Zannetti, Daly, & Freedman (2015) applies it to air pollution problems at Qarmat-Ali, Basra, Iraq, during 2003. Before their study, the soil had been contaminated by sodium dichromate. Since people who worked at the site have claimed that their health was threatened by exposure to dust contaminating hexavalent chromium [Cr(VI)], they tried to build a model of the situation. To estimate the Cr(VI) concentration in the soil, they used the AERMOD model and the DUSTRAN model. The AERMOD model was used to calculate the ambient concentration of PM10/Cr(VI). While the AERMOD is widely used in the scientific field as a certain technique for estimating atmospheric transport of pollutants, including particulate matter and any material attached to particles, the author describes that “the AERMOD model is routinely used without any additional recalibration with local data, ...” (Zannetti, Daly, & Freedman, 2015). As an improvement of this point, they combined the DUSTRAN that determines the wind erosion at the local site with it. To calculate the emission rate of dust due to wind erosion, DUSTRAN gives a threshold value which depends on three parameters extracted from a local data: the soil moisture, the soil composition, and the surface roughness. If the wind velocity is larger than the value of the threshold, it assumes that dust is emitted from a source area. In addition to calculating the amount of the dust emission, DUSTRAN provides estimations of the particle size distribution in the dust. And then, DUSTRAN can estimate the amount of particulate matter contained in the dust emission. They finally concluded that they were able to perform a partial validation of the model which is combined generally used model (AERMOD) and the wind erosion process (DUSTRAN), by comparing the simulation outputs with measurement data at the site.

            Third, Jensen and his research group (Jensen, et al., 2016) proved the ability of DUSTRAN to model the transport of sea salt aerosols (SSA). By comparing their results from the DUSTRAN simulations with meteorological data taken at the near coast Maine Yankee Nuclear Power Plant (NPP) and the Environmental Protection Agency-measured CASTNET data from Acadia National Park (NP). As mentioned above DUSTRAN includes dispersion models, however, it is not specialized to a specific matter. The author tried to apply it and evaluate its potential for the modeling of chloride particulate matter by using one of the general dispersion models: CALPUFF which is suitable for mid-size domains of up to 200 km. The author concluded that “Comparisons of simulated and measured data have provided encouragement as to the potential practical value of DUSTRAN in predicting the dispersion of atmospheric chloride from the SSA” (Jensen, et al., 2016). The author mentioned, more experimental data and multiple data sets for DUSTRAN’s input may improve accuracy of a simulation. In conclusion, we have studied applications of DUSTRAN, a dust dispersion modeling system developed by Pacific Northwest National Laboratory, to actual problems: dust concentration with wind erosion in southeastern Washington, contaminated dust emission in southern Iraq, and transports of salt salt aerosols. Each research applied a general dispersion model included in the DUSTRAN system to simulate own situation, and proved the potential of it to estimate the concentration of dust containing an interesting matter such as hexavalent chloride, PM10, and chloride. To get precise results, however, these researches pointed out the importance of the local data measurements at the site. Because wind velocity and the soil moisture contribute to the emission rate simulation, local measurements at the site should be done carefully not to make lacks of data. Finally, as an application of DUSTRAN to nuclear study fields, it has a possibility to simulate an atmospheric transportation of dust containing a radionuclide after an accidental release from nuclear facilities. In this case, it also needs a local meteorological data, so tireless efforts of measurements are an essential factor for simulation.

References

Jensen, P., Tran, T., Fritz, B., Rutz, F., Ross, S., Gorton, A., . . . Trainor, K. (2016). Preliminary Evaluation of the DUSTRAN Modeling Suite for Modeling Atmospheric Chloride Transport. Air Quality, Atmosphere & Health,10(1), 25-31. doi:10.1007/s11869016-0404-5

Shaw, W. J., Allwine, K. J., Fritz, B. G., Rutz, F. C., Rishel, J. P., & Chapman, E. G. (2008). An evaluation of the wind erosion module in DUSTRAN. Atmospheric Environment,42(8), 1907-1921. doi:10.1016/j.atmosenv.2007.11.022

Zannetti, P., Daly, A. D., & Freedman, F. R. (2015). Dispersion modeling of particulate matter containing hexavalent chromium during high winds in southern Iraq. Journal of the Air & Waste Management Association, 65(2), 171-185. doi:10.1080/10962247.2014.981317