12.2.1 Classification of Types of Activities and Inventories

A total of ten risks are assessed. Each risk, the type of risk, and its associated substances causing risk are listed in Table 12.1. Figure 12.2 depicts the location of risks throughout the city.

12.2.2 Estimation of Consequences

Step 2 involves estimating the consequence of each risk event. Equation (12.1) is used to assess consequences.

(12.1)

where:

A = affected area (ha)

δ = population density in a defined populated area (persons/ha)

f_A = correction factor for the populated area (part of circle)

f_d = correction factor for the populated area (distances)

f_m = correction factor for mitigation effects

Using this equation allows you to solve for C_a,s, which is the number of consequences (number of fatalities/accident) of an accident caused by the substance (subscript s) for each identified activity (subscript a). The consequence for each risk will be detailed in Sections 12.2.3–12.2.6.

12.2.3 Estimation of Probabilities

Step 3 is the estimation of the probability, or frequency, of each risk for both fixed installations and transportation risks. To calculate the frequency (P_i,s, number of accidents per year) of accidents involving a hazardous substance (subscript s) for each hazardous fixed installation (subscript i), it is necessary to calculate the related probability number, N_i,s. N_i,s can be calculated using Equation (12.2).

(12.2)

where:

N^* _i,s = average probability number for the installation and substance

n_l = probability number correction parameter for the frequency of loading/unloading operations

n_f = probability number correction parameter for the safety systems associated with flammable substances

n_o = probability number correction parameter for the organizational and management safety

n_p = probability number correction parameter for the wind direction toward the populated area

The relationship between N_i,s and P_i,s can be represented by Equation (12.3).

(12.3)

Therefore, once N is known, it is possible to solve for P, the frequency. International Atomic Energy Agency (1996) also includes a lookup table for common values of N, which gives us the corresponding P value.

Similarly, to calculate the frequency (P_t,s, number of accidents per year) of accidents during the transportation (subscript t) of a hazardous substance (subscript s), it is also necessary to calculate the related probability number, N_t,s, which can be calculated using Equation (12.4).

(12.4)

where:

N^* _t,s = average probability number for transportation of the substance

n_c = probability number correction parameter for the safety conditions of the transport system

n_tδ = probability number correction parameter for the traffic density

n_p = probability number correction parameter for wind direction toward the populated area

Again, the relationship between N_t,s and P_t,s can be represented by Equation (12.3), and the same table in International Atomic Energy Agency (1996) can be used to look up P values for common values of N. The frequency of each risk will be detailed in Sections 12.2.4–12.2.6.

Finally, once the estimated consequence and frequency are determined for each risk, those values can be used to determine the societal risk of each incident, and from there, the risk incidents can be prioritized. To address societal risk and prioritization of all dangers, a case application is necessary – this is addressed in Section 12.2.4, along with recommendations.

12.2.4 Illustrated Example: Classification of Types of Activities and Inventories

12.2.4.1 Risk Scenario #1: Ice Rink

The ice rink is selected since it serves as storage for ammonia. Ammonia is needed because it is used in the mechanical refrigeration system in ice rinks (US Environmental Protection Agency 2018). A Montreal ice rink claims they could bring their ammonia charge down to 175 lbs (O’Shea 2021). Ice rinks must report annual chemical inventory to the state if they have more than 500 pounds of ammonia. Ice rinks with more than 10,000 pounds of ammonia must prepare a risk management plan (US Environmental Protection Agency 2018). In this case, we assume the charge of 175 lbs is per month. Therefore, since 1 ton is equal to 2,000 lbs, the rink uses 1.05 tons of ammonia per year. The conversion for this weight is 175 lbs per month * 12 months per 1 year * 1ton per 2,000 lbs = 1.05 tons per year. Figure 12.3 depicts the location of the ice rink in Portland.

Before solving for the consequence, numerical values for the variables in Equation (12.1) must be solved first. Various tables from International Atomic Energy Agency (1996) are used to find these values. To begin, Table II is used to find the reference number for the substance of interest in relation to the fixed installation. From the table, the reference number for ammonia in relation to an ice rink is 31. The next step is to find the effect category for the risk. By knowing the weight in tons, and the reference number, Table IV could be used to find the effect category, which in this case is CII. With the effect category, Table V can be used to find the maximum effect distance and effect area, which in this case is 100 m and 1.5 ha (A), respectively. From there, table VI can be used to estimate the population density in the area of interest. In this situation, it is estimated that the populated density, δ, is 80 ha since the ice rink is in a busy residential area and an ice rink is a busy place with a lot of people entering and exiting daily.

Once the effect category and maximum effect distance are known, an fA & fd Diagram can be created to solve for those two values and fm. In the diagram, it is best to draw your area of interest, which has a radius of the maximum effect distance, found in Table V. Then, draw the affected area. For an effect category of CII, the affected area is a circle with a diameter of approximately the maximum effect distance. RRA focuses on the worst-case scenario of all situations. Therefore, in this diagram, the wind blows the affected area toward the highest population. fA is determined by estimating the average angle of the populated area within the circular area of interest, then by taking that estimated angle and the effect category to find the value of fA using table VII. In this case, fA is estimated to be about 80% of the area of interest, and for an effect category of CII, table VII shows that the value for fA is 1.0. fd is an estimation of the fraction of the “length or depth” of the populated density compared with the radius of the area of interest. In this case, it is estimated that the length of the population covered approximately 80% of the length of the radius. Therefore, fd is 0.8. As for fm, proposed values for fm can be found in table VIII. For this case, fm is estimated to be 0.1. Figure 12.4 depicts the fA & fd diagram of the ice rink. By using the abovementioned values, the consequence can be calculated by using Equation (12.1). Solving this equation gives you a value of 9.6 fatalities or accidents.

The next step is to solve for the values needed to find the frequency. Again, various tables from International Atomic Energy Agency (1996) are used to see these values. Since the reference number is already known, Table IX could be used to find the average probability number for fixed installations, N^* _i,s. For the ice rink, this value is 6. The ammonia is assumed to be loaded/unloaded one to two times per month. With that information, it is estimated that ten to fifty loadings/unloadings per year are done, so by using Table X, n_l is estimated to be 0. To solve for n_f, Table XI is used. After looking at this table, it is determined this value is not applicable since the substance of focus is not a flammable gas. Therefore, a value of 0 is used for nf in Equation (12.2) when solving for frequency. It is assumed that the ice rink has an average industry practice relating to safety, so n_o is 0 according to Table XII. Finally, n_p is estimated to be 0.5, using Table XIII, since this risk has an effect area category of CII and less than 100% of the area in the effect area is where people live. By substituting these values into Equation (12.2), N_i,s is found to be 6.5. By using Table XIV, P_i,s is found to be 3*10⁻⁷ events per year. Table 12.2 is a summary of constants and values for the ice rink scenario. Due to the limited space allocated to this research, the rest of the risk scenarios are summarized.

Description	Ice rink	Location	1
Reference number (Table II)	31	Average probability number, N*i,s (Table IX)	6
Weight (tons)	1.05	Correction parameter for frequency of load/unload, n (Table X)	0
Effect category (Table IV)	CII	Correction parameter for safety systems of flammable substances, n (Table XI)	0
Effective max distance (m) (Table V)	100	Correction parameter for the organizational and management safety, no (Table XII)	0
Effective area, A (ha) (Table V)	1.5	Correction parameter for wind direction in area, np (Table XIII)	0.5
Population density, δ (persons/ha) (Table VI)	80	Probability number, Ni,s Ni,s = N*i,s + n1 + nf + no + np	6.5
Correction factor for distribution of main populated area(s), fA (Table VII)	1	Frequency, Pi,s (accidents/year) (Table XIV)	3.0E−07
Correction factor for mitigation, fm (Table VIII)	0.1
Area correction factor, ⅛	0.8
Consequence, Ca,s (fatalities/accident) Ca,s = A * δ * fA * fd * fm	9.6

12.2.4.9 Risk Scenario #9: Gas Transportation

Gas transportation is selected because of the risk involved with carrying large amounts of petrol in one vehicle. In this gas transportation route, petrol is transported from the gas distribution center to local gas stations throughout this city. One centrally located gas station is chosen for this assessment, as suggested in Figure 12.5. The red path shows the path from the distribution center to the gas station and the yellow section shows the most populated 1 km area along the path, which will be the area of focus. The most populated and busy intersection is selected within that yellow section to continue the assessment. Table 12.10 summarizes the constants and values for the transportation scenario.

Description	Gas Transportation		Location	N/A
Reference Number (Table II)	6		Average Probability Number, N*t,s (Table XV)	8.5
Weight (tons)	32		International Transport code (Table XVI)	Combination first digit 3 and a digit 3
Effect Category (Table IV)	BII		Correction Parameter for Safety Conditions, nc (Table XVII)	0
Effective Max Distance (m) (Table V)	50		Correction Parameter for Traffic Density, ntδ (Table XVIII)	−3
Effective Area, A(Ha) (Table V)	0.4		Correction parameter for Wind Direction, np (Table XIX)	0
Population Density, δ (persons/Ha) (TableVI)	80		Probability Number, Nt,s Nt,s = N*t,s + nc + ntδ +np	5.5
Correction Factor for Distribution of Main Populated Area(s), fA (Table VII)	1		Frequency, Pt,s (accidents/year) (Table XX)	3.00E–06
Correction Factor for Mitigation, fm (Table VIII)	1
Area Correction Factor, fd	1
Consequence, Ca,s (fatalities/accident) Ca,s = A* δ* fA* fd* fm	32

12.2.4.10 Risk Scenario #10: Chlorine Transportation

Chlorine transportation is selected because of the risk involved with carrying large amounts of chlorine in one vehicle. In this chlorine transportation route, chlorine is transported from the trade port to pools throughout this city. For this assessment, one centrally located competition-sized pool is chosen. The red path shows the path from the trade port to the competition pool, and the yellow section shows the most populated 1 km area along the path, which will be the area of focus. The most populated and busy intersection is selected within that yellow section to continue the assessment, shown in Figure 12.6. Tank trailers used to transport chlorine on roads and highways have a capacity of 15–20 tons (SafeRack 2022). The worst-case scenario is used for this risk assessment, so a capacity of 20 tons of chlorine per truck will be used. Table 12.11 summarizes the constants and values for the chlorine transportation scenario.

Description	Chlorine transportation		Location	N/A
Reference number (Table II)	32		Average probability number, N*t,s (Table XV)	9.5
Weight (tons)	20		International transport code (Table XVI)	26 265 266
Effect category (Table IV)	Elll		Correction parameter for Safety Conditions, nc (Table XVII)	0
Effective max distance (m) (Table V)	500		Correction parameter for traffic density, ntδ (Table XVIII)	‒2.5
Effective area, A(ha) (Table V)	8		Correction parameter for wind direction, np (Table XIX)	0
Population density, δ(persons/Ha) (Table VI)	80		Probability number, Nt,s Nt,s = N*t,s + nc + ntδ + np	7
Correction factor for distribution of main populated area(s), fA (Table VII)	1		Frequency, Pt,r (accidents/year) (Table XX)	1.00E‒07
Correction factor for mitigation, fm (Table VIII)	0.1
Area correction factor, fd	1
Consequence, Ca,s (fatalities/accident) Ca,s = A * δ * fA * fd * fm	64

12.2.5 Societal Risk and Prioritization

The International Atomic Energy Agency (1996) suggests that the estimation of societal risk can be done as follows: (i) by classifying each activity using a scale of consequence classes and a scale of probability classes (the scales are shown in the manual), (ii) if certain activities present risks to the public from different substances, which can each cause accidents independently of each other, then sum up the risk from the substances that have the same class of consequences, and (iii) map all activities on a frequency vs. consequence matrix. Table 12.12 summarizes each risk activity’s classification based on each risk’s consequence and probability. After classifying each activity in Table 12.12, Step 1 of RRA is complete. And since only one substance for each activity is selected, we can skip Step 2.

Step 3 involved plotting the consequence and frequency of each activity in terms of the consequence vs. frequency matrix. The overall results are depicted in Figure 12.7.

Figure 12.8 displays a zoomed-in result capturing the bottom left side as indicated by the rectangle in Figure 12.7. In this case, gas transportation has a very high frequency compared to other elements. Forge risk has a very high consequence compared to the others. Pest control service, ice rink, and the transportation of chlorine have the highest frequency. Also, this diagram shows that the gas distribution center risk has the next highest consequence. The rest of the risk activities have relatively low frequency and consequence. The ALARA (As Low As Reasonably Achievable) principle can determine the societal risk. Thresholds are drawn in Figure 12.8 to depict tolerable risks, intolerable risks, and the ALARA region. The ALARA region needs more information before risks can be considered tolerable or intolerable. The threshold for acceptability is established by accounting for the probability class and consequence rather than just one or the other.

To prioritize risks, first, the risks in the intolerable region must be addressed. Then, the risks in the ALARA region should be evaluated further to decide if they can be deemed tolerable for reasons such as impractical mitigation methods or cost of correction exceeding improvements gained. ALARA risks deemed intolerable should be corrected next. Lastly, risks in the tolerable region do not need any modifications unless the consequence or frequency increases. Risks in the tolerable region only need to be monitored to ensure they do not worsen and cross into the ALARA or intolerable region. Table 12.13 depicts risks, their region, and a description of the risk, consequence, and frequency value.

12.2.6 Recommendations

The following recommendations are based on the results of the assessment and risk prioritization in Section 12.2.5:

12.3.1 Step 1: Identify Critical Routes and Assets

The comprehensive plan vision for Portland is as follows (City of Portland 2022):

Portland is a prosperous, healthy, equitable and resilient city where everyone has access to opportunity and is engaged in shaping decisions that affect their lives

Taking this mission statement, five critical routes are identified. Two different routes from the trade port to a pool are identified, as well as three routes from the gas distribution center to a popular gas station. Figure 12.9 depicts the routes involved. These routes involve the transportation of hazardous goods.

These five routes all cross over one intersection, so this intersection is evaluated in more detail. Four critical assets relating to the mission statement surround this intersection, including a bank, school, bus station, and hospital, thus making this intersection a critical intersection. Therefore, there are now five essential assets of this area, which will be evaluated in further detail throughout this assessment. Figure 12.10 shows the location of each critical asset.

Once identified, each critical asset is categorized as infrastructure, facilities, equipment, or personnel, as suggested in Table 12.14. The critical infrastructure (CI) – bus station, school, hospital, and bank – will be the main focus throughout this assessment. Still, the equipment and personnel of those facilities will be used for more detailed analysis when necessary.

Once critical routes and assets are identified, critical asset scoring must be completed. This is done through established critical asset factors and a value assigned to each factor. The value assigned to each factor will be ranked on a scale of 1 to 5, 1 being of very little importance and 5 being extremely important. Using Science Applications International Corporation’s (2002) guide, Table 12.15 is developed to show each critical asset factor, its value, and a description of the factor. Next, each of the five main critical assets is scored against the factors established in Table 12.15, as suggested in Table 12.16, indicating the most critical assets. And in this case, the hospital is the most critical, followed by the school and the critical intersection. The bus station and the bank are the least critical. This concludes Step 1 of the VA.

12.3.2 Step 2: Assess Vulnerabilities

Step 2 identifies and evaluates critical assets regarding their weaknesses and other vulnerabilities. Each critical asset is scored against multiple vulnerability factors. These vulnerability factors included visibility and attendance, access to the asset, and site-specific hazards. Each of these three factors is broken into two sub-elements. Factors and their sub-elements are as follows:

• Visibility and attendance
  • – Level of recognition (A)
  • – Attendance/users (B)
• Access to the asset
  • – Access proximity (C)
  • – Security level (D)
• Site-specific hazards
  • – Receptor impacts (E)
  • – Volume (F)

Each asset’s vulnerability is scored on a scale of 1 to 5 based on a table in Science Applications International Corporation’s (2002) research, which described each level of the scale for each vulnerability factor sub-element. Once each critical asset’s vulnerability is scored against the six sub-elements, the total vulnerability score, y, is calculated using Equation (12.5).

(12.5)

Table 12.17 depicts the results from the vulnerability factor scoring. These results show that the bus station is the most vulnerable asset, followed by the hospital, intersection, school, and bank, consecutively. This concludes Step 2.

12.3.3 Step 3: Assess Consequences

Step 3 is to identify assets with the most significant risk based on the asset’s criticality and vulnerability. The critical asset scoring completed in Step 1 and the vulnerability factor scoring in Step 2 are used to determine the criticality and vulnerability assets. Equations (12.6) and (12.7) are used to plot the criticality vs. vulnerability of each asset.

(12.6)

(12.7)

where x is the critical asset score for each critical asset, C_max is the maximum critically score (which in this case is 23), and y is the vulnerability score for each critical asset. By using these equations, X and Y for each asset could be calculated. These calculations are shown in Table 12.18.

A criticality and vulnerability matrix with four quadrants is then developed. Critical assets located in Quadrant I have high criticality and high vulnerability. Assets in Quadrant II have low criticality and high vulnerability. Assets in Quadrant III have low criticality and low vulnerability. Assets in Quadrant IV have high criticality and low vulnerability. Figure 12.11 depicts the criticality and vulnerability matrix. This concludes Step 3.

12.3.4 Step 4: Identify Countermeasures

Step 4 is to identify typical countermeasures to protect critical assets against an attack. Table 12.19 depicts a list of proposed countermeasures, the corresponding critical asset category, and the countermeasure function adapted from Science Applications International Corporation (2002).

12.3.5 Step 5: Estimate Countermeasure Costs

Step 5 estimates the capital, operating, and maintenance costs of the countermeasures proposed in Step 4. All countermeasures are broken down into “packages” based on the critical asset category that the countermeasure would assist. These “packages” are based on the “Critical asset category” column from Table 12.19. If a countermeasure is applied to a critical asset category, it is added to that critical asset category’s package. Each type of cost is determined to be high (H), medium (M), or low (L) based on values from Science Applications International Corporation (2002). Costs are determined based on estimates and data from Science Applications International Corporation (2002). The countermeasure function column is the same as the information found in Table 12.19. Table 12.20 shows the countermeasure cost estimates for infrastructure. Table 12.21 shows the countermeasure cost estimates for facilities. Table 12.22 shows the countermeasure cost estimates for equipment. Table 12.23 shows the countermeasure cost estimates for personnel.

12.3.6 Step 6: Security Operational Planning Development

An operational security plan is meant to prevent potential risks and consequences. The plan includes developing countermeasures, such as training and exercises, as well as other security measures. The scope for an operational security plan for Portland would be as follows:

To identify and prevent risks to protect personnel, deter criminal and/or terrorist activities and eliminate unauthorized access to critical assets.

Cloutier (2021) suggests a five-step process for operational security plans:

1. identify critical information
2. analyze threats
3. analyze vulnerabilities
4. assess the risk
5. determine countermeasures

These five steps are very similar to the steps in the VA. During these steps, critical information is identified by determining the critical assets of the area (VA Step 1). Threats are analyzed after establishing and assigning values to the critical asset factors (VA Step 1). Vulnerability is analyzed during the VA Step 2. The risk is assessed during the VA Step 3, where the consequence of risk on each critical asset is assessed. And finally, during the VA Steps 4–5, countermeasures are identified as well as the estimated cost for each countermeasure.

Now that those activities have been completed during this VA for Portland, the next step of the operational security plan is to implement the countermeasures. Once implemented, the success of the countermeasure would be evaluated to determine if the results are satisfactory or not. If the results are not satisfactory, these five steps would be repeated until the results are satisfactory.

12.4.1 Airborne (Air Pollution)

Figure 12.12 is taken from AQICN (https://aqicn.org/city/usa/oregon/portland) and shows Portland’s real-time air quality index as of Saturday, April 16, 2022 at 3 p.m. This map shows places where air quality is measured. As shown in the map, all the measurements in Portland are green, meaning the air quality is considered “good” and minimal pollutants are detected in the air.

AQICN also lists changes in air quality over the last forty-eight hours. Figure 12.13 breaks down pollution by different air pollutants and lists the minimum and maximum values for each. The overall air quality in Portland is an 18, which is considered “good.” The lower the number, the better the air quality because fewer pollutants are detected. This figure also shows that the pollution consists of mainly fine particle matter (PM_2.5) and nitrogen dioxide (NO₂). NO₂ is found in pollution from all three sources of continuous emissions listed previously, which all contribute to the total emission count for the city.

AQICN also displays historical data related to air pollution. For example, Figure 12.14 shows the daily data for NO₂ from 2020 to April 16, 2022. This figure shows that over the last few years, a low amount of NO₂ has been detected in emissions. Therefore, despite many continuous emission sources throughout the city, they do not produce an overwhelming or dangerous amount of NO₂.

12.4.2 Waterborne (Water Pollution)

EnviroAtlas (https://www.epa.gov/enviroatlas) shows water pollution throughout the Portland area. Figure 12.15 shows all impaired waterways in red, while Figure 12.16 shows the waterways that are assessed in blue. These waterways are assessed and determined to be impaired as they are degraded and do not meet the standards for many designated beneficial uses, such as aquatic life and drinking water.

Nitrate violations in surface water systems are also a concern. Again, higher values indicate a higher probability of a violation. This violation means more nitrate, such as NO₂, is in the surface water system than is allowed or safe. Overall, Portland has a better-than-average probability of a violation of nitrate in a surface water system, according to the scale in Figure 12.17. However, the northern outskirts of Portland have a higher probability, so the previously listed sources of continuous emissions, or similar sources, are likely found in those areas. Areas south of Portland have a lower probability of a violation, so there are likely not as many continuous emissions sources. Overall, there is little pollution in the surface water system in the center and other main areas of Portland, unlike the outskirts.

Figure 12.18 shows the nitrate violation in groundwater systems. A water quality index map from 2020 is shown in Figure 12.19. This map displays the water quality in certain areas in and around Portland and whether that measurement is better or worse or if there is no change from the previous year.

12.4.3 Soil (Ground Pollution)

EnviroAtlas can also show the movement of nitrogen attached to the soil particles eroding from the surface of agricultural fields, as depicted in Figure 12.20. Green areas have smaller amounts of nitrogen than blue or purple areas. High levels of nitrogen movement mean there is likely a high level of breakdowns of nitrates, meaning there could be a lot of pollution, such as NO_2, in the soil. Areas shaded in blue or purple have higher nitrogen levels, indicating a higher probability of pollution in the soil. NO₂ is found in the three sources of continuous emissions listed previously, meaning those sources or similar locations are likely located in the outskirts of Portland. Therefore, the soil on the edges of Portland has more pollution than the soil in the city’s center. Again, this makes sense because the areas on the outer edges, specifically the northern area of Portland, are more commercial and industrial than the center of Portland, which is more residential.

12.4.4 Risks and Associated Consequences

The more pollution in the environment (i.e. air, water, ground), the more at-risk the city’s citizens are. These risks can lead to consequences, including mortality and morbidity. Air pollution is the most significant risk to the health of the citizens in the city. Citizens who spend the most time in risk areas are more likely to develop health problems in the future. Figure 12.21 shows the cancer risk per million due to cumulative air toxics. Figure 12.22 shows respiratory risk due to cumulative air toxics. Interestingly, these numbers suggest that all people in Portland have the same risk category (i.e. they all have the same risk of developing cancer and respiratory issues due to air toxics, including pollution). Figure 12.23 depicts the risk of developing a non-cancer neurological risk due to cumulative air toxics, including pollution. Figure 12.24 shows the risk of cancer due to formaldehyde air toxics. Figure 12.25 shows the respiratory risk due to formaldehyde air toxics.

Although the data in both figures use different data and units to create their scales, the same color codes represent similar risk levels. The majority of Portland is all the same color, meaning the same risk. This makes sense because all buildings, including residential homes, businesses, apartment buildings, etc. have floors and furniture made from composite wood. Assuming these items are dispersed equally throughout the city among all buildings, the entire city has the same risk. Therefore, all citizens in Portland have roughly the same chance of developing the two issues due to formaldehyde.

12.4.5 EMP Assessment

EMP Assessment (EMPA) assesses EMP in an area at varying heights. EMP is a pulse of high-intensity electromagnetic radiation generated especially by a nuclear blast high above the earth’s surface and held to disrupt electronic and electrical systems (Zhang et al. 2022). EMP has the potential to affect extensive areas. If an area is affected, CIs will be severely impacted (National Coordinating Center for Communications 2019). EMP devices, including weapons and missiles, can explode in the air and release an electromagnetic wave, disrupting the electrical grid and causing damage to electronics such as computers, cell phones, radios, etc. (Cybersecurity and Infrastructure Security Agency 2022). Figure 12.26 visually represents how a high-altitude EMP detonation affects an area when it explodes (Security Team 2022).

The area that an EMP explosion covers depends on the height of the explosion. The EMP radius can be determined as long as the height of the burst (HOB) is known. The HOB and EMP radius are related using Equation (12.8) (EMPEngineering.com 2022; National Coordinating Center for Communications 2019).

(12.8)

The following analysis calculates how large the EMP radius would be if the HOB is at 25 km, 100 km, and 400 km above the center of Portland, and discusses which areas would be affected at each HOB. Since Portland is on the west coast, less land will be directly affected than if the blast occurred in a more central state, so the blast will also cover parts of the Pacific Ocean. If there are ships in the affected area, their electronics, such as radios, can be damaged too. Using Equation (12.8), a HOB of 25 km, the EMP radius is:

At the height of 25 km, the entire state of Oregon and Ishington area would be affected, including surrounding states as well as parts of Canada, as depicted by Figure 12.27.

At the height of 40 km, the entire state of Oregon and Ishington would be affected, including parts of Canada, Idaho, California, and Nevada, as suggested by Figure 12.28. At the height of 400 km, roughly 50% of the United States and Canada and Mexico would be affected, as suggested in Figure 12.29.

Figure 12.30 depicts EMP radius for the HOBs at 25 km, 40 km, 100 km, and 400 km, allowing for a better comparison of how the height affects EMP radius.

From all these figures, it is easy to see how an EMP blast in Portland could affect many areas across the continent. EMP blasts can be detrimental to a country because an extremely large area can be affected by just one blast. More specifically, if the blast is released above a location more in the center of the country, such as Omaha, NE, the blast could have the potential to affect practically all of the contiguous United States, as well as parts of Canada and Mexico, if the blast occurred at 400 km, as suggested by Figure 12.31.

Preventing an EMP attack is impossible, and reducing its effects is challenging (Electromagnetic Pulse Commission 2008). However, the Department of Homeland Security mitigates risks (Cybersecurity and Infrastructure Security Agency 2022).