Industrial Siting for Sustainable Communities

Industrial Siting for Sustainable Communities | Andrew Garrison

INDUSTRIAL SITING FOR SUSTAINABLE COMMUNITIES: CAN A STEEL MILL BE A VALUED PARTNER IN A SUSTAINABLE COMMUNITY?

ANDREW DENNIS GARRISON

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF URBAN AND REGIONAL PLANNING

UNIVERSITY OF FLORIDA

2020

Industrial Siting for Sustainable Communities | Andrew Garrison

To Tara, Will, Izzy, and Abby - whose love and patience encourage me to achieve my dreams.

Industrial Siting for Sustainable Communities | Andrew Garrison

TABLE OF CONTENTS

TABLE OF CONTENTS ...... 4 LIST OF FIGURES ...... 5 LIST OF ABBREVIATIONS ...... 6 ABSTRACT ...... 7 INTRODUCTION ...... 9 PURPOSE OF THE STUDY AND RESEARCH QUESTION ...... 12 SCOPE, ASSUMPTIONS, AND LIMITATIONS ...... 13 LITERATURE REVIEW ...... 17 METHODOLOGY ...... 25 DATA COLLECTION ...... 28 INTERPRETATION AND DISCUSSION OF ANALYSIS ...... 44 CONCLUSION ...... 47 LIST OF REFERENCES ...... 51 BIOGRAPHICAL SKETCH ...... 53 APPENDIX 1 – STEEL PLANTS IN NORTH AMERICA ...... 54 APPENDIX 2 – DETAIL OF DISTANCES FROM PLANT TO NEAREST MAJOR CITIES ...... 56

Industrial Siting for Sustainable Communities | Andrew Garrison

LIST OF FIGURES

Figure 1 - ArcelorMittal Burns Harbor, Burns Harbor IN (The Center for Land Use Interpretation 2020) ...... 9 Figure 2 – Inter-relationship of sustainability components as prepared by Terouhid et al...... 26 Figure 3 - Steel mill sites in North America (AIM Market Research 2013). See appendix 1 for detailed copy...... 29 Figure 4 - Google map sample of Gerdau Midlothian, Midlothian TX (maps.google.com 2020) ...... 30 Figure 5 - Completed data table capturing plant attributes ...... 36 Figure 6 - Sample city attribute data with US Census Bureau and geo-coded data...... 39 Figure 7 - Excel formula for calculating the distance in miles by two coordinate points ...... 41 Figure 8 - Sample of combined analysis merging plant and city data with distance calculation. See appendix 2...... 41 Figure 9 - Analysis results including both BOF and EAF facilities ...... 43 Figure 10 - Analysis results including EAF facilities only ...... 44 Figure 11 - Line chart showing the trend of distance in miles from plant to city over time ... 45

Industrial Siting for Sustainable Communities | Andrew Garrison

LIST OF ABBREVIATIONS

BOF Basic Oxygen Furnace EAF Electric Arc Furnace GRI Global Reporting Initiative LCA Life Cycle Assessment LCI Life Cycle Inventory LULU Locally Unwanted Land Use LNG Liquefied Natural Gas MSA Metropolitan Statistical Area NIMBY Not In My Backyard

Industrial Siting for Sustainable Communities | Andrew Garrison

ABSTRACT

Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Urban and Regional Planning ABSTRACT

INDUSTRIAL SITING FOR SUSTAINABLE COMMUNITIES: CAN A STEEL MILL BE A VALUED PARTNER IN A SUSTAINABLE COMMUNITY? By

Andrew Dennis Garrison April, 2020

Chair: Dr. Kathryn Frank Cochair: Dr. Christopher Silver Major: Master of Urban and Regional Planning

Understanding that industrial activities create negative consequences such as air pollution, water pollution, noise and light pollution, traffic congestion, and so on, it is logical to place industry away from urban centers. From a public engagement perspective,

NIMBYism and LULUism in public perception push planners to site polluting and visually unappealing facilities as far from residential property owners as possible. Yet doing so separates the industrial capital (plant, property, and equipment) from two key stakeholders in industrial processes: labor to operate the facility, and end consumers of the products.

Naturally, separating the plant from one of its key inputs and its end market creates additional transportation steps – moving labor to the plant and moving products from it – using other carbon-intensive transportation methods.

This research project offers to the planning community introductory information concerning the locations of steel mills in the United States relative to major urban areas.

Through a detailed, data-centric analysis, this project identifies a historical trend toward

Industrial Siting for Sustainable Communities | Andrew Garrison siting steel away from urban centers. Further, through a review of available scholarly and industry literature concerning sustainability objectives and facility siting, this research project provides foundational context for future research into industrial facility siting strategies.

Finally, the quantitative analysis yields the average distances from US steel mills to largest cities for purposes of trend analysis over time.

Industrial Siting for Sustainable Communities | Andrew Garrison

INTRODUCTION

For many, the word industry invokes images of smoke spewing from the tops of smokestacks and wastewater streaming from the corroding pipes of ominous factories. In many ways, these depictions of

Figure 1 - ArcelorMittal Burns Harbor, Burns Harbor IN (The Center industry as an opponent to for Land Use Interpretation 2020) environmental sustainability are correct. References to the environmental damage caused by different industrial actors abound – the Deepwater Horizon disaster in 20101 as one example

– and a wealth of data exists on the consequences of industrialization on the Earth’s environment2. The view of industrialization as the source of many environmental ills, therefore, would hold valid. Over the course of industrial history, humanity’s ability to mass produce products has led to landscape destruction, air-pollution, growth in demands on waste processing, and those are only the environmental consequences.

As planners work to implement and attain environmental sustainability objectives, one might question the contribution of industrial activity towards those objectives – after all, industry creates pollution, landscape destruction, and waste. There is, however, a paradox of sorts in that industry, specifically heavy industry, creates the very materials, tools, and products necessary to construct sustainable communities. Even the most sustainable buildings are constructed using materials that are not naturally found in the environment. As an

1 Many references exist. Here is but one available from the Guardian: https://www.theguardian.com/environment/2011/apr/20/deepwater-horizon-key-questions-answered

2 European Environment Agency: https://www.eea.europa.eu/themes/industry/industrial-pollution-in- europe/a-decade-of-industrial-pollution-data

Industrial Siting for Sustainable Communities | Andrew Garrison example, the Greenest Commercial Building in the World, the Bullitt Center in Seattle WA, is constructed using concrete, steel, glass, and petrochemical products (The Bullitt Center,

2014). All these products, even when responsibly sourced, require carbon-intensive procedures for production and extensive supply chains involving carbon-intensive transportation solutions.

Not limited to the building materials themselves, the infrastructural elements that support the sustainability initiatives require manufacturing within an industrial setting. Rails for light-rail transit consist of steel. The railcars themselves are composed of steel, glass, and plastics. Even bicycles, the highly-valued solution to personal urban mobility, contain steel and petrochemical components (Roseland 2012). Many bicycles are, in fact, born in the fiery inferno of a steel mill. In short, even the hallmarks of the sustainable built environment are produced via industrial processes.

Within the built environment, steel products are used extensively for construction – rebars for reinforcing concrete structures, H-beams for structural framing, sheets for roofing, and pipes among other uses (Organisation for Economic Co-Operation and Development

2010). Without steel mills to produce these products they do not exist – one cannot harvest rebar, H-beams, or steel tubes directly from nature – they must be produced in a dedicated facility. The dedicated facility – a steel mill – in its simplest terms consists of a furnace for converting iron and carbon, and casting equipment to form the resulting steel into very general shapes: billets, sheets, slabs, tubes, etc. The steel-making industry, classifies mills into two general categories dependent upon the type of furnace used in the iron to steel conversion process. Basic oxygen furnaces (BOF) are an older technology that requires combining coke, iron ore, and limestone to produce steel. Coke, a modified version of coal, is combusted to generate the heat necessary to fuse iron and carbon. In contrast, the electric arc furnace (EAF) achieves the high temperatures necessary for steel production through a 10

Industrial Siting for Sustainable Communities | Andrew Garrison high-voltage electric arc (American Iron and Steel Institute 2020). Differences between BOF and EAF extend beyond the energy source. BOF facilities are generally larger with higher annual steel outputs when contrasted to the smaller EAF facilities with lower annual outputs.

Another key distinction between mill types is the raw materials for each – the BOF facility is designed to convert primarily raw iron ore to steel while the EAF is used for steel scrap recycling (American Iron and Steel Institute 2020). For a perspective on steel-making facility scale, Figure 1 offers an aerial image of ArcelorMittal’s Indiana Harbor facility in Indiana

Harbor, Indiana. An integrated steel mill on the shores of Lake Michigan, ArcelorMittal

Indiana Harbor employs BOF’s for the conversion of iron ore into steel. Sprawling across

3000 acres, it contains multiple furnaces which yield more than six million tons of steel per year (ArcelorMittal 2019).

From a planner’s perspective, the dichotomy of needing industrial products but not wanting the negative externalities of industry presents a challenge to achieving the three components of sustainability – environmental, economic, and societal. This research project offers to the planning community introductory information concerning the steel manufacturing industry, and specifically the location of manufacturing facilities relative to selected US cities. Additionally, this research examines the recent historical trend in the spatial relationship of steel producing facilities to major US cities by calculating the linear distance between steel mills and the nearest major cities as determined by US Census Bureau data. This data analysis focuses only on the distances to major cities as defined by geographic centroids, and does not consider distances to larger regional populations.

The research study consists of two components: the first a literature review of facility siting, sustainability objectives for industrial facilities, and sustainability assessment frameworks; and the second component entails a data-centric analysis on the current geo- locations of steel mills in the contiguous United States relative to major urban centers. 11

Industrial Siting for Sustainable Communities | Andrew Garrison

PURPOSE OF THE STUDY AND RESEARCH QUESTION

The primary motivation for this research is a perceived gap in the planning literature concerning the development of sustainability communities. Much of the existing literature on the topic of sustainable communities focuses on the residential, commercial, recreational, and transport uses of the built environment, yet what authors such as Roseland do not directly discuss is the role and place of industrial land-uses within sustainable community (Roseland

2012). The motivation for planning as a profession, both implied and explicitly stated, is the organization of the built environment toward a balance of three general sustainability themes: economic, environmental, and societal (Carmona 2009 and Roseland 2012 p.7). The literature must therefore also consider the role of industrial land-uses in the built environment.

Modern physical capital, sustainable or otherwise, does not naturally exist. Rather, the construction and maintenance of the built environment requires the coordinated efforts of people to obtain and organize materials to construct the desired outcome, and those materials must be sourced from somewhere. Often the decision of where to source materials falls to the markets, and under the prevailing economic, market-driven paradigm, consumers generally satisfy their demands at the lowest possible economic price to the neglect of environmental and societal sustainability considerations. This research presupposes that a gap in the literature exists regarding the siting of industrial facilities toward achieving sustainability objectives. From an urban and regional planner’s perspective, achievement of sustainable communities is both implied and stated as an objective3, and the discipline of planning exists for the purpose of achieving sustainable communities (Carmona 2009). The challenge to planners is not if industry has a place in their communities, but rather where is that place?

3 The American Planning Association summarizes the point and succinctly states the need for research projects such as this. https://www.planning.org/divisions/sustainable/

Industrial Siting for Sustainable Communities | Andrew Garrison

For purposes of this research, it is assumed that the demand for steel exists independent of steel mill locations – meaning that if a builder has a project requiring 100 tons of steel, whether the mill stands 10 miles away or 1000 miles away is irrelevant from a demand-side perspective. The builder does not consider how far the steel travels so long as the price is right and it is available when needed, yet from an environmental perspective travel distance from point of production to point of consumption is included in the environmental load of the product (Seip, Betele and Johnsen 2000). The variable then is the distance that the steel must travel from the plant to the point of consumption.

From an environmental sustainability perspective, distance is mitigated with transportation which requires the combustion of diesel fuel and yields carbon emissions.

Distance is indicative of carbon emissions, where the greater the distance travelled, the greater the carbon emissions generated, and carbon emissions are contrary to sustainability objectives. The research question for this foundational study is: what does the existing literature suggest is the appropriate siting strategy for industrial land uses, and where are steel mills in the United States sited relative to concentrations of physical capital?

SCOPE, ASSUMPTIONS, AND LIMITATIONS

Because both the research topic and consequently the number of variables is so vast, one must draw clear distinctions on the scope of this specific study, key assumptions, and the limitations of the key assumptions. This is particularly true as it relates to the data analysis component.

The first component of the research question is the subset of industry to research.

Steel-making is selected as the industry of focus because of steel’s ubiquity in the built environment. Steel is a frequently used building material with a multitude of applications,

Industrial Siting for Sustainable Communities | Andrew Garrison and 50% of steel produced annually is destined for use in construction (Organisation for

Economic Co-Operation and Development 2010, Worldsteel Association 2020). Steel products are pervasive in urban spaces as framing for multi-story buildings, the infrastructure components such as rails and pipes, sheeting forming the roofs and facades of buildings, and used in more complex machines such as trains, cars, electrical components, appliances, lighting, and the list goes on. Steel is a key component of the built environment, and yet, while durable, steel products have a lifespan and must be replaced over time which means there is recurring demand.

The second component of the research question concerns sustainability, and what that term means with respect to the siting of industrial facilities. It is assumed that economic sustainability is disproportionately overrepresented in siting decisions, followed by societal sustainability, and environmental sustainability last. Under this assumption, the scope of this research study focuses specifically on environmental sustainability.

The first key assumption is that at the outset of the project it is not known whether a problem exists in practice. The literature review addresses the views on sustainability and sustainable facility siting; however none focus on the steel-making industry, and industry and market data does not provide a data source showing the proximity of steel mills to end customers. As a novel question with respect to facility siting, the first step is to determine the current status and develop a methodology that can be built upon.

The second key assumption is that the research study considers only steel mills in the

United States. This decision is made to both limit the volume of data for analysis, and to avoid the potential for confounding variables resulting from cultural and regulatory differences.

Industrial Siting for Sustainable Communities | Andrew Garrison

A third assumption is that all steel mills in the study area are owned by for-profit companies who possess the decision on when and where to invest capital in construction of new steel mills (AIM Market Research 2013). The consequence of this assumption is that steel mill owners are driven by the profit motive and will site their facilities to maximize profits. Further, this assumption implies that legislation can direct and encourage site location, but a steel-producing company cannot be directed to construct a mill in a given location. The choice to invest or not is voluntary and motivated by expected economic returns.

Another key consideration is the cost associated with constructing a steel manufacturing facility. In 2013, Benteler Steel invested $975 million to construct a plant in

Louisiana with an annual capacity of approximately 440,000 tons (KSLA News 2013). At

440,000 tons, this facility is relatively small, yet the cost of construction approached $1 billion. It is conceivable that political pressures could require the relocation of industrial facilities from existing locations to new locations, however given the investment required in plant, equipment, distribution networks, and the challenges of relocating or training a workforce, industry owners will prefer to not move facilities, and therefore that development of a steel mill in a given location represents a commitment of many years. Understanding the significant expense for constructing a steel-making facility is important as the implication is that one will not invest this capital without significant due diligence into the long-term profitability of the investment. In short, it is assumed that the choice to site a steel-making facility in a given location is voluntary and driven by the profit motive.

Steel mills are not strictly limited to the location of natural resources for plant siting, particularly those steel mills using EAF furnaces for scrap recycling (American Iron and

Steel Institute 2020). Scrap can be sourced from any place where steel-containing products are disposed of, and therefore are not necessarily limited to siting near iron ore deposits. The 15

Industrial Siting for Sustainable Communities | Andrew Garrison consequence of this assumption is that the site of EAF facilities can be flexible and not restricted to the location of natural resources.

Logically, distance between plants and consumer must be overcome by transportation solutions, whether by truck, boat, or rail. While the efficiency of transportation modes differs, the point remains the same – distance from plant to consumer must be mitigated by burning fuel to power the mode of transportation to move finished steel from plant to consumer. For this reason, distance is correlated to carbon emissions, where greater distance yields greater carbon emissions, and greater carbon emissions are the antithesis of the environmental sustainability objective.

The final key assumption is that the demand for steel is affected by market conditions, and not mill site location. The assumption implies that consumers are generally uninterested in the source of the steel consumed in construction projects, and instead are concerned with having the correct quality of material, when it is needed, and at the lowest price.

Summary of Key Assumptions

1. Before this study there is no known problem resulting from empirical data

analysis, only from casual observations.

2. This research study area covers all steel mills in the United States only.

3. Significant capital investment is required in constructing a new steel mill. In the

United States most often this is private investment, and the choice of where and

how much to invest is voluntary.

4. Steel mills are not limited to siting near iron ore mines, and have flexibility with

site selection.

Industrial Siting for Sustainable Communities | Andrew Garrison

5. Distance from plant to consumer is indicative of, and synonymous with, energy

consumption for transportation, and consequently carbon emissions expended in

that process.

6. Consumer demand drives the need for facility investment… legislation and/or

regulation do not.

Because of the assumptions made to limit the study’s scope and to mitigate potentially confounding variables, limitations are created. The primary limitation is that this study analyzes the current siting situation in contrast to one variable of one component of sustainability – transportation distance from plant to consumer. This study does not consider the regulatory environment and what consequences that may have on siting decisions.

However, the literature review section cites work conducted by Seip et al concerning the siting of paper mills, which mitigates the limitations resulting from the preceding assumptions. “Industry should be sited at locations where its environmental load does the least damage (Seip, Betele and Johnsen 2000, p.546).” Regardless of economic or political realities, according to Seip et al, industry should be sited where it produces the least environmental damage. If demand is fixed, meaning that emissions from production are fixed, then emissions from transportation is what should be minimized.

LITERATURE REVIEW

As stated in the introduction to this paper, this research project reviews the siting of steel mill facilities in the United States from a sustainability perspective. Frequently the planning body of literature focuses on the other major land-uses: residential, commercial, greenspace, transportation, recreation, and so on – and does not consider industrial land-uses.

Additionally, the literature applicable to this topic is varied, however this literature review

Industrial Siting for Sustainable Communities | Andrew Garrison attempts to draw a critical path by discussing topics relating to sustainability issues, attitudes toward industrial siting, a potential framework for research on the topic, two examples of industrial siting, and application of lifecycle assessment to steel mill siting decisions.

Sustainable urban design applies not only to environmental sustainability, but also economic and social (Carmona 2009 and Terouhid, Ries and Fard 2012). Of the sustainability principles highlighted by Carmona, point seven “the polluter pays” (2009) is illustrative of a central impetus of this research study. Through research conducted by the Global Carbon

Project, data indicates that developed countries are outsourcing pollution to undeveloped countries (Plumer 2017). China is the recipient of the carbon emissions that result from industrial producers sending manufacturing operations from the developed west in search of lower cost labor, and the impetus for this movement from developed to developing countries is primarily market-driven outcomes (Carmona 2009). To achieve sustainability, communities must adapt strategies to pay for their emissions, and in this case, owning the emissions of the products used to construct the community. As sustainable communities seek to construct buildings and infrastructure with the materials produced by heavy industry, the challenge from a planning perspective is to implement strategies that optimize the sustainability of the community: environmental, social, and economic, and doing so by taking ownership of the positive and negative consequences of production. One way to mitigate the environmental costs of construction may be to site industry within the community thereby locating the production capabilities close to the source of labor and the “sink” where products are consumed. Arguably, the siting decisions for industrial facilities, whether domestic or in a foreign country, are primarily motivated by economic factors subject to the prevailing economic paradigm. As this discussion moves into the framework for analyzing siting decisions, it is demonstrated that of the three general categories of sustainability, economic is considered to a disproportionately greater degree than social and environmental.

Industrial Siting for Sustainable Communities | Andrew Garrison

Mentioned frequently in this paper and the supporting literature are the three general components of sustainability – environmental, economic, and societal – and the need for further research into merging these three categories into a unified siting strategy (Roseland

2012, p.7 and Terouhid, Ries and Fard 2012, p30). By virtue of their place in the land-use management process, and as policy influencers, planners possess the ability to create conditions for siting industrial facilities toward sustainability objectives, however this cannot be done without understanding the key drivers of each of the three sustainability categories.

Further, as steel mill owners are independent actors – meaning that they may choose how and where to invest capital – a planner cannot direct. Planners must influence decisions, and influence results from understanding the motivations of each player in the sustainability categories and their “levers.”

The first category of sustainability – economic – is probably the most clearly defined category. Economic analysis, though incomplete from the standpoint of assigning costs to products, provides the most quantifiable and most easily assessable measure of sustainability

(Carmona 2009). Considering that the scope of this study is for-profit manufacturers, a sustainable for-profit business is one that yields an economic profit. Further, as for-profit businesses are driven exclusively by the profit motive, when all other factors remain equal, the site that permits the for-profit company to yield the most profit is the chosen location.

Though defined through concept of risks, Terouhid et al offer subcategories of economic sustainabilty that can be treated as levers (Terouhid, Ries and Fard 2012, p30, see also figure

2). From a site selection standpoint, those sites that offer the lowest risk, lowest cost for acquisition, construction, operations, and maintenance are optimal, and are measurable in dollars on the financial statements of the companies. Yet, this view is incomplete, and it is incomplete where economics inter-relates with the other two categories of sustainability – societal and environmental (Terouhid, Ries and Fard 2012).

Industrial Siting for Sustainable Communities | Andrew Garrison

From a planner’s perspective, heavy industry offers a variety of challenges, not least of which is the challenge of overcoming the public’s perception that such land-uses are locally unwelcome. NIMBYism – not in my backyard – and LULU’s – locally unwanted land uses – are sources of conflict between the public and planners (Boudet and Ortolano 2010). It stands to reason that siting heavy industry within the urban envelope increases the likelihood of the industrial being site objected-to by the community. From a sustainability perspective, the inter-relationship between societal and economic sustainability represents a significant challenge for industrial players (Briassoulis 1995 p.298 and Boudet and Ortolano 2010 p.5) as the objectives of a sustainable, livable city would seem to be in contradiction with the negative consequences of a heavy industrial site.

However, it must be noted that in dispassionate terms, disapproving of the manufacturing facility does not necessarily eliminate the demand for the products. Therefore, the optimal site for an industrial facility must be far enough to mitigate the social objections while still minimizing the environmental consequences, and permitting the owner to earn a profit. Societal pressures can influence legislation and legislation can directly influence the sites available for development and therefore the siting choices made by mill owners

(Azapegic 2004, p.640).

The theoretical underpinnings of this study begin with a review of the general categories of sustainability – environmental, social, and economic – and then relate a logic that shows that the categories of sustainability must be balanced to achieve sustainability. The levers for influencing sustainability exist in the inter-relationship between sustainability categories, and each of these levers are in turn a variable for analysis. Other variables to consider are the industries themselves where siting strategies for natural resource harvesting – industries that are restricted based on the location of the industrial inputs – are limited where

Industrial Siting for Sustainable Communities | Andrew Garrison other industries that convert natural resources to finished products may have some flexibility in siting.

Azapegic offers a framework for analyzing heavy industry, though specifically looking at mining and minerals industry. From a siting perspective, a mining facility is limited by the location of the minerals in the earth, however, economics remains the main influencing factor in the choice to operate. A mining company by its nature is environmentally destructive, yet it cannot yield the economic benefits of paid employment and social benefits like thriving communities without existing – and again, the mine exists to earn a profit for its owner (Azapegic 2004). Where Azapegic advances the study into siting is further refining the analysis into more narrowly defined indicators by leveraging GRI reporting guidelines. Various measures of financial performance of a company can indicate economic sustainability – return on invested capital will indicate how well a company has invested, dividends paid will show the success at generating cashflow, and financial investment in the community indicates the company’s desire to improve its surroundings and nearby residents (Azapegic 2004, p.650-651).

Likewise, environmental indicators at the business level can show how well a company is performing in achieving sustainability objectives – energy efficiency, air emissions (implied from operations), product durability and lifecycle, and so on. There are two points to make with regard to the indicator proposals from Azapegic. First, when measuring anything – sustainability or otherwise – it is essential to have a quantifiable object and a benchmark to compare to. Without a basis for comparison, a measurement is simply that, and no assessment of good or bad can be determined. Azapegic’s proposed integrated indicators merge together, in a quantifiable manner, the inter-relationship discussed by

Terouhid et al (Azapegic 2004 p.661 and Terouhid, Ries and Fard 2012 p.30). What

Azapegic proposes is a strategy for measuring the sustainability based on the inter- 21

Industrial Siting for Sustainable Communities | Andrew Garrison relationship between sustainability categories – integrated indicators (2004). Another market- based analysis looks to the paper industry – an industry not entirely reliant upon the physical location of natural resources for a plant siting decision, similar to the steel industry in that regard, and the assessment is plainly stated, “(i)ndustry should be sited at locations where its environmental load does the least damage (Seip, Betele and Johnsen 2000, p.546).” For purposes of this research study, two key points are extracted from this example from the paper industry. First, the introduction states that industry should be sited where the environmental load is least, and the environmental load should constitute all environmental impacts, not only the environmental impacts from operations. In other words, transportation of materials to and from the plant and transportation of finished products from the site contribute to the plant’s total environmental load. If one assumes that the demand for the product (paper in the case of Seip, or steel in this research study) will be the same regardless of where the facility is located, then environmental load can be reduced when the plant is sited in such a way that minimizes the total emissions resulting from transportation. The second point is that while optimal siting may be effective in mitigating environmental outcomes from industrial activity, the optimal site may not be available for industrial uses

(Seip, Betele and Johnsen 2000, p.551). One could conceive of a situation where the ideal location for a new industrial facility is a greenfield or other protected area, in which case these decisions belong to “the political sphere (Seip 2000).”

Industrial Siting for Sustainable Communities | Andrew Garrison

The steel manufacturing industry recognizes, and in fact leverages the iron product life cycle from production, to consumption, to recycling and reuse (Worldsteel Association

2020). Steel is infinitely recyclable, meaning that at the conclusion of a steel product’s Figure 2 - Steel use and reuse cycle. Steel can be recycled an infinite number of times. (Worldsteel Association, 2020) useful life, it can be recycled into a new steel product repeatedly and without loss of quality (Worldsteel Association 2020).

The cycle of production, consumption, and recycling creates a loop with both production and geographical components, and one method for assessing the costs of this product loop is a

Life Cycle Inventory (Garces 2018, p22). The life cycle inventory for steel products would consider the inputs and outputs of each process within a steel product’s lifetime including: raw material harvesting, manufacturing, distribution, consumption, disposal, and recycling

(The International Organization for Standardization 2006). A hypothetical LCI focusing on carbon emissions for a steel product would capture the carbon tonnage at each step of the process. The work prepared by Garces concerning community composting provides a sample for the construction of a decision-making process using LCI (Garces 2018). A thorough LCI on steel products from a sample set of steel mills requires additional research outside the scope of this study, but would add valuable information for a siting decision methodology.

What can be seen in the literature is an availability of theoretical models, but few tactical assessments of industries, siting strategies, industrial-spatial organization, and so on

(Terouhid, Ries and Fard 2012, p30). The theoretical models, however, inform a strategy for

Industrial Siting for Sustainable Communities | Andrew Garrison analyzing the current status of steel mill siting in the United States. From the perspective of siting future steel mills, the objective should be to shrink the loop from producer to consumer, and to place industry where its environmental burden is least (Garces 2018, Seip,

Betele and Johnsen 2000). Of the many variables affecting the siting decision of a steel mill, this research study offers information for only one component of the hypothetical steel LCI – transportation and shrinking the geographic component of the loop as a carbon emission mitigation strategy.

Likewise, as discussed with reference LNG siting, public and political influence for

LULU and NIMBY reasons can pressure mill owners to locate facilities at sub-optimal sites or not construct facilities at all (Boudet and Ortolano 2010). In this example, the societal levers of health, social values, aesthetics supersede the optimal environmental situation in a myopic interpretation of optimal siting. In other words, because an LNG facility (or steel mill, or paper mill, and so on) is not wanted in my backyard does not reduce the demand for the products of the facility.

Life cycle assessment, of which a life cycle inventory is a component, would be a valuable tool in analyzing the inter-relationship of sustainability components with regards to siting steel mills. One could envision a scenario where multiple, quantified life cycle inventories for proposed steel mill facility sites would inform the preferable location by showing the site with the lowest environmental load, best economic outcomes, and greatest societal acceptance.

Industrial Siting for Sustainable Communities | Andrew Garrison

METHODOLOGY

As discussed in the literature review section of this paper, Terouhid et al. provide a thorough analysis of the literature concerning sustainable facility siting. Their work walks through the some of the foundational research on facility siting from a pure economic basis to a more holistic view on facility siting including environmental and societal factors. Further, it is their conclusion that while a wealth of theoretical analysis exists that concerns the optimal, sustainable facility siting, what does not exist is research on practical application and case study (Terouhid, Ries, & Fard, 2012, p. 30).

This research project is intended to step into that gap and to perform a critical assessment of existing industrial facilities and their placement within their communities. By taking the work performed by Terouhid et al. as foundational and considering that spatial location of facilities is something that a planner can influence, this project plots a course through existing research on evaluation methods and then ultimately performs the detailed analysis on specific industrial sites. Further, Azapegic’s proposal of integrated indicators for the mining and minerals industry provides strategic direction on how one might assess the inter-relationship between sustainability indicators. The purpose of this study is to assess siting strategies, however, so there must also be a geo-spatial component.

Terouhid et al. propose a matrix of three broad risk categories for sustainability: environment, society, and economy (Terouhid, Ries, & Fard, 2012, p. 30). For purposes of this research study, these three categories are the basis for evaluating the sustainability of industrial sites, and they can be further subdivided into constituent components (figure 1).

This project, however, analyzes one specific variable – spatial location relative to major urban areas. It is presupposed that industrial facilities sited closer to urban centers will be more sustainable than those situated further from.

Industrial Siting for Sustainable Communities | Andrew Garrison

The next step in the research design process is to refine the data gathering method, and again the literature provides some direction to consider. It is already determined that there are three broad categories for determining the sustainability of a facility site: environment, society, and economy. Terouhid et al. propose some subdivisions of each of those categories (figure 2). The work of Terouhid et al. is built upon research conducted by

Greek researcher Helen Briassoulis who offers a thorough analysis of environmental criteria to consider (Briassoulis, 1995, p. 300-304). As discussed in this literature review, Briassoulis rightly concludes that there are far too many environmental variables to consider in reference to the number of environmental factors influenced by an industrial facility. “A considerable number and variety of environmental criteria exist and a multitude of factors affects their choice in a given facility siting situation, thus making the quest for best criteria irrelevant.

Instead, it is suggested that it is more important to choose them rationally within a given problem context (Briassoulis, 1995, p. 308).” Because the objective of this research study is to analyze the current siting of steel mills in the United States, the quantitative analysis focuses on siting relative to population cities by measuring distance.

Figure 3 – Inter-relationship of sustainability components as prepared by Terouhid et al.

Industrial Siting for Sustainable Communities | Andrew Garrison

The second step is determining the measurables for societal sustainability, and for that

Boudet and Ortolano provide some variables to consider in their analysis on contentious facility siting in California (Boudet & Ortolano, 2010). It is assumed in this study that industrial facilities are Locally Unwanted Land Uses (LULUs) and that therefore siting within an urban area will lead to objections from the community. What is also assumed is that while industrial facilities are not aesthetically pleasing and can contribute to poor community health, there are benefits such as employment, training, community engagement and sponsorships, and positive community building.

Following is the list of variables necessary to complete the analysis:

1. Plant Attributes

a. Plant Owner

b. Plant Name

c. Furnace Type – Basic Oxygen Furance (BOF) or Electric Arc Furnace (EAF)

d. City

e. State

f. Latitude

g. Longitude

h. Production Start – several assumptions are made regarding this date, however

this information is key to measuring impact of time and controlling for

population movement

2. City Attributes 27

Industrial Siting for Sustainable Communities | Andrew Garrison

a. City

b. State

c. Population

d. Latitude

e. Longitude

f. Population Date – consider the same explanation as presented in Production

Start above

3. Calculated Attributes

a. City Top 100

b. City Top 25

c. City Top 10

d. Plant Key – for data management purposes

e. Distance from plant to major city measured in miles

f. Outliers – additional exclusions, of which one is noted

4. Scenario calculation – for measuring the impact of population movement over time

DATA COLLECTION

Phase 1 – Collect Plant Attributes The data collection takes a two phased approach to finding information concerning steel mill sites and population centers within the US. First, the task is to identify the population of steel mills in the US, their production capacities, geographic locations, and time

Industrial Siting for Sustainable Communities | Andrew Garrison of the siting decision. The data to support this section is obtained from a variety of sources, however the primary source is market information provided by AIM market research who, in conjunction with the American Iron and Steel Institute provide many of the necessary data points: plant name, type of furnace (which proves to be a confounding variable), city, state, and production capacity (AIM Market Research 2013).

Figure 4 - Steel mill sites in North America (AIM Market Research 2013). See appendix 1 for detailed copy.

The source data table in connection with the map presented in figure 2 form the foundational table for Phase 1 of data collection. It is discovered through due diligence on the data that despite being recent information – dated 2013 – it is not entirely accurate. From the baseline dataset obtained from AIM Market Research, Warren Steel Holdings in Warren OH appears to be duplicated in the data, and therefore one occurrence is deleted. Mill ownership is not an essential variable in this analysis, though it can be indicative in obtaining other data.

What is an essential variable in this analysis is production capacity in the steel market, and for that reason having the same plant appearing twice in the data set would double-count 29

Industrial Siting for Sustainable Communities | Andrew Garrison the contribution of that mill into the total market output. Another data element excluded from this analysis is Eco Steel Recycling of Amory MS. Quite simply, during the due diligence phase of this project it could not be physically located on a map, and therefore was excluded from the analysis. Upon completion of the due diligence, 113 mills are identified in the contiguous United States, and the following variables are obtained: plant owner (a), plant name (b), furnace type (c), city (d), and state (e).

Step two in completing the plant attribute table is geo-locating and obtaining a latitude and longitude for each plant. This data is obtained through extensive use of Google maps and the aerial photography available through the satellite function. In most cases searching by plant name yields the approximate physical location of the plant on Google maps (see figure 3).

Figure 5 - Google map sample of Gerdau Midlothian, Midlothian TX (maps.google.com 2020)

Industrial Siting for Sustainable Communities | Andrew Garrison

The task of geo-coding each facility is accomplished through searching each production in Google Maps, recording the longitude and latitude to a point of two decimals.

At 38 degrees north latitude, one degree of latitude equals approximately 69 miles and one degree longitude equals approximately 54.6 miles (US Geological Survey 2020). For the sample of steel mills selected, the average latitude is 38 degrees, so therefore rounding to two decimal points risks 0.69 miles latitude and 0.55 miles longitude. Such a difference is inconsequential, and rounding to two decimal points is acceptable.

Through the course of the due diligence and data collection on plant location and geo- coding, age of plants became an obvious confounding variable. Basic oxygen furnaces

(BOF’s) are an older technology, and produce a significantly larger output than the relatively newer and smaller electric arc furnaces (EAF’s), and those BOF’s are clustered in the US’s traditional steel-making areas of western Pennsylvania/eastern Ohio and Chicagoland (AIM

Market Research 2013). The siting choice at the time of a BOF’s construction in the

Pittsburgh area would likely have been affected not only by market conditions at the time of planning, but also by other variables including the availability of raw materials and labor.

Further, it is an underlying assumption within this research study that distance to population center is indicative of carbon cost to move labor and materials. As such, it could be that at the time the large BOF’s of the rust belt were constructed, the centers of population were different than at the time of more recent EAF construction. Therefore, time is a variable and should be considered in the analysis. The definition of the time variable should, in principle, be the point when the siting decision occurred as that would be when all of the variables impacting the decision were synthesized to produce a decision to invest the capital in the plant. This information is impossible to determine without directly interviewing the decision-maker who made the choice.

Industrial Siting for Sustainable Communities | Andrew Garrison

Accepting that the date is necessary to yield a detailed analysis, several assumptions are made regarding what constitutes the decision date. For recently constructed plants, more information is available via the internet than older plants – such as the Big River Steel plant in Osceola Arkansas where construction began in 2014 (Big River Steel 2020). Though certainly the exact location of the plant was chosen before 2014, the year of construction provides a reasonable data upon which to assume the siting decision took place. In other cases, however, the actual construction dates are difficult to obtain, but production start dates are more readily available. By prioritizing the data collection based on annual production capacity, production start dates, or construction dates were collected for 55 of the 113 plants, including all plants with a production capacity of greater than one million tons per year (48).

Though not ideal, the 55 plants with recorded production start dates represent 79% of the total plant production capacity in this study (100% of BOF capacity and 68% of EAF capacity), are considered to be a representative sample, and all plant attributes (a to h) are complete.

Plant B/E City State Tons Lat Lon ProdYr A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 1879 AK Steel Corp - Ashland BOF Ashland KY 2546 38.5 -82.67 1910 (closed in 2019) AK Steel Corp - Butler EAF Butler PA 1543 40.83 -79.94 1908 AK Steel Corp - Mansfield EAF Mansfield OH 882 40.79 -82.53 AK Steel Corp - BOF Middletown OH 2899 39.5 -84.39 1899 Middletown Allegheny Ludlum - EAF Brackenridge PA 551 40.61 -79.73 1900 Brackenridge Allegheny Ludlum - EAF Latrobe PA 20 40.33 -79.37 Latrobe Allegheny Ludlum - EAF Midland PA 551 40.63 -80.46 1908 Midland Alton Steel EAF Alton IL 772 38.89 -90.15 1911 ArcelorMittal - Bayou EAF LaPlace LA 794 30.04 -90.47 1981 Steel (now Bayou steel group) ArcelorMittal - Burns BOF East Chicago IN 6173 41.62 -87.12 1964 32

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Plant B/E City State Tons Lat Lon ProdYr Harbor ArcelorMittal - Cleveland BOF Cleveland OH 2535 41.47 -81.67 1912 East ArcelorMittal - Cleveland BOF Cleveland OH 2094 41.47 -81.68 1912 West ArcelorMittal - Coatesville EAF Coatesville PA 970 39.97 -75.82 1793 ArcelorMittal - EAF Georgetown SC 1102 33.37 -79.29 1969 Georgetown (now Liberty Steel Georgetown) ArcelorMittal - Indiana BOF East Chicago IN 2205 41.66 -87.45 1882 Harbor #2 ArcelorMittal - Indiana BOF East Chicago IN 2976 41.66 -87.45 1882 Harbor #3 ArcelorMittal - Indiana BOF East Chicago IN 3638 41.66 -87.45 1882 Harbor #4 ArcelorMittal - Indiana EAF East Chicago IN 507 41.66 -87.45 1882 Harbor Bar ArcelorMittal - Riverdale BOF Riverdale IL 1102 41.65 -87.62 1918 ArcelorMittal - Steelton EAF Steelton PA 1213 40.23 -76.84 1865 ArcelorMittal - Vinton EAF El Paso TX 276 31.96 -106.59 1962 (now Vinton Steel) Arkansas Steel Associates EAF Newport AR 165 35.65 -91.24 Benteler Steel/Tube EAF Caddo- LA 440 32.34 -93.62 2013 (projected start-up Bossier scheduled 2018) Big River Steel, LLC EAF Osceola AR 1650 35.65 -89.94 2014 (projected start-up scheduled 2015) Bluescope Steel North EAF Delta OH 2183 41.57 -84.05 1996 America Carpenter Latrobe EAF Latrobe PA 61 40.3 -79.37 Specialty Steel (now Latrobe Specialty Steel) Carpenter Technology EAF Reading PA 193 40.36 -75.94 Corp. Cascade Steel Rolling EAF McMinnville OR 882 45.23 -123.16 1968 Mills Charter Steel Cleveland EAF Cleveland OH 248 41.44 -81.66 Charter Steel Saukville EAF Saukville WI 639 43.4 -87.95 Commercial Metals - EAF Birmingham AL 661 33.55 -86.8 Alabama Commercial Metals - EAF Magnolia AR 331 33.21 -93.23 Arkansas Commercial Metals - EAF Mesa AZ 287 33.29 -111.58 Mesa Commercial Metals - EAF Cayce SC 882 33.96 -81.05 South Carolina Commercial Metals - EAF Seguin TX 992 29.58 -98.03 Texas 33

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Plant B/E City State Tons Lat Lon ProdYr Crucible Industries EAF Syracuse NY 50 43.07 -76.21 Electralloy EAF Oil City PA 61 41.43 -79.72 Ellwood National Steel EAF Irvine PA 77 41.84 -79.27 Irvine Ellwood Quality Steels Co. EAF New Castle PA 386 40.99 -80.35 New Castle EVRAZ Claymont Steel EAF Claymont DE 496 39.81 -75.45 EVRAZ Pueblo EAF Pueblo CO 1213 38.23 -104.61 1881 Gallatin Steel (now Nucor EAF Ghent KY 1609 38.76 -85 1993 Gallatin) Gerdau Long Steel North EAF Beaumont TX 656 30.08 -94.07 America - Beaumont (now Optimus Steel) Gerdau Long Steel North EAF Rancho CA 750 34.09 -117.53 America - California (now Cucamonga CMC) Gerdau Long Steel North EAF Cartersville GA 904 34.24 -84.8 America - Cartersville Gerdau Long Steel North EAF Charlotte NC 452 35.34 -80.83 America - Charlotte Gerdau Long Steel North EAF Jackson TN 617 35.73 -88.81 America - Jackson Gerdau Long Steel North EAF Baldwin FL 661 30.28 -81.98 1978 America - Jacksonville (now CMC) Gerdau Long Steel North EAF Knoxville TN 496 35.98 -83.96 America - Knoxville (now CMC) Gerdau Long Steel North EAF Midlothian TX 1786 32.46 -97.03 1970 America - Midlothian Gerdau Long Steel North EAF Petersburg VA 1190 37.19 -77.45 1999 America - Petersburg Gerdau Long Steel North EAF Sayerville NJ 805 40.48 -74.32 America - Sayreville (now CMC) Gerdau Long Steel North EAF Paul MN 606 44.89 -93.01 America - St Paul Gerdau Long Steel North EAF Wilton IA 342 41.58 -91.04 America - Wilton Gerdau Special Steel EAF Smith AR 507 35.31 -94.37 North America - Fort Smith Gerdau Special Steel EAF Jackson MI 358 42.2 -84.36 North America - Jackson Gerdau Special Steel EAF Monroe MI 551 41.89 -83.36 North America - Monroe GKN Hoeganaes Corp. - EAF Gallatin TN 331 36.37 -86.42 Gallatin Haynes International EAF Kokomo IN 33 40.47 -86.16

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Plant B/E City State Tons Lat Lon ProdYr Keystone Steel and Wire EAF Peoria IL 1323 40.64 -89.65 1889 Le Tourneau Technologies EAF Longview TX 121 32.46 -94.74 (now Nucor Longview) Leggett & Platt Wire Rod EAF Sterling IL 2381 41.79 -89.71 1936 Lehigh Specialty EAF Latrobe PA 66 40.31 -79.38 Mid-American Steel EAF Oklahoma OK 331 34.08 -96.75 City North American Höganäs, EAF Hollsopple PA 298 40.19 -78.93 Inc. Hollsopple North American Stainless EAF Ghent KY 1543 38.73 -85.07 1990 Novolipetsk Steel EAF Portage IN 799 41.62 -87.16 Nucor - Yamato Steel EAF Armorel AR 2579 35.9 -89.77 1992 Nucor Steel - Arkansas EAF Blytheville AR 2646 35.94 -89.71 1993 Nucor Steel - Auburn EAF Auburn NY 496 42.95 -76.57 Nucor Steel - Berkeley EAF Huger SC 3439 33 -79.88 1995 Nucor Steel - Birmingham EAF Birmingham AL 661 33.54 -86.81 Nucor Steel - Decatur EAF Trinity AL 2403 34.64 -87.09 1997 Nucor Steel - Hertford EAF Cofield NC 992 36.35 -76.81 Nucor Steel - Indiana EAF Crawfordsville IN 2480 39.98 -86.82 1989 Nucor Steel - Jackson EAF Flowood MS 551 32.31 -90.13 Nucor Steel - Kankakee EAF Bourbonnais IL 849 41.18 -87.85 Nucor Steel - Marion EAF Marion OH 397 40.57 -83.14 Nucor Steel - Memphis EAF Memphis TN 882 35.05 -90.16 Nucor Steel - Nebraska EAF Norfolk NE 992 42.08 -97.37 Nucor Steel - Seattle EAF Seattle WA 783 47.57 -122.37 1904 Nucor Steel - South EAF Darlington SC 1047 34.38 -79.9 1968 Carolina Nucor Steel - Texas EAF Jewett TX 1213 31.34 -96.16 1975 Nucor Steel - Tuscaloosa EAF Tuscaloosa AL 1301 33.23 -87.51 1985 Nucor Steel - Utah EAF Plymouth UT 992 41.88 -112.2 Optima Specialty Steel EAF Ashland KY 402 38.37 -82.76 1963 (planned shutdown 2013) now Kentucky Electric Steel Severstal Columbus (now EAF Columbus MS 2370 33.45 -88.58 2007 SDI Columbus) Severstal Dearborn (Now EAF Dearborn MI 4519 42.3 -83.16 1920 AK Steel Dearborn) SSAB Axis Steel Works EAF Mobile AL 1378 30.94 -88.01 2001 SSAB Montpelier Works EAF Montpelier IA 1246 41.48 -90.82 1997 Standard Steel LLC EAF Burnham PA 231 40.64 -77.57 Steel Dynamics Butler Site EAF Butler IN 2976 41.37 -84.92 1996 Flat Roll Steel Div Steel Dynamics Columbia EAF Columbia City IN 2480 41.12 -85.35 2006 City Site Structural & Rail Div Steel Dynamics Pittsboro EAF Pittsboro IN 728 39.88 -86.48

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Plant B/E City State Tons Lat Lon ProdYr Site Engineered Bar Products Div Steel Dynamics Roanoke EAF Roanoke VA 722 37.27 -80 Bar Div Steel of West Virginia EAF Huntington WV 309 38.43 -82.43 The Timken Co - Faircrest EAF Canton OH 871 40.75 -81.44 The Timken Co - Harrison EAF Canton OH 683 40.77 -81.44 ThyssenKrupp Stainless EAF Calvert AL 1102 31.15 -87.99 2010 USA (Outokumpu) TMK - Ipsco Koppel EAF Koppel PA 496 40.84 -80.32 TPCO America (projected EAF Gregory TX 836 27.91 -97.27 start-up scheduled 2015) Union Electric Steel Corp. EAF Burgettstown PA 35 40.41 -80.41 - Harmon Creek Plant Universal Stainless & EAF Bridgeville PA 149 40.37 -80.1 Alloy Products US Steel - Fairfield Works BOF Fairfield AL 2400 33.48 -86.92 1917 US Steel - Gary Works BOF Gary IN 8102 41.61 -87.34 1906 (No. 1 BOP & Q-BOP) US Steel - Granite City BOF Granite City IL 2866 38.69 -90.14 1895 Works US Steel - Great Lakes BOF Ecorse MI 3527 42.26 -83.13 1901 Works US Steel - Mon Valley BOF Braddock PA 2899 40.4 -79.86 1937 Works V&M Star Steel Co EAF Youngstown OH 694 41.13 -80.68 Valbruna Slater Stainless EAF Ft. Wayne IN 61 41.07 -85.17 1925 Inc Warren Steel Holdings EAF Warren OH 441 41.21 -80.82 (now AM Warren) Whemco Steel Castings EAF Midland PA 65 40.63 -80.45 Nucor Brandenburg EAF Brandenburg KY 1200 38 -86.17 2022 Figure 6 - Completed data table capturing plant attributes

Phase 2 – Collect City Attributes The second step in data collection is determining the city locations to contrast with plant locations, and for this data the US Census Bureau provides much of what is required for the six key attributes. Further, as discussed in Phase 1, a time-phased element is critical to mitigating the confounding variables of population migration over time. Therefore, population data by city is selected for four time periods based on the census: 2010, 2000,

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1990, and 1980. Population data by city is not easily located for censuses before 1980, however and again, to reduce the influence of confounding variables, this study concentrates on the pattern of siting decisions in recent years.

Through several data files obtained through the US Census Bureau, a table is constructed for attributes a through f, where the census data provides: city (a), state (b), population (c), and population date/census year (f) (United States Census Bureau 1990,

United States Census Bureau 2010). In the same manner as the steel mills are geo-coded, so too are the cities by using Google Maps to identify the approximate latitude and longitude rounded to two decimal places. Again, for the scale of this analysis, it is assumed that a fraction of a degree latitude or longitude will not significantly skew the outcome of the analysis.

Year City State Total Lat Long Rank TOP TOP25 TOP10 (1,000) 100 2010 New York NY 8175.133 40.66 -73.94 1 X X X 2010 Los Angeles CA 3792.621 34.02 -118.41 2 X X X 2010 Chicago IL 2695.598 41.84 -87.68 3 X X X 2010 Houston TX 2099.451 29.79 -95.39 4 X X X 2010 Philadelphia PA 1526.006 40.01 -75.13 5 X X X 2010 Phoenix AZ 1445.632 33.57 -112.09 6 X X X 2010 San Antonio TX 1327.407 29.47 -98.53 7 X X X 2010 San Diego CA 1307.402 32.82 -117.13 8 X X X 2010 Dallas TX 1197.816 32.79 -96.77 9 X X X 2010 San Jose CA 945.942 37.3 -121.82 10 X X X 2010 Indianapolis IN 829.718 39.78 -86.15 11 X X 2010 Jacksonville FL 821.784 30.34 -81.66 12 X X 2010 San Francisco CA 805.235 37.73 -123.03 13 X X 2010 Austin TX 790.39 30.3 -97.75 14 X X 2010 Columbus OH 787.033 39.98 -82.98 15 X X 2010 Fort Worth TX 741.206 32.78 -97.35 16 X X 2010 Louisville KY 741.096 38.17 -85.65 17 X X 2010 Charlotte NC 731.424 35.21 -80.83 18 X X 2010 Detroit MI 713.777 42.38 -83.1 19 X X 2010 El Paso TX 649.121 31.85 -106.43 20 X X 2010 Memphis TN 646.889 35.1 -89.98 21 X X 2010 Nashville TN 626.681 36.17 -86.79 22 X X 2010 Baltimore MD 620.961 39.3 -76.61 23 X X

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Year City State Total Lat Long Rank TOP TOP25 TOP10 (1,000) 100 2010 Boston MA 617.594 42.34 -71.02 24 X X 2010 Seattle WA 608.66 47.62 -122.35 25 X X 2010 Washington DC 601.723 38.9 -77.02 26 X 2010 Denver CO 600.158 39.76 -104.88 27 X 2010 Milwaukee WI 594.833 43.06 -87.97 28 X 2010 Portland OR 583.776 45.54 -122.65 29 X 2010 Las Vegas NV 583.756 36.23 -115.26 30 X 2010 Oklahoma City OK 579.999 35.47 -97.51 31 X 2010 Albuquerque NM 545.852 35.1 -106.65 32 X 2010 Tucson AZ 520.116 32.15 -110.87 33 X 2010 Fresno CA 494.665 36.78 -119.79 34 X 2010 Sacramento CA 466.488 38.57 -121.47 35 X 2010 Long Beach CA 462.257 33.81 -118.16 36 X 2010 Kansas City MO 459.787 39.13 -94.55 37 X 2010 Mesa AZ 439.041 33.4 -111.72 38 X 2010 Virginia Beach VA 437.994 36.78 -76.03 39 X 2010 Atlanta GA 420.003 33.76 -84.42 40 X 2010 Colorado CO 416.427 38.87 -104.76 41 X Springs 2010 Omaha NE 408.958 41.26 -96.05 42 X 2010 Raleigh NC 403.892 35.83 -78.64 43 X 2010 Miami FL 399.457 25.78 -80.21 44 X 2010 Cleveland OH 396.815 41.48 -81.68 45 X 2010 Tulsa OK 391.906 36.13 -95.9 46 X 2010 Oakland CA 390.724 37.77 -122.23 47 X 2010 Minneapolis MN 382.578 44.96 -93.27 48 X 2010 Wichita KS 382.368 37.69 -97.35 49 X 2010 Arlington TX 365.438 32.7 -97.12 50 X 2010 Bakersfield CA 347.483 35.35 -119.04 51 X 2010 New Orleans LA 343.829 30.05 -89.93 52 X 2010 Anaheim CA 336.265 33.82 -118.02 53 X 2010 Tampa FL 335.709 27.97 -82.48 54 X 2010 Aurora CO 325.078 39.69 -104.69 55 X 2010 Santa Ana CA 324.528 33.74 -117.88 56 X 2010 St. Louis MO 319.294 38.64 -90.24 57 X 2010 Pittsburgh PA 305.704 40.44 -79.98 58 X 2010 Corpus Christi TX 305.215 27.75 -97.17 59 X 2010 Riverside CA 303.871 33.94 -117.39 60 X 2010 Cincinnati OH 296.943 39.14 -84.51 61 X 2010 Lexington KY 295.803 38.04 -84.46 62 X 2010 Anchorage AK 291.826 61.17 -149.28 63 X 2010 Stockton CA 291.707 37.98 -121.31 64 X 2010 Toledo OH 287.208 41.66 -83.58 65 X 2010 St. Paul MN 285.068 44.95 -93.1 66 X 2010 Newark NJ 277.14 40.72 -74.17 67 X 38

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Year City State Total Lat Long Rank TOP TOP25 TOP10 (1,000) 100 2010 Greensboro NC 269.666 36.1 -79.83 68 X 2010 Buffalo NY 261.31 42.89 -78.86 69 X 2010 Plano TX 259.841 33.05 -96.75 70 X 2010 Lincoln NB 258.379 40.81 -96.68 71 X 2010 Henderson NV 257.729 36.01 -115.04 72 X 2010 Fort Wayne IN 253.691 41.09 -85.14 73 X 2010 Jersey City NJ 247.597 40.71 -74.06 74 X 2010 St. Petersburg FL 244.769 27.76 -82.64 75 X 2010 Chula Vista CA 243.916 32.63 -117.02 76 X 2010 Norfolk VA 242.803 36.92 -76.24 77 X 2010 Orlando FL 238.3 28.42 -81.23 78 X 2010 Chandler AZ 236.123 33.28 -111.85 79 X 2010 Laredo TX 236.091 27.56 -99.49 80 X 2010 Madison WI 233.209 43.09 -89.43 81 X 2010 Winston-Salem NC 229.617 36.1 -80.26 82 X 2010 Lubbock TX 229.573 33.56 -101.89 83 X 2010 Baton Rouge LA 229.493 30.44 -91.13 84 X 2010 Durham NC 228.33 35.98 -78.9 85 X 2010 Garland TX 226.876 32.91 -96.63 86 X 2010 Glendale AZ 226.721 33.53 -112.41 87 X 2010 Reno NV 225.221 39.55 -119.85 88 X 2010 Hialeah FL 224.669 25.87 -80.3 89 X 2010 Chesapeake VA 222.209 36.68 -76.3 90 X 2010 Scottsdale AZ 217.385 33.68 -111.86 91 X 2010 North Las Vegas NV 216.961 36.29 -115.09 92 X 2010 Irving TX 216.29 32.86 -96.97 93 X 2010 Fremont CA 214.089 37.5 -122.08 94 X 2010 Irvine CA 212.375 33.68 -117.77 95 X 2010 Birmingham AL 212.237 33.53 -86.8 96 X 2010 Rochester NY 210.565 43.17 -77.62 97 X 2010 San Bernardino CA 209.924 34.14 -117.29 98 X 2010 Spokane WA 208.916 47.67 -117.43 99 X 2010 Gilbert AZ 208.453 33.31 -111.74 100 X Figure 7 - Sample city attribute data with US Census Bureau and geo-coded data.

Upon review of the population data it is determined that one single scale is insufficient for estimating siting decisions, and that there must be a point at which a city is no longer considered to be a population center. Further, considering that the population data is sampled over time, the selection of cities cannot be determined on absolute population, but

Industrial Siting for Sustainable Communities | Andrew Garrison rather relative to other cities. Therefore, only the top 100 cities by population are considered for each census year.

Phase 3 – Calculated Attributes With all data assembled from external sources, the process of calculation begins by ranking cities by population by census year. With the cities organized in this method, each city is assigned to a ranked category. As all cities that are included in the source data are within the top 100 by year, each city is assigned a value of “X” for TOP100. By rank, all cities by population by year in the top 25 by population are assigned a value of “X” for

TOP25, and the same method for TOP10. Thus, New York City, which is the largest city in the US in each census year is assigned a value of “X” for TOP100, “X” for TOP25, and “X” for TOP10. Conversely, Seattle ranked 25 in census year 2010. Therefore, Seattle receives a value of “X” for TOP100, “X” for TOP25, but no value for TOP10. This strategy allows for measuring the distance from plants to cities by considering size of population centers, and considering the same over time. This analysis completes attributes a, b, and c.

Distance is measured by calculating a straight line from the latitude and longitude coordinates for the plants to the same coordinates for each of the 100 cities by population year. This is achieved through a calculation in Excel (figure 7)4.

4 Though these functions are available in Excel for Office 365, it is important to mention that the strategy for the calculation and format was obtained from a third party: https://blog.batchgeo.com/manipulating-coordinates-in- excel/

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=(ACOS((SIN(plant latitude*PI()/180)*SIN(city latitude*PI()/180)+COS(plant latitude*PI()/180)*COS(city latitude*PI()/180)*COS(city longitude*PI()/180-plant longitude*PI()/180))))*(3443.89849*1.15078)

Figure 8 - Excel formula for calculating the distance in miles by two coordinate points

Finally, through the data analysis it is observed that ArcelorMittal Coatesville in

Coatesville Pennsylvania is potentially an irregular data point. In the due diligence phase, it is observed that steel production had taken place on the same site in Coatesville since 1793, and further that the present day facility contains and EAF. It is impossible for an EAF to have been constructed in 1793, and therefore the siting decision took place before modern methods of production were available. For this reason, ArcelorMittal Coatesville is an outlier and is excluded from the detailed analysis.

Key Plant Type City State Tons Lat Lon Prod Year Year City State Total (1,000) Lat Long Rank TOP100 TOP25 TOP10 Distance 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010New York NY 8175.133 40.66 -73.94 1X X X 713.5329488 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Los Angeles CA 3792.621 34.02 -118.41 2X X X 1754.315626 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Chicago IL 2695.598 41.84 -87.68 3X X X 9.510421695 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Houston TX 2099.451 29.79 -95.39 4X X X 933.1597274 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Philadelphia PA 1526.006 40.01 -75.13 5X X X 661.8123103 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Phoenix AZ 1445.632 33.57 -112.09 6X X X 1448.99471 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010San Antonio TX 1327.407 29.47 -98.53 7X X X 1045.251856 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010San Diego CA 1307.402 32.82 -117.13 8X X X 1728.177647 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Dallas TX 1197.816 32.79 -96.77 9X X X 797.1006908 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010San Jose CA 945.942 37.3 -121.82 10X X X 1839.695805 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Indianapolis IN 829.718 39.78 -86.15 11X X 153.9449209 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Jacksonville FL 821.784 30.34 -81.66 12X X 853.6290252 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010San Francisco CA 805.235 37.73 -123.03 13X X 1891.945556 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Austin TX 790.39 30.3 -97.75 14X X 971.6417526 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Columbus OH 787.033 39.98 -82.98 15X X 269.5137345 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Fort Worth TX 741.206 32.78 -97.35 16X X 818.1179784 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Louisville KY 741.096 38.17 -85.65 17X X 266.2146255 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Charlotte NC 731.424 35.21 -80.83 18X X 579.9434033 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Detroit MI 713.777 42.38 -83.1 19X X 235.0655457 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010El Paso TX 649.121 31.85 -106.43 20X X 1242.827886 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Memphis TN 646.889 35.1 -89.98 21X X 475.820642 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Nashville TN 626.681 36.17 -86.79 22X X 386.2948214 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Baltimore MD 620.961 39.3 -76.61 23X X 600.7178726 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Boston MA 617.594 42.34 -71.02 24X X 851.0872774 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Seattle WA 608.66 47.62 -122.35 25X X 1742.214629 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Washington DC 601.723 38.9 -77.02 26X 590.1846211 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Denver CO 600.158 39.76 -104.88 27X 914.6396908 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Milwaukee WI 594.833 43.06 -87.97 28X 94.69914632 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Portland OR 583.776 45.54 -122.65 29X 1760.775624 1A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 18792010Las Vegas NV 583.756 36.23 -115.26 30X 1528.375102

Figure 9 - Sample of combined analysis merging plant and city data with distance calculation. See appendix 2.

Phase 4 – Scenario Calculation 41

Industrial Siting for Sustainable Communities | Andrew Garrison

It is expected that steel mill facilities are constructed in response to market conditions present at the time they are conceived. For this reason, distance from plant to city is compared on through several scenario based on plant start date to census date.

1. Scenario 1 – Baseline: the distance of all plants to the nearest TOP100 city, TOP25

city, and TOP 10 city based on 2010 census data.

2. Scenario 2 – Plants built in the 2010’s: the distance of all plants built after 2010 to the

nearest TOP100 city, TOP25 city, and TOP10 city based on 2010 census data.

3. Scenario 3 – Plants built in the 2000’s: the distance of all plants built after 2000 to the

nearest TOP100 city, TOP25 city, and TOP10 city based on 2000 census data.

4. Scenario 4 – Plants built in the 1990’s: the distance of all plants built after 1990 to the

nearest TOP100 city, TOP25 city, and TOP10 city based on 1990 census data.

5. Scenario 5 – Plants built in the 1980’s: the distance of all plants built after 1980 to the

nearest TOP100 city, TOP25 city, and TOP10 city based on 1980 census data.

6. Scenario 6 – Plants built before 1980: the distance of all plants built in or before 1980

to the nearest TOP100 city, TOP25 city, and TOP10 city based on 1980 census data.

7. Scenario 7 – Nucor Brandenburg: the distance of Brandenburg Kentucky to the

nearest TOP100 city, TOP25 city, and TOP10 city based on 2010 census data. It is

learned through this study that steel manufacturer Nucor – owner and operator of

multiple EAF facilities in the US – plans to invest over $1 billion to construct a new

EAF facility in Brandenburg Kentucky (Brown 2019). This example offers a truly

contemporary example to analyze and test in the model as it is a plant for which the

siting decision is made in response to current market conditions.

Industrial Siting for Sustainable Communities | Andrew Garrison

Each of these scenarios is calculated and assembled into a single consolidated table by plant where the calculation provides the nearest TOP100, TOP25, and TOP10 city by each plant per the conditions stated above. With this information, the calculation can be summarized into average distances.

Avg Min Avg Min Avg Min Distance to Distance to Distance to Top100 City Top25 City Top10 City (miles) (miles) (miles) Scenario1 Baseline 54.1 119.7 265.7 Scenario7 Nucor Brandenburg 30.7 30.7 277.4 Scenario2 Plants Built in 2010s 108.9 112.2 312.0 Scenario3 Plants Built in 2000s 41.8 211.8 375.8 Scenario4 Plants Built in 1990s 66.4 111.7 304.7 Scenario5 Plants Built in 1980s 39.5 88.7 302.2

Scenario6 Plants Built Before 1980 35.9 92.9 218.8

Figure 10 - Analysis results including both BOF and EAF facilities

Upon review of the calculations, it is noted that within the baseline calculation are the

BOF operations in Illinois, Pennsylvania, Kentucky, Indiana, and Michigan. All recent steel mill constructions are EAF facilities and based on this information it is unlikely that a new

BOF facility would be constructed. Therefore, to remove the bias resulting from the BOF facilities, a second analysis is constructed that looks specifically at the same calculation but for EAF facilities only.

Industrial Siting for Sustainable Communities | Andrew Garrison

Avg Min Avg Min Avg Min Distance to Distance to Distance to Top100 City Top25 City Top10 City EAF (miles) (miles) (miles) Scenario1 Baseline 58.9 125.6 276.5 Scenario7 Nucor Brandenburg 30.7 30.7 277.4 Scenario2 Plants Built in 2010s 108.9 112.2 312.0 Scenario3 Plants Built in 2000s 41.8 211.8 375.8 Scenario4 Plants Built in 1990s 66.4 111.7 304.7 Scenario5 Plants Built in 1980s 39.5 88.7 302.2

Scenario6 Plants Built Before 1980 46.6 114.3 278.8

Figure 11 - Analysis results including EAF facilities only

INTERPRETATION AND DISCUSSION OF ANALYSIS

In both the combined BOF and EAF analysis, and EAF only analysis, a pattern emerges with respect to the mean distance from plant to city. Because all recent plant constructions in the past 60 years are EAF facilities, and there are no known BOF facilities planned for future construction, the focus of this discussion entails only on the EAF-specific analysis. The results displayed in Figure 10 show the mean distance of steel mill facility to the nearest major population center. For example, under Scenario 1 – Baseline, the mean distance of an EAF facility to a city ranked in the TOP100 by population based on the 2010 census is 58.9 miles.

The mean distance of an EAF facility to a city ranked in the TOP25 by population based on the 2010 census is 125.6 miles. The mean distance of an EAF facility to a city ranked in the TOP10 by population based on the 2010 census is 276.5 miles. However, this information is not intended to be used in isolation; rather this data is an indicator of a trend occurring with in practice with siting steel mills and it must be considered in relation to the other data points surrounding. What emerges is the time-phased pattern of distance growing

Industrial Siting for Sustainable Communities | Andrew Garrison over time. For example, EAF facilities constructed before 1980 were a mean 46.6 miles from the TOP100 city nearest the plant.

Figure 12 - Line chart showing the trend of distance in miles from plant to city over time

Several patterns emerge when considering the graphical representation of the data above. Possibly the most obvious distinction is the difference in distance between plants and

TOP10 cities when compared to plants to TOP25 and TOP100 cities. What this data indicates is that EAF facilities are constructed in closer proximity to smaller cities and in rural areas.

As discussed earlier in this study, cities represent three key resources for steel manufacturers: a source for manual labor, a source for recyclable materials, and a destination for finished products. What this data suggests is that while labor may be able to be sourced relatively locally to the plant, recyclable material is traveling a greater distance from TOP10 cities to

Industrial Siting for Sustainable Communities | Andrew Garrison plants, and finished steel is traveling a greater distance to the biggest markets for consumption.

Another trend that can be seen is a steady increase in distance from plant to city peaking in the 2000’s. This peak is driven by the start of production at a ThyssenKrupp stainless steel facility in Calvert, Alabama. At the time of production start in 2010 (which, again, means that the siting decision took place sometime before 2010), the nearest TOP100 city was Mobile Alabama – only 33 miles away. However, the nearest TOP25 city was

Memphis Tennessee – 297 miles away.

The trend supported by figure 12 is that through the 1980’s, 1990’s, and 2000’s, new steel mill facilities were being constructed at further and further distances from the nearest major population centers, which in turn requires a greater amount of energy to move materials to and from the plant. The expected new EAF facility in Nucor Brandenburg appears to be a favorable turn toward siting the mill closer to a population center – in this case TOP100 and TOP25 city Louisville Kentucky, and TOP10 city Chicago. Because of the timeliness of the decision to construct a new mill in Brandenburg, this Nucor facility presents an ideal opportunity for additional research on assessing the exact motivations for site selection and the inter-relationship of sustainability objectives resulting from that decision.

Of the two trends documented in this analysis, it is the first – distance to TOP10 cities, that is indicative of a potential problem. The distance calculated between plants and

TOP10 cities is not large because there are fewer TOP10 cities; rather the number is large because new EAF facilities are being constructed in rural areas away from major cities. By association, the finished steel products needed for new building construction, roadway maintenance, infrastructure development, and so on are traveling hundreds of miles to reach a point of consumption.

Industrial Siting for Sustainable Communities | Andrew Garrison

The research prepared by Seip et al makes clear the desired outcome, that industry should be sited as close to the point of consumption as possible. This has the distinct benefit of mitigating the carbon emissions resulting from transporting finished products to the point of consumption. This quantitative research illustrates relative gaps between the location of steel manufacturers, and some of the nearest likely markets for consumption of the finished materials. While the announcement of the construction of Nucor Brandenburg represents a change in previous site selections, the trend of constructing mills further population centers in the 1990s and 2000s indicate a growth in the distance that steel must travel to the point of final consumption.

The research question that this quantitative component seeks to answer is: where are steel mills in the United States sited relative to concentrations of physical capital? The data yielded in this research study show that EAF steel mills are located at a distance from the

US’s largest cities by a minimum distance of 270 miles, and further the data indicates that in the 1990’s and 2000’s there was a trend of siting new mill constructions further from major cities. The literature on the topic of sustainable industrial siting states that one objective should be to shrink the geographic loop thereby mitigating emissions resulting from transportation. The data indicates that perhaps that loop is not shrinking.

CONCLUSION

This research project began with an illustration of ArcelorMittal Burns Harbor Works in Burns Harbor, Indiana. The image was selected to illustrate the dichotomy of sustainability objectives, specifically environmental, and juxtaposing with the demands of modern cities for the materials produced in heavy industry facilities. Subject to current building technologies steel, in this case, is an integral component of the built environment and even the most

Industrial Siting for Sustainable Communities | Andrew Garrison decorated of sustainable structures (Bullitt Foundation 2014), and to have steel one must have steel mills and the negative consequences that accompany them.

If sustainable communities and regions are the objective, then planners must consider not just operational sustainability, but also the developmental sustainability. By not proactively encouraging the placement production facilities near to sources of labor and demand, the carbon cost of essential products is greater due to the emissions resulting from transportation and therefore contrary to the principles of sustainability. On a related point, so long as for-profit industries are integral to the design, construction, and maintenance of cities, it is imperative that planners understand the motivations and profit-drivers of these industries.

Capital investment on the scale of a production facility can represent a commitment to a place for many years.

As noted in the literature review section, the developed world, for a variety of reasons is pushing the production of steel to the developing world such that carbon emissions in the developed world are decreasing while carbon emissions globally are increasing. Even domestically within the United States, the production of steel is moving away from the major urban centers to rural areas away from urban centers. The motivations for this shift are primarily economic, as evidenced by Plumer that lower cost production areas can produce comparable materials at prices that consumers are willing to pay, however it is arguable that such a practice is not environmentally, economically, or socially sustainable. One can observe a microcosm of this behavior even within the United States as new steel making facilities are sited in locations away from major cities. With distance comes the need for transportation, transportation requires energy, energy is obtained from combusting fossil fuels which yield carbon emissions. Some of these carbon emissions could be mitigated by siting steel making facilities closer to the end destination for finished products.

Industrial Siting for Sustainable Communities | Andrew Garrison

In the detailed data analysis of steel plant locations relative to population centers, two trends emerged: one that there is considerable distance between top 10 cities by population and steel mills, and that there was an increase in distance between plants and cities in the

1980’s, 1990’s, and 2000’s. Recent siting decisions appear to be reversing the second trend, however the first – significant distance between major cities and steel mills – persists. One important distinction is that cities in this study are defined by both population as reported by the US Census Bureau and by approximate centroid as obtained via Google maps. This definition does not consider larger regional population centers such as metropolitan statistical areas (MSA’s) which when substituted into this calculation methodology. Enhancing the definition of what constitutes a population center and recalculating this analysis is an opportunity for future research and could alter the conclusions of this paper.

There are many variables to consider when discussing the siting decisions, especially siting decisions for which an independent third party is making the ultimate choice. Further research is required not only to enhance the findings of this particular study into the steel industry, but also to broaden the scope into other industries, to challenge and improve upon the methodology employed by this study, to broaden the scope into other industries and land- uses, to compare and contrast with prevailing planning strategies, to challenge industrial supply chains, and many other topics.

This research study provides introductory information on the current status of steel mill siting in the United States relative to major cities written for the benefit of the planning community. While the literature review focuses on reduction of the environmental load of manufactured products resulting from transportation, this research study does not conclude that simply siting new steel mills immediately next to consumers is optimal. Rather, this research study addresses one variable – distance – from one sustainability component – environmental – to augment a discussion on industrial facility siting. From a planning 49

Industrial Siting for Sustainable Communities | Andrew Garrison perspective, this research study illustrates the distance that essential building materials may be traveling to reach construction locations in cities, and how far waste scrap may be traveling to reach facilities for recycling. As planners encounter future opportunities to develop industrial spaces within their areas of influence, they should keep in mind Seip et al’s analysis that industry should be sited in locations that provide the least environmental load.

There may be future opportunities to influence siting decisions for new EAF steel mills, and when encountered, planners should consider shrinking the loop as a means of mitigating emissions from transportation and locate the production facility closer to the end consumer.

Industrial Siting for Sustainable Communities | Andrew Garrison

LIST OF REFERENCES

AIM Market Research. 2013. "steel.org." Steel Plants of North America. Jun. https://www.sierraenergy.com/Viewer.ashx?Id=56.

American Iron and Steel Institute. 2020. Steel Production. Accessed Mar 2020. https://www.steel.org/steel-technology/steel-production.

ArcelorMittal. 2019. "About ArcelorMittal Indiana Harbor." usa.arcelormittal.com. Jun. Accessed Mar 2020. https://usa.arcelormittal.com/~/media/Files/A/Arcelormittal-USA-V2/our- operations/Fact%20sheets/2019_IndianaHarbor.pdf.

Azapegic, Adisa. 2004. "Developing a Framework for Sustainable Development Indicators." Journal of Cleaner Production 12 (6): 639-662. doi:10.1016/s0959-6526(03)00075-1.

Big River Steel. 2020. "Big River Steel Overview." Big River Steel. Accessed Feb 2020. https://bigriversteel.com/about/overview/.

Boudet, Hilary Shaffer, and Leonardo Ortolano. 2010. "A Tale of Two Sitings: Contentious Politics in Liquefied Natural Gas Facility Siting in California." Journal of Planning Education and Research 30 (1): 5-21. doi:10.1177/0739456X10373079.

Briassoulis, Helen. 1995. "Environmental Criteria in Industrial Facility Siting Decisions: An Analysis." Environmental Management 19 (2): 297-311. doi:10.1007/bf02471998.

Brown, Wesley. 2019. "Nucor reveals plans to build new plate steel mill in rural northwest Kentucky community." Talk Business and Politics. Apr 1. Accessed Mar 2020. https://talkbusiness.net/2019/04/nucor-reveals-plans-to-build-new-plate-steel-mill-in-rural- northwest-kentucky-community/.

Bullitt Foundation. 2014. The Bullitt Center Core & Shell As-Built Product List. 1. Accessed 12 2019. http://bullittcenter.dreamhosters.com/wp-content/uploads/2013/12/Bullitt-Center-As- Built-Product-List-Jan-20141.pdf.

Carmona, Matthew. 2009. "Sustainable Urban Design – Principles to Practice." International Journal of Sustainable Development 12 (1): 48-XX. doi:10.1504/ijsd.2009.027528.

Garces, Kimmel Chamat. 2018. "Optimal Scale of Urban Composting Systems." Gainesville, FL: Univ of Florida.

International Living Future Institute. 2014. "Living Building Challenge 3.0 - A Visionary Path to a Regenerative Future." www.living-future.org. Accessed Mar 2020. https://living- future.org/wp-content/uploads/2016/12/Living-Building-Challenge-3.0-Standard.pdf.

KSLA News. 2013. Benteler breaks ground on $975M steel mill at Port of Caddo-Bossier. Sep 16. Accessed Mar 2020. https://www.ksla.com/story/23446204/benteler-breaks-ground-on- 975m-steel-mill-at-port-of-caddo-bossier/.

Organisation for Economic Co-Operation and Development. 2010. Perspectives on Steel by Steel- Using Industries. Informational briefing, Paris: OECD. 51

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Plumer, Brad. 2017. A Closer Look at How Rich Countries “Outsource” Their CO2 Emissions to Poorer Ones. April 18. Accessed 2020. https://www.vox.com/energy-and- environment/2017/4/18/15331040/emissions-outsourcing-carbon-leakage.

Roseland, Mark. 2012. Toward Sustainable Communities. Gabriola Island: New Society Publishers.

Seip, Knut L, Hallgeir Betele, and Keill Johnsen. 2000. "Siting of Paper Mills: Is a Pristine Environment an Industrial Resource/." Environmental Science & Technology 34 (4): 546-551. doi:10.1021/es9904181.

Terouhid, Seyyed Amin, Robert Ries, and Maryam Mirhadi Fard. 2012. "Towards Sustainable Facility Location - A Literature Review." Journal of Sustainable Development (Canadian Center of Science and Education) 5 (7): 18-34. doi:10.5539/jsd.v5n7p18.

The Center for Land Use Interpretation. 2020. "INDIANA HARBOR WORKS STEEL PLANT, INDIANA." clui.org. Mar. Accessed Mar 2020. https://clui.org/ludb/site/indiana-harbor-works-steel- plant.

The International Organization for Standardization. 2006. "Environmental management - Life cycle assessment - Principles and framework." ISO 14040:2006. Accessed 4 2020. https://www.iso.org/obp/ui/#iso:std:iso:14040:ed-2:v1:en.

United Nations Environment Programme. 2002. Industry as a Partner for Sustainable Development: 10 Years after Rio: the UNEP Assessment. Paris: United Nations Environment Programme Division of Technology, Industry, and Economics. Accessed 2019. https://www.unenvironment.org/resources/report/10-years-after-rio-unep-assessment- executive-summary.

United States Census Bureau. 1990. Table 1. 1980 and 1990 CENSUS COUNTS for CITIES WITH 1990 POPULATION . Washington DC: United States Census Bureau.

United States Census Bureau. 2010. Table 27. Incorporated Places With 100,000 or More Inhabitants in 2010--Population: 1970 to 2010. Washington DC: United States Census Bureau.

US Geological Survey. 2020. "How much distance does a degree, minute and second cover on your maps?" US Geological Survey. Accessed Mar 2020. https://www.usgs.gov/faqs/how-much- distance-does-a-degree-minute-and-second-cover-your-maps?qt- news_science_products=0#qt-news_science_products.

Worldsteel Association. 2020. "Steel's Contribution to a Low Carbon Future." Worldsteel Association Position Paper. Brussels: Worldsteel Association. https://www.worldsteel.org/en/dam/jcr:7ec64bc1-c51c-439b-84b8- 94496686b8c6/Position_paper_climate_2020_vfinal.pdf.

Industrial Siting for Sustainable Communities | Andrew Garrison

BIOGRAPHICAL SKETCH

Andrew Garrison is a data analyst and strategist for a global mining and manufacturing company. He received his BS Business Administration in finance from the

University of Pittsburgh in 2002 and anticipates earning the Master of Urban Planning from the University of Florida in 2020. His work experience includes consulting for government entities, developing financial and risk-management controls for for-profit companies, logistics, and purchasing. Andrew presently resides in Rotterdam, the Netherlands with his family.

Industrial Siting for Sustainable Communities | Andrew Garrison

APPENDIX 1 – STEEL PLANTS IN NORTH AMERICA

Industrial Siting for Sustainable Communities | Andrew Garrison

APPENDIX 2 – DETAIL OF DISTANCES FROM PLANT TO NEAREST MAJOR

CITIES

Optimal Industrial Siting for Sustainable Communities | Andrew Garrison

PLANT Scenario1 Company Plant B/E City Stat Tons Lat Lon Prod City Top 100 City Top 100 City City Top25 City City Top10 e Yr Dist Top25 Dist Top10 Dist A. Finkl & Sons A. Finkl & Sons Co. EAF Chicago IL 100 41.72 -87.59 1879 Chicago Chicago Chicago 9.51 9.51 9.51 AK AK Steel Corp - Ashland (closed BOF Ashland KY 2546 38.5 -82.67 1910 Lexington Chicago Steel in 2019) 102.28 Columbus 103.71 351.31 Corp AK Steel Corp AK Steel Corp - Butler EAF Butler PA 1543 40.83 -79.94 1908 Pittsburgh 27.06 Columbus 170.56 Philadelp 259.53 hia AK Steel Corp AK Steel Corp - Mansfield EAF Mansfield OH 882 40.79 -82.53 Columbus Chicago 60.84 Columbus 60.84 277.19 AK Steel Corp AK Steel Corp - Middletown BOF Middletown OH 2899 39.5 -84.39 1899 Cincinnati Chicago 25.72 Columbus 82.02 236.59 Allegheny Allegheny Ludlum - Brackenridge EAF Brackenridge PA 551 40.61 -79.73 1900 Pittsburgh Technologies 17.64 Columbus 176.90 Philadelp 246.13 hia Allegheny Allegheny Ludlum - Latrobe EAF Latrobe PA 20 40.33 -79.37 Pittsburgh Technologies 33.03 Baltimore 163.02 Philadelp 225.18 hia Allegheny Allegheny Ludlum - Midland EAF Midland PA 551 40.63 -80.46 1908 Pittsburgh Technologies 28.45 Columbus 140.32 Philadelp 284.30 hia Alton Steel Alton Steel EAF Alton IL 772 38.89 -90.15 1911 St. Louis Chicago 17.96 Indianapo 222.66 242.01 lis ArcelorMittal ArcelorMittal - Bayou Steel (now EAF LaPlace LA 794 30.04 -90.47 1981 New Orleans Houston Houston Bayou steel group) 32.34 295.46 295.46 ArcelorMittal ArcelorMittal - Burns Harbor BOF East Chicago IN 6173 41.62 -87.12 1964 Chicago Chicago Chicago 32.67 32.67 32.67 ArcelorMittal ArcelorMittal - Cleveland East BOF Cleveland OH 2535 41.47 -81.67 1912 Cleveland Detroit Chicago 0.86 96.84 311.59 ArcelorMittal ArcelorMittal - Cleveland West BOF Cleveland OH 2094 41.47 -81.68 1912 Cleveland Detroit Chicago 0.69 96.45 311.08 ArcelorMittal ArcelorMittal - Coatesville EAF Coatesville PA 970 39.97 -75.82 1793 Philadelphia 36.67 Philadelp 36.67 Philadelp 36.67 hia hia ArcelorMittal ArcelorMittal - Georgetown EAF Georgetown SC 1102 33.37 -79.29 1969 Charlotte Charlotte (now Liberty Steel Georgetown) 154.73 154.73 Philadelp 513.83

Industrial Siting for Sustainable Communities | Andrew Garrison

PLANT Scenario1 Company Plant B/E City Stat Tons Lat Lon Prod City Top 100 City Top 100 City City Top25 City City Top10 e Yr Dist Top25 Dist Top10 Dist hia ArcelorMittal ArcelorMittal - Indiana Harbor #2 BOF East Chicago IN 2205 41.66 -87.45 1882 Chicago Chicago Chicago 17.20 17.20 17.20 ArcelorMittal ArcelorMittal - Indiana Harbor #3 BOF East Chicago IN 2976 41.66 -87.45 1882 Chicago Chicago Chicago 17.20 17.20 17.20 ArcelorMittal ArcelorMittal - Indiana Harbor #4 BOF East Chicago IN 3638 41.66 -87.45 1882 Chicago Chicago Chicago 17.20 17.20 17.20 ArcelorMittal ArcelorMittal - Indiana Harbor EAF East Chicago IN 507 41.66 -87.45 1882 Chicago Chicago Chicago Bar 17.20 17.20 17.20 ArcelorMittal ArcelorMittal - Riverdale BOF Riverdale IL 1102 41.65 -87.62 1918 Chicago Chicago Chicago 13.50 13.50 13.50 ArcelorMittal ArcelorMittal - Steelton EAF Steelton PA 1213 40.23 -76.84 1865 Baltimore 65.48 Baltimore 65.48 Philadelp 91.72 hia ArcelorMittal ArcelorMittal - Vinton (now EAF El Paso TX 276 31.96 -106.59 1962 El Paso El Paso Phoenix Vinton Steel) 12.09 12.09 338.68 Yamato/Sumito Arkansas Steel Associates EAF Newport AR 165 35.65 -91.24 Memphis Memphis Dallas mo 80.61 80.61 372.96 Benteler Steel Benteler Steel/Tube (projected EAF Caddo-Bossier LA 440 32.34 -93.62 2013 Garland Dallas Dallas start-up scheduled 2018) 179.72 186.24 186.24 Big River Steel Big River Steel, LLC (projected EAF Osceola AR 1650 35.65 -89.94 2014 Memphis Memphis Dallas start-up scheduled 2015) 38.11 38.11 437.73 Bluescope Steel Bluescope Steel North America EAF Delta OH 2183 41.57 -84.05 1996 Toledo Detroit Chicago 25.09 74.33 188.37 Carpenter Steel Carpenter Latrobe Specialty EAF Latrobe PA 61 40.3 -79.37 Pittsburgh Steel (now Latrobe Specialty 33.57 Baltimore 162.15 Philadelp 225.03 Steel) hia Carpenter Steel Carpenter Technology Corp. EAF Reading PA 193 40.36 -75.94 Philadelphia 49.18 Philadelp 49.18 Philadelp 49.18 hia hia Cascade Steel Cascade Steel Rolling Mills EAF McMinnville OR 882 45.23 -123.16 1968 Portland Seattle San Jose 32.77 169.77 552.90 Charter Steel Charter Steel Cleveland EAF Cleveland OH 248 41.44 -81.66 Cleveland Detroit Chicago 2.95 98.60 312.36 Charter Steel Charter Steel Saukville EAF Saukville WI 639 43.4 -87.95 Milwaukee Chicago Chicago 23.54 108.78 108.78 Commercial Commercial Metals - Alabama EAF Birmingham AL 661 33.55 -86.8 Birmingham Nashville Houston Metals 1.38 181.23 568.36 Commercial Commercial Metals - Arkansas EAF Magnolia AR 331 33.21 -93.23 Garland Dallas Dallas Metals 198.18 207.39 207.39 58

Industrial Siting for Sustainable Communities | Andrew Garrison

PLANT Scenario1 Company Plant B/E City Stat Tons Lat Lon Prod City Top 100 City Top 100 City City Top25 City City Top10 e Yr Dist Top25 Dist Top10 Dist Commercial Commercial Metals - Mesa EAF Mesa AZ 287 33.29 -111.58 Gilbert Phoenix Phoenix Metals 9.35 35.24 35.24 Commercial Commercial Metals - South EAF Cayce SC 882 33.96 -81.05 Charlotte Charlotte Metals Carolina 87.37 87.37 Philadelp 530.86 hia Commercial Commercial Metals - Texas EAF Seguin TX 992 29.58 -98.03 San Antonio San San Metals 31.04 Antonio 31.04 Antonio 31.04 Crucible Crucible Industries EAF Syracuse NY 50 43.07 -76.21 Rochester New New Industries 71.52 York 203.60 York 203.60 G.O. Carlson Electralloy EAF Oil City PA 61 41.43 -79.72 Pittsburgh Detroit 69.81 185.98 Philadelp 259.86 hia Ellwood Group Ellwood National Steel Irvine EAF Irvine PA 77 41.84 -79.27 Buffalo Detroit 75.59 200.03 Philadelp 250.63 hia Ellwood Group Ellwood Quality Steels Co. New EAF New Castle PA 386 40.99 -80.35 Pittsburgh Castle 42.70 Columbus 154.99 Philadelp 282.75 hia EVRAZ North EVRAZ Claymont Steel EAF Claymont DE 496 39.81 -75.45 Philadelphia America 21.90 Philadelp 21.90 Philadelp 21.90 hia hia EVRAZ North EVRAZ Pueblo EAF Pueblo CO 1213 38.23 -104.61 1881 Colorado El Paso Phoenix America Springs 45.01 453.15 528.41 J.V. Arcelor Gallatin Steel (now Nucor EAF Ghent KY 1609 38.76 -85 1993 Cincinnati Louisville Chicago Mittal & Gerdau Gallatin) 37.22 53.90 255.66 Long Steel North America Gerdau Long Gerdau Long Steel North EAF Beaumont TX 656 30.08 -94.07 Houston Houston Houston Steel North America - Beaumont (now 81.63 81.63 81.63 America Optimus Steel) Gerdau Long Gerdau Long Steel North EAF Rancho CA 750 34.09 -117.53 Riverside Los Los Steel North America - California (now CMC) Cucamonga 13.12 Angeles 50.66 Angeles 50.66 America Gerdau Long Gerdau Long Steel North EAF Cartersville GA 904 34.24 -84.8 Atlanta Nashville Chicago Steel North America - Cartersville 39.71 174.55 548.51 America Gerdau Long Gerdau Long Steel North EAF Charlotte NC 452 35.34 -80.83 Charlotte Charlotte Steel North America - Charlotte 8.99 8.99 Philadelp 448.94 America hia Gerdau Long Gerdau Long Steel North EAF Jackson TN 617 35.73 -88.81 Memphis Memphis Chicago Steel North America - Jackson 79.05 79.05 426.99 59

Industrial Siting for Sustainable Communities | Andrew Garrison

PLANT Scenario1 Company Plant B/E City Stat Tons Lat Lon Prod City Top 100 City Top 100 City City Top25 City City Top10 e Yr Dist Top25 Dist Top10 Dist America Gerdau Long Gerdau Long Steel North EAF Baldwin FL 661 30.28 -81.98 1978 Jacksonville Steel North America - Jacksonville (now 19.55 Jacksonvil 19.55 Philadelp 775.96 America CMC) le hia Gerdau Long Gerdau Long Steel North EAF Knoxville TN 496 35.98 -83.96 Lexington Nashville Chicago Steel North America - Knoxville (now CMC) 145.14 158.76 451.97 America Gerdau Long Gerdau Long Steel North EAF Midlothian TX 1786 32.46 -97.03 1970 Arlington Dallas Dallas Steel North America - Midlothian 17.41 27.39 27.39 America Gerdau Long Gerdau Long Steel North EAF Petersburg VA 1190 37.19 -77.45 1999 Norfolk Steel North America - Petersburg 69.36 Baltimore 152.91 Philadelp 231.88 America hia Gerdau Long Gerdau Long Steel North EAF Sayerville NJ 805 40.48 -74.32 Newark New New Steel North America - Sayreville (now CMC) 18.38 York 23.53 York 23.53 America Gerdau Long Gerdau Long Steel North EAF Paul MN 606 44.89 -93.01 St. Paul Chicago Chicago Steel North America - St Paul 6.05 340.97 340.97 America Gerdau Long Gerdau Long Steel North EAF Wilton IA 342 41.58 -91.04 Madison Chicago Chicago Steel North America - Wilton 132.98 174.42 174.42 America Gerdau Special Gerdau Special Steel North EAF Smith AR 507 35.31 -94.37 Tulsa Dallas Dallas Steel North America - Fort Smith 102.95 222.02 222.02 America Gerdau Special Gerdau Special Steel North EAF Jackson MI 358 42.2 -84.36 Toledo Detroit Chicago Steel North America - Jackson 54.83 65.66 172.40 America Gerdau Special Gerdau Special Steel North EAF Monroe MI 551 41.89 -83.36 Toledo Detroit Chicago Steel North America - Monroe 19.54 36.42 222.54 America GKN Hoeganaes GKN Hoeganaes Corp. - Gallatin EAF Gallatin TN 331 36.37 -86.42 Nashville Nashville Chicago 24.84 24.84 384.35 Haynes Haynes International EAF Kokomo IN 33 40.47 -86.16 Indianapolis Chicago International 47.73 Indianapo 47.73 123.47 lis Keystone Steel Keystone Steel and Wire EAF Peoria IL 1323 40.64 -89.65 1889 Chicago Chicago Chicago 131.86 131.86 131.86 Le Tourneau Le Tourneau Technologies (now EAF Longview TX 121 32.46 -94.74 Garland Dallas Dallas Technologies Nucor Longview) 114.35 120.44 120.44

Industrial Siting for Sustainable Communities | Andrew Garrison

PLANT Scenario1 Company Plant B/E City Stat Tons Lat Lon Prod City Top 100 City Top 100 City City Top25 City City Top10 e Yr Dist Top25 Dist Top10 Dist Leggett & Platt Leggett & Platt Wire Rod EAF Sterling IL 2381 41.79 -89.71 1936 Madison Chicago Chicago 91.05 104.71 104.71 Whemco Steel Lehigh Specialty EAF Latrobe PA 66 40.31 -79.38 Pittsburgh 32.87 Baltimore 162.92 Philadelp 225.60 hia Mid-American Mid-American Steel EAF Oklahoma City OK 331 34.08 -96.75 Plano Dallas Dallas Steel 71.25 89.24 89.24 North American North American Höganäs, Inc. EAF Hollsopple PA 298 40.19 -78.93 Pittsburgh Höganäs Hollsopple 58.02 Baltimore 137.89 Philadelp 201.43 hia North American North American Stainless EAF Ghent KY 1543 38.73 -85.07 1990 Cincinnati Louisville Chicago Stainless 41.38 49.88 255.40 NLMK Indiana Novolipetsk Steel EAF Portage IN 799 41.62 -87.16 Chicago Chicago Chicago 30.86 30.86 30.86 Nucor Nucor - Yamato Steel EAF Armorel AR 2579 35.9 -89.77 1992 Memphis Memphis Chicago Corporation 56.59 56.59 425.97 Nucor Nucor Steel - Arkansas EAF Blytheville AR 2646 35.94 -89.71 1993 Memphis Memphis Chicago Corporation 60.06 60.06 422.45 Nucor Nucor Steel - Auburn EAF Auburn NY 496 42.95 -76.57 Rochester New New Corporation 55.20 York 208.49 York 208.49 Nucor Nucor Steel - Berkeley EAF Huger SC 3439 33 -79.88 1995 Charlotte Charlotte Corporation 162.26 162.26 Philadelp 551.92 hia Nucor Nucor Steel - Birmingham EAF Birmingham AL 661 33.54 -86.81 Birmingham Nashville Houston Corporation 0.90 181.92 567.55 Nucor Nucor Steel - Decatur EAF Trinity AL 2403 34.64 -87.09 1997 Birmingham Nashville Chicago Corporation 78.56 107.17 499.05 Nucor Nucor Steel - Hertford EAF Cofield NC 992 36.35 -76.81 Chesapeake Corporation 36.40 Baltimore 204.34 Philadelp 269.12 hia Nucor Nucor Steel - Indiana EAF Crawfordsville IN 2480 39.98 -86.82 1989 Indianapolis Chicago Corporation 38.16 Indianapo 38.16 136.28 lis Nucor Nucor Steel - Jackson EAF Flowood MS 551 32.31 -90.13 Baton Rouge Memphis Houston Corporation 142.19 193.18 357.06 Nucor Nucor Steel - Kankakee EAF Bourbonnais IL 849 41.18 -87.85 Chicago Chicago Chicago Corporation 46.49 46.49 46.49 Nucor Nucor Steel - Marion EAF Marion OH 397 40.57 -83.14 Columbus Chicago Corporation 41.67 Columbus 41.67 252.03 Nucor Nucor Steel - Memphis EAF Memphis TN 882 35.05 -90.16 Memphis Memphis Dallas Corporation 10.76 10.76 410.23 61

Industrial Siting for Sustainable Communities | Andrew Garrison

PLANT Scenario1 Company Plant B/E City Stat Tons Lat Lon Prod City Top 100 City Top 100 City City Top25 City City Top10 e Yr Dist Top25 Dist Top10 Dist Nucor Nucor Steel - Nebraska EAF Norfolk NE 992 42.08 -97.37 Omaha Chicago Chicago Corporation 88.70 498.42 498.42 Nucor Nucor Steel - Seattle EAF Seattle WA 783 47.57 -122.37 1904 Seattle Seattle San Jose Corporation 3.58 3.58 710.93 Nucor Nucor Steel - South Carolina EAF Darlington SC 1047 34.38 -79.9 1968 Charlotte Charlotte Corporation 78.02 78.02 Philadelp 469.65 hia Nucor Nucor Steel - Texas EAF Jewett TX 1213 31.34 -96.16 1975 Dallas Dallas Dallas Corporation 106.48 106.48 106.48 Nucor Nucor Steel - Tuscaloosa EAF Tuscaloosa AL 1301 33.23 -87.51 1985 Birmingham Memphis Houston Corporation 45.96 191.60 521.85 Nucor Nucor Steel - Utah EAF Plymouth UT 992 41.88 -112.2 Denver Phoenix Phoenix Corporation 410.10 574.84 574.84 Optima Optima Specialty Steel (planned EAF Ashland KY 402 38.37 -82.76 1963 Lexington Chicago Acquisitions shutdown 2013) now Kentucky 95.18 Columbus 111.99 353.95 Electric Steel Severstal North Severstal Columbus (now SDI EAF Columbus MS 2370 33.45 -88.58 2007 Birmingham Memphis Houston America columbus) 102.83 139.39 474.15 Severstal North Severstal Dearborn (Now AK EAF Dearborn MI 4519 42.3 -83.16 1920 Detroit Detroit Chicago America Steel Dearborn) 6.33 6.33 234.23 SSAB Americas SSAB Axis Steel Works EAF Mobile AL 1378 30.94 -88.01 2001 New Orleans Memphis Houston 129.94 309.58 447.49 SSAB Americas SSAB Montpelier Works EAF Montpelier IA 1246 41.48 -90.82 1997 Madison Chicago Chicago 132.14 164.16 164.16 Trimaran Standard Steel LLC EAF Burnham PA 231 40.64 -77.57 Baltimore Partners 105.74 Baltimore 105.74 Philadelp 135.85 hia Steel Dynamics Steel Dynamics Butler Site Flat EAF Butler IN 2976 41.37 -84.92 1996 Fort Wayne Detroit Chicago Roll Steel Div 22.50 116.90 146.40 Steel Dynamics Steel Dynamics Columbia City EAF Columbia City IN 2480 41.12 -85.35 2006 Fort Wayne Chicago Site Structural & Rail Div 11.14 Indianapo 101.80 130.61 lis Steel Dynamics Steel Dynamics Pittsboro Site EAF Pittsboro IN 728 39.88 -86.48 Indianapolis Chicago Engineered Bar Products Div 18.84 Indianapo 18.84 149.40 lis Steel Dynamics Steel Dynamics Roanoke Bar Div EAF Roanoke VA 722 37.27 -80 Greensboro Charlotte 81.48 149.82 Philadelp 324.18 hia Steel Dynamics Steel of West Virginia EAF Huntington WV 309 38.43 -82.43 Columbus Chicago 111.19 Columbus 111.19 364.17

Industrial Siting for Sustainable Communities | Andrew Garrison

PLANT Scenario1 Company Plant B/E City Stat Tons Lat Lon Prod City Top 100 City Top 100 City City Top25 City City Top10 e Yr Dist Top25 Dist Top10 Dist The Timken Co The Timken Co - Faircrest EAF Canton OH 871 40.75 -81.44 Cleveland Chicago 52.02 Columbus 97.08 332.85 The Timken Co The Timken Co - Harrison EAF Canton OH 683 40.77 -81.44 Cleveland Chicago 50.68 Columbus 97.83 332.49 ThyssenKrupp ThyssenKrupp Stainless USA EAF Calvert AL 1102 31.15 -87.99 2010 New Orleans Memphis Houston Stainless USA (Outokumpu) 138.31 296.53 450.99 TMK - Ipsco TMK - Ipsco Koppel EAF Koppel PA 496 40.84 -80.32 Pittsburgh 32.92 Columbus 152.19 Philadelp 279.21 hia TPCO America TPCO America (projected start- EAF Gregory TX 836 27.91 -97.27 Corpus San San up scheduled 2015) Christi 12.65 Antonio 132.24 Antonio 132.24 Union Electric Union Electric Steel Corp. - EAF Burgettstown PA 35 40.41 -80.41 Pittsburgh Steel Corp Harmon Creek Plant 22.74 Columbus 139.00 Philadelp 280.24 hia Universal Universal Stainless & Alloy EAF Bridgeville PA 149 40.37 -80.1 Pittsburgh Stainless & Products 7.96 Columbus 154.58 Philadelp 263.76 Alloy Products hia US Steel US Steel - Fairfield Works BOF Fairfield AL 2400 33.48 -86.92 1917 Birmingham Nashville Houston Corporation 7.74 186.21 560.05 US Steel US Steel - Gary Works (No. 1 BOP BOF Gary IN 8102 41.61 -87.34 1906 Chicago Chicago Chicago Corporation & Q-BOP) 23.69 23.69 23.69 US Steel US Steel - Granite City Works BOF Granite City IL 2866 38.69 -90.14 1895 St. Louis Chicago Corporation 6.41 Indianapo 226.65 253.61 lis US Steel US Steel - Great Lakes Works BOF Ecorse MI 3527 42.26 -83.13 1901 Detroit Detroit Chicago Corporation 8.44 8.44 235.47 US Steel US Steel - Mon Valley Works BOF Braddock PA 2899 40.4 -79.86 1937 Pittsburgh Corporation 6.90 Columbus 167.39 Philadelp 251.30 hia V&M Star Steel V&M Star Steel Co EAF Youngstown OH 694 41.13 -80.68 Cleveland Co 57.32 Columbus 144.69 Philadelp 301.67 hia Acciaierie Valbruna Slater Stainless Inc EAF Ft. Wayne IN 61 41.07 -85.17 1925 Fort Wayne Chicago Valbruna 2.09 Indianapo 103.07 140.59 lis Warren Steel Warren Steel Holdings (now AM EAF Warren OH 441 41.21 -80.82 Cleveland Holdings Warren) 48.41 Columbus 141.80 Philadelp 310.04 hia Whemco Steel Whemco Steel Castings EAF Midland PA 65 40.63 -80.45 Pittsburgh 27.99 Columbus 140.82 Philadelp 283.78 hia 63

Industrial Siting for Sustainable Communities | Andrew Garrison

PLANT Scenario1 Company Plant B/E City Stat Tons Lat Lon Prod City Top 100 City Top 100 City City Top25 City City Top10 e Yr Dist Top25 Dist Top10 Dist Nucor Nucor Brandenburg EAF Brandenburg KY 1200 38 -86.17 2022 Louisville Louisville Chicago Corporation 30.66 30.66 277.42