Town Council

450 S. Parish Avenue Johnstown, CO 80534 970-587-4664 JohnstownCO.gov Town Council Work Session 450 S. Parish, Johnstown, CO Monday, July 13, 2026 at 6:00 PM Mission Statement: Enhancing the quality of life of our residents, businesses, and visitors through community focused leadership. Agenda Call to Order Agenda Items 1. Consideration for Data Center Development 2. November Ballot Measures Adjourn Americans with Disabilities Act Notice In accordance with the Americans with Disabilities Act and other applicable laws, persons who need accommodation in order to attend or participate in this meeting should contact Town Hall at 970-587-4664 no later than 48 hours before the meeting in order to request such assistance. De conformidad con la Ley de Discapacitados Estadounidenses y otras leyes vigentes, los individuos que necesitan adaptaciones funcionales para asistir o participar en esta reunión deberán comunicarse con la Municipalidad marcando el 970 587- 4664 a lo más tardar 48 horas antes de dicha reunión para solicitarla. Page 1 of 26  450 S. Parish Avenue Johnstown, CO 80534 970-587-4664 JohnstownCO.gov Town Council Work Session Communication Agenda Date: July 13, 2026 Subject: Consideration for Data Center Development Attachments: 1. Data Center Presentation Presented by: Sarah Crosthwaite, Economic Development Director Jennifer Simmons, Planning and Development Director Work Session Item Description: The following memorandum provides an overview of data centers, including their scale, utility demands, land use considerations, and potential economic impacts and partnership opportunities. The purpose of this memo is to provide Town Council with information and to solicit feedback on the direction Council would like staff to take regarding the development of a policy for the attraction and development of data centers within the Town. I. DEFINING DATA CENTERS • Specialized facilities that house computer systems and digital infrastructure such as servers, storage systems, and networking equipment. • Designed to store, process, and distribute large amounts of data securely and efficiently. • Operate 24/7 with built-in redundancy (backup power, cooling systems, security) to ensure reliability. • Range from enterprise and small facilities (boutique/local providers) to large-scale “hyperscale” facilities/campuses operated by major technology companies. II. DATA CENTER TYPES & EXAMPLES Boutique Colorado Data Center Examples: • CoreSite – Downtown Denver: 157,000 SF facility; campus expected to expand incrementally; 5–10 MW (not verified, estimated). Moderate power demand; designed for redundancy rather than massive load. Supports the tech ecosystem rather than acting as a major tax generator. • Iron Mountain DEN-1 – Downtown Denver (industrial corridor along I-70): 180,000 sq. ft. facility (6- acre campus); 14.4 MW. Uses renewable energy sources. Creates strong tax revenue with relatively Page 2 of 26  low service demand (i.e. Police, Fire, School impact). • Colorado Colocation (Darwin Data Center) – Lakewood: 5,000 SF facility; campus expected to expand incrementally; 2 MW. Minimal power strain; serves regional companies and IT providers. Provides modest but stable tax revenue. • Earthnet Data Center (Massive Networks) – Boulder: 24,686 SF (shared building with other users); 1–5 MW range. Very low power strain; serves startups, research, and regional businesses. Limited fiscal impact but important for the local tech ecosystem. Hyperscale U.S. Data Center Examples: • Amazon Web Services – Northern Virginia (Ashburn “Data Center Alley”): One of the largest concentrations of data centers in the world, supporting AWS cloud infrastructure. Approximately 300 data centers distributed throughout the region; 3,900 MW. • Microsoft – Quincy, Washington: Campus leveraging access to affordable hydropower from the Columbia River. 270-acre campus; 622 MW. • Google – Council Bluffs, Iowa: Campus supporting Google Cloud, Search, and YouTube operations; expected to expand incrementally. 2.9 million SF campus (approximately 66 acres); 40–90 MW per individual facility. • Meta – Altoona, Iowa: Facility supporting Facebook, Instagram, and WhatsApp platforms. 5+ million SF facility (approximately 114 acres); 1,400 MW. Site Selection Factors for Hyperscale Data Centers: • As of 2026, Colorado does not have any operational hyperscale data centers. While the state has attracted smaller enterprise and colocation facilities, it has generally not been competitive for hyperscale investment due to a combination of factors, including the absence of targeted state incentives, a lack of a coordinated statewide data center attraction strategy, regulatory and permitting considerations, and constraints related to available power infrastructure and electrical capacity. • Requires hundreds to thousands of acres of land, typically contiguous. • Built in phases over many years. • Extremely high utility demand; 24/7 operations (different from a home that has peak vs. non-peak hours of consumption). • Strategic location decisions based on: o Power availability and cost including ability to scale up. o Access to fiber connectivity and reliability. o Climate (for cooling efficiency). o Robust tax and policy environment (local, regional, and state incentives). Page 3 of 26 III. DATA CENTER UTILITY IMPACTS Energy Scale Difference between Boutique and Hyperscale: • Boutique: 1–15 MW (power) • Hyperscale: 100–1,000+ MW (power) Energy Efficiency: Data centers require large amounts of reliable, continuous power to operate efficiently. Existing power providers in CO are unable to meet those demands in the near-term without significantly investing in expanding their infrastructure. Power providers such as Xcel Energy and United Power have created ‘Large Load’ request processes that put the burden on large power developers/applicants to fund the studies and infrastructure upgrades required to meet their demand. These processes have a goal to ensure residents and existing power users are not affected nor impacted from a rate perspective or access to power on a large load user coming onto the grid. PVREA does not have a ‘Large Load’ request process. Data Centers are increasingly located near wind and solar farms. This strategy helps absorb excess renewable energy that might otherwise be wasted. Data centers can utilize this surplus power, improving overall energy efficiency and reducing renewable energy waste. Case Study – Google Campus, Pine Island, Minnesota (1,900 MW): In partnership with Xcel Energy, Google is developing a clean energy data center campus designed to be carbon free. It includes: • 200 MW of solar power • 1,400 MW of wind energy • 300 MW iron air battery system Waste Heat Recovery: Waste heat recovery means data centers can capture excess heat generated by servers and repurpose it for beneficial uses, improving overall energy efficiency and reducing wasted energy. Depending on location and available infrastructure, recovered waste heat can be used to heat nearby commercial buildings, residential developments, district energy systems, greenhouses, or industrial facilities, reducing overall energy demand. Municipalities can encourage or require waste heat recovery through development standards, building codes, or development agreements where appropriate and economically feasible. Case Study – U.S. National Renewable Energy Laboratory (NREL), Golden, Colorado: Since 2010, NREL has utilized waste heat generated from an on-site data center to heat its laboratory and office building. The project includes: • An on-site data center where the heat it generates is used to heat the remainder of the building • Waste heat recovery used to heat a 220,000-square-foot laboratory and office facility • Successful operation since 2010, demonstrating the feasibility of capturing and reusing excess heat. A model that has helped advance broader adoption of waste heat recovery technologies in data Page 4 of 26  center design *Power Demand Equivalency – Context for Johnstown: Total Johnstown Housing Units: 8,097 (SFH & Multi); estimated overall energy consumption of 26 MW (during peak). Power Level Equivalent Homes (2,000 sq. ft. Scale Reference home approx.) 1 MW ~309 homes 10 MW ~3,086 homes Comparable to a small town 50 MW ~15,432 homes Comparable to a mid-size city (ex. Raleigh, NC) 100 MW ~30,863 homes 1,000 MW (1 GW) ~308,632 homes Comparable to a principal city (ex. Los Angeles, CA) Water Demand & Cooling Technology: Data center cooling systems are becoming more advanced and are designed to reduce both energy and water use over time. Many modern facilities utilize several water efficient cooling systems. Below is a general description of several of the more common cooling systems. • Air Cooling: One of the most common and traditional cooling methods used in data centers. This system uses air conditioning units, vents, and ducts to remove heat generated by servers and IT equipment. Cool air is circulated through server rooms while hot air is exhausted away from the equipment. This process is not efficient or effective for data centers utilizing large amounts of electricity. • Open-Loop Cooling: Uses water evaporation to cool IT rooms and equipment. Water is circulated through cooling towers where heat is released through evaporation into the atmosphere. This process is similar to evaporative cooling methods used in agriculture and industrial operations. It is highly effective for removing heat but is highly water intensive. • Closed-Loop Cooling: Continuously recycles and reuses water instead of discharging it after one use. Heated water is cooled through a cooling tower or heat exchanger and then recirculated back through the system. This process can reduce water waste and can be supplemented by incorporating recycled wastewater, capturing rainwater, and non-potable water sources. • Direct-to-Chip Cooling: Delivers liquid coolant directly to GPUs and CPUs through tubes or cooling plates. The liquid absorbs heat at the source before circulating to a heat exchanger. Because direct- to-chip cooling systems use liquid coolants, operators select non-corrosive, electrically non- conductive fluids and incorporate leak detection sensors, high-quality seals, and preventative Page 5 of 26  monitoring to minimize the risk of leaks. Cooling systems must also comply with environmental and safety regulations to protect personnel, equipment, and the surrounding environment. This process is highly efficient in delivering coolant where needed, comparable to drip irrigation in agriculture. However, this is a costly system and requires specialized infrastructure and maintenance. *Water Cooling Technology Ranking: Cooling Relative Relative Efficiency Considerations System Water Use Energy Intensity Air Lowest Highest Requires little to no process water. Not efficient Cooling from an energy perspective, requires higher energy demand to cool facility. Closed- Low Low Continuously recycles and reuses water instead Loop of discharging it after one use. More energy efficient than air cooling. Some makeup water may be needed. Direct- Moderate Lowest Delivers liquid coolant to GPUs and CPUs to-Chip -Low through tubes or cooling plates. The liquid absorbs the heat efficiently. The liquid must be disposed of properly and building these types of data centers are very costly and require specialized infrastructure and maintenance. Small amounts of makeup water may be needed. Open- Highest Moderate Uses water evaporation to remove heat from IT Loop equipment. Water is circulated through cooling towers, where heat is released into the atmosphere through evaporation. Offers good energy efficiency but has the highest water consumption due to evaporation and continuous replacement of new water. *Disclaimer: The estimates and equivalency comparisons in the previous tables are provided for illustrative purposes only and are based on publicly available research and generalized assumptions. They are intended to provide context for the relative scale of potential energy use and cooling technology efficiency. They should not be interpreted as definitive, site-specific, or guaranteed values. Actual resource consumption varies widely based on factors such as facility size, technology, operations, cooling systems, climate, and efficiency. The table should not be relied upon as a precise representation of the energy or water-cooling technology efficiency of any proposed data center in Johnstown. Page 6 of 26 IV. FISCAL IMPACT & EMPLOYMENT Tax revenue will depend on the size of the facility. Boutique facilities can provide minimal to moderate property and personal business property tax revenue while hyperscale facilities generate high tax revenue. Both project types often request incentives from local and state partners, with hyperscale projects being fully reliant (incentive driven) on property and sales tax rebates and waiver of fees. Fiscal Pros: • Strong Property Tax Base: Data centers often represent high capital investment, leading to significant property tax revenues due to the value of the building and infrastructure. • Personal Property Tax Revenue: Equipment housed within data centers (servers, hardware) can generate substantial personal property tax revenues, depending on state law and depreciation schedules. • Minimal Service Demand: Data centers typically require limited municipal services (e.g., schools, public safety, parks), resulting in a favorable cost-to-revenue ratio. Fiscal Cons: • Incentive Sensitivity: Data center projects often seek tax incentives or abatements, which can reduce near-term fiscal benefits but, in the long term, do provide a revenue stream. • Depreciation of Equipment: Personal property (PP) tax revenues may decline over time as equipment depreciates. However, as equipment is replaced with new assets, those assets are placed on new depreciation schedules, generating additional personal property tax revenues. • Limited Multiplier Effect: Compared to other commercial or industrial uses, data centers generate less secondary economic activity (e.g., retail, hospitality). Employment Impact: Facilities typically have low employment density, meaning they generate relatively few permanent jobs compared to the amount of land and infrastructure they use. In the regional context, unemployment rates are currently 4.8% in Weld County and 4.2% in Larimer County, both of which include individuals who are not actively participating in the workforce. This suggests that, overall, most individuals who are able and willing to work are already employed in a relatively tight labor market. Within this environment, attracting data centers is often viewed as a strategic economic development approach because they do not significantly compete for the already limited local talent pool that other industries rely on for hiring and retention. In Johnstown specifically, the local labor force is 12,284 people, which grew by 8.35% from 2024 to 2025. The Town’s unemployment rate is approximately 4%, which is 0.3% below the national average. Taken together, these indicators reflect a growing but still competitive labor market, where job-creating industries must be considered alongside their ability to align with available workforce capacity. Employment Pros: Page 7 of 26  • High-Wage Technical Jobs (Long-term): Positions in IT, engineering, and facility management tend to be well-paid. • Construction Jobs (Short-Term): Development phases can generate significant temporary employment. Employment Cons: • Limited Permanent Employment: Once operational, data centers typically employ relatively few people per square foot compared to other land uses. • Specialized Workforce Needs: Jobs may require highly specialized skills, which may not align with the existing local workforce without targeted training programs. V. INCENTIVES CASE STUDY – COLORADO The following is a fictional case study to represent the potential revenue and incentives that a data center could generate and request, specific to Johnstown within Weld County. The table below outlines key assumptions of the fictional project. Assumption Value Data Center Size 35 MW New Machinery & Equipment Investment $2,000,000,000 Assessed Value Rate 29.0% Assessed Value $580,000 Weld County Mill Levy Rate 15.038 mills Town of Johnstown Mill Levy Rate 23.947 mills Refund Percentage per Year (incentive) 50.0% The following scenarios assume that data center equipment and machinery are replaced on either a 3- or 5- year cycle, with each replacement beginning a new depreciation schedule for personal business property tax purposes. The depreciation schedules have been fast tracked to account for the replacement of the machinery and equipment. The examples also assume a hypothetical Town incentive equal to a 50% rebate of eligible personal business property tax to demonstrate how such an incentive could function over time. 3-Year Depreciation, Revenue, & Incentive Scenario: Year Depreciation Assessed Taxes Due to Taxes Due to 50% Refund to Net New Schedule Value Weld County Town of Company Revenue to Johnstown Town Page 8 of 26 Year 1 92.0% $533,600,000 $8,024,277 $12,778,119 $6,389,060 $6,389,060 Year 2 50.0% $290,000,000 $4,361,020 $6,944,630 $3,472,315 $3,472,315 Year 3 25.0% $145,000,000 $2,180,510 $3,472,315 $1,736,158 $1,736,158 Total $968,600,000 $14,565,807 $23,195,064 $11,597,532 $11,597,532 5-Year Depreciation, Revenue, & Incentive Scenario: Year Depreciation Assessed Value Taxes Due to Taxes Due to 50% Refund to Net New Schedule Weld County Town of Company Revenue to Johnstown Town Year 1 92.0% $533,600,000 $8,024,277 $12,778,119 $6,389,060 $6,389,060 Year 2 75.0% $435,000,000 $6,541,530 $10,416,945 $5,208,473 $5,208,473 Year 3 50.0% $290,000,000 $4,361,020 $6,944,630 $3,472,315 $3,472,315 Year 4 40.0% $232,000,000 $3,488,816 $5,555,704 $2,777,852 $2,777,852 Year 5 22.0% $127,600,000 $1,918,849 $3,055,637 $1,527,819 $1,527,819 Total $1,618,200,000 $24,334,492 $38,751,035 $19,375,518 $19,375,518 *The Town refunds 50% of new Town tax revenue from this investment to the company each year for 3 or 5 years. Weld County property taxes are collected by the County and are not part of the Town's incentive; shown for context only. VI. LAND USE & DEVELOPMENT CODE CONSIDERATIONS Johnstown’s current Land Use Development Code (LUDC) does not specifically define or classify data centers as a standalone land use. As a result, data centers would currently be categorized as Warehouse with Indoor Storage, which is permitted only through a Use by Special Review (USR) process within the I-1 (Light Industrial) and I-2 (Heavy Industrial) zoning districts. Based on the Town’s current zoning, there are fewer than 160 acres west of I-25 that are zoned I-1 and could independently accommodate a data center application through the existing USR process. Because the LUDC does not contain standards specific to data centers, any application submitted today would be reviewed under the existing Warehouse with Indoor Storage criteria. The current Code does not address the unique characteristics of data centers, including high electrical demand, water use, cooling technologies, backup power systems, noise, and other environmental and infrastructure considerations discussed in this memorandum. As communities continue to evaluate data center development, many have established land use classifications and development standards that distinguish between different types of facilities based on their scale and operational characteristics. Two common classifications include: • Boutique Data Centers: Smaller facilities with relatively compact footprints that are often suited for infill or adaptive reuse projects. While these facilities can also be developed on greenfield sites, Johnstown’s available industrial land could readily accommodate a boutique data center campus from a land availability perspective. • Hyperscale Data Centers: Large campus-style developments that typically occupy greenfield sites and require significant electrical infrastructure. Although they encompass substantial acreage, these Page 9 of 26  facilities generally have low day-to-day activity levels, with relatively few employees and limited traffic once operational. Land Use Development Pros: • Low traffic generation and minimal impact on road networks (after construction activities cease). • Limited demand for public services (schools, parks, etc.). • Can serve as a long-term, stable land use with minimal disruption to surrounding areas. Land Use Development Cons: • Large land consumption with relatively low employment density. • May limit opportunities for more active or mixed-use development. • Often visually and functionally less integrated into community fabric. • Rapid advancements in technology may reduce the usefulness of current data center facilities over time, creating uncertainty about their future adaptability and redevelopment potential. VII. COUNCIL DIRECTION REQUESTED Based on the information presented in this memorandum, staff is seeking Council feedback on the following policy considerations: • Approval Process: Should data centers be permitted by right, through a Use by Special Review (USR) process, or prohibited within the Town? • Land Use Classification: Should the Town establish a dedicated land use classification for data centers within the Land Use Development Code (LUDC)? If so, should the Town distinguish between boutique and hyperscale data centers based on their scale, operational characteristics, and potential impacts? • Zoning Districts: In which zoning districts, if any, should data centers be permitted? • Development Standards: If permitted, what development standards or review criteria should be incorporated to address topics such as electrical demand, water use, cooling technology, backup power systems, noise, environmental impacts, and compatibility with surrounding land uses? • Economic Development Incentives: Should the Town consider offering economic development incentives for data center projects? If so, what types of incentives, if any, would be appropriate (e.g., infrastructure participation, fee waivers, tax increment financing, or other performance-based incentives)? • Performance Metrics: What performance metrics should a data center project be required to meet to be eligible for incentives? Examples may include capital investment, job creation, wage levels, renewable energy commitments, water conservation measures, waste heat recovery, public Page 10 of 26  infrastructure improvements, or other community benefits. REFERENCES 1. DataBank. “What Are the Benefits of Using Solar and Wind Energy in Data Centers?” Accessed 2026. https://www.databank.com/faq/what-are-the-benefits-of-using-solar-and-wind-energy- in-data-centers/. 2. Data Center Map. “Data Center Locations and Industry Directory.” Accessed 2026. https://www.datacentermap.com/. 3. Environmental and Energy Study Institute. “Data Centers and Water Consumption.” Accessed 2026. https://www.eesi.org/articles/view/data-centers-and-water-consumption. 4. Environmental Health News. “New Data Centers Tap Unused Wind and Solar Power to Lower Costs and Cut Waste.” Accessed 2026. https://www.ehn.org/new-data-centers-tap-unused- wind-and-solar-power-to-lower-costs-and-cut-waste. 5. Nature Forward. “Data Centers and Water Use.” Accessed 2026. https://natureforward.org/data-centers-and-water-use/. 6. Super Micro Computer, Inc. (n.d.). Direct-to-chip liquid cooling. Accessed 2026, from https://www.supermicro.com/en/glossary/direct-to-chip-liquid-cooling 7. U.S. Department of Energy. “Clean Energy Resources to Meet Data Center Electricity Demand.” Accessed 2026. https://www.energy.gov/oe/clean-energy-resources-meet-data-center- electricity-demand. 8. World Resources Institute. “From Energy Use to Air Quality, the Many Ways Data Centers Affect U.S. Communities.” Published February 17, 2026. https://www.wri.org/insights/us-data-center- growth-impacts. Reviewed and Approved for Presentation, Town Manager Page 11 of 26  Data Center Discussion TOWN COUNCIL WORK SESSION JULY 13, 2026 Page 12 of 26 Objectives • Define Data Centers • Explain the variety of data center sizes • Discuss potential impacts and opportunities • Receive Town Council direction regarding future policy Page 13 of 26 What is a Data Center? • Houses servers and digital infrastructure (stores data digitally) • Operates 24/7 • Requires reliable power and cooling • Range from boutique facilities to hyperscale campuses Page 14 of 26 Boutique vs. Hyperscale – Not all Data Centers are the same Page 15 of 26 Exhibit from American Planning Association; Technology Division. Webinar presented April 2026 https://www.youtube.com/watch?v=3Wp6DGEfoLs Page 16 of 26 Utility Factors – Energy & Power Considerations Power Demand • Boutique 1-15 MW • Hyperscale 100-1,000 MW Power Providers • Xcel Energy & United Power require large load applicants to fund infrastructure improvements related so that existing customers are not affected from a reliability and rate perspective. PVREA currently does not have a formal large load process. • Data centers operate 24/7 and require reliable uninterrupted electricity Johnstown Considerations • Total Johnstown Housing Units: 8,097 (SFH & Multi); estimated overall energy consumption of 26 MW (during peak). Power Level Equivalent Homes Scale Reference (2,000 sq. ft. home approx.) 1 MW ~309 homes 10 MW ~3,086 homes Comparable to a small town 50 MW ~15,432 homes Comparable to a mid-size city (ex. Raleigh, NC) 100 MW ~30,863 homes 1,000 MW (1 GW) ~308,632 homes Comparable to a principal city (ex. Los Angeles, CA) Page 17 of 26 Utility Factors – Water Cooling & Emerging Technologies Data Center Industry Trends • Modern data centers increasingly prioritize renewable energy integration (ex. locating near renewable energy sources such as wind/solar farms), water conservation (ex. cooling technologies), and energy recovery technologies (ex. waste heat) to reduce environmental impacts. • Water demand depends almost entirely on the cooling technology selected. Modern facilities increasingly use closed-loop systems, direct-to-chip cooling, recycled water, and waste heat recovery to reduce both energy and water consumption. Cooling System Water Use Efficiency Considerations Air Cooling Lowest Requires little to no process water. Not efficient from an energy perspective, requires higher energy demand to cool facility. Closed-Loop Low Continuously recycles and reuses water instead of discharging it after one use. More energy efficient than air cooling. Some makeup water may be needed. Direct-to-Chip Moderate Low Delivers liquid coolant to GPUs and CPUs through tubes or cooling plates. The liquid absorbs the heat efficiently. The liquid must be disposed of properly and building these types of data centers are very costly and require specialized infrastructure and maintenance. Small amounts of makeup water may be needed. Open-Loop Highest Uses water evaporation to remove heat from IT equipment. Water is circulated through cooling towers, where heat is released into the atmosphere through evaporation. Offers good energy efficiency but has the highest water consumption due to evaporation and continuous replacement of new water. It is important to note that data center cooling systems are becoming more advanced and are designed to reduce both energy and water use over time. Page 18 of 26  Economic Factors – Fiscal & Employment Impact Data Center Fiscal Benefits • Building and infrastructure generate property tax revenue • Servers & IT equipment (machinery and equipment) can generate substantial personal property tax revenue • As equipment is replaced, new depreciation schedules begin, creating an ongoing source of tax revenue. • Data centers are considered low cost to serve; typically require limited municipal services once operational (Police, Fire, etc.) Johnstown Considerations • Many projects request local and state incentives to remain competitive. • Personal property tax revenue declines as equipment depreciates but can be renewed through future equipment replacement cycles. • Limited Secondary Spending; compared to other commercial or industrial uses, data centers generate less secondary economic activity (e.g., retail, hospitality). Data Center Employment Impact • During construction data centers create 100-1,000 of temporary construction jobs • During operations data centers employment impact is significantly lower but includes high-paying technical positions (final employment number depends on size of data center) Johnstown Considerations • Limited workforce competition; with regional unemployment around 4% and a tight labor market, data centers generally do not compete heavily with other employers for local workers. Page 19 of 26  Fictional Data Center Project – Revenue & Incentive Values The following is a fictional case study to represent the potential revenue and incentives that a data center could generate and request, specific to Johnstown within Weld County. 3-Year Depreciation, Revenue, & Incentive Scenario Year Depreciation Assessed Value Taxes Due to Taxes Due to 50% Refund Net New Schedule (%) Weld County Town of to Company Revenue Johnstown to Town Assumption Value Year 1 92.0% $533,600,000 $8,024,277 $12,778,119 $6,389,060 $6,389,060 Year 2 50.0% $290,000,000 $4,361,020 $6,944,630 $3,472,315 $3,472,315 Data Center Size 35 MW Year 3 25.0% $145,000,000 $2,180,510 $3,472,315 $1,736,158 $1,736,158 New Machinery & Equipment Investment $2,000,000,000 Total $968,600,000 $14,565,807 $23,195,064 $11,597,532 $11,597,532 Assessed Value Rate 29.0% 5-Year Depreciation, Revenue, & Incentive Scenario Assessed Value $580,000 Year Depreciation Assessed Value Taxes Due to Taxes Due to 50% Refund to Net New Weld County Mill Levy Rate 15.038 mills Schedule (%) Weld County Town of Company Revenue Johnstown to Town Town of Johnstown Mill Levy Rate 23.947 mills Year 1 92.0% $533,600,000 $8,024,277 $12,778,119 $6,389,060 $6,389,060 Refund Percentage per Year 50.0% Year 2 75.0% $435,000,000 $6,541,530 $10,416,945 $5,208,473 $5,208,473 Year 3 50.0% $290,000,000 $4,361,020 $6,944,630 $3,472,315 $3,472,315 Year 4 40.0% $232,000,000 $3,488,816 $5,555,704 $2,777,852 $2,777,852 Year 5 22.0% $127,600,000 $1,918,849 $3,055,637 $1,527,819 $1,527,819 Total $1,618,200,000 $24,334,492 $38,751,035 $19,375,518 $19,375,518 Page 20 of 26 Land Use & Development Factors – Johnstown Framework Where does Johnstown stand today? • Data centers are not identified or defined in the Land Use Development Code. • If a data center was proposed, it would be categorized as Warehouse with Indoor Storage. • Allowed only through a Use by Special Review (USR) in the following zoning districts: • I-1 Light Industrial • Approximately 100 acres available west of/adjacent to the interstate • I-2 Heavy Industrial • No land available Johnstown Considerations • The LUDC does not currently contain standards addressing: • Electrical demand • Backup power systems • Water use & cooling systems • Environmental impacts • If an application for a data center was submitted today, it would be able to be processed. However, today’s LUDC was not written with data centers in mind. Page 21 of 26 Town Council Feedback & Direction Approval Process: Should data centers be permitted by right, through a Use by Special Review (USR) process, or prohibited within the Town? Land Use Classification: Should the Town establish a dedicated land use classification for data centers within the Land Use Development Code (LUDC)? If so, should the Town distinguish between boutique and hyperscale data centers based on their scale, operational characteristics, and potential impacts? Zoning Districts: In which zoning districts, if any, should data centers be permitted? Development Standards: If permitted, what development standards or review criteria should be incorporated to address topics such as electrical demand, water use, cooling technology, backup power systems, noise, environmental impacts, and compatibility with surrounding land uses? Economic Development Incentives: Should the Town consider offering economic development incentives for data center projects? If so, what types of incentives, if any, would be appropriate (e.g., infrastructure participation, fee waivers, tax increment financing, or other performance-based incentives)? Performance Metrics: What performance metrics should a data center project be required to meet to be eligible for incentives? Examples may include capital investment, job creation, wage levels, renewable energy commitments, water conservation measures, waste heat recovery, public infrastructure improvements, or other community benefits. Can we legally prohibit data centers? Page 22 of 26  Thank You Questions Sarah Crosthwaite Jenn Simmons Economic Development Director Planning & Development Director scrosthwaite@johnstownco.gov jsimmons@johnstownco.gov Page 23 of 26  450 S. Parish Avenue Johnstown, CO 80534 970-587-4664 JohnstownCO.gov Town Council Work Session Communication Agenda Date: July 13, 2026 Subject: November Ballot Measures Attachments: None Presented by: Matt LeCerf, Town Manager Work Session Item Description: Over the past few months, Town Council has briefly discussed potential ballot measures to ask the Johnstown electors to consider. While Council did not provide information related to specific election cycles, one of the opportunity elections is quickly approaching in November 2026. In order to ask the voters to consider a ballot measure, we must engage with both Larimer and Weld County to conduct a coordinated election. In this instance, the two counties would produce, mail ballots to the registered electors of the Town of Johnstown, and tally votes of the responses to the questions the Town Council would consider placing on the ballot. A tentative calendar of milestones that must be achieved, to be included in the November 2026 election are provided as well as a very high level estimate of the cost to participate in the coordinated election. Those ballot measure questions that have been generally discussed by Council are as described below. Calendar Milestones for November 2026 Coordinated Election: July 24 – Last Day to notify Weld and Larimer Counties August 24 – Last day to sign IGAs with Counties September 18 – Last day for pro/con statements to Meghan September 21 – Last day to submit ballot question and ballot issue notice October 2 – Ballots may be mailed November 3 – Election Day Estimated Cost: $40,000 - $50,000 HOME RULE CHARTER (HRC) AMENDMENTS Term Limits Council has brought up a change to propose term limits for Town Council. Currently, as outlined in the Home Rule Charter states the following: Section 2.4. - Term of Office; Time of Taking Office; Oath. A. Each Councilmember shall be elected for a four (4) year term. Councilmembers' terms shall Page 24 of 26 be staggered, as provided by ordinance. The Mayor shall be elected for a four (4) year term. There currently is no reference to term limits within the HRC and this was originally approved and included in the HRC. If Council desires to ask the voters to consider an amendment that includes term limits, Staff would request guidance pertaining to a number of detailed items including: regarding the total number years a Mayor and/or Councilmember may serve. There are a number of details related to this matter Staff would also need to receive including: 1. How many years or terms can a Town Council person serve? Typically, as outlined in State Statute term limits are set at 2 terms of 4 years each. Options for term limits may include: (2, 4 year terms (8 total); 3, 4 year terms (12 total)). 2. Can a Councilmember serve the proposed number of terms and then run for the position of Mayor in series? 3. Is the quantification of time based on the number of terms elected, or for example, can an elected official be appointed and then elected formally for the consecutive terms? 4. Is there a number of years the elected official must be off the Town Council before they can run again for office? Town Manager Title Change Council has asked about the desire to change the title of the Town Manager to either Chief Administrative Officer (CAO) or Chief Executive Officer (CEO). Currently, the position of Town Manager is included in the HRC. The term City Manager, Town Manager, or County Manager as applicable is synonymous with local governments and is inherently recognized as the prescriptive title in the profession. Furthermore, it compliments the form of government the Town of Johnstown and most municipalities in the U.S. exist; a Council-Manager form of government. Within this structure, the position of Town Manager functions as the CAO and in other instances it functions as the CEO. This information is simply provided for some background into the profession. If Council desires to ask the voters for a title change, they would need to approve this amendment by modifying Section 8 of the HRC. Upon approval, all references to the Town Manager in the Johnstown Municipal Code would need to be modified and updated, presumably through one blanket ordinance for efficiency. TABOR MEASURES Open Space, Parks & Trails Sales & Use Tax In April 2026, the voters of the Community were asked to consider approving an Open Space, Parks, & Trails Sales and Use Tax. The TABOR question for this purposed ask for a 0.5% sales and use tax. The ballot measure presented to the voters failed by a 52.5% to 47.5% margin. As part of the recent FY 2027 Budget planning, it was suggested by Town Council to consider asking voters the question again. If Town Council desires to ask the voters in the November elections, what would the ask of the community be for this sales tax initiative? STAFF RECOMMENDATIONS: Staff's recommendation based on the financial cost associated with a coordinated election, is that we do not pursue any initiatives at this time in November 2026. The Town's municipal elections occur every two years. Staff believes during our regular elections would be the Page 25 of 26 appropriate time period to ask voters these, or any other questions for consideration. Any impacts as a result of waiting until the April 2028 municipal election cycle would be minimal to the long-term strategies of the Town of Johnstown. Reviewed and Approved for Presentation, Town Manager Page 26 of 26