On the agenda: Buena Vista meeting — Data Center (May 20)

AGENDA
PLANNING AND ZONING COMISSION
TOWN OF BUENA VISTA, COLORADO
May 20, 2026 7:00 PM
In-person Meeting will be held at the Buena Vista Community Center with alternate zoom link availability
for the public to also attend virtually. To participate in Public Comment and/or Public Hearings you must
attend in-person or use the following link:

https://us02web.zoom.us/j/87822908708?pwd=72vEGLNBxthCN0OYKue7rbshbxDzRb.1
Meeting ID: 878 2290 8708

Passcode: BVP&Z

I.

CALL TO ORDER

II.

PLEDGE OF ALLEGIANCE

III.

ROLL CALL

IV.

AGENDA ADOPTION

V.

RATIFICATION OF MINUTES – April 22, 2026

VI.

PUBLIC COMMENT

VII.

BUSINESS ITEMS
1.
Business Item – Introductory Discussion on Data Centers

VIII.

STAFF/Commission Interaction
1.
Housing Needs Assessment Survey (Closes May 22)
a)
https://chaffeehousingplan.org/
2.
Transportation Masterplan Update
a)
b)
https://my-bv.com/transportation-master-plan-2026

IX.

ADJOURNMENT

Next meeting – June 3, 2026

This Agenda may be Amended
Posted at Buena Vista Town Hall and www.buenavistaco.gov

Planning & Zoning Commission Meeting
Wednesday, April 22, 2026, 7:00 p.m.
Buena Vista Community Center
Tony LaGreca called the meeting to order at 7:00 p.m.

Staff Present:

Title
Chair
Vice Chair
Commissioner
Commissioner
Commissioner
Alternate
Alternate

Quorum? YES
Present?
Present
Present
Present
Present
Present
Not Present
<vacant>

AF

Attendee Name
Tony LaGreca
Blake Bennetts
Tina Bennetts
Dave Kosley
Jared Lane
Lisa Field
<vacant>

Roll Call: Ally

T

Pledge of Allegiance: LaGreca

Marika Kopp: Present

Ally Kennedy: Present

Commissioner Kosley motioned to approve the agenda, commissioner Lane seconded, motion passed
unanimously.
Commissioner B. Bennetts moved to approve the April 1, 2026 minutes, Commissioner T. Bennetts
seconded, motion passed unanimously.

D
R

Public Comment: None; public comment was opened at 7:02; closed at 7:02 pm.
Business Items:

Public Hearing – LaSirena Temporary Vendor

Staff Presentation: Kennedy presented an overview of the temporary vendor, LaSirena, the
history of their operation and the public notice objection requiring the commission’s review. La
Sirena have submitted all required documentation, passed all inspections and have reduced
their signing to be code compliant.
Applicant Application: Evan Winger, owner of LaSirena, expressed gratitude for the
commission’s time. He urged the planning department to review the public noticing
requirements for temporary vendors in that if concerns brought forth anonymously are being
addressed to allow the department to approve/deny without having to bring forth to the
Commission.
Public Comments: None. Opened @ 7:08 pm; Closed at 7:08 pm
Commissioner Questions

Q: LaGreca inquired how the process is going? Kennedy and Kopp detailed that this is a new
process and some of the other E Main temp vendors expressed their frustration around the
public noticing requirement; LaGreca encouraged to revise the public noticing requirements
Q: B. Bennetts posed the option of a petition (to avoid anonymous complaints) with x number of
signatures. Planning will need to consult with legal
Commissioner discussion and Vote
B. Bennetts motioned to approve La Sirena temporary vendor permit, T. Bennetts seconded the
motion, motion passed unanimously.

●
●
●

D
R

●
●
●
●

Amazon application has formally been withdrawn; the applicant cited that the Chaffee County
Planning department and Board of Trustees brought forth items that were unable to be met
prior to the continuation date of May 12, 2026; they will be seeking a different location to serve
this area
Welcome to Queennie Beckelhymer, the new administrative assistant for the Planning and
Recreation departments
Temp Vendor Update: 11 permitted vendors, 8 anticipated
Sketch plan joint work session - posted notice didn’t go out in time, but after further review
more time was needed - 10% of water allocated needs to come from a different bucket that
general
City Market building permit is well under review; wanting to break ground this summer
Counter Culture - CDOT permit obtained, need to work with other agencies to schedule
No T. Bennetts at May 6, 2026meeting
Housing needs assessment is live; led by Chaffee County; commissioners encouraged to take and
widely share the survey; kick-off community meeting on May 5 in the Pinon Room

AF

●

T

Staff/Commission Interaction:

Adjournment:

Commissioner B. Bennetts motioned to adjourn the meeting, Commissioner Lane seconded; motion
passed at 7:31 p.m.
Next Planning & Zoning Commission Meeting: Wednesday, May 6, 2026 at 7:00 pm.

Respectfully submitted:
Tony LaGreca
Commission Chair

Ally Kennedy
Planning Technician

DATE:

May 15, 2026

TO:

Planning and Zoning Commission

FROM:

Marika Kopp, Planning Director

RE:

Initial Discussion on Data Centers

Purpose: Staff is beginning work on a potential temporary moratorium related to data centers and
similar high-intensity digital infrastructure uses for future consideration by the Buena Vista Board of
Trustees (BOT). This effort is being initiated after a general discussion and support from the BOT at the
May 12, 2026 meeting in recognition of the rapid national growth of data center development and the
significant infrastructure, utility, land use, and growth management implications these uses can create
for communities.
At this stage, staff is not seeking formal recommendations or action from the Planning & Zoning
Commission. Rather, staff would like to begin a broader policy conversation and receive early feedback
from the Commission regarding general zoning guidance on Data Center (and similar) uses.
Discussion: As staff develop additional research and potential future regulations, staff is seeking
feedback from the Commission on:
1. Should data centers be treated as a distinct land use category within the Town’s zoning code
rather than grouped under general industrial or commercial uses?
2. Are there existing zoning districts where these uses may or may not be appropriate?
3. Are there concerns about this proposed use?
a. Specificity is appreciated (i.e. regarding noise, backup generators, visual impacts,
lighting, or water consumption, etc.)
4. What information would the Commission want available before making future
recommendations on regulations or code amendments?
Background: Across the country, communities are seeing increasing interest in data center
development driven by cloud computing, artificial intelligence (AI), cryptocurrency processing, and
digital storage demand. These uses can create unique planning considerations related to:
• Electrical infrastructure demand
• Water consumption and cooling systems
• Noise and backup generator operations
• Large building footprints
• Economic development expectations versus employment generation
• Long-term land use compatibility and growth management

The American Planning Association (APA) and other planning organizations have increasingly
recommended that communities proactively evaluate how these uses should be addressed in local
zoning codes before proposals are received.
Optional Pre-Reading Resources
The following APA articles may help provide context prior to discussion:
• Data Centers Evolved: A Primer for Planners
• Zoning for Data Centers and Cryptocurrency Mining
• Managing AI Build-Out in a Winner-Take-Most World
Staff has also attached an October 2025 APA Zoning Practice publication titled The Physical Footprint of
Artificial Intelligence, which provides a planner-focused overview of zoning, infrastructure, water, and
utility considerations associated with data centers
Conclusion
This discussion represents the first step in the Town’s potential code amendment and policy review
process related to data centers and AI-related infrastructure uses. At this stage, staff is primarily
seeking broad policy guidance, community considerations, and initial direction from the Planning &
Zoning Commission before drafting future zoning and code amendments for future consideration.
Any feedback, concerns, desired outcomes, or initial questions the Commission would like staff to
research further are welcomed and appreciated as this process moves forward.

OCTOBER 2025 | VOL. 42, NO. 10

ZONING
PRACTICE

Unique Insights | Innovative Approaches | Practical Solutions

The Physical Footprint
of Artificial Intelligence

In this Issue: What Are the Physical Needs of AI? | How Is AI Infrastructure Regulated (or Not)? | What Should Planners Be Thinking About? | Where Can Planners Learn
More?

The Physical Footprint
of Artificial Intelligence
By Charlie Nichols, aicp
Every time you ask ChatGPT, Gemini, or Claude a question, you are tapping into a
sprawling, power-hungry network of machines. Somewhere, a data center’s processors
are whirring, fans are spinning, and megawatts of electricity are flowing.
Artificial intelligence (AI) may feel virtual, but its footprint is intensely physical.
Behind every chatbot interaction, predictive algorithm, or autonomous system lies
a vast network of data centers, power
generators, and electricity transmission
and distribution infrastructure. As vast as it
is now, the demand for computing power
is growing at an exponential rate, and local
zoning is on the front lines.

This issue of Zoning Practice explores
the physical effects of AI deployment and
highlights core considerations for local
planning and zoning. It begins with a summary of the land use characteristics of the
system of data centers that host and serve
contemporary AI models before highlighting noteworthy regulatory approaches and
areas of opportunity for zoning updates
and land use decision-making processes.

Data center
infrastructure
in the United
States, 2025
(Credit: NREL)

Zoning Practice | American Planning Association | October 2025 2

What Are the Physical Needs of
AI?

When we think about artificial intelligence, we often imagine abstract ideas
or algorithms, software, or maybe a chat
assistant or a robot. But AI is deeply physical. It runs on powerful hardware that
lives in large buildings, draws enormous
amounts of electricity, and requires robust
infrastructure to keep it cool and operational. These needs are shaping land use
decisions in ways many communities have
never dealt with before.
AI Lives in Data Centers
The primary home of AI is the data center.
These are large, sometimes windowless,
buildings filled with servers, networking
equipment, and backup systems. While
some are sleek and high-tech, many look
like simple warehouses. But inside, the
technology is anything but simple.
AI workloads require far more computational power than traditional cloud
computing. That means more servers
packed with graphics processing units
(GPUs), which are optimized for machine
learning tasks. These GPUs are energy-intensive and generate a significant amount
of heat (Shehabi et al. 2024; Casey 2025).
This is why the design, location,
and infrastructure of data centers have
become such a big deal. For example,
Meta’s Altoona, Iowa, data-center campus
has more than five million square feet of
space and is still growing (Miller 2022).
Data centers themselves fall into several distinct categories. Edge or micro
facilities are the smallest, often modular
container-sized enclosures ranging from
a few hundred to a few thousand square
feet. Enterprise data centers, typically
operated by corporations or universities,
can range from about 5,000 to 50,000
square feet, sometimes larger. Colocation
facilities lease space to multiple tenants and often fall between 50,000 and
600,000 square feet, with many averaging
around 150,000 square feet. At the largest
scale are hyperscale data centers, typically
built by major cloud or AI providers, which
can easily reach hundreds of thousands
of square feet per building and exceed
one million square feet across a campus
(Zhang 2023).
While many forecasts focus on power

demand rather than square footage, it is
possible to translate one into the other.
Deloitte estimates that AI-driven data
centers could require up to 123 gigawatts
(GW) of capacity in the U.S. by 2035, compared to roughly 4 GW today (Stansbury
et al. 2025). Real-world projects suggest
that every megawatt of IT load requires
between 5,000 and 12,000 square feet of
total building area. Applying that ratio to
123 GW implies a national buildout of 615
million to 1.48 billion square feet of data
center space, equivalent to about 22 to
53 square miles. Land use estimates point
in a similar direction, with recent projects averaging 0.5 to 1.5 acres per MW,
which would translate to roughly 96 to
288 square miles of U.S. land devoted to
AI-related data center campuses by 2035
(Stansbury et al. 2025).

AI Needs Lots of Electricity
Power demand is one of the most critical limiting factors in scaling AI. The
U.S. Department of Energy’s Secretary of
Energy Advisory Board notes that legacy
hyperscale data centers have typically
connected at 20–50 megawatts (MW),
but utilities are now receiving AI-driven
connection requests for single campuses
of 300–1,000 MW (2024). To put the
low end of that new range in context, a
300 MW facility running around the clock
would consume about 2.6 terawatt-hours
a year—roughly the annual electricity
use of 250,000 U.S. homes (calculated

A proposed 612acre hyperscale
data center
campus in Cedar
Rapids, Iowa
(Credit: QTS)

Zoning Practice | American Planning Association | October 2025 3

with the U.S. EIA average of 10,500 kWh
per household). These unprecedented
loads are forcing planners, utilities, and
regulators to rethink siting, transmission
capacity, and community-impact mitigation.
This demand is driving data centers
to locate near existing transmission infrastructure, substations, or power plants.
In some cases, new substations or transmission lines are being proposed just to
support AI infrastructure. Local planners
are being asked to approve not just buildings, but energy projects with regional
impacts.
There is also growing concern about
the climate impacts of AI. Researchers
estimate that the cumulative carbon emissions from AI models could reach 3.66
to 8.72 million tons in the U.S. alone—the
equivalent of driving an average gasoline-powered car nine to 22 billion miles
(Ding et al. 2025; USEPA 2024). This has
led to pressure for data centers to run on
renewable energy, adding another layer
of land use complexity as solar or wind
farms are proposed nearby or colocated
together with data centers.

Annual Water Withdrawal (Millions of Gallons)

Top-five U.S.
Google data
centers by annual
water withdrawals,
2024 (Credit:
Google’s 2025
Environmental
Report)

1,600
1,400
1,200
1,000

AI Needs Water and Cooling
All that power generates heat, and that
heat has to go somewhere. Most data
centers use a combination of air- and
watercooling systems. Some of the largest
AIfocused facilities can consume hundreds
of thousands of gallons of water per day

AI Needs Fiber and Connectivity
Finally, AI infrastructure depends on highspeed fiberoptic connections. Training
models and delivering AI services both
require fast, reliable data transmission.
This can drive the need for new fiber lines,
telecom infrastructure, or even small-cell
installations in rural or suburban areas
(RVA LLC 2025; Walker 2024).
It’s not just big cities seeing these
investments. Some rural areas are gaining
interest from AI developers because they
offer space, lower land costs, and cooperative local governments—provided they
can offer fiber access and a willing utility
partner.

How Is AI Infrastructure
Regulated (or Not)?

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800
600

for evaporative cooling (Lei et al. 2025;
Shehabi et al. 2024; Selsky 2022). That’s
raising concerns in water-scarce regions
or places where water infrastructure is
already stretched thin.
For example, in The Dalles, Oregon, a
dispute between Google and the city over
water use became national news when
the city council approved a water agreement to support Google’s data center
expansion, despite local concerns about
long-term water availability (Selsky 2022).
Water and cooling infrastructure also
raise siting questions. Should data centers
be allowed in areas with limited water supply? What happens when a tech company
becomes one of the largest users of
municipal water? These questions are
starting to reach planning commissions
and city councils.

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Golf Courses

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400
200
0
Council Bluffs, Mayes County,
Berkeley
Papillion, NE The Dalles, OR
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OK
County, SC
Google Data Center Locations

If your city or county does not already
have a data center, just wait. The odds
are increasing that a tech company, or the
utility that serves them, will soon come
knocking. Yet most local governments
are not fully prepared to regulate AI infrastructure. In many places, the regulatory
framework is either nonexistent or built for
a different era of technology.
Zoning Codes Rarely Mention AI
or Data Centers
Many zoning codes still make no explicit
reference to “artificial intelligence” or even
to “data centers.” Where definitions are

Zoning Practice | American Planning Association | October 2025 4

absent, planners may choose to slot these
facilities into broad buckets such as warehousing, light-industrial, or public-utility
uses, even though the buildings may be
packed wall-to-wall with servers instead of
pallets.
Yet these facilities behave very differently from the categories they’re often
shoehorned into, and there are many
reasons why local governments may want
to specifically define data center uses
(Morley 2022). Their continuous operation
demands megawatts of electricity and,
in many climates, hundreds of thousands
of gallons of cooling water per day; the
equipment generates heat and noise; and
the employment footprint is minimal. When
such impacts are overlooked, communities can be blindsided—as happened
in Prince William County, Virginia, where
approval of a massive datacenter corridor
sparked backlash over noise, power delivery, and land use compatibility.
Recognizing this mismatch, an
increasing number of jurisdictions have
begun to write data-center-specific rules.
Loudoun County, Virginia, imposes
façade, screening, lighting, and pedestrian-connectivity standards on by-right
data centers to blunt visual impacts while
leveraging their tax base (§4.06.02).
Prince William County uses a Data Center
Opportunity Zone Overlay to funnel projects to infrastructure-served parcels and
require design review (§32-509). Missoula
County, Montana, offers a different model.
The county’s ordinance, crafted for cryptocurrency mines, confines those operations
to industrial zones and requires them to
offset 100 percent of their electricity use
with renewable energy (§5.10). Because
cryptocurrency mines and large‑scale
data centers both run continuously, draw
high‑density power, and employ few
on‑site workers, planners can adapt the
same toolkit—clear land use definitions,
targeted overlay districts, and energy‑focused performance standards—to data
centers when communities want comparable safeguards.
Looking ahead, AI training clusters
dwarf the loads discussed in 2022, with
utilities now fielding single-campus interconnection requests of 300 MW and
more. The zoning fundamentals remain the
same, but the stakes are higher. Without

proactive definitions, locational criteria,
and impact standards, local governments
risk conceding critical decisions about
land, water, and grid capacity to developers’ timetables rather than community
goals.

Many AI Facilities Are Allowed by
Right
In areas that do allow data centers
by right, local officials often have little
authority to influence their design or siting (Morley 2022). Developers may be able
to build massive facilities with only administrative approval. If the project complies
with the basic zoning and building code, it
can move forward, even if it brings significant impacts to neighboring properties or
the local infrastructure system.
This hands‑off, by‑right approach can
leave neighbors in the dark when a campus that draws 100 MW or more of power
is permitted the same way a warehouse
is. Such facilities may also require hundreds of thousands of gallons of cooling
water per day and generate continuous
low‑frequency noise from chillers, pumps,
and backup generators (Van Geet and
Sickinger 2024). Without a public‑hearing
trigger, residents may not learn what is
coming until the bulldozers roll.
That said, relying on discretionary use permits alone is not a perfect
fix. Case‑by‑case approvals can introduce
uncertainty, increase timelines, and duplicate reviews that utilities already perform
when they decide whether to supply the
necessary electricity and water. A more
balanced strategy is to embed objective,
use‑specific standards (e.g., caps on
sound at the property line, requirements
for renewable‑energy procurement, and

Data Center
Alley in Loudoun
County, Virginia
(Credit: Gerville/
iStock/Getty
Images Plus)

Zoning Practice | American Planning Association | October 2025 5

water‑recycling targets) directly into the
zoning code. Guidance from the Urban
Land Institute shows how clear definitions,
overlay districts, and measurable performance thresholds can give developers
predictability while still protecting community interests (Miet 2024). By pairing these
standards with early coordination among
planners, utilities, and residents, communities can address local impacts without
resorting to duplicative or open‑ended discretionary reviews.
Infrastructure Approvals May Be
Handled Separately
Adding to the complexity, the infrastructure
needed to support AI such as transmission lines, substations, power generation
facilities, battery energy storage. and fiber
installations is often regulated under different frameworks. Utilities may have their
own review and siting authority at the state
level, which can bypass local land use
processes entirely.
Large solar or wind projects, for example, are pre-empted from local control in
more than 20 U.S. states, leaving local
governments to vet the data-center building, while the power generation facility that
feeds it is debated elsewhere (Gomez and
Morley 2023; Morley 2025). Fragmented
approvals make it hard for planners to tally

cumulative effects such as substations,
access roads, or groundwater withdrawals.
Battery-energy-storage systems
(BESS) create another layer of complexity,
and a clear trend of data centers colocating BESS on-site is accelerating
(ZincFive 2024). Some states exempt utility-scale BESS that are colocated with
generation assets, while others treat them
as industrial equipment needing only an
electrical permit. Where local authority
does apply, recent guidance recommends
clear definitions, district regulations, and
objective safety standards, thermal-runaway monitoring, minimum setbacks, and
emergency-response plans to avoid
ad-hoc hearings (Ross and Vadali 2024).
Developers are now bundling data
centers with on-site renewables and storage in microgrid “energy parks,” aiming
to bypass long interconnection queues
and control energy costs. Recent projects in Texas and Virginia pair hundreds
of megawatts of generation and storage
with adjacent server halls, creating hybrid
campuses that straddle state energy-facility review, regional transmission rules, and
local zoning (DiGangi 2025). To keep pace,
planners can identify jurisdictional triggers
early, embed measurable performance
standards (e.g., noise caps, screening, or
renewable-energy sourcing) in their codes,

The Eland Solarplus-Storage
Center in Kern
County, California
(Credit: The Desert
Photo/iStock/Getty
Images Plus)

Zoning Practice | American Planning Association | October 2025 6

and coordinate with utilities so local and
state reviews proceed on aligned timelines.
Environmental Review Is
Inconsistent
Environmental review of AI infrastructure
also varies widely. In states that require
environmental impact statements (EIS),
large-scale data centers may undergo
detailed scrutiny. But in states without EIS
laws, or for smaller projects, there may be
minimal analysis of water use, energy consumption, or greenhouse gas emissions
(Morris 2024).
Even where review is required, the
focus may be on the building itself, rather
than the full ecosystem of impacts. For
example, if a local code does not require
review of off-site power infrastructure or
supporting utility upgrades, critical issues
related to energy delivery, environmental
impact, or long-term capacity may fall
through the cracks.
Local Governments Are Starting
to Catch Up
Local governments are no longer standing
still while hyperscale campuses spring
up at the edge of town. Since 2023, a
wave of city councils, county boards, and
planning commissions have begun moving data centers out of catch‑all industrial
categories and into their own, better‑defined regulatory boxes. Some jurisdictions,
such as Atlanta, now require special‑use
permits tied to energy, water, and noise
studies (Ordinance 25-O-1063). Others,
such as Cedar Rapids, Iowa, leverage
community‑benefit agreements to ensure
local reinvestment when a project wins
approval (Pratt 2025).
Approaches vary, but the trend is
unmistakable: Communities are adopting
objective, use‑specific standards rather
than relying solely on ad‑hoc discretionary
permits. Some ordinances steer projects
into infrastructure‑served corridors, others
set caps on sound and water use, and a
growing number link approvals to renewable energy procurement or on‑site
battery storage. Table 1 highlights seven
recent examples illustrating the breadth of
new zoning language, overlay districts,
and design guidelines that together show
local governments are indeed catching up.

Table 1. Examples of Recent Local Regulatory Updates for Data Centers

Jurisdiction
Atlanta, GA

Brainerd, MN

Chandler, AZ

Tempe, AZ

Phoenix, AZ

Sugar Grove, IL

Frederick County,
MD

How it regulates data-center
impacts
Requires a special-use permit
for every new data center and
empowers the city council to
review water-consumption, energyefficiency, and noise-mitigation plans
(Ordinance 25O1063, 2024)
Prohibits data centers unless the
planning commission approves
a conditional-use permit that
addresses cooling noise and utility
demand (Ordinance No. 1581, 2025)
Adds a data center use category;
limits the use to Planned Area
Development zones and sets size,
generator-testing and water-recycling
standards (Ordinance No. 5033, 2022)
Requires a water use plan and
enhanced setbacks next to homes
and schools, and “innovation hubs”
(Ordinance No. O2025-23, 2025)
Defines “data center,” restricts
locations, and introduces design
standards such as façade articulation
and noise studies (Ordinance
G-7396, 2025)
Creates a dedicated district with
height limits, façade screening, and
a master-utility-plan requirement
(Ordinance No. 2022-1206B, 2022)
Establishes an overlay zone that
limits where data centers can be built
(Bill No. 25-05, 2025)

What Should Planners Be
Thinking About?

Artificial intelligence may sound futuristic,
but the decisions that shape its physical
footprint are being made today. Local
governments that wait too long to prepare
may find themselves reacting to projects
rather than guiding them. So what should
planners be thinking about now?
Think About Scale
AI infrastructure often hides in plain sight
until its true footprint emerges. What looks
like a single “warehouse” can blossom
into a portfolio buildout—multiple server
Zoning Practice | American Planning Association | October 2025 7

halls, two substations, a battery yard, and
a 30-inch water main, all staged over a
decade (USDOE SEAB 2024). To avoid
approving these megaprojects one slice at
a time, some jurisdictions now demand a
phased master plan up front. For example,
Loudoun County, Virginia, requires every
data-center rezoning to include a “Data
Center Development Plan” showing the full
buildout of power feeds, cooling infrastructure, and utility corridors before the first
site plan is approved (2025).
Regional utilities are following suit by
running scenario-based load models to
test whether transmission and groundwater supplies can keep up. A 2024 white
paper by Energy + Environmental Economics describes how such models
informed Portland (Oregon) General
Electric’s latest integrated-resource plan
and helped local planners identify future
right-of-way corridors for two new 230-kV
lines (Riu et al. 2024). By asking for phased
utility exhibits and participating in utility
load-growth scenarios, planners can make
sure each new server hall fits into a system-wide picture rather than becoming an
isolated surprise.

Many comprehensive plans still
treat “technology infrastructure”
as an afterthought, yet data
center proposals are now shaping
decisions on land supply, energy
policy, water allocation, and
broadband.

Think About Alignment With Your
Plans
Many comprehensive plans still treat
“technology infrastructure” as an afterthought, yet data-center proposals are
now shaping decisions on land supply, energy policy, water allocation, and
broadband. Start by inventorying where
AI-related facilities touch existing plan
elements—utilities, environmental stewardship, economic development—and flag the
gaps.
One emerging best practice is to link

data-center approvals directly to community climate goals. Embedding such
benchmarks in comprehensive plans or
codes gives planners clear decision criteria and ensures that new AI infrastructure
advances, rather than conflicts with, local
resiliency objectives.
Plans can also weave data-center
growth into broadband and workforce
strategies. The U.S. Department of Energy’s 2024 report on AI infrastructure
recommends that local governments coordinate land-use designations with state
broadband-expansion maps so that fiber
corridors serving data centers double as
backbone routes for underserved neighborhoods (USDOE SEAB 2024). Aligning
these layers up front helps planners
negotiate public-benefit clauses—such as
dark-fiber setasides or training programs,
rather than scrambling for concessions
late in the process.
Updating your plan first and then
adopting measurable standards that flow
from it gives applicants clarity, while ensuring projects advance the community’s
long-term vision.
Think About Infrastructure
Capacity
AI campuses can overwhelm local utilities
faster than many other land uses. Virginia’s Joint Legislative Audit and Review
Commission estimates that data centers
will require 11 gigawatts (GW) of new electric generation and transmission in that
state alone by 2035, roughly one-third of
Dominion Energy’s entire current system
(VJLARC 2024). National modeling by
Energy + Environmental Economics shows
a similar surge, with some balancingareas
seeing load grow 25 percent in a single
decade under an “AI-high” scenario (Riu et
al. 2024).
Water systems face parallel stress. At
Google’s complex in The Dalles, Oregon,
public records show cooling demand
could top one-quarter of the city’s current supply, prompting a 2023 agreement
that pauses future phases unless new
wells come online (Selsky 2022). Quincy,
Washington, responded to similar pressures by creating a special water rate
class and meter fee for data centers to
fund infrastructure upgrades (2025). These
examples point to tools planners can

Zoning Practice | American Planning Association | October 2025 8

The Three Mile
Island nuclear
power plant
in Middleton,
Pennsylvania,
which is coming
back online to
power Microsoft
data centers
(Credit: gsheldon/
iStock Editorial/
Getty Images Plus)

adopt: cumulative-demand studies
embedded in utility master plans, tiered
rate structures that recover capital costs,
and permit conditions that link new construction to confirmed water-capacity
projects.
Electric and water systems are only
part of the picture. Broadband providers
may need additional conduit banks, and
public works departments often discover
that construction traffic surpasses roaddesign volumes. Objective, use-specific
standards, such as requiring a utilityinfrastructure plan that maps ultimate
substations, mains, and fiber routes, plus
haul-route and pavement-repair agreements, give planners leverage without
duplicating state or utility reviews.
Think About Cumulative Impacts
A single 30 MW data center can feel
benign, yet clusters of 10 or more along
one corridor may push peak electric
load past a gigawatt, double truck traffic
during construction, and raise ambient
sound by up to 10 dBA at nearby homes
(VJLARC 2024). Project-by-project review
often misses these system-level effects, so
several jurisdictions now require applicants
to look beyond their parcel lines.
Clustering can also amplify benefits

if managed deliberately. Developers in
Texas and Virginia now pair multiple
server halls with a shared microgrid that
combines on-site solar, wind, and battery
storage—an “energy-park” model that
eases interconnection delays and helps
regions meet renewable-energy goals
(DiGangi 2025). By mapping preferred
corridors for both data centers and their
supporting infrastructure, planners can
steer growth to areas where capacity,
compatibility, and community returns align.
Think About Equity and
Community Benefits
Data-center projects promise major capital
investment but generate few long-term
jobs and can offload noise, truck traffic,
and resource use onto nearby neighborhoods. Additionally, new cost analyses
show that ordinary ratepayers are already
footing most of the bill for AI’s voracious
appetite for electricity.
Monitoring Analytics, the independent
market monitor for PJM Interconnection,
the largest regional transmission organization in the U.S., calculated that between
2024 and 2025 data-center electricity
demand added about $25 to the typical
household’s monthly bill (Biryukov 2025).
PJM now projects that AI and data-center
Zoning Practice | American Planning Association | October 2025 9

A North Dakota
data center using
nonconductive
fluid to cool
servers rather
than air or
water cooling
systems (Credit:
halbergman/E+)

demand will double the region’s energy
use by 2033, whereas growth would have
been only 15 percent by 2040 without new
campuses (JLARC 2024).
In response to this and other similar
projections of effects on ratepayers, lawmakers in New Jersey (AB 5466), Oregon
(HB 3546), and other states have introduced bills or tariffs to place data centers
in a separate rate class or require them to
“bring their own clean power,” so everyday customers are not forced to subsidize
the electricity needs of trillion-dollar tech
companies (Levy 2025). More communities are also moving to tie approvals to
arrangements that deliver measurable
local benefits.
For example, Cedar Rapids, Iowa,
required QTS to sign a community
benefits agreement (CBA) that will
return about $18 million over 20 years for
workforce training, broadband expansion, and green-infrastructure projects
(Pratt 2025). Legal guidance stresses clear
milestones, third-party verification, and
enforcement clauses to keep such agreements credible (Eisenson 2023).
Meanwhile, Quincy, Washington, created a special water rate class for data
centers in 2024, adding higher volumetric
charges and meter fees earmarked for
new wells and main upgrades. Targeted
surcharges turn one user’s high demand
into system-wide resilience.
By weaving CBAs and host-community fees into zoning approvals or
development agreements, planners can
ensure that AI infrastructure acts as a

catalyst for broader community gain rather
than an enclave of private benefit.

Where Can Planners Learn
More?

As artificial intelligence infrastructure
expands, planners have a growing need to
stay informed about what these facilities
are, how they function, and how to plan for
them thoughtfully. The good news is that
several helpful resources already exist, and
more are emerging every year.
Follow the Energy
Many AI-related land use challenges stem
from energy demand. That means energy
planning organizations are a good place
to start. Resources from the U.S. Department of Energy, National Renewable
Energy Laboratory, and Lawrence Berkeley National Laboratory offer insights into
data center energy use, grid impacts, and
cooling technologies (Shehabi et al. 2024;
USDOE SEAB 2024; Van Geet and Sickinger 2024).
State and regional energy offices are
also useful partners. They can help planners understand energy trends, forecasted
demand, and opportunities to align AI-related development with state energy goals.
Watch the Water
Water use is another key issue, especially
in places facing drought or groundwater
depletion. Reports from the U.S. Environmental Protection Agency, as well as local
water utilities and watershed management
agencies, can help assess water-related
impacts of AI infrastructure.
Planners can also look to academic
and journalistic research on water use in
cooling systems, which varies significantly
based on the type of cooling and climate
zone (Berreby 2024).
Track Technology and Land Use
Trends
For a broad view of how technology
affects land use, the Lincoln Institute of
Land Policy and the Urban Land Institute
have both published helpful materials.
These organizations explore how emerging technologies from AI to autonomous
vehicles are reshaping cities, infrastructure, and land markets.

Zoning Practice | American Planning Association | October 2025 10

Local case studies can also be
instructive. Some jurisdictions have started
sharing lessons learned from planning
for large-scale data centers or tech campuses. For example, Loudoun (2024; 2025)
and Fairfax (2024) Counties in Virginia offer
planning documents and staff reports that
shed light on real-world challenges and
solutions.
Build Cross-Sector Relationships
Planning for AI infrastructure requires collaboration. It touches on land use, utilities,
economic development, and environmental protection. Building relationships with
energy providers, water utilities, economic
development groups, and regional planning agencies can help planners spot
opportunities and anticipate challenges.
Conferences like the American Planning Association’s National Planning
Conference, Grid Forward, or Smart Cities
Connect often include sessions on technology infrastructure. These events are a
great way to hear from peers and industry
experts.
AI infrastructure is no longer a faroff idea; it’s already shaping land use
decisions in communities across the
country. For planners, this presents both
challenges and opportunities. By understanding what AI infrastructure is, what it
requires, and how it fits into broader planning goals, local governments can prepare
for development that is sustainable, equitable, and forward-looking.
As with many emerging trends, the
best path forward is to stay curious, build
partnerships, and think holistically. AI may
be powered by algorithms, but the future it
creates will depend on human decisions,
including the choices planners make
today.

References and Resources
Berreby, David. 2024. “As Use of AI Soars, So
Does the Energy and Water It Requires.” Yale
Environment 360, February 6.
Biryukov, Nikita. 2025. “Power Companies Warn
Lawmakers About Their Plans to Tackle Rising
Bills.” New Jersey Monitor, April 25.
Casey, Evan. 2025. “Microsoft Built Five Data

Center Campuses in This Iowa City. Here’s
What Wisconsin Can Expect.” Wisconsin Public
Radio, May 15.

About the
Author

DiGangi, Diana. 2025. “Microgrid ‘Energy
Parks’ Could Ease Strain from Rising Power
Demand, Report Says.” Utility Dive, July 23.
Ding, Zhaohao, Jianxiao Wang, Yiyang Song,
Xiaokang Zheng, Guannan He, Xiupeng
Chen, Xiupeng Chen, Tiance Zhang, Wei-Jen
Lee, and Jie Song. 2025. “Tracking the Carbon
Footprint of Global Generative Artificial Intelligence.” The Innovation 6(5): 100866.
Eisenson, Matthew. 2023. “Experts Identify
Best Practices for Negotiating and Drafting
Community Benefits Agreements.” Climate
Law, September 27.
Fairfax (Virginia) Department of Planning Development, County of. 2024. Data Centers Report
and Recommendations.
Gomez, Alexsandra, and David Morley. 2023.
Solar@Scale: A Local Government Guidebook
for Improving Large-Scale Solar Development
Outcomes. Chicago: American Planning Association; Washington, DC: International City/County
Management Association.
Lei, Nuoa, Jun Lu, Arman Shehabi, and
Eric Masanet. 2025. The Water Use of Data
Center Workloads: A Review and Assessment
of Key Determinants. Berkeley, CA: Lawrence
Berkeley National Laboratory.
Levy, Marc. 2025. “As Electric Bills Rise, Evidence
Mounts That Data Centers Share Blare. States
Feel Pressure to Act.” Associated Press, August 8.
Loudoun (Virginia), County of. 2024. “Data Center Growth and Energy Constraints.” Board of
Supervisors Transportation and Land Use Committee Information Item, June 20.

Charlie Nichols,
aicp, is the Director
of Planning and
Development
for Linn County,
Iowa. He leads
a 15-person
department
and has written
pioneering zoning
ordinances for
utility-scale solar,
nuclear energy,
and hyperscale
data centers.
Nichols received
his master’s
degree in urban
and regional
planning from
the University
of Iowa and has
been working
in the field of
planning for over
10 years. Outside
of work, he enjoys
tending to his
backyard chickens
and working on
home renovation
projects with his
wife and three
children.

Loudoun (Virginia), County of. 2025. Data Center
Standards & Locations.
Miet, Hannah. 2024. “Local Guidelines for Data
Center Development.” Washington, D.C.: Urban
Land Institute.
Miller, Rich. 2022. “The New MegaCampuses:
The World’s Largest Data Center Projects.”
Data Center Frontier, November 1.
Zoning Practice | American Planning Association | October 2025 11

Morley, David. 2022. “Zoning for Data Centers and Cryptocurrency Mining.” Zoning Practice, June. American Planning
Association.
Morley, David. 2025. “Wait, Who Approves Large-Scale Solar
Siting?” APA Blog, March 3.
Morris, Jackson. 2024. “Data Centers Gobbling Up Existing
Nukes Threatens Grid Decarb Goals.” National Resources
Defense Council Expert Blog, July 11.
Pratt, Richard. 2025. “Cedar Rapids Council Approves Development Agreement for QTS Data Center Project.” Corridor
Business Journal, January 30.
Prince William (Virginia) Planning Office, County of. 2022.
DPA2021-0020: Data Center Opportunity Zone Overlay District Comprehensive Review.
Quincy (Washington), City of. 2025. Rate Resolution 25-709.
Riu, Isabelle, Dieter Smiley, Stephen Bessasparis, and Kushal
Patel. 2024. Load Growth Is Here to Stay, But Are Data Centers? San Francisco: Energy + Environmental Economics.

U.S. Energy Information Administration. 2024. Use of Energy
Explained: Electricity Use in Homes.
U.S. Environmental Protection Agency (USEPA). 2024. Greenhouse Gas Equivalencies Calculator.
Virginia Joint Legislative Audit and Review Commission
(VJLARC). 2024. Virginia Data Center Study: Electric Infrastructure and Customer Rate Impacts.
Van Geet, Otto, and David Sickinger. 2024. Best Practices for
Energy-Efficient Data Center Design. Washington, D.C.: U.S.
Department of Energy Federal Energy Management Program.
Walker, Willy. 2024. “The Future of Real Estate Is Digital: How
Data Centers and 5G Are Shaping the Next Generation of
Infrastructure.” Walker & Dunlop Market Trends, October 30.
Zhang, Mary. 2023. “Types of Data Centers: Enterprise,
Colocation, Hyperscale.” Dgtl Infra, November 26.
ZincFive. 2024. “Data Center Energy Storage Industry
Insights Report 2024.”

Ross, Brian, and Monika Vadali. 2024. “Battery Energy Storage Systems.” Zoning Practice, March.
RVA LLC. 2025. “The Underappreciated Need to Enable AI
and Data Center Growth.” Washington, DC: Fiber Broadband
Association.
Selsky, Andrew. 2022. “Oregon City Drops Fight to Keep
Google Water Use Private.” Associated Press, December 15.
Shehabi, Arman, Sarah J. Smith, Alex Hubbard, Alex Newkirk,
Nuoa Lei, Md Abu Bakar Siddik, Billie Holecek, Jonathan
Koomey, Eric Masanet, and Dale Sartor. 2024. 2024 United
States Data Center Energy Usage Report. Berkeley, CA:
Lawrence Berkeley National Laboratory.
Stansbury, Martin, Kelly Marchese, Kate Hardin, and Carolyn
Amon. 2025. “Can U.S. infrastructure Keep Up With the AI
economy?” Deloitte Insights, June 24.
U.S. Department of Energy, Secretary of Energy Advisory Board
(USDOE SEAB). 2024. “Recommendations on Powering Artificial Intelligence and Data Center Infrastructure.”

ZONING PRACTICE OCTOBER 2025 | VOL. 42, NO. 10. Zoning Practice (ISSN 1548–

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