Prepared by Aaron Wang, Skyline High School, Sammamish, Washington
Research snapshot: May 23–24, 2026

Important: This is a screening study, not an engineering feasibility study, site recommendation, or claim that any parcel is available. It identifies leads and questions for qualified stakeholders to investigate.

Contents

Executive summary

Data centers continuously remove heat from servers. Under the right conditions, some of that heat may support a nearby greenhouse, food processor, aquaculture operation, drying facility, building, or other heat user.

Heat is difficult and expensive to move long distances, and rural and urban sites have different surroundings. This study therefore tested two questions:

In Quincy, can public data identify nearby parcels or existing heat users that deserve closer review? In downtown Seattle, can public data identify nearby building-density signals that justify a different urban screening pathway?

The proof-of-concept screen found:

These findings do not establish a viable project. In Quincy, they suggest asking whether a compatible heat-using business could locate or expand near the source. In Seattle, they support examining nearby buildings, campuses, or business-district systems. Both cases show why screening must be tailored to local conditions.

Quincy case study: M Street data center cluster

Data centers screened

The parcel screen used four data center records clustered around M Street. Street addresses came from operator or industry sources, and representative coordinates were derived from those addresses with the U.S. Census Geocoder.

ID Facility record Address used for mapping Representative coordinates Evidence basis
WA003 Vantage WA1 Quincy campus 2101 M St NE 47.248500681, -119.815393797 Vantage campus page plus secondary directory records
WA004 SDC Quincy / Sabey Quincy 2200 M St NE 47.248620103, -119.814735424 Sabey operator page
WA005 H5 Quincy Data Center 1711 M St NE 47.248610243, -119.817382040 H5 operator page
WA009 H5 Quincy II and III campus 1500 M St NE representative point 47.248493365, -119.818233560 H5 Quincy II and H5 Quincy III operator pages

The points represent geocoded facility addresses, not surveyed heat-recovery equipment or pipe connection locations. The H5 Quincy II and III coordinate is a representative point based on 1500 M Street NE because the Census service did not resolve the other published campus address, 1305 Intermodal Way NE.

Parcel-screening methodology

A Python screening program queried the public GIS services and produced the 33-record review queue summarized below.

Public GIS layers

The script queried these live public services on May 23, 2026:

  1. Grant County parcel layer
  2. Grant County vacant or undeveloped parcel layer
  3. City of Quincy zoning layer
  4. City of Quincy future land-use layer

Processing steps

  1. Load the four selected data center points shown above.
  2. Query parcels in a bounding box around the cluster.
  3. Calculate a representative parcel point by averaging the polygon vertices returned by the GIS service.
  4. Calculate straight-line distance from that point to each selected data center using the Haversine formula and an Earth radius of 6,371 kilometers.
  5. Retain parcels no more than 1.0 kilometer from the nearest selected data center point.
  6. Retain records flagged in the vacant layer or described as industrial land or cropland.
  7. Query zoning and future land use at the representative parcel point.
  8. Assign a first-pass triage category using public ownership labels, property classes, land-use descriptions, and zoning intersections.

This process returned 33 records. Each record was labeled as a GIS lead only, not evidence of availability, buildability, utility capacity, or project suitability.

Triage results

Triage category Count What it means for screening
Likely data-center-owned or expansion-associated 17 Relevant mainly if an operator wants to integrate reuse into campus planning; not independently available land
Likely utility or public infrastructure 6 Useful for understanding infrastructure and public control; not assumed developable
Port-owned candidate needing availability review 3 Possible economic-development discussion leads; availability and infrastructure unverified
Industrial or food/logistics ownership lead 3 Nearby ownership or facility leads; current operations, thermal demand, and interest unverified
Agricultural edge needing land-use review 3 Requires agricultural, zoning, water, environmental, and community review
Manual review 1 Public attributes did not support a confident first-pass category
Total 33 Screening leads only

The owner labels used in this screen are snapshots from public GIS records. They may be incomplete or outdated and must be verified before use.

Lead-level audit table

The table below publishes the minimum fields needed to audit the 33-lead count without republishing owner names or street addresses. Parcel numbers are public GIS identifiers. Distance is from the parcel’s vertex-mean screening point to the nearest mapped data center address point. Lead IDs follow the screen’s triage order; they are not rankings of availability or suitability.

Lead Public parcel ID Nearest data center Distance (km) First-pass triage category
NP001 042005100 WA005 0.139 Port-owned; availability review required
NP002 042005099 WA009 0.628 Port-owned; availability review required
NP003 040411088 WA004 0.737 Port-owned; availability review required
NP004 312822000 WA009 0.670 Industrial or food/logistics ownership lead
NP005 312839000 WA003 0.877 Industrial or food/logistics ownership lead
NP006 040410312 WA009 0.962 Industrial or food/logistics ownership lead
NP007 040411111 WA004 0.132 Likely data-center-owned or expansion-associated
NP008 313738000 WA004 0.138 Likely data-center-owned or expansion-associated
NP009 313856000 WA009 0.144 Likely data-center-owned or expansion-associated
NP010 313734000 WA004 0.206 Likely data-center-owned or expansion-associated
NP011 040411118 WA004 0.306 Likely data-center-owned or expansion-associated
NP012 313736000 WA003 0.316 Likely data-center-owned or expansion-associated
NP013 313735000 WA004 0.320 Likely data-center-owned or expansion-associated
NP014 042005201 WA009 0.352 Likely data-center-owned or expansion-associated
NP015 313739000 WA004 0.406 Likely data-center-owned or expansion-associated
NP016 040411116 WA004 0.466 Likely data-center-owned or expansion-associated
NP017 042005202 WA003 0.513 Likely data-center-owned or expansion-associated
NP018 042005200 WA003 0.607 Likely data-center-owned or expansion-associated
NP019 040411115 WA004 0.630 Likely data-center-owned or expansion-associated
NP020 200807000 WA009 0.660 Likely data-center-owned or expansion-associated
NP021 040411117 WA004 0.770 Likely data-center-owned or expansion-associated
NP022 040414040 WA004 0.805 Likely data-center-owned or expansion-associated
NP023 200980000 WA004 0.805 Likely data-center-owned or expansion-associated
NP024 313737000 WA003 0.090 Likely utility or public infrastructure
NP025 040411112 WA004 0.182 Likely utility or public infrastructure
NP026 313855000 WA009 0.262 Likely utility or public infrastructure
NP027 042005203 WA004 0.514 Likely utility or public infrastructure
NP028 040414050 WA004 0.650 Likely utility or public infrastructure
NP029 312823001 WA009 0.939 Likely utility or public infrastructure
NP030 200799000 WA004 0.828 Agricultural edge; land-use review required
NP031 200802000 WA005 0.865 Agricultural edge; land-use review required
NP032 200806000 WA009 0.888 Agricultural edge; land-use review required
NP033 313748000 WA009 0.880 Manual review required

Every row remains a GIS lead only. The table is not evidence of availability, buildability, utility capacity, owner interest, heat demand, or project suitability.

Existing heat-user distance screen

A second Python screen calculated straight-line Haversine distances between mapped data centers and source-backed heat-user leads from the two public datasets below.

The heat-user inventory used official public datasets where available, including:

For the four M Street data center points:

The state reporting dataset locates Lamb Weston – Quincy at 47.234413, -119.869914. The four calculations were:

Data center point Straight-line distance to Lamb Weston – Quincy
H5 Quincy II and III (WA009) 4.2039 km
H5 Quincy (WA005) 4.2684 km
Vantage WA1 (WA003) 4.4038 km
SDC Quincy / Sabey (WA004) 4.4550 km

This is a distance-only result. It does not show Lamb Weston’s thermal demand, interest, pipe route, elevation, rights-of-way, economics, or compatibility with recoverable data center heat. The facility was identified through state reporting data and was not contacted as part of this screen.

Quincy interpretation

The screen suggests three different stakeholder pathways:

1. Operator-led or campus-adjacent reuse

Many of the closest parcel leads appear associated with data center operators or related entities. They may matter if an operator chooses to preserve space for heat exchangers, heat pumps, thermal storage, piping, or a colocated heat-using facility. They should not be treated as land available to an outside developer.

2. Port and economic-development review

Port-owned industrial parcels may be useful discussion leads because the Port has an economic-development role. A serious review would still need to confirm availability, access, zoning, utilities, water and sewer, current commitments, and community priorities.

3. Existing or new industrial heat users

Nearby industrial and food/logistics records can help identify facilities to contact about thermal needs. Their presence does not prove useful demand. Because the closest source-backed existing user identified in this screen was more than 4 kilometers away, recruiting or expanding a compatible business closer to the heat source may deserve consideration alongside any existing-user retrofit.

Possible Quincy-area use categories for further study include greenhouses, controlled-environment agriculture, aquaculture, food processing, crop or industrial drying, process-water preheating, and other industrial uses. These are categories to investigate—not proposed projects.

Seattle case study: Equinix SE2 and an urban screening pathway

Quincy’s industrial and agricultural setting is not a template for every data center. An urban facility may be closer to buildings with space-heating or hot-water loads, but it also involves different ownership, engineering, street, and seasonal-demand constraints. Equinix SE2 was screened as a test of that contrast.

Facility and active-use evidence

Item Public evidence Screening interpretation
Facility Equinix’s current SE2 page lists 2001 Sixth Ave., Suite 350, Seattle, 36,382 square feet of colocation space, power and cooling redundancy, certifications, and tour and sales links. Strong primary evidence that Equinix currently markets the facility with current specifications and contact paths
Infrastructure record PeeringDB’s SE2/SE3 record lists 2001 Sixth Avenue, status ok, an update date of September 26, 2025, and 110 network records. Supports an “appears active” assessment; PeeringDB is public, community-maintained infrastructure data
Network ecosystem PeeringDB’s network-facility query returned 110 records when checked. Evidence of a substantial interconnection ecosystem, not a complete customer list; records combine SE2 and SE3
Building context Data Center Map’s Westin Building page describes a multi-tenant carrier hotel and lists Equinix SE2 among multiple building operators. Shows that heat-reuse decisions could involve Equinix, building ownership and management, and building engineers

The selected screening coordinate was 47.614387209504, -122.338437296894, derived from the published 2001 Sixth Avenue address. It represents the facility address, not a surveyed heat-recovery connection point.

Residential and building proximity screen

The SE2 coordinate falls in Census Tract 72.02, King County, Washington. The Census Reporter profile, using U.S. Census Bureau ACS 2024 five-year estimates, reports:

Measure Result
Population 3,899
Housing units 2,795
Occupied units / households 2,386
Renter-occupied units 2,147
Owner-occupied units 239

A supplemental OpenStreetMap Overpass check counted mapped ways with building=residential, building=apartments, or building=house around the screening coordinate:

Radius from SE2 screening point Mapped residential-building ways
500 meters 67
1,000 meters 285

The Census tract is not a circular service area, and OpenStreetMap is a contributed map rather than an official building inventory. These results are proximity signals only. They do not show which buildings have compatible heating systems, whether a pipe route is practical, or whether SE2 exposes usable heat.

What the Seattle screen supports

The evidence supports treating SE2 as an example of an active urban data center that deserves a different kind of screening from Quincy. Potential questions include:

The first conversation should involve Equinix, Westin Building ownership or management, and the engineers responsible for data center cooling and building systems. Network-presence records should not be used to imply that a particular company is an SE2 tenant or can authorize heat recovery.

What remains unknown

No public source reviewed for this case establishes:

Those gaps do not void the urban example. They define the next stage of careful screening and reinforce the larger conclusion that no single reuse model fits every site.

What these screens do not prove

The screens do not establish:

A high-priority lead means only that public data supports asking more specific questions.

Questions for a feasibility review

A qualified stakeholder review would need to ask:

  1. What cooling system is used, and what heat temperature, flow, and annual profile are recoverable?
  2. For parcel-based opportunities, which parcels are already committed to buildings, substations, easements, stormwater systems, or expansion?
  3. What nearby businesses or buildings have compatible year-round or seasonal thermal demand?
  4. What would heat exchangers, heat pumps, storage, piping, operation, and maintenance cost?
  5. Who would own and operate the recovery equipment, and who would pay?
  6. What energy savings, products, jobs, emissions effects, or other public benefits could result?
  7. What utility, water, sewer, permitting, reliability, zoning, and land-use constraints apply?
  8. What Tribal, cultural, environmental, agricultural, and community consultation is required?
  9. Would the benefits justify a deeper engineering and financial feasibility study?

How the screens can be checked

The distance screens used the standard Haversine calculation with an Earth radius of 6,371 kilometers. The coordinates needed to check the four published Lamb Weston distances appear on this page.

For the Quincy parcel screen, construct a WGS84 query envelope from the four data center points by extending the minimum and maximum latitudes by 0.015 degrees and the longitudes by 0.02 degrees. Query the four public ArcGIS layers listed above, calculate a representative point by averaging all vertices returned for each parcel polygon, and compare that point with all four data center coordinates. Keep the record when its shortest Haversine distance is no more than 1 kilometer and its public land description is vacant, industrial, or cropland. Then query zoning and future land use at that same representative point. The vertex-mean point is a screening approximation, not a geometric centroid or surveyed location.

For the Seattle screen, use the published 2001 Sixth Avenue address and the screening coordinate shown above. Locate its census tract and read the population and housing measures from the linked ACS profile. For the supplemental map check, run this Overpass query once with RADIUS set to 500 and once with it set to 1000:

[out:json][timeout:120];
way(around:RADIUS,47.614387209504,-122.338437296894)
  ["building"~"^(residential|apartments|house)$"];
out count;

The published counts are a May 24, 2026 snapshot; contributed map data can change, and a busy public Overpass endpoint may time out.

Because the ArcGIS services are live, rerunning the method later may produce different records as parcel geometry, ownership labels, or planning layers change.

Source and attribution notes

The public sources used for the findings are linked directly on this page. Exact results reflect dated snapshots and may change as live records are revised. Quincy sources were accessed on May 23, 2026, and Seattle sources on May 24, 2026, unless otherwise noted.

Bottom line

These proof-of-concept screens show that public data can organize transparent, locally tailored questions around data centers. They do not identify ready-made waste-heat projects.

For Quincy, the first practical opportunity may be less about sending heat to a distant user and more about creating value close to the source. For Seattle, the density around SE2 supports reviewing nearby building or business-district systems. In both places, the next step is to bring the operator, property stakeholders, engineers, potential heat users, and community into a fact-based feasibility screen.

This page documents a student research project. Findings should be independently verified by data center operators, utilities, local governments, landowners, engineers, potential heat users, Tribal governments, and affected communities before they inform any decision.