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Environmental engineers

Also called Air quality engineer, Hazardous waste engineer, Remediation engineer, Sustainability engineer, Carbon engineer

In brief

In May 2025, BLS counted 38,340 US environmental engineers, with median pay of $107,110 a year. Of the BLS counts since 2021, the highest was 45,440, in May 2022. The earliest figure here is an estimate of 12,000 from 1950, not measured the same way as today's count. The last full technology era for environmental engineers: GIS-integrated site assessment, 2005 to 2020.

What the sources say

Official outlook

BLS projects employment to grow 6.3% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend.

Last updated .

Cite this page
APA

Future History. (2026, October 11). Environmental engineers: jobs and pay since 1950 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/17-2081

Chicago

Future History. "Environmental engineers: jobs and pay since 1950." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/17-2081.

BibTeX

@misc{futurehistory_17_2081, author = {{Future History}}, title = {Environmental engineers: jobs and pay since 1950}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/17-2081}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }

The access date is today's date on your device.

drag to travel through time
1850187519001925195019752000now
2026
Known then as Sanitary Engineer (civil engineering sub-specialty; water supply, sewage, and public health)
Known then as Sanitary Engineer (formalized under the American Sanitary Engineering Intersociety Board, incorporated 1955)
Known then as Environmental Engineer (AAEE renamed from American Academy of Sanitary Engineers, 1966; BLS still tracks under Civil Engineers)
Known then as Environmental Engineer (recognized distinct practice area; still bundled with Civil Engineers in BLS OEWS pre-2000 SOC)
Known then as Environmental Engineers (BLS SOC 17-2081, first tracked as separate code in 2000 SOC revision)
Known today as Environmental Engineers (BLS SOC 17-2081, first tracked as separate code in 2000 SOC revision)
Projected to still be called Environmental Engineers (BLS SOC 17-2081, first tracked as separate code in 2000 SOC revision)
Data from the May 2025 survey
US Employment
38K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$107,110

≈ $104,364 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1854

John Snow maps the Broad Street cholera outbreak in London, demonstrating that contaminated water (not "miasma") is the disease vector. Snow's dot-map methodology -- the first epidemiological GIS -- becomes the intellectual foundation for sanitary engineering: engineers must now design water systems around the specific contamination pathways that transmit disease. The US sanitary engineering profession adopts Snow's framework within a decade.

Beat · 1955

The American Sanitary Engineering Intersociety Board is incorporated in Delaware on October 21, 1955 -- the first formal self-governance body for the sanitary engineering profession, jointly sponsored by ASCE, the American Public Health Association, the American Society for Engineering Education, the American Water Works Association, and the Water Pollution Control Federation. The incorporation marks the transition from sanitary engineering as an informal civil engineering sub-specialty to a recognized distinct profession with its own certification standards.

Beat · 1966

The American Sanitary Engineering Intersociety Board renames itself the Environmental Engineering Intersociety Board (EEIB) and its roster becomes the American Academy of Environmental Engineers (AAEE). This naming change from "sanitary" to "environmental" reflects the profession's broadening mandate beyond water and sewage to include air pollution, industrial waste, and emerging chemical contamination. By 1967 the AAEE becomes a standalone organization with its own bylaws and officers, not merely a roster under a board.

Beat · 1970

April 22, 1970: the first Earth Day draws 20 million Americans into the streets. Eight months later, on December 2, 1970, President Nixon signs the executive order creating the Environmental Protection Agency. The Clean Air Act is signed December 31, 1970. These events transform environmental engineering from a small specialty into a federally mandated profession: every major industrial facility, every new highway, every major development now requires environmental review, permitting, and ongoing compliance oversight by licensed engineers.

Beat · 1980

December 11, 1980: President Carter signs the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA) -- the Superfund statute -- into law, in direct response to the Love Canal disaster in Niagara Falls, New York, where a neighborhood built over a former chemical waste dump had been evacuated in 1978. CERCLA creates a trust fund (financed by taxes on chemical and petroleum industries) for cleaning up contaminated sites and imposes strict joint-and-several liability on current and former site owners. The law generates a sustained wave of Remedial Investigation and Feasibility Study work that employs environmental engineers for the next two decades.

Beat · 2024

April 10, 2024: EPA finalizes the first-ever Maximum Contaminant Levels (MCLs) for PFOA and PFOS in drinking water at 4 parts per trillion -- the most significant new contaminant regulation in the Safe Drinking Water Act's history. On the same day, EPA proposes to designate PFOA and PFOS as CERCLA hazardous substances. The PFAS rules are expected to trigger the largest wave of environmental remediation work since the original Superfund NPL buildout of the 1980s-90s, with thousands of water utility upgrades, well investigations, and contaminated-site remediations requiring PE-signed environmental engineering work.

How to read this number

OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.

Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.

Official statistic: Copied by a script from a statistics agency table or a published study's table, not retyped by hand. BLS figures and the forecast and exposure tables are also re-checked against that table on every data run. Researched context: Researched from the cited source rather than copied from it by a script, so it is not machine-checked yet. Spot a mistake? Each figure has a “Report an error” link.

Cited forecasts · present → 2035

Will AI replace environmental engineers? What the research says

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.

What published forecasts say
Forecast change in the number of people doing this work, as published by each named source. Bars share one scale on every role, centred on zero and reaching the end at ±30%. Grey marks a small change, 3% or less either way.
BLS Employment Projections 2025-35
→ 2035
+6.3%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 17-2081 (Environmental engineers): 39.1 thousand jobs in 2025, projected 41.6 thousand in 2035, a change of +2.4 thousand (+6.3%). Matrix employment counts all jobs in the occupation, including self-employed workers. The average for all occupations in this cycle is +3.5%.
Official statisticReport an error
How exposed is this work to AI (research measures)
Scores as published by each study. Each row says what it measures. These measure what AI could technically do, not forecasts of jobs lost.
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
50%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 17-2081.00 Environmental Engineers. Shown: human-rated β = 0.5, the share of the occupation's tasks an LLM could do in at least half the time at equal quality, counting tasks that need LLM-powered software at half weight (β = E1 + 0.5 × E2). Other published measures for this occupation: human-rated α (LLM alone) 0.241 and γ (all LLM-assisted) 0.759; GPT-4-rated β 0.556. This measures how much of the work an LLM could touch, not how many jobs disappear.

Official statisticReport an error
Today, in this role

What's changing day to day for environmental engineers

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereManage environmental data from multi-well groundwater monitoring networks, soil sampling programs, and air monitoring stations using EarthSoft EQuIS AI: configure automated sample data import from laboratory electronic data deliverables (EDDs)

Manage environmental data from multi-well groundwater monitoring networks, soil sampling programs, and air monitoring stations using EarthSoft EQuIS AI: configure automated sample data import from laboratory electronic data deliverables (EDDs); set AI-driven exceedance alerts against regulatory standards (MCLs, RBSLs, ACLs); generate automated compliance monitoring reports for quarterly RCRA or CERCLA regulatory submissions; review AI-flagged exceedances and anomalies before submitting signed reports to state or federal agencies.[11],[4]

Tools picking this up
Where your edge is

EQuIS AI can process thousands of laboratory results against regulatory thresholds automatically and flag exceedances in minutes rather than the days required for manual spreadsheet review, but the engineer must verify that the correct regulatory standards are loaded (standards change: PFOA/PFOS MCLs finalized April 2024 are dramatically lower than prior health advisory levels), that the EDD import correctly mapped analytes and units, and that anomalous results reflect actual detections rather than laboratory QA/QC issues. Regulatory submissions signed by a PE carry enforcement exposure if exceedance reporting is incorrect; AI data management tools reduce effort but not accountability.

AI is sitting alongside you hereMonitor and analyze environmental performance data from facility-wide air, water, and soil monitoring networks using IBM Environmental Intelligence Suite AI: configure real-time sensor data ingest from CEMS (continuous emissions monitoring systems), water quality sensors, and weather stations

Monitor and analyze environmental performance data from facility-wide air, water, and soil monitoring networks using IBM Environmental Intelligence Suite AI: configure real-time sensor data ingest from CEMS (continuous emissions monitoring systems), water quality sensors, and weather stations; set AI anomaly detection thresholds calibrated to permit limits; review flagged deviations; generate automated compliance reports; use IBM EIS climate risk analytics to assess physical climate risks (extreme precipitation, drought, sea-level rise) that could affect facility environmental performance under future climate scenarios.[9],[14]

Where your edge is

IBM EIS can process sensor data at a scale and frequency that no human monitoring review could match, but distinguishing a genuine permit exceedance from a sensor malfunction, a maintenance blowdown event, or a calibration artifact requires process knowledge and site familiarity that the anomaly detection algorithm lacks. Build a structured anomaly triage protocol: for every EIS flag, cross-reference the timestamp against the operations log, confirm sensor calibration status, and verify against any nearby monitoring corroboration before initiating the regulatory deviation reporting clock. Premature regulatory notification for a false positive is costly; a missed notification for a genuine exceedance is worse.

AI is sitting alongside you hereDevelop corporate GHG inventories and SEC climate disclosure reports (Scope 1 [direct combustion], Scope 2 [purchased electricity], and Scope 3 [value chain] emissions) using Watershed AI or Persefoni: connect the platform to enterprise utility, fuel, and supply chain data sources

Develop corporate GHG inventories and SEC climate disclosure reports (Scope 1 [direct combustion], Scope 2 [purchased electricity], and Scope 3 [value chain] emissions) using Watershed AI or Persefoni: connect the platform to enterprise utility, fuel, and supply chain data sources; configure emission factor libraries (EPA, GHG Protocol, IPCC AR6); review AI-generated inventory calculations, hotspot analyses, and data-quality flags; prepare GHG disclosures compliant with the SEC's March 2024 climate disclosure final rule (Scope 1 and 2 required for large accelerated filers from FY2025) and GHG Protocol Corporate Standard; coordinate with legal and finance on materiality determinations for climate risk disclosures.[7],[12],[16]

Tools picking this up
Where your edge is

Watershed AI and Persefoni automate the data aggregation and emission factor application steps that previously consumed weeks of spreadsheet work, but Scope 3 inventory accuracy depends on the quality of supplier-reported emission data: AI cannot verify whether a supplier's reported emission factor is current, methodology-consistent, or applicable to your specific procurement category. The SEC's disclosure final rule requires that material Scope 1/2 data undergo limited assurance (and eventually reasonable assurance) from a qualified third party; build internal controls documentation for your GHG data collection and calculation methodology so the AI platform's outputs are auditable. AACE International's GHG inventory quality management guidelines and ISO 14064 are the relevant standards.

Where environmental engineers go next

Natural next steps for someone with your foundation: not exits, evolutions.

What each move takes

A direction you could grow

Architectural and Engineering Managers

Senior environmental engineers who develop project management, client development, and technical leadership skills are well-positioned to move into Engineering Manager or Practice Leader roles at AEC and environmental consulting firms (AECOM, Stantec, Tetra Tech, Brown and Caldwell, Arcadis). This transition is especially timely as firms need leaders who can govern AI tool adoption, deciding which environmental data management, GHG accounting, and geospatial AI platforms to deploy, setting quality standards for AI-assisted permit applications and remediation designs, and building team capability in AI-augmented workflows. The IRA-driven surge in renewable energy permitting, grid infrastructure, and PFAS remediation has made environmental engineering practice management a high-demand function; BLS projects sustained demand for engineering managers tied to infrastructure and energy-transition investment through 2034.

What you'd add
· Client development and proposal writing: fee negotiation for T&M and lump-sum environmental contracts, go/no-go analysis, scope clarification
· AI tool governance for regulated practice: building team review standards for AI-assisted permit applications and regulatory submissions that carry PE accountability
· Contract law fundamentals for environmental consulting: EPA cost-reimbursable contracts (FAR compliance), state agency contracts, and NCP-compliant Superfund work assignment management
· People management: hiring environmental engineers and scientists, conducting performance reviews, developing junior staff from EIT to PE licensure
What it takesSome new skills to pick up
Tools of the era

How has the work of environmental engineers changed since 1850?

The tools that defined the work, one line per era. Select an era to see how it reshaped the work.

  • Field survey instruments, hydraulic slide rules, and draft tables (sanitary engineering era)

    The sanitary engineer of the 19th and early 20th centuries worked with transits, levels, and chains for field survey; hydraulic slide rules and nomographs for sizing pipes and sewers; and hand-drafted plans on linen. Water supply design required knowledge of Darcy-Weisbach pipe friction, Hazen-Williams flow coefficients, and sedimentation principles -- all computed by hand. The engineering output was a set of blueprints and specifications reviewed by municipal water boards. No computers, no simulation software; the engineer's craft was in knowing the empirical formulas and applying judgment about soil conditions, topography, and population growth.

    Effect on the work

    This era's constraint was not computation speed but knowledge scarcity: only a few hundred engineers in the US had the combination of hydraulic theory and public-health knowledge required for municipal water and sewage system design. The 1855 Chicago sewage system (Ellis Chesbrough) and the 1842 New York Croton Aqueduct expansion set the professional template.

  • Laboratory analytical equipment, physical process models, and IBM mainframe batch computing

    The post-war era brought gas chromatography (GC, widespread by the 1960s) and atomic absorption spectroscopy (AAS) to environmental analysis -- tools that let engineers measure contaminant concentrations at parts-per-million levels for the first time. Physical scale models of watersheds and river systems were built in hydraulics laboratories to simulate pollution plume behavior. IBM mainframe batch computing arrived at universities and large engineering firms by the mid-1960s, enabling numerical water-quality modeling (Streeter-Phelps dissolved oxygen models, early QUAL2E runs). The sanitary engineer's analytical power grew substantially, but the computational bottleneck meant most design calculations were still done on desk calculators.

  • EPA regulatory computer models (SWMM, QUAL2E, AERMOD predecessors) and early CAD

    The 1970 Clean Air Act and 1972 Clean Water Act created a new demand: regulatory-grade computer models for permit applications. EPA developed and released SWMM (Storm Water Management Model, 1971), QUAL2E (water quality modeling, 1985 release), and the Gaussian dispersion models that would evolve into today's AERMOD -- all designed to run on minicomputers and early workstations. Engineers who could run these models became highly valuable because permit applications required them. AutoCAD's 1982 release began displacing hand drafting. The Personal Computer (IBM PC, 1981) brought spreadsheet analysis (Lotus 1-2-3) to the desktop, enabling mass-balance calculations and data management that had previously required dedicated computing time.

    Effect on the work

    Regulatory computer modeling created a productivity step-change: an environmental engineer with SWMM or QUAL2E could analyze a watershed's water quality under dozens of scenarios in a week -- work that would have taken a team of engineers months by hand. This expanded the scale of projects that small consulting firms could competitively bid.

  • CERCLA Superfund software stack (MODFLOW, RBCA risk calculators, EQuIS data management)

    The Superfund remediation wave of the 1990s created a specialized software ecosystem. USGS MODFLOW (1984 first release, widely adopted by the early 1990s) became the standard groundwater flow and contaminant transport model for CERCLA Remedial Investigation reports -- every RI/FS for a significant groundwater plume required a calibrated MODFLOW model. Risk-Based Corrective Action (RBCA) calculators (ASTM E1739, 1995) standardized how cleanup levels were derived from toxicological data, reducing engineer time spent on risk calculations. EarthSoft EQuIS (first commercial release 1993) automated the management of large multi-well monitoring datasets. Geographic Information Systems (ArcGIS, ESRI) began replacing paper site maps for contaminated site characterization by the mid-1990s.

    Effect on the work

    MODFLOW and the CERCLA software stack made the US the dominant global market for contaminated-site remediation engineering. The National Priorities List grew to more than a thousand sites by the mid-1990s; each required a multi-year investigation and feasibility study. This sustained high employment for environmental engineers through the decade despite the profession's youth.

  • GIS-integrated site assessment, electronic data deliverables (EDDs), and cloud-based compliance reporting

    The 2005-2020 era consolidated the digital infrastructure that environmental engineers now run on. ESRI ArcGIS became the standard platform for site characterization mapping, regulatory reporting, and environmental data visualization. Electronic Data Deliverables (EDDs) from analytical laboratories replaced paper chain-of-custody forms, enabling direct database loading of thousands of sample results -- the workflow that EQuIS automated fully. EPA's e-reporting initiatives required electronic NPDES discharge monitoring reports and Title V compliance certifications, moving permit management from paper to online portals. The BreezoMeter and IQAir AirVisual Pro real-time air quality APIs (mid-2010s) gave engineers live ambient monitoring data for compliance cross-checking.

    Effect on the work

    The EDD workflow change alone reduced data-management labor per investigation project at consulting firms that adopted it fully by 2010 -- according to EarthSoft's own case studies. This did not reduce headcount significantly (demand grew faster than productivity gains) but it shifted junior-engineer time from data entry toward analysis.

  • AI-powered environmental monitoring, GHG accounting, and geospatial analysis (IBM EIS, ArcGIS GeoAI, Watershed AI, Persefoni)

    The current AI era for environmental engineers is differentiated from prior automation in one key respect: it is reaching into the analysis and judgment layer, not just data management. IBM Environmental Intelligence Suite (EIS, 2021 launch) applies machine learning to multi-source sensor streams -- CEMS, water quality sensors, weather stations -- for anomaly detection at scale. ESRI ArcGIS GeoAI (2023) automates land-cover classification and habitat sensitivity mapping from satellite imagery, compressing the geospatial screening phase of a NEPA environmental assessment from weeks to days. Watershed AI and Persefoni automate Scope 1/2/3 GHG inventory data collection and SEC disclosure report preparation -- the workflow the SEC's March 2024 climate disclosure rule made mandatory for large accelerated filers from FY2025. GoldSim AI extends the CERCLA probabilistic fate-and-transport modeling environment with uncertainty quantification. Autodesk Innovyze AI automates stormwater hydraulic scenario generation for NPDES permit applications.

    Effect on the work

    The IRA (Inflation Reduction Act, 2022) directs $369B toward clean energy and climate resilience infrastructure -- renewable energy permitting, EV battery manufacturing, grid transmission -- each project requiring NEPA review, CWA permitting, and CAA compliance. AI tools that compress the permitting analysis phase multiply the capacity of a single environmental engineer across the expanded project pipeline. BLS projects +4% employment growth for 17-2081 through 2034 in this environment.

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Environmental Engineers employment and pay by year

On record since1850
Latest US employment38,340 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$107,110 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+6.3% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 26 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
195012,000n/aEst., National Academies of Sciences Researched contextReport
197020,000n/aEst., Encyclopedia.com Researched contextReport
199951,450$54,890BLS OEWS 1999 (employment) Official statisticBLS OEWS September 2001 (pay) Official statisticReport
200345,480$62,800BLS OEWS May 2003 Official statisticReport
200447,690$66,480BLS OEWS May 2004 Official statisticReport
200550,140$68,090BLS OEWS May 2005 Official statisticReport
200651,370$69,940BLS OEWS May 2006 Official statisticReport
200751,210$72,350BLS OEWS May 2007 Official statisticReport
200852,590$74,020BLS OEWS May 2008 Official statisticReport
200950,610$77,040BLS OEWS May 2009 Official statisticReport
201049,800$78,740BLS OEWS May 2010 Official statisticReport
201150,350$79,050BLS OEWS May 2011 Official statisticReport
201250,850$80,890BLS OEWS May 2012 Official statisticReport
201353,020$82,220BLS OEWS May 2013 Official statisticReport
201453,240$83,360BLS OEWS May 2014 Official statisticReport
201552,600$84,560BLS OEWS May 2015 Official statisticReport
201652,280$84,890BLS OEWS May 2016 Official statisticReport
201752,640$86,800BLS OEWS May 2017 Official statisticReport
201853,070$87,620BLS OEWS May 2018 Official statisticReport
201953,150$88,860BLS OEWS May 2019 Official statisticReport
202050,260$92,120BLS OEWS May 2020 Official statisticReport
202142,660$96,820BLS OEWS May 2021 Official statisticReport
202245,440$96,530BLS OEWS May 2022 Official statisticReport
202339,880$100,090BLS OEWS May 2023 Official statisticReport
202437,950$104,170BLS OEWS May 2024 Official statisticReport
202538,340$107,110BLS OEWS May 2025 Official statisticReport
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