Waste Connections (WCN) EBITDA (2015 - 2026)
Waste Connections' EBITDA was $811.03 million in Q2 2026, down 0.8% from $817.44 million a year earlier but up 11.7% from the prior quarter.
Waste Connections (WCN) EBITDA (2015 - 2026) Analysis & Trends
On a trailing twelve-month basis, Waste Connections' EBITDA was $3.14 billion through Jun 30, 2026, up 23.3% year-over-year; for FY2025, it came in at $3.14 billion, up 29.8% from FY2024.
- EBITDA has now increased for five consecutive years, with a five-year compound annual growth rate of 19.4% (FY2020 to FY2025).
- In earlier years, EBITDA was $2.42 billion in FY2024 (+1.0%), $2.4 billion in FY2023 (+3.5%), $2.32 billion in FY2022 (+16.3%) and $1.99 billion in FY2021 (+53.7%).
- Quarterly EBITDA has moved between $182.79 million (Q4 2024) and $817.44 million (Q2 2025) over five years.
- Compared with a year earlier, EBITDA was higher in four of the last eight quarters, with growth averaging 40.1%.
- The best year-over-year quarter for EBITDA over five years was Q4 2025 (growth of 333.5%); the worst was Q4 2024 (a decline of 61.7%).
- Per Business Quant data, WCN's EBITDA in the three quarters before Q2 2026 was $726.09 million (Q1 2026), $792.33 million (Q4 2025) and $806.25 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Waste Management | 92.87 Bn | 91.78 Bn | 2.73 Bn | 2.03 Bn |
| 2 | Republic Services | 71.30 Bn | 70.91 Bn | 1.87 Bn | 1.42 Bn |
| 3 | Waste Connections | 42.70 Bn | 42.33 Bn | 1.08 Bn | 813.37 Mn |
| 4 | Clean Harbors | 16.65 Bn | 13.66 Bn | 608.78 Mn | 392.01 Mn |
| 5 | GFL Environmental | 16.62 Bn | 14.73 Bn | 385.80 Mn | 756.90 Mn |
| 6 | Casella Waste Systems | 5.85 Bn | 4.97 Bn | 178.80 Mn | 109.21 Mn |
| 7 | Onterris | 501.28 Mn | 460.56 Mn | 82.26 Mn | 19.16 Mn |
| 8 | Perma Fix Environmental Services | 245.42 Mn | 136.98 Mn | -2.50 Mn | -6.00 Mn |
| 9 | Deep Isolation Nuclear | 144.15 Mn | 144.15 Mn | 707,000.00 | -3.22 Mn |
| 10 | Comstock | 135.32 Mn | 2.29 Mn | -896,073.00 | -26.59 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 813.37 Mn |
| Mar 31, 2026 | 728.26 Mn |
| Dec 31, 2025 | 794.44 Mn |
| Sep 30, 2025 | 808.42 Mn |
| Jun 30, 2025 | 819.51 Mn |
| Mar 31, 2025 | 729.84 Mn |
| Dec 31, 2024 | 184.82 Mn |
| Sep 30, 2024 | 816.17 Mn |
| Jun 30, 2024 | 756.09 Mn |
| Mar 31, 2024 | 674.13 Mn |
| Dec 31, 2023 | 479.26 Mn |
| Sep 30, 2023 | 608.97 Mn |
| Jun 30, 2023 | 598.12 Mn |
| Mar 31, 2023 | 559.65 Mn |
| Dec 31, 2022 | 556.38 Mn |
| Sep 30, 2022 | 560.31 Mn |
| Jun 30, 2022 | 557.28 Mn |
| Mar 31, 2022 | 492.64 Mn |
| Dec 31, 2021 | 464.67 Mn |
| Sep 30, 2021 | 493.64 Mn |
Waste Connections EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ebitda&ticker=WCN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "WCN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=WCN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();