Is Climate Change Real?
Science vs. Media Coverage

Seven independent datasets — thermometers, satellites, ocean buoys, tide gauges, ice cores, glacier surveys, and atmospheric CO₂ — examined against the claims made by politicians, journalists, and skeptics on all sides.

Common claims vs. what the data shows
Claim“Climate change is a hoax / not real”
EvidenceEvery major independent temperature dataset — NASA GISTEMP, NOAA GlobalTemp, Berkeley Earth, HadCRUT5 — shows the same warming signal. The 2001–2020 average was approximately 1.09 °C above pre-industrial levels. Datasets were assembled by independent teams using different methodologies and station networks. All four agree within 0.1 °C.
Claim“It's just natural cycles”
EvidenceIPCC AR6 (2021) attribution analysis: greenhouse gases contributed approximately +1.0 °C of warming from 1850–2019; natural forcings (solar, volcanic) contributed only ±0.1 °C. The physical fingerprint — tropospheric warming combined with stratospheric cooling — matches greenhouse gas forcing, not solar or volcanic drivers.
Claim“CO₂ has always fluctuated — nothing unusual”
EvidenceCO₂ has fluctuated naturally, but ice-core records show pre-industrial levels were stable near 280 ppm for ~10,000 years. Mauna Loa measurements recorded 390.1 ppm in 2010 and 427.4 ppm in 2025 — a ~9.5% increase in 15 years. Current levels are likely the highest in at least 800,000 years of ice-core records.
Claim“The media exaggerates — it's not that bad”
EvidencePartly supported in both directions. Some media coverage overstates near-term certainty and conflates projections with current measurements. At the same time, economic and impact studies show actual damages have outpaced IPCC's mid-range projections in several categories. The science itself is not exaggerated; the framing of timelines often is.
Claim“Scientists keep revising their models — they don't know anything”
EvidenceModel updates are a feature of science, not a bug. The core warming prediction — CO₂ doubling produces ~3 °C of equilibrium warming — has remained stable since Charney (1979). What has changed is confidence bounds (narrowed), ice sheet dynamics (worse), and short-term extreme weather attribution (stronger). Revision toward precision ≠ unreliability.
Part 1 of 7

Surface Temperature – What The Thermometers Show

Climate skeptics often argue that temperature records are unreliable, manipulated by urban heat islands, or limited to a small number of politically motivated institutions. This is testable. Four independent teams — at NASA (U.S.), NOAA (U.S.), the Met Office/CRU (UK), and Berkeley Earth (independent nonprofit) — assembled global temperature records using different station networks, methodologies, and quality-control procedures.

The result: all four datasets show essentially the same warming signal, agreeing within approximately 0.1 °C at any given year. Independent replication across different methodologies is the strongest possible evidence of a real signal.

Global Mean Surface Temperature — 2001–2020 Average Anomaly vs. 1850–1900 Baseline 4 datasets
NASA GISTEMP v4 +1.09 °C
NOAA GlobalTemp v5 +1.07 °C
HadCRUT5 (Met Office / CRU) +1.09 °C
Berkeley Earth BEST +1.12 °C
IPCC AR6 best estimate (same period) +1.09 °C (±0.1 °C likely range)

Source: IPCC AR6 WGI, Table SPM.1. Berkeley Earth uses ~40,000 station records vs. ~7,000 in earlier NOAA analysis. The agreement across sample sizes and methodologies rules out systematic station-bias explanations.

2024 became the first calendar year to exceed 1.5 °C above pre-industrial levels (the Paris Agreement threshold), according to Berkeley Earth, NOAA, and Copernicus Climate Change Service data. 2025 ranked as the 3rd-warmest year on record. All ten of the hottest years in the instrumental record have occurred since 2010.

One of the most persistent skeptic arguments is that warming is an artefact of cities growing around weather stations. Berkeley Earth specifically tested this: their analysis of rural-only stations shows the same warming trend as urban stations. Satellite datasets (RSS and UAH lower troposphere) — which have no surface station bias whatsoever — also show warming, though with somewhat different short-term variability. The urban heat island effect is real and scientifically documented, but it affects local temperature in cities, not the global average trend.

What would change this conclusion?

Evidence of systematic, coordinated data falsification across all four independent datasets (NASA, NOAA, UK Met Office, Berkeley Earth) operating under different governments and funding sources, with no whistleblowers across thousands of scientists over decades. Alternatively: satellite data (RSS/UAH) showing flat or declining trends contradicting surface records. Neither has occurred.

Part 1 takeawayFour independent global temperature datasets using different methodologies, station networks, and national institutions all show the same warming signal: approximately 1.09 °C above pre-industrial levels for 2001–2020. Satellite records broadly corroborate surface records. Urban heat island effects have been controlled for and do not explain the trend.
Part 2 of 7

CO₂ and the Greenhouse Signal

The longest continuous direct atmospheric CO₂ measurement is the Keeling Curve, maintained at NOAA's Mauna Loa Observatory in Hawaii since 1958. The site was chosen specifically for its remoteness from industrial sources. The measurement has been independently replicated at dozens of stations globally.

Atmospheric CO₂ Concentration — Key Milestones Mauna Loa / NOAA GML
Pre-industrial average (ice cores, ~1750) ~280 ppm
1958 (first Mauna Loa measurement) 315.7 ppm
2010 annual mean 390.1 ppm
2020 annual mean 412.5 ppm
2025 annual mean 427.4 ppm
Change 2010–2025 +37.3 ppm (+9.5%)
Current level vs. 800,000-yr ice-core record Likely highest in 800,000 years

The physics of the greenhouse effect has been understood since the 19th century (Fourier 1824, Tyndall 1859, Arrhenius 1896). CO₂ absorbs outgoing infrared radiation and re-emits it in all directions, trapping heat in the lower atmosphere. This is not a hypothesis — it is measured directly in laboratory spectroscopy and confirmed by satellite observations of outgoing longwave radiation.

The expected physical fingerprint of greenhouse-gas-driven warming includes: (1) greater warming at night than during the day — confirmed; (2) greater warming at the poles than the tropics — confirmed; (3) warming of the troposphere coupled with cooling of the stratosphere — confirmed; (4) increased downward longwave radiation at the surface — directly measured. Natural solar forcing would produce a different fingerprint: uniform tropospheric warming without stratospheric cooling.

Critics correctly note that CO₂ has varied naturally over Earth's history — between roughly 180 ppm (ice ages) and 280 ppm (interglacials) over the past 800,000 years based on Antarctic ice cores. What makes the current increase anomalous is its speed: those natural cycles operated over 10,000–100,000 years. The current 150-ppm increase above the pre-industrial baseline has occurred in approximately 200 years — orders of magnitude faster than natural glacial-interglacial transitions.

⚠ Isotopic confirmation of human origin

The additional CO₂ in the atmosphere is not of natural origin. Fossil fuel combustion produces CO₂ depleted in carbon-13 and carbon-14 (“dead carbon” from ancient organisms). Atmospheric CO₂ shows a consistent isotopic decline matching fossil fuel signatures — a direct chemical fingerprint of the source. This has been measured and published in peer-reviewed literature since the 1970s.

Part 2 takeawayCO₂ has risen from 280 ppm (pre-industrial) to 427.4 ppm (2025) — a level not seen in at least 800,000 years of ice-core records. The increase is confirmed by independent stations globally and bears an isotopic signature of fossil fuel combustion. The greenhouse mechanism is established 19th-century physics confirmed by direct measurement.
Part 3 of 7

Ocean Heat Content and Sea Level Rise

Surface air temperature records cover only the atmosphere, which holds a small fraction of Earth's total heat. The ocean absorbs over 90% of the excess heat trapped by greenhouse gases. Ocean heat content (OHC) is therefore a more reliable measure of planetary energy imbalance than surface temperatures alone — it is less affected by short-term atmospheric variability like El Niño events.

Upper Ocean Heat Content (0–700 m) — NOAA NCEI 2021–2025
2021 Record high (at time)
2022 Record high (at time)
2023 Record high (at time)
2024 Record high (at time)
Consecutive record highs 4 straight years (2021–2024)
Deep ocean (0–2000 m) trend Also rising — consistent with surface signal

Source: NOAA National Centers for Environmental Information (NCEI), Ocean Heat Content dataset. Independent analyses from Cheng et al. (2023) using Argo float network data broadly concur.

Global mean sea level is measured by satellite altimetry (TOPEX/Poseidon from 1993, followed by Jason-1/2/3, and Sentinel-6) and by a global network of tide gauges dating back to the 19th century. The two measurement systems are independent and agree closely on trends.

Global Mean Sea Level — Satellite Altimetry (NASA/CNES) 1993–2025
Average rate since 1993 ~3–4 mm/year
Rate in early 1990s ~2.2 mm/year
Rate in recent years (2020s) ~4–5 mm/year
Rate change since 1993 ~Doubled (accelerating)
Total rise since 1993 ~105 mm (~4.1 inches)
Primary drivers Thermal expansion + ice melt

The acceleration of sea level rise matters as much as the absolute amount. A constant rate would suggest a manageable linear future. Acceleration means the rate itself is increasing — consistent with ice sheet dynamics adding to thermal expansion, and inconsistent with a stable or natural cycle explanation.

Part 3 takeawayUpper ocean heat content reached record highs in each of 2021, 2022, 2023, and 2024 — four consecutive years. Global mean sea level has risen ~105 mm since 1993 and the rate has roughly doubled, from ~2.2 mm/yr in the early 1990s to ~4–5 mm/yr in the 2020s. Both measurements are confirmed by independent instrument systems.
Part 4 of 7

Ice, Glaciers, and the Cryosphere

The National Snow and Ice Data Center (NSIDC) has tracked Arctic sea ice extent using satellite passive microwave data continuously since 1979. This is a 46-year dataset with no surface station issues — the data comes from orbiting satellites measuring microwave emissions from ice and open ocean.

Arctic Sea Ice — NSIDC Satellite Record 1979–2025
Long-term trend (September minimum) −12% per decade since 1979
Total area lost (September min.) ~40% reduction since 1979
Multi-year ice (thick, old ice) Declining faster than total extent
Arctic amplification Warming 3–4× faster than global average
Measurement method Satellite passive microwave (no station bias)

The World Glacier Monitoring Service (WGMS) maintains records from over 150 reference glaciers worldwide, with some measurements dating to the 1880s. Mass balance (the difference between snow accumulation and melt) has been negative globally since the 1980s and accelerating since the 2000s.

Global Glacier Mass Balance — World Glacier Monitoring Service (WGMS)
Period Avg. Annual Mass Balance Trend Notes
1970s–1980s −~0.2 m w.e./yr Negative Mass loss beginning across most regions
1990s −~0.3 m w.e./yr Accelerating Alpine, Andean, and Himalayan glaciers all losing
2000s −~0.5 m w.e./yr Accelerating GRACE satellite gravity confirmed ice mass loss
2010s −~0.8 m w.e./yr Accelerating ~95% of WGMS reference glaciers retreating
2020s (to 2024) −~1.0 m w.e./yr Accelerating 2022–2023 worst mass loss years on record

Note: m w.e. = metres water equivalent. Independent confirmation from NASA GRACE and GRACE-FO satellite gravimetry (which measures changes in Earth's gravitational field caused by mass redistribution) matches WGMS direct measurements.

Ice sheets are a different category from mountain glaciers — they are continental-scale bodies of ice that store most of the world's freshwater. Both Greenland and Antarctica are losing mass, confirmed by three independent methods: GRACE satellite gravimetry (mass change), altimetry (surface height change), and input-output mass balance (measuring snowfall in vs. ice flow out). All three agree that both ice sheets are losing mass at accelerating rates.

Part 4 takeawayArctic sea ice has declined ~12% per decade since 1979 (satellite passive microwave — no surface station bias). Glacier mass balance globally has been negative since the 1980s and is accelerating: ~95% of monitored reference glaciers are retreating. Greenland and Antarctic ice sheets are losing mass confirmed by three independent methods. The cryosphere changes are consistent with greenhouse-driven warming, not natural variability.
Part 5 of 7

Attribution – What Is Actually Causing the Warming?

Attribution science answers the question: of the observed warming, how much is caused by which forcing? IPCC AR6 (2021) produced the most comprehensive attribution analysis to date, drawing on thousands of peer-reviewed papers.

Attribution of 1850–2020 Warming — IPCC AR6, SPM Figure 2 Best estimates with likely ranges
Well-mixed greenhouse gases (CO₂, CH₄, N₂O, F-gases) +1.0 °C to +2.0 °C (best: +1.5 °C)
Short-lived climate forcers (tropospheric ozone, etc.) +0.1 °C to +0.3 °C
Aerosols (cooling effect — sulfate particles) −0.5 °C to −0.0 °C (masking warming)
All human influences combined +0.8 °C to +1.3 °C (best: +1.07 °C)
Natural forcings (solar + volcanic) −0.1 °C to +0.1 °C (best: −0.1 °C)
Internal variability (El Niño, ocean cycles) Cannot explain multi-decadal trend
Observed warming (1850–2020) ~+1.1 °C

Multiple independent physical fingerprints distinguish greenhouse warming from natural forcing:

Fingerprint
GHG prediction
Solar prediction
Observed
Stratosphere
Cooling (heat trapped below)
Warming (more solar input)
Cooling ✓ GHG
Troposphere
Warming
Warming
Warming (both consistent)
Night vs. Day
Nights warming faster
Days warming faster
Nights warming faster ✓ GHG
Polar amplification
Poles warm 3–4× faster
Uniform warming
Arctic +3–4× global ✓ GHG
Outgoing IR radiation
Decreasing in CO₂ bands
Increasing (more solar reflected)
Decreasing in CO₂ bands ✓ GHG
Downward IR at surface
Increasing
Not applicable
Directly measured increasing ✓ GHG

Solar output has been directly measured by satellite since 1978 (ACRIM and later SORCE datasets). Since 1980, solar irradiance has shown no statistically significant upward trend — in fact, the period from approximately 2000–2020 had slightly lower solar output. Observed warming has continued and accelerated during this period of flat or declining solar forcing. The correlation between solar output and global temperature that existed in the early 20th century broke down after 1980, precisely when CO₂ forcing overtook solar as the dominant driver.

Part 5 takeawayIPCC AR6 attributes +1.07 °C of the observed ~1.1 °C warming to human activities (primarily greenhouse gases), with natural forcing contributing only ±0.1 °C. Multiple independent physical fingerprints — stratospheric cooling, greater night warming, polar amplification, declining outgoing infrared in CO₂ absorption bands — match greenhouse gas forcing and rule out solar or volcanic explanations. Solar output has shown no significant upward trend since 1980.
Part 6 of 7

Media Coverage vs. What the Science Says

Core scientific conclusions — that warming is occurring, that it is human-caused, and that it will continue — are well-represented in mainstream media. The consensus itself is not overstated: multiple surveys of climate scientists (e.g., Cook et al. 2013, Lynas et al. 2021) find 97%+ agreement on human-caused warming among actively publishing researchers. This figure appears frequently in coverage and is defensible.

Common Media Framings vs. IPCC AR6 Position
Media Framing IPCC / Scientific Position Assessment
“Climate change causes [specific extreme weather event]” Attribution science shows climate change alters probability and intensity — rarely causes single events. Framing varies by event type. Oversimplified
“We have X years to act or it's too late” IPCC uses probability-based timelines for specific warming thresholds, not binary deadlines. Every fraction of a degree matters. Misleading framing
“Sea levels will rise [specific feet] by 2100” AR6 gives scenario-dependent ranges (0.3–1.0 m likely for SSP1-2.6 to SSP5-8.5). High-end tail risks up to ~2 m possible but less likely. Often conflates scenarios
“1.5°C target” treated as safe threshold 1.5°C limits (not eliminates) severe impacts. Damage functions are continuous, not step-function at 1.5°C. Framing oversimplifies
Reporting on damages, displacement, food security AR6 WG2: observed impacts are outpacing mid-range projections in several regions and sectors. Often understated
Skeptic claims of “no warming since X” Cherry-picking start years to exploit short-term variability. Statistical trend analysis over full record is unambiguous. Statistically invalid

A documented pattern in media coverage — particularly in earlier decades — was “false balance”: giving equal airtime or column space to scientists representing 97% consensus and contrarian researchers representing 3%. A 2004 analysis by Boykoff and Boykoff (Global Environmental Change) found 53% of US newspaper articles gave roughly equal weight to both sides. This created a public perception of scientific controversy that did not reflect the actual distribution of expert opinion. Subsequent media guidelines have reduced but not eliminated this pattern.

Multiple peer-reviewed studies (Oreskes and Conway, Brulle 2014, Supran and Oreskes 2017) have documented concerted and funded efforts to manufacture doubt about climate science, drawing parallels to tobacco industry tactics. ExxonMobil's internal research from the 1970s and 1980s accurately modeled future warming that the company's public communications then disputed. This is documented from internal corporate records and has been reported in peer-reviewed journals (Supran et al., Science 2023).

Part 6 takeawayCore scientific conclusions about warming and its cause are accurately represented in mainstream media. Specific framings — binary deadlines, single-event causation, conflation of scenarios — frequently diverge from IPCC language. False balance in earlier decades created exaggerated public perception of scientific controversy. Corporate-funded doubt campaigns are documented in the peer-reviewed literature. Economic impact coverage has tended to understate rather than overstate observed harms.
Part 7 of 7

Claims vs. Evidence — and Both Sides Steelmanned

Major Claims Evaluated Against Primary Source Data
Claim Verdict Key Evidence
The planet has warmed since 2010 ✓ High confidence All 4 temperature datasets, 2025 = 3rd-warmest year on record
CO₂ has increased substantially ✓ High confidence 390.1 (2010) → 427.4 ppm (2025) at Mauna Loa and 80+ other stations
The Earth is accumulating heat ✓ High confidence Ocean heat content record highs 4 consecutive years (2021–2024)
Sea level is rising and accelerating ✓ High confidence ~105 mm total rise since 1993; rate roughly doubled
Cryosphere shows warming changes ✓ High confidence Arctic ice −12%/decade; ~95% of glaciers retreating
Natural factors explain the warming ✕ Not supported Solar forcing: flat/declining since 1980. Natural forcing: ±0.1°C (IPCC AR6)
Human GHGs explain most of the warming ✓ Strong Attribution: +1.07°C human-caused vs. +1.1°C observed. 6 physical fingerprints confirmed.
Climate models are unreliable △ Partly false 1970s–1990s model projections for global mean temperature match observations closely; regional projections less precise. Core warming prediction stable since 1979.
Warming stopped after [specific year] ✕ Statistically false Based on cherry-picked start years. Full-record trend unambiguous. 10 hottest years all since 2010.
Current warming is within natural historical range ✕ Not supported Speed of change is orders of magnitude faster than natural glacial cycles. CO₂ levels likely unprecedented in 800k years.
Argument
Strongest version
Climate sensitivity uncertainty
The equilibrium climate sensitivity (ECS) — how much warming results from CO₂ doubling — has a wide IPCC range of 2.5–4.0°C (AR6). The low end of this range (~2.5°C) implies significantly less near-term harm than the high end (~4.0°C). Near-term warming trajectories could track closer to lower-bound projections, and some published studies argue ECS may be toward the lower end. Policy prescriptions often assume the middle or upper range.
Regional complexity
Global averages mask significant regional heterogeneity. Some regions may benefit from warming in certain respects (longer growing seasons in high latitudes, ice-free navigation routes). The aggregate damage function is negative but distribution matters enormously, and not all impacts are harms.
Model limitations
Climate models perform better at global averages than regional projections. Cloud feedbacks remain the largest source of uncertainty in ECS estimates. Some tipping points (West Antarctic Ice Sheet, Amazon dieback) involve deep uncertainty that models handle poorly. Model uncertainty cuts both ways — toward worse outcomes as often as better — but the uncertainty is real.
Adaptation vs. mitigation
Some economists (e.g., Nordhaus, Lomborg at varying points) argue discount rates and adaptation options make aggressive near-term mitigation less cost-effective than widely assumed. This is a legitimate economic debate about the right policy response — not a denial of the physical science. The question of how much to spend now vs. later is genuinely contested among serious researchers.
Rebuttal to steelman
The strongest skeptic arguments are about the magnitude of projected impacts, model uncertainty, and policy economics — not about whether warming is occurring or is human-caused. The physical science foundation (observed warming, GHG forcing, attribution) is robustly established. Legitimate scientific debate exists at the frontier; it does not extend to the core measured findings reviewed in this article.
Argument
Strongest version
Tipping points
Climate systems may contain non-linear tipping points — the West Antarctic Ice Sheet, permafrost carbon release, Amazon dieback, Atlantic meridional overturning circulation weakening — that could produce step-change catastrophic outcomes well before central projections suggest. The IPCC itself noted increasing concern about tipping cascades in AR6. The fat tail of risk is genuinely alarming and is not well-captured in headline projections.
Damage undercounting
Standard economic damage functions may systematically undercount non-market harms: ecosystem services, biodiversity loss, subsistence agriculture, psychological impacts of displacement, and conflict-amplification effects. IPCC AR6 WG2 found observed damage in multiple sectors exceeds mid-range projections.
Rebuttal to alarm steelman
Tipping point and fat-tail arguments are scientifically legitimate but remain areas of active research with high uncertainty. The IPCC does not currently project high-probability near-term catastrophe at 1.5–2.0°C above pre-industrial levels, though it assigns non-negligible probability to worse outcomes at higher warming. Serious vs. catastrophic outcomes depend heavily on the mitigation trajectory over the next 20–30 years.
1.09 °C
Global warming above pre-industrial levels (2001–2020 average) across four independent temperature datasets, all agreeing within 0.1 °C.
427.4 ppm
Atmospheric CO₂ in 2025, up from 390.1 ppm in 2010. Likely the highest in 800,000 years of ice-core records. Isotopically confirmed as human in origin.
~105 mm
Total sea level rise since 1993, with the rate roughly doubling from ~2.2 mm/yr to ~4–5 mm/yr. Confirmed by satellite altimetry and independent tide gauge networks.
−12% / decade
Arctic sea ice decline since 1979 (September minimum extent). Satellite passive microwave measurement — no surface station bias possible.
4 years
Consecutive years of record upper ocean heat content (0–700 m): 2021, 2022, 2023, 2024. The ocean absorbs >90% of excess planetary heat.
±0.1 °C
Total contribution of natural climate forcings (solar + volcanic) to observed warming per IPCC AR6. Human greenhouse gases explain virtually all of the observed ~1.1 °C.
What would change this conclusion?

The warming: If all four independent temperature datasets (NASA, NOAA, UK Met Office, Berkeley Earth) were shown to share a common systematic error explaining ~1.1 °C of apparent warming, and satellite records showed a divergent flat trend — this has not occurred.

The attribution: If solar irradiance were shown to have increased substantially since 1980 (satellite measurements show it has not), or if a natural forcing mechanism were identified producing the specific greenhouse fingerprints (stratospheric cooling, greater night warming, polar amplification) — this has not been identified.

The CO₂ record: If isotopic analysis of atmospheric CO₂ did not match fossil fuel combustion signatures, and if independent stations globally showed diverging measurements — this has not occurred.

NASA GISTEMP v4data.giss.nasa.gov/gistemp
NOAA GlobalTemp v5 / NCEIncei.noaa.gov
Berkeley Earth BESTberkeleyearth.org/data
HadCRUT5 — Met Office / Climatic Research Unit — metoffice.gov.uk/hadobs/hadcrut5
Mauna Loa CO₂ / NOAA GMLgml.noaa.gov/ccgg/trends
NOAA NCEI Ocean Heat Contentncei.noaa.gov/access/global-ocean-heat-content
NASA/CNES Sea Level Change (TOPEX, Jason series, Sentinel-6) — sealevel.nasa.gov
NSIDC Arctic Sea Ice Newsnsidc.org/arcticseaicenews
World Glacier Monitoring Service (WGMS)wgms.ch
IPCC AR6 Working Group I (Physical Science Basis, 2021) — ipcc.ch/report/ar6/wg1
IPCC AR6 Working Group II (Impacts, Adaptation and Vulnerability, 2022) — ipcc.ch/report/ar6/wg2
Cite this article TruthBased.org. “Is Climate Change Real? Science vs. Media Coverage.” Updated March 2026. https://www.truthbased.org/climate-change
Support Our Work

If you value data-driven fact-checking, consider supporting TruthBased.org. Every contribution helps us research and publish more articles.

☕ Support on Ko-fi ♥ Liberapay (via PayPal)

Accepts Google Pay, Apple Pay, PayPal, and credit/debit cards

Donate with Crypto

We use Binance — Binance-to-Binance transfers are fee-free and instant. Scan the QR code or copy the address.

QR code for Ethereum / BSC / OPBNB (All EVM Chains)
Ethereum / BSC / OPBNB (All EVM Chains) 0xb39106930b8c29536a6505274f4cc8b4c3b06569 Send ETH, BNB, USDT, USDC, or any ERC-20/BEP-20 token. Same address works on Ethereum, BSC, and OPBNB.
QR code for Bitcoin (BTC)
Bitcoin (BTC) 1NB5zA3352iHkAQbsQgSZNPXNidW1pW54i
QR code for Solana (SOL & SPL Tokens)
Solana (SOL & SPL Tokens) EWF1hbTyRbXZw2ZNr1qo8YUYUT6z5vwZrSLC8umncL5K
QR code for XRP (XRP Ledger)
XRP (XRP Ledger) rNxp4h8apvRis6mJf9Sh8C6iRxfrDWN7AV
⚠ Memo (required): 488087572 Both address AND memo are required or funds will be lost.
QR code for Litecoin (LTC)
Litecoin (LTC) LS6yUqARHBE1tk2mcpjNbw2xNamyWQQD1h
QR code for Stellar (XLM)
Stellar (XLM) GABFQIK63R2NETJM7T673EAMZN4RJLLGP3OFUEJU5SZVTGWUKULZJNL6
⚠ Memo (required): 392701693 Both address AND memo are required or funds will be lost.
QR code for USDT (Tron / TRC-20)
USDT (Tron / TRC-20) TLkvs7NtMEKGoQ8s8KkShurZEe2Y6NXZQH Send USDT only on the Tron network.

⚠ Always verify the network before sending. Wrong network = possible permanent loss. Send a small test amount first.