Graph analysis can organize the documented relationships behind the U.S. Volkswagen diesel emissions scandal—among vehicle programs, software development, researchers, regulators, company personnel and legal proceedings. It cannot, by itself, prove who was responsible or identify a “most central” actor. The government case materials and Volkswagen’s own account provide evidence for building a dated, attributed relationship map, but they do not establish a completed graph study or verified network metrics.
What was the Volkswagen emissions scandal?
The U.S. Environmental Protection Agency said software in certain Volkswagen, Audi and Porsche diesel vehicles detected when a vehicle was undergoing an emissions test. During the test, the software enabled full emissions controls; in normal driving, those controls were less effective. EPA said the identified 2.0-liter vehicles emitted nitrogen oxides (NOx) up to 40 times the standard. In a separate notice about certain 3.0-liter vehicles, EPA said emissions were up to nine times the standards. Those are EPA’s separate statements for the identified engine groups, not a single figure for every affected car.
The distinction between test and road operation is central to understanding the case. A dynamometer test follows a prescribed procedure; ordinary driving does not. The software’s ability to recognize the test conditions meant the emissions-control behavior observed during testing did not represent normal road use, according to EPA’s account.
How did VW’s defeat device work?
| Operating condition | Control behavior described by EPA | What the distinction means |
|---|---|---|
| Official emissions test | Full emissions controls were turned on when the software detected testing. | Test results reflected the stronger-control mode. |
| Normal driving | The effectiveness of those controls was reduced. | EPA said the identified vehicles emitted NOx above the applicable standards, with different stated maximum comparisons for 2.0-liter and certain 3.0-liter groups. |
Volkswagen’s 2016 annual report also says the software recognized the official test driving curve and switched between modes. That is the company’s description of the software; EPA’s notices and DOJ’s case materials describe the conduct and its legal significance from the government’s perspective.
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Which vehicles and figures are covered by the U.S. case?
EPA’s notices distinguish engine groups and model years. The available official summaries identify vehicle categories and year ranges, but do not provide a complete model-by-model list here.
| Vehicle group | EPA notice | Model years in the notice | EPA’s emissions comparison |
|---|---|---|---|
| Certain 2.0-liter diesel vehicles | September 18, 2015 | 2009–2015 | Up to 40 times the standard |
| Certain 3.0-liter vehicles | November 2, 2015 | 2014–2016 | Up to nine times the standards |
These figures come from EPA’s undated “Learn About Volkswagen Violations” enforcement page, accessed in 2026. The U.S. Department of Justice’s case summary describes an alleged scheme involving approximately 590,000 U.S. diesel vehicles from approximately May 2006 to November 2015. That is a U.S. case figure and timeframe, not a count of all vehicles worldwide.
Volkswagen’s 2016 annual report, published in 2017, separately says discrepancies between testing and actual road use were identified in around eleven million vehicles worldwide. That global figure is Volkswagen’s company-reported description; it is not interchangeable with the DOJ’s U.S. case count.
How did the scandal get uncovered?
The public U.S. enforcement phase began in September 2015, but the road-testing discrepancy was identified earlier. In its January 11, 2017 account, DOJ says a West Virginia University study commissioned by the International Council on Clean Transportation (ICCT) found substantial differences between road and dynamometer NOx results in March 2014. Regulators then questioned and tested vehicles. DOJ alleges that Volkswagen employees concealed the software and gave regulators misleading explanations.
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- March 2014: According to DOJ’s January 11, 2017 release, ICCT-commissioned West Virginia University testing identified substantial road-versus-dynamometer NOx discrepancies.
- After the study: DOJ says regulators questioned and tested vehicles. The DOJ account alleges that VW employees concealed the software and supplied misleading explanations during this process.
- September 18, 2015: EPA issued a Notice of Violation concerning certain model-year 2009–2015 2.0-liter diesel vehicles.
- November 2, 2015: EPA issued a separate Notice of Violation concerning certain model-year 2014–2016 3.0-liter vehicles.
- June 28, 2016 and January 11, 2017: DOJ announced a settlement framework in 2016 and later described criminal charges and Volkswagen’s plea agreement in 2017.
The chronology shows why the graph should include dated events rather than treating every relationship as simultaneous. A research test, a regulator’s inquiry, a notice of violation and a criminal plea are different events with different participants and legal status.
Who was involved, and what can the records establish?
A graph can make the case easier to inspect by distinguishing roles from conclusions about culpability. DOJ’s January 2017 release describes interactions involving Volkswagen personnel, EPA, the California Air Resources Board (CARB), ICCT and West Virginia University. Volkswagen’s annual report describes internal audit work and an external investigation. These materials identify candidate people, institutions and events for a relationship map; they do not make every person or organization in that map equally responsible.
Technical and corporate actors
Vehicle and engine programs, software development, engineers, managers and corporate entities belong in the graph where the records document their relationships. An edge such as “developed” or “supervised” should be tied to a specific source passage and time period. Being named in an indictment or described in a government account is not, by itself, a finding of guilt.
Research and oversight actors
ICCT commissioned the West Virginia University study described by DOJ. EPA and CARB appear in the oversight and testing chronology. The relationships matter: a commissioned study led to reported test discrepancies; regulatory questioning and testing followed. But the graph should not imply that researchers or regulators participated in the alleged concealment simply because their nodes connect to the same events.
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Investigations and legal actors
Volkswagen says its internal audit examined processes and control systems, while an external Jones Day investigation reviewed interviews, documents and data. DOJ’s criminal case account describes charges and plea terms. A graph should separately represent an investigation, an allegation, a charge, a guilty plea and a settlement; collapsing these into one “involved in scandal” connection would obscure important differences.
How can graph analysis explain the VW scandal?
Graph analysis represents entities as nodes and documented relationships as edges. For this case, the useful product is initially a transparent, time-aware evidence map—not a ranking of villains or a claim that network mathematics has proven causation.
1. Define the nodes
Include only entities or events needed to answer a clear question. Candidate node types include people, corporate entities, regulators, researchers, vehicle or engine families, studies, notices, meetings, legal filings, settlements and dated events. Record a node’s type and a stable identifier so, for example, a company entity is not confused with a vehicle program.
2. Record typed, sourced edges
Use specific relationship labels such as “employed by,” “supervised,” “developed,” “tested,” “commissioned,” “contacted,” “questioned,” “disclosed to,” “charged by,” “pleaded guilty to” and “settled with.” Each edge should include its date or time range, source, and whether it is a documented formal relationship, an allegation, a company representation or a procedural outcome.
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- Example: ICCT — commissioned — West Virginia University study; attach the relationship to DOJ’s January 11, 2017 account and the study chronology it describes.
- Example: EPA — issued notice to — Volkswagen-related entities; record the notice date and the engine/model-year group rather than treating both notices as one event.
- Example: Volkswagen — pleaded guilty to — charges; represent this as a plea outcome, not as a generic link to every individual named in the case.
3. Preserve time and uncertainty
A temporal graph or dated edge list helps prevent a role held in one year from being presented as continuing indefinitely. It also makes the procedural posture visible: an allegation made in a DOJ account is not the same kind of evidence as an agreed plea term, and Volkswagen’s explanation is the company’s account rather than an independent finding.
4. Ask answerable questions before calculating metrics
With a documented dataset, a researcher could ask which organizations connect the testing and regulatory stages, how the sequence of events changed over time, or which claims rest on a single source. Any centrality score or community grouping would depend on choices such as which nodes and edge types count, whether edges are directed, and how allegations are weighted. The reviewed government and company materials do not establish a completed graph-analysis study, a most-central actor, or a community that concealed information. Such findings would require original, reproducible analysis and should be labeled accordingly.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do DOJ’s account and Volkswagen’s account differ?
The two accounts serve different purposes and should be attributed rather than blended into one uncontested narrative.
| Source | What it says | How to read it |
|---|---|---|
| DOJ case page and January 11, 2017 release | Describes an alleged scheme, the government’s account of regulatory interactions, charges, and Volkswagen’s agreement to plead guilty. | Use “alleges” for disputed conduct and distinguish charges from the plea terms. |
| Volkswagen Group Annual Report 2016, published 2017 | Describes internal audit and Jones Day investigation processes, the company’s account of the software and timeline, and its tracing of the origins to its U.S. diesel strategy and EA 189 engine development. | Identify it as Volkswagen’s account; do not present the company’s explanation as a government finding. |
The difference is not a reason to discard either source. It is a reason to preserve provenance in the graph: every claim should remain connected to who made it, when, and in what context.
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What were the financial and legal consequences in the U.S. case?
DOJ’s case page says Volkswagen agreed to plead guilty to charges including conspiracy, wire fraud, Clean Air Act violations, obstruction of justice and false statements, and agreed to a $2.8 billion criminal penalty. The penalty is the criminal penalty described in that case account, not a total of all civil settlements or customer remedies.
A separate DOJ settlement announcement dated June 28, 2016 set a condition that Volkswagen achieve at least an 85% recall rate for affected 2.0-liter vehicles under specified programs; additional sums would go to the mitigation trust fund if the rate was not achieved. The announcement also quoted EPA Administrator Gina McCarthy: “Today’s settlement restores clean air protections that Volkswagen so blatantly violated.” The recall condition belongs to those specified programs and should not be read as a general current repair-status statement.
DOJ’s January 11, 2017 release quoted Deputy Director McCabe: “Volkswagen’s data deception defrauded the U.S. government, violated the Clean Air Act and eroded consumer trust.” These statements convey the government’s public position; the legal character of a claim still depends on whether it was alleged, charged, admitted in a plea or imposed as a settlement term.
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