How does a catalytic converter work and why are they stolen?

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1. 1

   Catalytic converter (Wikipedia)

   WikipediaPublished Oct 15, 2026Checked Oct 17, 2026

   “A catalytic converter is an exhaust emission control device which converts toxic gases and pollutants in exhaust gas from an internal combustion engine into less-toxic pollutants by catalyzing a redox reaction. Catalytic converters are usually used with internal combustion engines fueled by gasoline (petrol), including lean-burn engines, and sometimes on kerosene heaters and stoves. The first widespread introduction of catalytic converters was in the United States automobile market. To comply with the US Environmental Protection Agency's stricter regulation of exhaust emissions, most gasoline-powered vehicles starting with the 1975 model year are equipped with catalytic converters. These "two-way" oxidation converters combine oxygen with carbon monoxide (CO) and unburned hydrocarbons (HC) to produce carbon dioxide (CO2) and water (H2O). "Three-way" converters, which also reduce oxides of nitrogen (NOx), were first commercialized by Volvo on the California-specification 1977 240 cars. When U.S.”

2. 2

   2020–2022 catalytic converter theft ring (Wikipedia)

   WikipediaPublished Oct 7, 2026Checked Oct 17, 2026

   “From 2020 to 2022, an organized criminal group stole and then resold catalytic converters through the United States. The regional theft rings sent their stolen catalytic converters to DG Auto Parts in Freehold, New Jersey, who removed the precious metals from them and ground them into dust. The precious metals were then sold to Dowa Metals and Mining America for refining, after which they were sent to Japan; these sales are believed to have generated approximately $545 million in revenue for DG Auto Parts. The investigation that led to the discovery of the interstate theft ring was prompted by a wave of catalytic converter thefts in the Oklahoma area in late 2020 and early 2021, with similar rises across the United States. On May 2, 2021, police became aware of Tyler Curtis, the owner of Curtis Cores in Broken Arrow, Oklahoma, when he was involved in a traffic stop where (among other illicit things) 128 catalytic converters were found in the bed of his pickup truck; all had jagged edges, suggesting they had been stolen. By September, a team of investigators had linked Curtis Cores with DG Auto Parts, which was owned by Navin and Tinu Khanna.”

3. 3

   Stricter vehicle standards reduce total pollutants but increase the fraction of toxic organics.

   Environmental science and ecotechnology (Yang et al.)Published Jul 25, 2026Checked Oct 17, 2026

   “Notably, a modern hybrid vehicle emitted nearly twice the mass of OVOCs (25.4 mg km-1) compared to its conventional counterpart (13.3 mg km-1), driven by frequent engine start-stop cycles that reduce aftertreatment efficiency. This distinct operational profile allows us to identify specific compounds-namely, vinyl acetate and methyl t-butyl ether-as molecular markers for hybrid powertrains in our study. Consequently, despite superior fuel economy, this tested hybrid vehicle exhibited a 69% increase in non-carcinogenic health risks and nearly double the carcinogenic risk, overwhelmingly dominated by aromatics and toxic OVOCs such as acrolein. Furthermore, while absolute emissions declined, persistent aromatics continued to account for over 70% of the secondary organic aerosol formation potential. These findings highlight a critical tension between fuel efficiency advancements and toxicological impacts, suggesting that future emission regulations must transition from total mass limits to species-specific controls to fully safeguard public health.”

4. 4

   NOx/N2O Formation and Coordinated Urea-SCR Control in an Ultra-Lean Hydrogen-Fueled Automotive SI Engine: Engine Mapping and WLTC Strategy Evaluation.

   ACS omega (Jiang et al.)Published Feb 13, 2026Checked Oct 17, 2026

   “Engine and SCR bench tests are performed to obtain brake thermal efficiency (BTE) and raw/converted NOx characteristics across a wide range of speeds and loads. Based on these calibrated engine and SCR maps, a WLTC-based vehicle model is established to compare an economy-oriented strategy with a low-NOx-oriented strategy. Results show that under ultralean combustion with excess air ratios λ = 2.4-3.0, the engine achieves a maximum BTE of 43% with generally low raw NOx emissions at low and medium loads. The SCR system delivers nearly 100% NOx conversion at appropriate exhaust temperatures when the NH3/NOx ratio is maintained at 1.1-1.3. For both strategies, WLTC tailpipe NOx remains below 35 mg/km, and the economy-oriented strategy yields the lowest hydrogen consumption. The study indicates that coordinated control of ultralean hydrogen combustion and a high-efficiency SCR system is a feasible pathway to high-efficiency, low-NOx operation for hydrogen-fueled automotive engines.”

5. 5

   Characterizing On-Road CO2 and NOx Emissions of LNG and Diesel Container Trucks Using Portable Emission Measurement System.

   Sensors (Basel, Switzerland) (Zhao et al.)Published Mar 16, 2026Checked Oct 17, 2026

   “To characterize HDVs' emission characteristics, real-driving emissions from China VI LNG and diesel-powered container trucks were measured employing portable emissions measurement systems (PEMS). The results reveal that high CO2 emissions predominantly occur during low- to medium-speed acceleration and at speeds above 40 km/h with an acceleration exceeding 0.3 m/s2 on highways, whereas emissions on port roads are more dispersed. A third-degree polynomial function fits emissions well with vehicle-specific power (VSP). Engine parameters mainly influence CO2 emissions for LNG trucks, while VSP and acceleration significantly impact diesel trucks. The Random Forest model achieves superior prediction accuracy, particularly in highway scenarios, and significantly better CO2 forecasting for LNG-powered trucks. These findings validate the effectiveness of PEMS-based sensing in characterizing low-carbon HDVs' real-world emissions. The integration of multi-source sensor data and machine learning also provides a reference for intelligent sensing in transportation environmental monitoring.”