A 2021 source-apportionment study of vehicular emissions in the Beijing-Tianjin-Hebei (BTH) region of China used the WRF-CAMx model with the PSAT tagging module to quantify vehicular contributions to NOx, nitrate, and PM2.5, split into local and non-local (regionally transported) components, but excluded vehicle-emitted volatile organic compounds (VOCs) and their secondary organic aerosol (SOA) products, and did not examine ozone (O3) formation from vehicular NOx and VOCs or diagnose the physical and chemical processes by which near-surface vehicular emissions are transported over long distances and transformed into secondary pollutants downwind. The open problem is to complete that assessment: quantify, with source tagging, the contributions of vehicular VOC and semi-/intermediate-volatility organic compound (S/IVOC) emissions to SOA and of vehicular NOx and VOCs to O3 across the BTH receptor cities, decompose them into local versus non-local parts, and diagnose the governing processes (vertical mixing, heterogeneous reactions, aqueous-phase oxidation).

Background

Motor vehicles emit nitrogen oxides (NOx), primary fine particulate matter (PM2.5, particles smaller than 2.5 micrometers), and a large inventory of volatile organic compounds (VOCs) near the surface. Through atmospheric chemistry these primary emissions generate secondary pollutants: O3 forms photochemically from NOx and VOCs under sunlight, nitrate (NO3-) forms from oxidized NOx and ammonia, and secondary organic aerosol (SOA) forms when VOCs and semi-/intermediate-volatility organic compounds (SVOCs and IVOCs, organic compounds with saturation concentrations between those of VOCs and primary particulate matter) are oxidized to low-volatility products that condense onto particles. Because these secondary species form over hours to days, pollution measured in one city can originate from emissions in cities hundreds of kilometers away - regional transport.

The Beijing-Tianjin-Hebei (BTH) region, a cluster of 13 heavily polluted cities in northern China, is a classic setting for this problem. Lang et al. (2021, doi:10.1016/j.scitotenv.2021.147304) simulated calendar year 2014 with the WRF (Weather Research and Forecasting) meteorological model coupled to the CAMx (Comprehensive Air-quality Model with Extensions) chemical transport model (a regional air-quality model that computes emission, chemistry, transport, and removal of pollutants), using its PSAT (Particulate Source Apportionment Technology) module, which tags emissions by source and tracks their chemically transformed products to each receptor. They found that vehicles contributed on annual average about 25.8% of nitrate and 15.8% of PM2.5 in BTH, that the non-local share of the vehicular contribution was much larger for nitrate than for NOx, and that regional transport became more important on haze days (daily PM2.5 above 75 μ\mug m−3^{-3}), summarizing the distance decay of source-to-receptor influence with a power law.

However, that study treated only NOx, nitrate, and PM2.5, and reported no vehicle-tagged SOA or O3 results. Vehicle-emitted VOCs, which can oxidize to SOA and add to PM2.5, and O3 formation from vehicular NOx and VOCs were outside its reported contributions, and it did not diagnose which processes (vertical mixing that lifts near-surface exhaust into the regional boundary layer, heterogeneous reactions on particle surfaces, aqueous-phase oxidation in droplets) enable near-surface vehicular emissions to travel far downwind and become secondary pollutants there.

Since then the enabling pieces have matured: a nationwide measurement-based on-road IVOC emission inventory exists (Wang et al. 2022, doi:10.1016/j.envpol.2022.119887); volatility-basis-set SOA schemes (which represent organic aerosol as a continuum of volatility bins) have been shown to capture Chinese SOA when fed with S/IVOC emissions (Miao et al. 2021, doi:10.5194/acp-21-16183-2021); mobile-source S/IVOC-induced SOA has been quantified China-wide with the CMAQ (Community Multiscale Air Quality) model (Zhao et al. 2022, doi:10.1021/acs.est.2c07265); and on-road IVOC-to-SOA tagging has been demonstrated over Europe (Manavi and Pandis 2024, doi:10.5194/acp-24-891-2024). On the ozone side, CMAQ-ISAM (Integrated Source Apportionment Method) has apportioned Beijing O3 by vehicle type (Cao et al. 2024, doi:10.1016/j.envint.2024.109002), and a tagged WRF-Chem (WRF coupled with online chemistry) study has attributed BTH O3 to NOx versus VOC sources by region with process analysis of transport (Zhang et al. 2026, doi:10.1016/j.envpol.2026.127914).

Problem Statement

For the Beijing-Tianjin-Hebei region, extend the vehicle-source-tagged regional-transport assessment of Lang et al. (2021) to the secondary pollutants it excluded. Specifically: (1) quantify, with source tagging, the contribution of vehicular emissions to secondary organic aerosol and to PM2.5 including its organic component, and to O3 formation from vehicular NOx and VOCs, for each of the BTH receptor cities; (2) decompose each of these vehicular contributions into local (within-receptor-city) and non-local (regionally transported) parts, including how the decomposition changes between clean and haze conditions; and (3) diagnose the physical and chemical processes - such as vertical mixing that entrains near-surface exhaust into the regional boundary layer and free troposphere, heterogeneous reactions, and aqueous-phase oxidation - by which near-surface vehicular emissions are carried over long distances and chemically transformed into secondary pollutants in downwind regions. The single overarching objective is a process-explained, source-tagged account of the total secondary-pollutant impact of vehicular emissions at BTH regional scale, of which the tagged concentration fields, the local/non-local decomposition, and the process attribution are jointly necessary components.

References

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