Source apportionment modeling provides valuable information on the contributions of different source sectors and/or source regions to ozone (O₃) or fine particulate matter (PM_2.5) concentrations. This information can be useful in designing air quality management strategies and in understanding the potential benefits of reducing emissions from a particular source category. The Comprehensive Air quality Model with Extensions (CAMx) offers unique source attribution tools, called the Ozone and Particulate Source Apportionment Technology (OSAT/PSAT), which track source contributions. We present results from a CAMx source attribution modeling study for a summer month and a winter month using a recently evaluated European CAMx modeling database developed for Phase 3 of the Air Quality Model Evaluation International Initiative (AQMEII). The contributions of several source sectors (including model boundary conditions of chemical species representing transport of emissions from outside the modeling domain as well as initial conditions of these species) to O₃ or PM_2.5 concentrations in Europe were calculated using OSAT and PSAT, respectively. A 1-week spin-up period was used to reduce the influence of initial conditions. Evaluation focused on 16 major cities and on identifying source sectors that contributed above 5 %. Boundary conditions have a large impact on summer and winter ozone in Europe and on summer PM_2.5, but they are only a minor contributor to winter PM_2.5. Biogenic emissions are important for summer ozone and PM_2.5. The important anthropogenic sectors for summer ozone are transportation (both on-road and non-road), energy production and conversion, and industry. In two of the 16 cities, solvent and product also contributed above 5 % to summertime ozone. For summertime PM_2.5, the important anthropogenic source sectors are energy, transportation, industry, and agriculture. Residential wood combustion is an important anthropogenic sector in winter for PM_2.5 over most of Europe, with larger contributions in central and eastern Europe and the Nordic cities. Other anthropogenic sectors with large contributions to wintertime PM_2.5 include energy, transportation, and agriculture.

Multi-pollutant chemical transport models (CTMs) are being routinely used to predict the impacts of emission controls on the concentrations and deposition of primary and secondary pollutants. While these models have a fairly comprehensive treatment of the governing atmospheric processes, they are unable to correctly represent processes that occur at very fine scales, such as the near-source transport and chemistry of emissions from elevated point sources, because of their relatively coarse horizontal resolution. Several different approaches have been used to address this limitation, such as using fine grids, adaptive grids, hybrid modeling, or an embedded sub-grid scale plume model, i.e., plume-in-grid (PinG) modeling. In this paper, we first discuss the relative merits of these various approaches used to resolve sub-grid scale effects in grid models, and then focus on PinG modeling which has been very effective in addressing the problems listed above. We start with a history and review of PinG modeling from its initial applications for ozone modeling in the Urban Airshed Model (UAM) in the early 1980s using a relatively simple plume model, to more sophisticated and state-of-the-science plume models, that include a full treatment of gas-phase, aerosol, and cloud chemistry, embedded in contemporary models such as CMAQ, CAMx, and WRF-Chem. We present examples of some typical results from PinG modeling for a variety of applications, discuss the implications of PinG on model predictions of source attribution, and discuss possible future developments and applications for PinG modeling.

Intercontinental transport of atmospheric pollution (ITAP) can offset the impact of local emission control efforts, impact human and ecosystem health, and play a role in climate forcing. This study aims to determine the role of ITAP caused by East Asian anthropogenic emissions (EAAEs) under current and future emission and climate scenarios. The contribution from EAAEs is determined using a "brute force method" in which results from simulations with and without EAAEs are compared. ITAP from East Asia is enhanced in the future due to faster wind speeds aloft and a stronger low pressure center near eastern Russia that facilitate enhanced westerly export in the free troposphere and stronger southerly transport near the surface, increased gaseous precursor emissions, and increased temperatures. As a result, the contribution of ozone (O₃) generated by EAAEs to the global average O₃ mixing ratio increases by ~0.8 ppb from 1.2 ppb in 2001 to 2.0 ppb in 2050. The contribution of PM_2.5 generated by EAAEs to the global PM_2.5 level increases by ~0.07 μg m⁻³ from 0.32 μg m⁻³ in 2001 to 0.39 μg m⁻³ in 2050, despite a non-homogenous response in PM_2.5 resulting from cloud and radiative feedbacks. EAAEs can increase East Asian biogenic secondary organic aerosol by 10–81%, indicating that it is largely controllable. EAAEs also increase the deposition of nitrogen, black carbon, and mercury both locally and downwind, implying that they may play a role in climate feedbacks and ecosystem health of these regions. These results show that EAAEs have a large impact on global air quality and climate, especially on downwind regions. Such impacts may be enhanced under future climate and emission scenarios, demonstrating a need to synergize global pollution control and climate mitigation efforts.

The Community Multiscale Air Quality (CMAQ) modeling system Version 5.0 (CMAQv5.0) was released by the U.S. Environmental Protection Agency (EPA) in February 2012, with an interim release (v5.01) in July 2012. Because CMAQ is a community model, the EPA encourages the development of proven alternative science treatments by external scientists and developers that can be incorporated as part of an official CMAQ release. This paper describes the implementation, evaluation, and testing of a plume-in-grid (PinG) module in CMAQ 5.01. The PinG module, also referred to as Advanced Plume Treatment (APT), provides the capability of resolving sub-grid-scale processes, such as the transport and chemistry of point-source plumes, in a grid model. The new PinG module in CMAQ 5.01 is applied and evaluated for two 15-day summer and winter periods in 2005 to the eastern United States, and the results are compared with those from the base CMAQ 5.01. Eighteen large point sources of NOx in the eastern United States were selected for explicit plume treatment with APT in the PinG simulation. The results show that overall model performance is negligibly affected when PinG treatment is included. However, the PinG model predicts significantly different contributions of the 18 sources to pollutant concentrations and deposition downwind of the point sources compared to the base model.