Numerical air quality models (AQMs) have been applied more frequently over the past decade to address diverse scientific and regulatory issues associated with deteriorated air quality in China. Thorough evaluation of a model's ability to replicate monitored conditions (i.e., a model performance evaluation or MPE) helps to illuminate the robustness and reliability of the baseline modeling results and subsequent analyses. However, with numerous input data requirements, diverse model configurations, and the scientific evolution of the models themselves, no two AQM applications are the same and their performance results should be expected to differ. MPE procedures have been developed for Europe and North America, but there is currently no uniform set of MPE procedures and associated benchmarks for China. Here we present an extensive review of model performance for fine particulate matter (PM_2.5) AQM applications to China and, from this context, propose a set of statistical benchmarks that can be used to objectively evaluate model performance for PM_2.5 AQM applications in China. We compiled MPE results from 307 peer-reviewed articles published between 2006 and 2019, which applied five of the most frequently used AQMs in China. We analyze influences on the range of reported statistics from different model configurations, including modeling regions and seasons, spatial resolution of modeling grids, temporal resolution of the MPE, etc. Analysis using a random forest method shows that the choices of emission inventory, grid resolution, and aerosol- and gas-phase chemistry are the top three factors affecting model performance for PM_2.5. We propose benchmarks for six frequently used evaluation metrics for AQM applications in China, including two tiers – “goals” and “criteria” – where goals represent the best model performance that a model is currently expected to achieve and criteria represent the model performance that the majority of studies can meet. Our results formed a benchmark framework for the modeling performance of PM_2.5 and its chemical species in China. For instance, in order to meet the goal and criteria, the normalized mean bias (NMB) for total PM_2.5 should be within 10 % and 20 %, while the normalized mean error (NME) should be within 35 % and 45 %, respectively. The goal and criteria values of correlation coefficients for evaluating hourly and daily PM_2.5 are 0.70 and 0.60, respectively; corresponding values are higher when the index of agreement (IOA) is used (0.80 for goal and 0.70 for criteria). Results from this study will support the ever-growing modeling community in China by providing a more objective assessment and context for how well their results compare with previous studies and to better demonstrate the credibility and robustness of their AQM applications prior to subsequent regulatory assessments.

The Yangtze River Delta (YRD) and the megacity of Shanghai are host to one of the busiest port clusters in the world; the region also suffers from high levels of air pollution. The goal of this study was to estimate the contributions of shipping to regional emissions, air quality, and population exposure and to characterize the importance of the geographic spatiality of shipping lanes and different types of ship-related sources for the baseline year of 2015, which was prior to the implementation of China's Domestic Emission Control Areas (DECAs) in 2016. The WRF-CMAQ model, which combines the Weather Research and Forecasting model (WRF) and the Community Multi-scale Air Quality (CMAQ) model, was used to simulate the influence of coastal and inland-water shipping, port emissions and ship-related cargo transport on air quality and on the population-weighted concentrations (which is a measure of human exposure). Our results showed that the impact of shipping on air quality in the YRD was primarily attributable to shipping emissions within 12 NM (nautical miles) of shore, but emissions coming from the coastal area between 24 and 96 NM still contributed substantially to ship-related PM_2.5 concentrations in the YRD. The overall contribution of ships to the PM_2.5 concentration in the YRD could reach 4.62 µg m⁻³ in summer when monsoon winds transport shipping emissions onshore. In Shanghai city, inland-water going ships were major contributors (40 %–80 %) to the shipping impact on urban air quality. Given the proximity of inland-water ships to the urban populations of Shanghai, the emissions of inland-water ships contributed more to population-weighted concentrations. These research results provide scientific evidence to inform policies for controlling future shipping emissions; in particular, in the YRD region, expanding the boundary of 12 NM from shore in China's current DECA policy to around 100 NM from shore would include most of shipping emissions affecting air pollutant exposure, and stricter fuel standards could be considered for the ships on inland rivers and other waterways close to residential regions.