Modeling particulate nitrate in China: Current findings and future directions

Particulate nitrate (pNO3) is now becoming the principal component of PM2.5 during severe winter haze episodes in many cities of China. To gain a comprehensive understanding of the key factors controlling pNO3 formation and driving its trends, we reviewed the recent pNO3 modeling studies which mainly focused on the formation mechanism and recent trends of pNO3 as well as its responses to emission controls in China. The results indicate that although recent chemical transport models (CTMs) can reasonably capture the spatial-temporal variations of pNO3, model-observation biases still exist due to large uncertainties in the parameterization of dinitrogen pentoxide (N2O5) uptake and ammonia (NH3) emissions, insufficient heterogeneous reaction mechanism, and the predicted low sulfate concentrations in current CTMs. The heterogeneous hydrolysis of N2O5 dominates nocturnal pNO3 formation, however, the contribution to total pNO3 varies among studies, ranging from 21.0% to 51.6%. Moreover, the continuously increasing PM2.5 pNO3 fraction in recent years is mainly due to the decreased sulfur dioxide emissions, the enhanced atmospheric oxidation capacity (AOC), and the weakened nitrate deposition. Reducing NH3 emissions is found to be the most effective control strategy for mitigating pNO3 pollution in China. This review suggests that more field measurements are needed to constrain the parameterization of heterogeneous N2O5 and nitrogen dioxide (NO2) uptake. Future studies are also needed to quantify the relationships of pNO3 to AOC, O3, NOx, and volatile organic compounds (VOCs) in different regions of China under different meteorological conditions. Research on multiple-pollutant control strategies involving NH3, NOX, and VOCs is required to mitigate pNO3 pollution, especially during severe winter haze events.

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry-meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O₃) and fine particulate matter (PM_2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O₃, sulfate, nitrate, ammonium, elemental carbon, tropospheric O₃ residual, and column nitrogen dioxide (NO₂). For example, the mean biases have been reduced by more than 10 W m^-2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O₃. However, relatively large biases still exist for cloud predictions, some PM_2.5 species, and PM₁₀ that warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O₃, nitrogen oxide (NO _x ), volatile organic compounds (VOCs), and PM_2.5 by 3.1% (up to 27.8%), 4.2% (up to 16.2%), 6.6% (up to 50.9%), 5.8% (up to 46.6%), and 8.6% (up to 49.1%), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry-meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O₃) and fine particulate matter (PM_2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O₃, sulfate, nitrate, ammonium, elemental carbon, tropospheric O₃ residual, and column nitrogen dioxide (NO₂). For example, the mean biases have been reduced by more than 10 W m^-2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O₃. However, relatively large biases still exist for cloud predictions, some PM_2.5 species, and PM₁₀ that warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O₃, nitrogen oxide (NO _x ), volatile organic compounds (VOCs), and PM_2.5 by 3.1% (up to 27.8%), 4.2% (up to 16.2%), 6.6% (up to 50.9%), 5.8% (up to 46.6%), and 8.6% (up to 49.1%), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

Secondary aerosol formation and its linkage with synoptic conditions during winter haze pollution over eastern China

Eastern China has been facing severe winter haze pollution due mainly to secondary aerosol. Existing studies have suggested that stagnant weather or fast chemical production led to frequent haze in this region. However, few works focus on the linkage between secondary production of sulfate, nitrate, and ammonium (SNA) and synoptic conditions, and their joint contribution to PM_2.5. In this study, by combining in-situ measurements on meteorology and aerosol chemical composition at three main cities together with a regional model with improved diagnose scheme, we investigated the chemical formation and accumulation of main secondary composition, i.e. SNA under typical synoptic conditions. It is indicated that SNA did play a vital role in haze pollution across eastern China, contributing more than 40% to PM_2.5 mass concentration. As most fast developing region, the Yangtze River Delta (YRD) was slightly polluted during stable weather with local chemical production accounting for 61% SNA pollution. While under the influence of cold front, the pollution was aggravated and advection transport became the predominant contributive process (85%). Nevertheless, the chemical production of SNA was notably enhanced due to the uplift of air pollutant and elevated humidity ahead of the cold front, which then facilitated the heterogeneous and aqueous-phase oxidation of precursors. We also found the substantial difference in the phase equilibrium of nitrate over the land surface and ocean due to changes in temperature, ammonia availability and dry deposition. This study highlights the close link between synoptic weather and chemical production, and the resultant vertical and spatial heterogeneity of pollution.

Comparison of PM2.5 Chemical Components over East Asia Simulated by the WRF-Chem and WRF/CMAQ Models: On the Models’ Prediction Inconsistency

High levels of atmospheric concentration of PM2.5 (particulate matters less than 2.5 μm in size) are one of the most urgent societal issues over the East Asian countries. Air quality models have been used as an essential tool to predict spatial and temporal distribution of the PM2.5 and to support relevant policy making. This study aims to investigate the performance of high-fidelity air quality models in simulating surface PM2.5 chemical composition over the East Asia region in terms of a prediction consistency, which is a prerequisite for accurate air quality forecasts and reliable policy decision. The WRF-Chem (Weather Research and Forecasting-Chemistry) and WRF/CMAQ (Weather Research and Forecasting/Community Multiscale Air Quality modeling system) models were selected and uniquely configured for a one-month simulation by controlling surface emissions and meteorological processes (model options) to investigate the prediction consistency focusing the analyses on the effects of meteorological and chemical processes. The results showed that the surface PM2.5 chemical components simulated by both the models had significant inconsistencies over East Asia ranging fractional differences of 53% ± 30% despite the differences in emissions and meteorological fields were minimal. The models’ large inconsistencies in the surface PM2.5 concentration were attributed to the significant differences in each model’s chemical responses to the meteorological variables, which were identified from the multiple linear regression analyses. Our findings suggest that the significant models’ prediction inconsistencies should be considered with a great caution in the PM2.5 forecasts and policy support over the East Asian region.

Vapor-wall deposition in chambers: theoretical considerations

In order to constrain the effects of vapor-wall deposition on measured secondary organic aerosol (SOA) yields in laboratory chambers, researchers recently varied the seed aerosol surface area in toluene oxidation and observed a clear increase in the SOA yield with increasing seed surface area (Zhang, X.; et al. Proc. Natl. Acad. Sci. U.S.A. 2014, 111, 5802). Using a coupled vapor-particle dynamics model, we examine the extent to which this increase is the result of vapor-wall deposition versus kinetic limitations arising from imperfect accommodation of organic species into the particle phase. We show that a seed surface area dependence of the SOA yield is present only when condensation of vapors onto particles is kinetically limited. The existence of kinetic limitation can be predicted by comparing the characteristic time scales of gas-phase reaction, vapor-wall deposition, and gas-particle equilibration. The gas-particle equilibration time scale depends on the gas-particle accommodation coefficient αp. Regardless of the extent of kinetic limitation, vapor-wall deposition depresses the SOA yield from that in its absence since vapor molecules that might otherwise condense on particles deposit on the walls. To accurately extrapolate chamber-derived yields to atmospheric conditions, both vapor-wall deposition and kinetic limitations must be taken into account.

Uncertainty in biogenic isoprene emissions and its impacts on tropospheric chemistry in East Asia

In this study, the accuracy of biogenic isoprene emission fluxes over East Asia during two summer months (July and August) was examined by comparing two tropospheric HCHO columns (ΩHCHO) obtained from the SCIAMACHY sensor and the Community Multi-scale Air Quality (CMAQ v4.7.1) model simulations, using three available biogenic isoprene emission inventories over East Asia: i) GEIA, ii) MEGAN and iii) MOHYCAN. From this comparative analysis, the tropospheric HCHO columns from the CMAQ model simulations, using the MEGAN and MOHYCAN emission inventories (Ω(CMAQ, MEGAN) and Ω(CMAQ, MOHYCAN)), were found to agree well with the tropospheric HCHO columns from the SCIAMACHY observations (Ω(SCIA)). Secondly, the propagation of such uncertainties in the biogenic isoprene emission fluxes to the levels of atmospheric oxidants (e.g., OH and HO2) and other atmospheric gaseous/particulate species over East Asia during the two summer months was also investigated. As the biogenic isoprene emission fluxes decreased from the GEIA to the MEGAN emission inventories, the levels of OH radicals increased by factors of 1.39 and 1.75 over Central East China (CEC) and South China, respectively. Such increases in the OH radical mixing ratios subsequently influence the partitioning of HO(y) species. For example, the HO2/OH ratios from the CMAQ model simulations with GEIA isoprene emissions were 2.7 times larger than those from the CMAQ model simulations based on MEGAN isoprene emissions. The large HO2/OH ratios from the CMAQ model simulations with the GEIA biogenic emission were possibly due to the overestimation of GEIA biogenic isoprene emissions over East Asia. It was also shown that such large changes in HO(x) radicals created large differences on other tropospheric compounds (e.g., NO(y) chemistry) over East Asia during the summer months.

Modeling the role of alkanes, polycyclic aromatic hydrocarbons, and their oligomers in secondary organic aerosol formation

A computationally efficient method to treat secondary organic aerosol (SOA) from various length and structure alkanes as well as SOA from polycyclic aromatic hydrocarbons (PAHs) is implemented in the Community Multiscale Air Quality (CMAQ) model to predict aerosol concentrations over the United States. Oxidation of alkanes is predicted to produce more aerosol than oxidation of PAHs driven by relatively higher alkane emissions. SOA from alkanes and PAHs, although small in magnitude, can be a substantial fraction of the SOA from anthropogenic hydrocarbons, particularly in winter, and could contribute more if emission inventories lack intermediate volatility alkanes (>C(13)) or if the vehicle fleet shifts toward diesel-powered vehicles. The SOA produced from oxidation of alkanes correlates well with ozone and odd oxygen in many locations, but the lower correlation of anthropogenic oligomers with odd oxygen indicates that models may need additional photochemically dependent pathways to low-volatility SOA.

Radiocarbon (14C) diurnal variations in fine particles at sites downwind from Tokyo, Japan in summer

The radiocarbon ((14)C) of total carbon (TC) in atmospheric fine particles was measured at 6 h or 12 h intervals at two sites, 50 and 100 km downwind from Tokyo, Japan (Kisai and Maebashi) in summer 2007. The percent modern carbon (pMC) showed clear diurnal variations with minimums in the daytime. The mean pMC values at Maebashi were 28 ± 7 in the daytime and 45 ± 16 at night (37 ± 15 for the overall period). Those at Kisai were 26 ± 9 in the daytime and 44 ± 8 at night (37 ± 12 for the overall period). This data indicates that fossil sources were major contributors to the daytime TC, while fossil and modern sources had comparable contributions to nighttime TC in the suburban areas. At both sites, the concentration of fossil carbon as well as O(3) and the estimated secondary organic carbon increased in the daytime. These results suggest that fossil sources around Tokyo contributed significantly to the high daytime concentration of secondary organic aerosols (SOA) at the two suburban sites. A comparison of pMC and the ratio of elemental carbon/TC from our particulate samples with those from three end-member sources corroborates the dominant role of fossil SOA in the daytime.

Contrasting diurnal variations in fossil and nonfossil secondary organic aerosol in urban outflow, Japan

Diurnal variations of fossil secondary organic carbon (SOC) and nonfossil SOC were determined for the first time using a combination of several carbonaceous aerosol measurement techniques, including radiocarbon (¹⁴C) determinations by accelerator mass spectrometry, and a receptor model (chemical mass balance, CMB) at a site downwind of Tokyo during the summer of 2007. Fossil SOC showed distinct diurnal variation with a maximum during daytime, whereas diurnal variation of nonfossil SOC was relatively small. This behavior was reproduced by a chemical transport model (CTM). However, the CTM underestimated the concentration of anthropogenic secondary organic aerosol (ASOA) by a factor of 4-7, suggesting that ASOA enhancement during daytime is not explained by production from volatile organic compounds that are traditionally considered major ASOA precursors. This result suggests that unidentified semivolatile organic compounds or multiphase chemistry may contribute largely to ASOA production. As our knowledge of production pathways of secondary organic aerosol (SOA) is still limited, diurnal variations of fossil and nonfossil SOC in our estimate give an important experimental constraint for future development of SOA models.