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A comprehensive understanding of the effects of meteorology, emissions, and chemistry on severe haze is critical in the mitigation of air pollution. However, such an understanding is greatly hindered by the nonlinearity of atmospheric systems. In this study, we developed the quantitative decoupling analysis (QDA) method to quantify the effects of emissions, meteorology, chemical reactions, and their nonlinear interactions on fine particulate matter (PM2.5) pollution by running built in scenario simulations in each model step. Different from previous methods, the QDA method achieves a fully decomposed analysis of hourly changes in the PM2.5 concentration during pollution events into seven parts, including the pure meteorological contribution (M), the pure emissions contribution (E), the pure chemistry contribution (C), and the interactions among these processes (i.e., ME, MC, EC, and MCE). Via embedding the QDA method into the Weather Research and Forecasting-Nested Air Quality Prediction Modeling System, we employed this method and combined it with the Integrated Process Rate method to study a typical heavy haze episode in Beijing. We evaluate the model performance against in situ meteorological and air quality observations and describe the QDA analytical factors of this case. Results showed that M varied most significantly at different stages of the episode, from 0.21 µg·m-3·h-1 during the accumulation stage to -11.82 µg·m-3·h-1 during the removal stage, indicating that the pure meteorological contribution dominated the hourly fluctuation amplitude of the PM2.5 concentration. M acted as the most important cleaner for PM2.5 in non-polluting periods but stopped being effective at this and instead became a contributor in the accumulation stage such that PM2.5 tended to grow rapidly under the superimposed influence of emissions and chemical processes, which would probably mark the beginning of a heavy pollution event. The contribution of E ranged from 0.63 to 0.88 µg·m-3·h-1 owing to the diurnal variation of emissions. The pure chemical contribution was shown to increase with the level of haze, becoming the largest (0.37 µg·m-3·h-1) in the maintenance period, which was 25% higher than during the pre-contamination period. And C+CE made a significant contribution in the accumulation and maintenance stages, indicating that chemical reactions are more important in the polluted period than in other periods. Nonnegligible nonlinear effects exist among the processes of meteorology, emissions, and chemistry on PM2.5 concentrations (-1.83 to 2.44 µg·m-3·h-1)--something that has generally been ignored in previous studies and during the development of heavy-pollution control strategies. The nonlinear effects are helpful in eliminating the interference of other processes and obtaining a more purified result of the target process and have important indicative significances. The ratio of CE to C is positively correlated with the chemical speed. For precursors like NH3, the smaller value of CE in the most polluted period indicated that NH3 was more deficient, and thus reducing emissions of it in that period would have had the most efficient controlling effect on the PM2.5. This study highlights that the QDA method can be used to realize an in-depth understanding of the effects of adverse meteorological conditions in haze and to judge whether the precursors are excessive or not. Not only can the QDA method provide researchers and policymakers with valuable information for understanding the key factors behind heavy pollution, but it can also help modelers to identify the sources of uncertainties in numerical models. [ABSTRACT FROM AUTHOR]

Owing to the substantial traffic emissions in urban areas, especially near road areas, the concentrations of pollutants, such as ozone (O3) and its precursors, have a large gap with the regional averages and their distributions cannot be captured accurately by traditional single-scale air-quality models. In this study, a new version of a regional-urban-streetnetwork model (IAQMS-street v2.0) is presented. An upscaling module is implemented in IAQMS-street v2.0 to calculate the impact of mass transfer to regional scale from street network. The influence of pollutants in street network is considered in the concentration calculation on regional scale, which is not considered in a previous version (IAQMS-street v1.0). In this study, the simulated results in Beijing during August 2021 by using IAQMS-street v2.0, IAQMS-street v1.0, and the regional model (NAQPMS) are compared. On-road traffic emissions in Beijing, as the key model-input data, were established using intelligent image-recognition technology and real-time traffic big data from navigation applications. The simulated results showed that the O3 and nitrogen oxides (NOx) concentrations in Beijing were reproduced by using IAQMS-street v2.0 both on regional scale and street scale. The prediction fractions within a factor of two (FAC2s) between simulations and observations of NO and NO2 increased from 0.11 and 0.34 in NAQPMS to 0.78 and 1.00 in IAQMS-street v2.0, respectively. The normalized mean biases (NMBs) of NO and NO2 decreased from 2.67 and 1.33 to -0.25 and 0.08. the concentration of NOx at street scale is higher than that at the regional scale, and the simulated distribution of pollutants on regional scale was improved in IAQMS-street v2.0 compared with that in IAQMS-street v1.0. We further used the IAQMS street v2.0 to quantify the contribution of local on-road traffic emissions to the O3 and NOx emissions and analyze the effect of traffic-regulation policies in Beijing. Results showed that heavy-duty trucks are the major source of on-road traffic emissions of NOx. The relative contributions of local traffic emissions to NO2, NO, and O3 emissions were 53.41, 57.45, and 8.49%, respectively. We found that traffic-regulation policies in Beijing largely decreased the concentrations of NOx and hydrocarbons (HC); however, the O3 concentration near the road increased due to the decrease consumption of O3 by NO. To decrease the O3 concentration in urban areas, controlling the local emissions of HC and NOx from other sources requires consideration. [ABSTRACT FROM AUTHOR]

Changes in land use might affect the combined C, N, and P stoichiometry in soil. The Plain Afforestation Program, which converts low-yield croplands or abandoned lands into forest, shrub, and/or grassland, was a famous land reforestation project in Beijing. To clarify the spatial distribution, stoichiometric characteristics, and controlling factors of carbon (C), nitrogen (N), and phosphorus (P), four typical Plain Afforestation forests including Robinia pseudoacacia, Pinus tabuliformis, Ailanthus altissima, and Salix matsudana plantations were selected in Yongding River plain afforestation area, Beijing. Leaf, litter, and soil C, N, and P concentrations and their stoichiometric relationships were analyzed. The results showed that the concentrations of N and P in the four plantations were in order of R. pseudoacacia>A. altissima>S. matsudana >P. tabuliformis in leaf and litter. Compared with leaves, the concentrations of C for P. tabuliformis were highest. The concentrations of N and P, as well as N:P for R. pseudoacacia plantation, were significantly higher than those for the other plantations. C and N concentrations were the highest in surface soil (0-10 cm), and C:N and C:P both demonstrated the trend of litter>soil in the plantations with the exception of S. matsudana. The total N concentration of leaf was positively correlated with that of litter in the four plantations. Overall, our findings suggested the growth of R. pseudoacacia, P. tabuliformis, and S. matsudana was mainly restricted by P, while that of A. altissima was constrained by N. In addition, it is a feasible method that uses nitrogen fertilizer when tending the artificial forest in the plain area. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of the effects of meteorology, emission and chemistry on severe haze is critical in the mitigation of air pollution. However, such understanding is largely hindered by the nonlinearity of atmospheric chemistry systems. Here, we developed a novel quantitative decoupling analysis (QDA) method to quantify the effects of emission, meteorology, chemical reaction, and their nonlinear interactions on the fine particulate matter (PM2.5) pollution based on the accompanying simulations for different atmospheric processes. Via embedding the QDA method into the Weather Research and Forecasting-Nested Air Quality Prediction Modeling System (WRF-NAQPMS) model, we first employed this method into a typical heavy haze episode in Beijing. Different from the previously sensitive simulation method, which usually linked to a certain period, the QDA achieves the fully decomposing analysis of PM2.5 concentration during any pollution event into seven different parts, including meteorological contribution (M), emission contribution (E), chemical contribution (C), and interactions among these drivers (i.e., ME, MC, EC and MCE). The results show that the meteorology contribution varied significantly at different stages of episode, from 0.21 µg·m-3·h-1 during accumulation period to -11.82 µg·m-3·h-1 during the removal period, dominating the hourly changes of PM2.5 concentrations. The chemical contributions were shown to increase with the level of haze, which become largest (0.37 µg·m-3·h-1) at the maintenance period, 25 % higher than that during the clean period. The contribution of primary emission is relatively stable in all stages due to the use of fixed emission during the simulation. Besides, the QDA method highlights that there exist nonnegligible coupling effects of meteorology, emission and chemistry on PM2.5 concentrations (-1.83 to 2.44 µg·m-3·h-1), which were commonly ignored in previous studies and the development of heavy-pollution control strategies. These results indicate that the QDA method can not only provide researchers and policy makers with valuable information for understanding of key factors to heavy pollution, but also help the modelers to find out the sources of uncertainties among numerical models. [ABSTRACT FROM AUTHOR]

An online coupled regional climate–chemistry–aerosol model (RIEMS-Chem) was developed and utilized to investigate the mechanisms of haze formation and evolution and aerosol radiative feedback during winter haze episodes in February–March 2014 over the Beijing-Tianjin-Hebei (BTH) region in China. Model comparison against a variety of observations demonstrated a good ability of RIEMS-Chem in reproducing meteorological variables, planetary boundary layer (PBL) heights, PM 2.5 , and its chemical components, as well as aerosol optical properties. The model performances were remarkably improved for both meteorology and chemistry by taking aerosol radiative feedback into account. The domain-average aerosol radiative effects (AREs) were estimated to be - 57 W m -2 at the surface, 25 W m -2 in the atmosphere, and - 32 W m -2 at the top of atmosphere (TOA) during a severe haze episode (20–26 February), with the maximum hourly surface ARE reaching - 384 W m -2 in southern Hebei province. The average feedback-induced changes in 2 m air temperature (T2), 10 m wind speed (WS10), 2 m relative humidity (RH2), and PBL height over the BTH region during the haze episode were - 1.8 ∘ C, - 0.5 m s -1 , 10.0 %, and - 184 m, respectively. The BTH average changes in PM 2.5 concentration due to the feedback were estimated to be 20.0 µ g m -3 (29 %) and 45.1 µ g m -3 (39 %) for the entire period and the severe haze episode, respectively, which demonstrated a significant impact of aerosol radiative feedback on haze formation. The relative changes in secondary aerosols were larger than those in primary aerosols due to enhanced chemical reactions by aerosol feedback. The feedback-induced absolute change in PM 2.5 concentrations was largest in the haze persistence stage, followed by those in the growth stage and dissipating stage. Process analyses on haze events in Beijing revealed that local emission, chemical reaction, and regional transport mainly contributed to haze formation in the growth stage, whereas vertical processes (diffusion, advection, and dry deposition) were major processes for PM 2.5 removals. Chemical processes and local emissions dominated the increase in PM 2.5 concentrations during the severe haze episode, whereas horizontal advection contributed to the PM 2.5 increase with a similar magnitude to local emissions and chemical processes during a moderate haze episode on 1–4 March. The contributions from physical and chemical processes to the feedback-induced changes in PM 2.5 and its major components were explored and quantified through process analyses. For the severe haze episode, the increase in the change rate of PM 2.5 (9.5 µ g m -3 h -1) induced by the feedback in the growth stage was attributed to the larger contribution from chemical processes (7.3 µ g m -3 h -1) than that from physical processes (2.2 µ g m -3 h -1), whereas, during the moderate haze episode, the increase in the PM 2.5 change rate (2.4 µ g m -3 h -1) in the growth stage was contributed more significantly by physical processes (1.4 µ g m -3 h -1) than by chemical processes (1.0 µ g m -3 h -1). In general, the aerosol–radiation feedback increased the accumulation rate of aerosols in the growth stage through weakening vertical diffusion, promoting chemical reactions, and/or enhancing horizontal advection. It enhanced the removal rate through increasing vertical diffusion and vertical advection in the dissipation stage, and had little effect on the change rate of PM 2.5 in the persistence stage. [ABSTRACT FROM AUTHOR]

Despite extensive studies into the characterization of particle number size distributions at ground level, realtime measurements above the urban canopy in the megacity of Beijing have never been performed to date. Here we conducted the first simultaneous measurements of size-resolved particle number concentrations at ground level and 260m in urban Beijing from 22 August to 30 September. Our results showed overall similar temporal variations in number size distributions between ground level and 260 m, yet periods with significant differences were also observed. Particularly, accumulation-mode particles were highly correlated (r² = 0:85) at the two heights, while Aitken-mode particles presented more differences. Detailed analysis suggests that the vertical differences in number concentrations strongly depended on particle size, and particles with a mobility diameter between 100 and 200 nm generally showed higher concentrations at higher altitudes. Particle growth rates and condensation sinks were also calculated, which were 3.2 and 3.6 nm h-1, and 2.8x10-2 and 2.9x10-2 s-1, at ground level and 260 m, respectively. By linking particle growth with aerosol composition, we found that organics appeared to play an important role in the early stage of the growth (09:00-12:00 LT) while sulfate was also important during the later period. Positive matrix factorization of size-resolved number concentrations identified three common sources at ground level and 260 m, including a factor associated with new particle formation and growth events (NPEs), and two secondary factors that represent photochemical processing and regional transport. Cooking emission was found to have a large contribution to small particles and showed much higher concentration at ground level than 260m in the evening. These results imply that investigation of NPEs at ground level in megacities needs to consider the influences of local cooking emissions. The impacts of regional emission controls on particle number concentrations were also illustrated. Our results showed that regional emission controls have a dominant impact on accumulation-mode particles by decreasing gas precursors and particulate matter loadings, and hence suppressing particle growth. In contrast, the influences on Aitken particles were much smaller due to the enhanced new particle formation (NPF) events. [ABSTRACT FROM AUTHOR]

Winter has the worst air pollution of the year in the megacity of Beijing. Despite extensive winter studies in recent years, our knowledge of the sources, formation mechanisms and evolution of aerosol particles is not complete. Here we have a comprehensive characterization of the sources, variations and processes of submicron aerosols that were measured by an Aerodyne high-resolution aerosol mass spectrometer from 17 December 2013 to 17 January 2014 along with offline filter analysis by gas chromatography/ mass spectrometry. Our results suggest that submicron aerosols composition was generally similar across the winter of different years and was mainly composed of organics (60%), sulfate (15%) and nitrate (11%). Positive matrix factorization of high- and unit-mass resolution spectra identified four primary organic aerosol (POA) factors from traffic, cooking, biomass burning (BBOA) and coal combustion (CCOA) emissions as well as two secondary OA (SOA) factors. POA dominated OA, on average accounting for 56%, with CCOA being the largest contributor (20%). Both CCOA and BBOA showed distinct polycyclic aromatic hydrocarbons (PAHs) spectral signatures, indicating that PAHs in winter were mainly from coal combustion (66%) and biomass burning emissions (18%). BBOA was highly correlated with levoglucosan, a tracer compound for biomass burning (r² = 0:93), and made a considerable contribution to OA in winter (9%). An aqueous-phase-processed SOA (aq- OOA) that was strongly correlated with particle liquid water content, sulfate and S-containing ions (e.g. CH2SO+ 2) was identified. On average aq-OOA contributed 12% to the total OA and played a dominant role in increasing oxidation degrees of OA at high RH levels (> 50%). Our results illustrate that aqueous-phase processing can enhance SOA production and oxidation states of OA as well in winter. Further episode analyses highlighted the significant impacts of meteorological parameters on aerosol composition, size distributions, oxidation states of OA and evolutionary processes of secondary aerosols. [ABSTRACT FROM AUTHOR]

Secondary organic aerosol (SOA) constitutes a large fraction of OA, yet remains a source of significant uncertainties in climate models due to incomplete understanding of its formation mechanisms and evolutionary processes. Here we evaluated the effects of photochemical and aqueous-phase processing on SOA composition and oxidation degrees in three seasons in Beijing, China, using high-resolution aerosol mass spectrometer measurements along with positive matrix factorization. Our results show that aqueous-phase processing has a dominant impact on the formation of more oxidized SOA (MO-OOA), and the contribution of MO-OOA to OA increases substantially as a function of relative humidity or liquid water content. In contrast, photochemical processing plays a major role in the formation of less oxidized SOA (LO-OOA), as indicated by the strong correlations between LO-OOA and odd oxygen (Ox = O3 + NO2) during periods of photochemical production (R2 = 0.59-0.80). Higher oxygen-to-carbon ratios of SOA during periods with higher RH were also found indicating a major role of aqueous-phase processing in changing the oxidation degree of SOA in Beijing. Episodes analyses further highlight that LO-OOA plays a more important role during the early stage of the formation of autumn/winter haze episodes while MO-OOA is more significant during the later evolution period. [ABSTRACT FROM AUTHOR]