The interaction of aerosols and the planetary boundary layer (PBL) plays an important role in deteriorating urban air quality. Aerosols from different sources may have different effects on regulating PBL structures owing to their distinctive dominant compositions and vertical distributions. To characterize the complex feedback of aerosols on PBL over the Beijing megacity, multiple approaches, including in situ observations in the autumn and winter of 2016–2019, backward trajectory clusters, and large-eddy simulations, were adopted. The results revealed notable distinctions in aerosol properties, vertical distributions and thermal stratifications among three types of air masses from the West Siberian Plain (Type-1), Central Siberian Plateau (Type-2) and Mongolian Plateau (Type-3). Low loadings of 0.28 ± 0.26 and 0.15 ± 0.08 of aerosol optical depth (AOD) appeared in the Type-1 and Type-2, accompanied by cool and less stable stratification, with a large part (80%) of aerosols concentrated below 1500 m. For Type-3, the AOD and single scattering albedo (SSA) were as high as 0.75 ± 0.54 and 0.91 ± 0.05, demonstrating severe pollution levels of abundant scattering aerosols. Eighty percent of the aerosols were constrained within a lower height of 1150 m owing to the warmer and more stable environment. Large-eddy simulations revealed that aerosols consistently suppressed the daytime convective boundary layer regardless of their origins, with the PBL height (PBLH) decreasing from 1120 m (Type-1), 1160 m (Type-2) and 820 m (Type-3) in the ideal clean scenarios to 980 m, 1100 m and 600 m, respectively, under polluted conditions. Therefore, the promotion of absorbing aerosols below the residual layer on PBL could be greatly hindered by the suppression effects generated by both absorbing aerosols in the upper temperature inversion layer and scattering aerosols. Moreover, the results indicated the possible complexities of aerosol-PBL interactions under future emission-reduction scenarios and in other urban regions.

The determination of both stable nitrogen (δ¹⁵N–NO₃⁻) and stable oxygen (δ¹⁸O–NO₃⁻) isotopic signatures of nitrate in PM₂.₅ has shown potential for an approach of assessing the sources and oxidation pathways of atmospheric NOx (NO+NO₂). In the present study, daily PM₂.₅ samples were collected in the megacity of Beijing, China during the winter of 2017–2018, and this new approach was used to reveal the origin and oxidation pathways of atmospheric NOx. Specifically, the potential of field δ¹⁵N–NO₃⁻ signatures for determining the NOx oxidation chemistry was explored. Positive correlations between δ¹⁸O–NO₃⁻ and δ¹⁵N–NO₃⁻ were observed (with R² between 0.51 and 0.66, p < 0.01), and the underlying environmental significance was discussed. The results showed that the pathway-specific contributions to NO₃⁻ formation were approximately 45.3% from the OH pathway, 46.5% from N₂O₅ hydrolysis, and 8.2% from the NO₃+HC channel based on the δ¹⁸O-δ¹⁵N space of NO₃⁻. The overall nitrogen isotopic fractionation factor (εN) from NOx to NO₃⁻ on a daily scale, under winter conditions, was approximately +16.1‰±1.8‰ (consistent with previous reports). Two independent approaches were used to simulate the daily and monthly ambient NOx mixtures (δ¹⁵N-NOx), respectively. Results indicated that the monthly mean values of δ¹⁵N-NOx compared well based on the two approaches, with values of −5.5‰ ± 2.6‰, −2.7‰ ± 1.9‰, and −3.2‰ ± 2.2‰ for November, December, and January (2017–2018), respectively. The uncertainty was in the order of 5%, 5‰ and 5.2‰ for the pathway-specific contributions, the εN, and δ¹⁵N-NOx, respectively. Results also indicated that vehicular exhaust was the key contributor to the wintertime atmospheric NOx in Beijing (2017–2018). Our advanced isotopic perspective will support the future assessment of the origin and oxidation of urban atmospheric NOx.

It is widely recognized that green infrastructures in urban ecosystems provides important ecosystem services, including air purification. The potential absorption of nitrogen oxides (NOₓ) by urban trees has not been fully quantified, although it is important for air pollution mitigation and the well-being of urban residents. In this study, four common tree species (Sophora japonica L., Fraxinus chinensis Roxb., Populus tomentosa Carrière, Sabina chinensis (L.)) in Beijing, China, were studied. The dual stable isotopes (¹⁵N and ¹⁸O) and a Bayesian isotope mixing model were applied to estimate the sources contributions of potential nitrogen sources to the roadside trees based on leaf and soil sampling in urban regions. The following order of sources contributions was determined: soil > dry deposition > traffic-related NOₓ. The capacity of urban trees for NOₓ removal in the city was estimated using a remote sensing and GIS approach, and the removal capacity was found to range from 0.79 to 1.11 g m⁻² a⁻¹ across administrative regions, indicating that 1304 tons of NOₓ could be potentially removed by urban trees in 2019. Our finding qualified the potential NOₓ removal by urban trees in terms of atmospheric pollution mitigation, highlighting the role of green infrastructure in air purification, which should be taken into account by stakeholders to manage green infrastructure as the basis of a nature-based approach.

Black carbon (BC) exerts a large impact on climate radiative forcing and public health, and such impacts depend strongly on chemical composition and mixing state. Here a single particle aerosol mass spectrometry (SPA-MS) along with an aerosol chemical speciation monitor was employed to characterize the composition and mixing state of BC-containing particles in summer and winter in Beijing. Approximately 2 million BC-containing particles were chemically analyzed, and the particles were classified into nine and eight different types in summer and winter, respectively, according to mass spectral signatures and composition. The BC-containing particles in summer were dominated by the type of nitrate-related BC (BC-N, 56.7%), while in winter the BC mixed with organic carbon (OC) and sulfate (BCOC-S), and OC and nitrate (BCOC-N) were two dominant types accounting for 44.9% and 16.6%, respectively. The number fractions of BC-N in summer, and BCOC-N and BC-SN in winter increased largely during periods with severe air pollution, suggesting the enhanced secondary formation on BC-containing particles. We also found that the primary emissions of the biomass burning and coal combustion can affect BC mixing state substaintially as indicated by the considerable fraction of BC mixed with levoglucosan and polycyclic aromatic hydrocarbons in winter. Bivariate polar plots and back trajectory analysis indicated that the sulfate-associated BC-containing particles were mostly from regional transport while the nitrate-related type was more from local production. The optical parameter of absorbing Ångström exponents (AAE) of BC was 1.2 and 1.5 in summer and winter, respectively, and the AAE dependence of BC mixing state was also different in the two seasons. While higher fractions of BC-N were observed during lower AAE periods in summer, the variations of dominant OC-related BC-containing particles in winter were fairly stable as a function of AAE.

Recently, ground ozone has become one major airborne pollutant and the frequency of ozone-induced pollution episodes has increased rapidly across China. However, due to the lack of long-term observation data, relevant research on the characteristics and influencing factors of urban ozone concentrations remains limited. Based on ground ozone observation data during 2006–2016, we quantified the causality influence of individual meteorological factors on ozone concentrations in Beijing using a convergent cross mapping (CCM) method. The result indicated that the influence of each meteorological factor on ozone concentrations varied significantly across seasons and years. At the inter-annual scale, all-year meteorological influences on ozone concentrations were much more stable than seasonal meteorological influences. At the seasonal scale, meteorological influences on ozone concentrations were stronger in spring and autumn. Amongst multiple individual factors, temperature was the key meteorological influencing factor for ozone concentrations in all seasons except winter, when wind, humidity and SSD exerted major influences on ozone concentrations. In addition to temperature, air pressure was another meteorological factor that exerted strong influences on ozone concentrations. At both the inter-annual and seasonal scale, the influence of temperature and humidity on ozone concentrations was generally stable whilst that of other factors experienced large variations. Different from PM2.5, meteorological influences on ozone concentrations were relatively weak in summer, when ozone concentrations were the highest in Beijing. Given the generally stable meteorological influences on ozone concentrations and human-induced emissions of VOCs and NOx across seasons, warming induced notable increase in summertime biogenic emissions of VOCs and NOx can be a major driver for the increasing ozone pollution episodes. This research provides useful references for understanding long-term meteorological influences on ozone concentrations in mega cities in China.

Fine particulate matter (PM2.5) air pollution outbreaks have recently occurred frequently in China. However, evidence of the associations between short-term exposure to PM2.5 and cardiovascular morbidity is still limited in China. This study aimed to evaluate the associations between PM2.5 and hospital emergency room visits (ERVs) for cardiovascular diseases in urban areas in Beijing. Daily counts of cardiovascular ERVs were collected from ten large general hospitals from Jan 1 to Dec 31, 2013. Air pollution data were obtained from the Beijing Environmental Protection Bureau including 17 monitoring stations. A generalized additive Poisson model was used to examine the associations between PM2.5 and cardiovascular ERVs after controlling for seasonality, day of the week, public holidays, influenza outbreaks, and weather conditions. In total, there were 56,221 cardiovascular ERVs during the study period. The daily mean PM2.5 concentration was 102.1 μg/m³, ranging from 6.7 μg/m³ to 508.5 μg/m³. Per 10 μg/m³ increase in PM2.5 was associated with a 0.14% (95% confidence interval [CI]: 0.01%–0.27%) increase in cardiovascular ERVs at lag3. Cumulative delayed estimates were greatest at lag0–5 (0.30%, 95% CI: 0.09%–0.52%). The estimates of percentage change in daily ERVs per 10 μg/m³ increase in PM2.5 were 0.56% (95%CI: 0.16%–0.95%) for ischemic heart disease (IHD) at lag0–1, 0.81% (95%CI: 0.05%–1.57%) for heart rhythm disturbances (HRD) at lag0–1 and 1.21% (95%CI: 0.27%–2.15%) for heart failure (HF) at lag0, respectively. The effects of PM2.5 on IHD ERVs during high temperature days (>11.01 °C) were significantly higher than that on low temperature days (≤11.01 °C) at lag0, lag0–1, lag0–3 and lag0–5 (P < 0.05). The study suggests that PM2.5 has acute impacts on cardiovascular ERVs in Beijing, especially on IHD, HRD and HF. The effects of PM2.5 on IHD ERVs vary by temperature.

Several dense haze-fog (HF) episodes were occurred in the North China Plain (NCP), especially over Beijing in January 2013 characterized by a long duration, a large influential region, and an extremely high PM2.5 values (>500 μg m−3). In this study, we present the characteristics of aerosol optical properties and radiative forcing using Cimel sun-sky radiometer measurements during HF and no haze-fog (NHF) episodes occurred over Beijing during 1–31 January, 2013. The respective maximum values of daily mean aerosol optical depth at 440 nm (AOD440) were observed to be 1.21, 1.43, 1.52, and 2.21 occurred on 12, 14 19, and 28 January. It was found that the Ångström exponent (AE) values were almost higher than 1.0 during all the days with its maximum on 26 January (1.53), suggests the dominance of fine-mode particles. The maximum (minimum) aerosol volume size distributions occurred during dense HF (NHF) days with larger particle volumes of fine-mode. The single scattering albedo, asymmetry parameter, and complex refractive index values during HF events suggest the abundance of fine-mode particles from anthropogenic (absorbing) activities mixed with scattering dust particles. The average shortwave direct aerosol radiative forcing (DARF) values at the bottom-of-atmosphere (BOA) during HF and NHF days were estimated to be 112.29 ± 42.18 W m−2 and −58.61 ± 13.09 W m−2, while at the top-of-atmosphere (TOA) the forcing values were −45.78 ± 22.17 W m−2 and −18.64 ± 5.84 W m−2, with the corresponding heating rate of 1.61 ± 0.48 K day−1 and 1.12 ± 0.31 K day−1, respectively. The DARF values retrieved from the AERONET were in good agreement with the SBDART computed both at the TOA (r = 0.95) and the BOA (r = 0.97) over Beijing in January 2013.

The number and mass concentration, size distribution, and the concentration of 16 elements were studied in aerosol samples during the Spring Festival celebrations in 2013 in Beijing, China. Both the number and mass concentration increased sharply in a wide range from 10 nm to 10 μm during the firecrackers and fireworks activities. The prominent increase of the number concentration was in 50 nm–500 nm with a peak of 1.7 × 105/cm3 at 150 nm, which is 8 times higher than that after 1.5 h. The highest mass concentration was in 320–560 nm, which is 4 times higher than the control. K, Mg, Sr, Ba and Pb increased sharply during the firework activities in PM10. Although the aerosol emission from firework activities is a short-term air quality degradation event, there may be a substantial hazard arising from the chemical composition of the emitted particles.

Benefiting from the pollution controls implemented by the Chinese government, the concentrations of PM₂.₅, SO₂, NO₂ and CO showed a significant decrease in Beijing during 2013–2017. In this study, an observation-based method was employed to estimate the relative contributions of regional transport (MaxRTC) and local emissions (MinLEC) to air pollutant levels during 2013–2017 in Beijing. The results showed that the MaxRTC to SO₂ and PM₂.₅ increased significantly over the five years, while those to CO and NO₂ changed little. Furthermore, the difference in the emissions control efficiency (ΔECE) between Beijing (receptor region) and Shijiazhuang (source region), which refers to the concentration changes corresponding to unit emission changes of a certain air pollutant between the two regions, was introduced to verify the estimated variation in MaxRTC and MinLEC over 2013–2017. The negative value of ΔECE found for PM₂.₅ and SO₂ supports the conclusion of an increasing effect of regional transport. This implies that local emissions control alone is not adequate for mitigating Beijing's air pollution, especially with the demand for continuously improving air quality. Joint prevention and control with regard to air quality on a regional scale is more important and urgent in the next Five-Year Plan.

Suffered from serious air pollution, Beijing, the capital of China, has implemented multiple measures to reduce the discharge of PM₂.₅ (particulate matter with aerodynamic diameters of less than 2.5 μm). The average annual PM₂.₅ concentration of Beijing has shown a continued decline in recent years. However, the improvement was not obvious during the heating season, which had heavier pollution than the non-heating season. Analyzing the spatial distribution of PM₂.₅ concentrations during heating and non-heating seasons, as well as their spatial differences, is believed to benefit the study of spatial-temporal variation of air pollution and provide scientific reference for the control of air pollution in Beijing. In this study, land use regression (LUR) model was employed to simulate the spatial distribution of PM₂.₅ concentrations in Beijing during heating and non-heating seasons in 2015. The spatial distribution of the concentration difference between heating and non-heating seasons was analyzed, and the influencing factors were also examined. The results showed that: (1) PM₂.₅ concentrations during heating and non-heating seasons, as well as their differences, were clearly at a maximum in the south and east of Beijing and at a minimum in the north and west; (2) the area with the biggest concentration difference was situated in a suburban area to the south and east, as well as in outer suburbs to the southeast and northwest; and (3) wind speed, area of transport land and industrial-mining-warehouse land were the main influence factors for the PM₂.₅ concentration difference in the central, eastern and southern area. Heating activity was not the only cause for the increased PM₂.₅ concentration during the heating season, vehicle emission, industrial discharge and regional transport of pollutants also played varied roles in PM₂.₅ pollution in different area.