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Abstract. New particle formation (NPF) and subsequent particle growth are importantsources of condensation nuclei (CN) and cloud condensation nuclei (CCN).While many observations have shown positive contributions of NPF to CCN atlow supersaturation, negative NPF contributions were often simulated inpolluted environments. Using the observations in a coastal city of Qingdao,Beijing, and Gucheng in north China, we thoroughly evaluate the simulatednumber concentrations of CN and CCN using an NPF-explicit parameterizationembedded in the WRF-Chem model. For CN, the initial simulation shows largebiases of particle number concentrations at 10–40 and 40–100 nm. Byadjusting the process of gas–particle partitioning, including the massaccommodation coefficient (MAC) of sulfuric acid, the phase changes in primary organic aerosol emissions, and the condensational amount of nitric acid, the improvement of the particle growth process yields substantially reduced overestimation of CN. Regarding CCN, secondary organic aerosol (SOA) formed from the oxidation of semi-volatile and intermediate-volatility organic compounds (S/IVOCs) is called SI-SOA, the yield of which is an important contributor. At default settings, the SI-SOA yield is too high without considering the differences in precursor oxidation rates. Lowering the SI-SOA yield under linear H2SO4 nucleation scheme results in much-improved CCN simulations compared to observations. On the basis of the bias-corrected model, we find substantially positive contributions of NPF to CCN at low supersaturation (∼ 0.2 %) over broad areas of China, primarily due to competing effects of increasing particle hygroscopicity, a result of reductions in SI-SOA amount, surpassing that of particle size decreases. The bias-corrected model is robustly applicable to other schemes, such as the quadratic H2SO4 nucleation scheme, in terms of CN and CCN, though the dependence of CCN on SI-SOA yield is diminished likely due to changes in particle composition. This study highlights potentially much larger NPF contributions to CCN on a regional and even global basis.

 

Abstract. In the summer of 2017, heavy ozone pollution swamped most of the North ChinaPlain (NCP), with the maximum regional average of daily maximum 8 h ozoneconcentration (MDA8) reaching almost 120 ppbv. In light of the continuingreduction of anthropogenic emissions in China, the underlying mechanisms forthe occurrences of these regional extreme ozone episodes are elucidated fromtwo perspectives: meteorology and biogenic emissions. The significantpositive correlation between MDA8 ozone and temperature, which is amplifiedduring heat waves concomitant with stagnant air and no precipitation,supports the crucial role of meteorology in driving high ozoneconcentrations. We also find that biogenic emissions are enhanced due tofactors previously not considered. During the heavy ozone pollution episodesin June 2017, biogenic emissions driven by high vapor pressure deficit(VPD), land cover change and urban landscape yield an extra mean MDA8 ozoneof 3.08, 2.79 and 4.74 ppbv, respectively, over the NCP, which togethercontribute as much to MDA8 ozone as biogenic emissions simulated using theland cover of 2003 and ignoring VPD and urban landscape. In Beijing, thebiogenic emission increase due to urban landscape has a comparable effect onMDA8 ozone to the combined effect of high VPD and land cover change between2003 and 2016. In light of the large effect of urban landscape on biogenicemission and the subsequent ozone formation, the types of trees may becautiously selected to take into account of the biogenic volatile organic compound (BVOC) emission during the afforestation of cities. This study highlights the vital contributions ofheat waves, land cover change and urbanization to the occurrence of extremeozone episodes, with significant implications for ozone pollution control ina future when heat wave frequency and intensity are projected to increaseunder global warming. 

Abstract. pH is an important property of aerosol particles but is difficult to measure directly. Several studies have estimated the pH values for fine particles in northern China winter haze using thermodynamic models (i.e., E-AIM and ISORROPIA) and ambient measurements. The reported pH values differ widely, ranging from close to 0 (highly acidic) to as high as 7 (neutral). In order to understand the reason for this discrepancy, we calculated pH values using these models with different assumptions with regard to model inputs and particle phase states. We find that the large discrepancy is due primarily to differences in the model assumptions adopted in previous studies. Calculations using only aerosol-phase composition as inputs (i.e., reverse mode) are sensitive to the measurement errors of ionic species, and inferred pH values exhibit a bimodal distribution, with peaks between −2 and 2 and between 7 and 10, depending on whether anions or cations are in excess. Calculations using total (gas plus aerosol phase) measurements as inputs (i.e., forward mode) are affected much less by these measurement errors. In future studies, the reverse mode should be avoided whereas the forward mode should be used. Forward-mode calculations in this and previous studies collectively indicate a moderately acidic condition (pH from about 4 to about 5) for fine particles in northern China winter haze, indicating further that ammonia plays an important role in determining this property. The assumed particle phase state, either stable (solid plus liquid) or metastable (only liquid), does not significantly impact pH predictions. The unrealistic pH values of about 7 in a few previous studies (using the standard ISORROPIA model and stable state assumption) resulted from coding errors in the model, which have been identified and fixed in this study.

 

To tackle the severe fine particle (PM_2.5) pollution in China, the government has implemented stringent control policies mainly on power plants, industry, and transportation since 2005, but estimates of the effectiveness of the policy and the temporal trends in health impacts are subject to large uncertainties. By adopting an integrated approach that combines chemical transport simulation, ambient/household exposure evaluation, and health-impact assessment, we find that the integrated population-weighted exposure to PM_2.5(IPWE) decreased by 47% (95% confidence interval, 37–55%) from 2005 [180 (146–219) μg/m³] to 2015 [96 (83–111) μg/m³]. Unexpectedly, 90% (86–93%) of such reduction is attributed to reduced household solid-fuel use, primarily resulting from rapid urbanization and improved incomes rather than specific control policies. The IPWE due to household fuels for both cooking and heating decreased, but the impact of cooking is significantly larger. The reduced household-related IPWE is estimated to avoid 0.40 (0.25–0.57) million premature deaths annually, accounting for 33% of the PM_2.5-induced mortality in 2015. The IPWE would be further reduced by 63% (57–68%) if the remaining household solid fuels were replaced by clean fuels, which would avoid an additional 0.51 (0.40–0.64) million premature deaths. Such a transition to clean fuels, especially for heating, requires technology innovation and policy support to overcome the barriers of high cost of distribution systems, as is recently being attempted in the Beijing–Tianjin–Hebei area. We suggest that household-fuel use be more highly prioritized in national control policies, considering its effects on PM_2.5exposures.

 

Understanding the formation processes of particles and cloud condensation nuclei (CCN) in pristine environments is a major challenge in assessing the anthropogenic impacts on climate change. Using a state‐of‐the‐art model that systematically simulates the new‐particle formation (NPF) from condensable vapors and multi‐scale transport of chemical species, we find that NPF contributes ∼90% of the particle number and ∼80% of the CCN at 0.5% supersaturation (CCN0.5%) in the pristine Amazon boundary layer during the wet season. The corresponding contributions are only ∼30% and ∼20% during the dry season because of prevalent biomass burning. In both seasons, ∼50% of the NPF‐induced particles and ∼85% of the NPF‐induced CCN0.5% in the boundary layer originate from the long‐range transport of new particles formed hundreds to thousands of kilometers away. Moreover, about 50%–65% of the NPF‐induced particles and 35%–50% of the NPF‐induced CCN0.5% originate from the downward transport of new particles formed aloft.

 

The frequent episodes of severe air pollution over China during recent years have posed serious health threats to densely populated eastern China. Although several studies investigated the linkage between enhanced severity and frequency of air pollution and the large‐scale weather patterns over China, the day‐to‐day covariability between them, as well as its local and remote mechanisms, has not been systematically documented. The wintertime synoptic covariability between PM_2.5and large‐scale meteorological fields is studied using surface observations of PM_2.5in 2013/2014–2016/2017 and ERA‐Interim meteorological fields through maximum covariance analysis (MCA). The first MCA mode (MCA1) suggests a consistent accumulation of ambient PM_2.5as a result of weakened winds that block the pollutant removal passage in heavily polluted areas of eastern China, as well as moist air from southeast coast favoring haze formation. A northeast–southwest belt that extends into northeastern China and central China on each end is more sensitive to MCA1. The second MCA mode (MCA2) shows a north–south dipole in PM_2.5linked to the contrast of boundary layer height and surface wind speed between northern and southern regions of China. Spatial patterns of both modes are supported by the GEOS‐Chem chemistry transport model with realistic emission inventory. The spatial patterns of the two modes are robust on the interannual time scales. Based on that, we investigate the variability of the first two modes of the identified modes on the multidecadal scale by projecting GPM_500 pattern to 1981–2010. Correlation analysis of the projected time series and climate indices over 30 years indicates the possible linkage of Arctic oscillation, ENSO indices, Pacific decadal oscillation and east Atlantic/western Russia to regional air pollution patterns over China.