Showing papers on "Haze published in 2020"

Unexpected air pollution with marked emission reductions during the COVID-19 outbreak in China.

Abstract: The absence of motor vehicle traffic and suspended manufacturing during the coronavirus disease 2019 (COVID-19) pandemic in China enabled assessment of the efficiency of air pollution mitigation. Up to 90% reduction of certain emissions during the city-lockdown period can be identified from satellite and ground-based observations. Unexpectedly, extreme particulate matter levels simultaneously occurred in northern China. Our synergistic observation analyses and model simulations show that anomalously high humidity promoted aerosol heterogeneous chemistry, along with stagnant airflow and uninterrupted emissions from power plants and petrochemical facilities, contributing to severe haze formation. Also, because of nonlinear production chemistry and titration of ozone in winter, reduced nitrogen oxides resulted in ozone enhancement in urban areas, further increasing the atmospheric oxidizing capacity and facilitating secondary aerosol formation.

Amplified transboundary transport of haze by aerosol-boundary layer interaction in China

Abstract: Although air quality in China has substantially improved since 2013 as a consequence of the clean air action, severe haze events still frequently strike megacities despite strict local emissions reduction efforts. Long-range transport and local accumulation as well as chemical transformation have been deemed as key factors of heavy haze pollution; however, the formation mechanisms of regional long-lasting haze and the physical and chemical connections between different megacities clusters are still poorly understood. Here we present that long-range transport and aerosol–boundary layer feedback may interact rather than act as two isolated processes as traditionally thought by investigating typical regional haze events in northern and eastern China. This interaction can then amplify transboundary air pollution transport over a distance of 1,000 km and boost long-lasting secondary haze from the North China Plain to the Yangtze River delta. Earlier emission reduction before the pollution episodes would provide better air pollution mitigation in both regions. Our results show an amplified transboundary transport of haze by aerosol–boundary layer interaction in China and suggest the importance of coordinated cross-regional emission reduction with a focus on radiatively active species like black carbon. Secondary air pollution events are enhanced in the Yangtze River delta, China, due to the interaction of long-range transport and aerosol–boundary layer feedback, according to a combination of observations and simulations of haze events from 2013 to 2018.

Puzzling haze events in China during the coronavirus (COVID-19) shutdown.

Abstract: It is a puzzle as to why more severe haze formed during the New Year Holiday in 2020 (NYH-20), when China was in an unprecedented state of shutdown to contain the coronavirus (COVID-19) outbreak, than in 2019 (NYH-19). We performed a comprehensive measurement and modeling analysis of the aerosol chemistry and physics at multiple sites in China (mainly in Shanghai) before, during, and after NYH-19 and NYH-20. Much higher secondary aerosol fraction in PM2.5 were observed during NYH-20 (73%) than during NYH-19 (59%). During NYH-20, PM2.5 levels correlated significantly with the oxidation ratio of nitrogen (r 2 = 0.77, p < 0.01), and aged particles from northern China were found to impede atmospheric new particle formation and growth in Shanghai. A markedly enhanced efficiency of nitrate aerosol formation was observed along the transport pathways during NYH-20, despite the overall low atmospheric NO2 levels.

Fast sulfate formation from oxidation of SO 2 by NO 2 and HONO observed in Beijing haze

Abstract: Severe events of wintertime particulate air pollution in Beijing (winter haze) are associated with high relative humidity (RH) and fast production of particulate sulfate from the oxidation of sulfur dioxide (SO2) emitted by coal combustion. There has been considerable debate regarding the mechanism for SO2 oxidation. Here we show evidence from field observations of a haze event that rapid oxidation of SO2 by nitrogen dioxide (NO2) and nitrous acid (HONO) takes place, the latter producing nitrous oxide (N2O). Sulfate shifts to larger particle sizes during the event, indicative of fog/cloud processing. Fog and cloud readily form under winter haze conditions, leading to high liquid water contents with high pH (>5.5) from elevated ammonia. Such conditions enable fast aqueous-phase oxidation of SO2 by NO2, producing HONO which can in turn oxidize SO2 to yield N2O.This mechanism could provide an explanation for sulfate formation under some winter haze conditions.

An unexpected catalyst dominates formation and radiative forcing of regional haze

Abstract: Although regional haze adversely affects human health and possibly counteracts global warming from increasing levels of greenhouse gases, the formation and radiative forcing of regional haze on climate remain uncertain. By combining field measurements, laboratory experiments, and model simulations, we show a remarkable role of black carbon (BC) particles in driving the formation and trend of regional haze. Our analysis of long-term measurements in China indicates declined frequency of heavy haze events along with significantly reduced SO2, but negligibly alleviated haze severity. Also, no improving trend exists for moderate haze events. Our complementary laboratory experiments demonstrate that SO2 oxidation is efficiently catalyzed on BC particles in the presence of NO2 and NH3, even at low SO2 and intermediate relative humidity levels. Inclusion of the BC reaction accounts for about 90-100% and 30-50% of the sulfate production during moderate and heavy haze events, respectively. Calculations using a radiative transfer model and accounting for the sulfate formation on BC yield an invariant radiative forcing of nearly zero W m-2 on the top of the atmosphere throughout haze development, indicating small net climatic cooling/warming but large surface cooling, atmospheric heating, and air stagnation. This BC catalytic chemistry facilitates haze development and explains the observed trends of regional haze in China. Our results imply that reduction of SO2 alone is insufficient in mitigating haze occurrence and highlight the necessity of accurate representation of the BC chemical and radiative properties in predicting the formation and assessing the impacts of regional haze.

Fast oxidation of sulfur dioxide by hydrogen peroxide in deliquesced aerosol particles.

Abstract: Atmospheric sulfate aerosols have important impacts on air quality, climate, and human and ecosystem health. However, current air-quality models generally underestimate the rate of conversion of sulfur dioxide (SO2) to sulfate during severe haze pollution events, indicating that our understanding of sulfate formation chemistry is incomplete. This may arise because the air-quality models rely upon kinetics studies of SO2 oxidation conducted in dilute aqueous solutions, and not at the high solute strengths of atmospheric aerosol particles. Here, we utilize an aerosol flow reactor to perform direct investigation on the kinetics of aqueous oxidation of dissolved SO2 by hydrogen peroxide (H2O2) using pH-buffered, submicrometer, deliquesced aerosol particles at relative humidity of 73 to 90%. We find that the high solute strength of the aerosol particles significantly enhances the sulfate formation rate for the H2O2 oxidation pathway compared to the dilute solution. By taking these effects into account, our results indicate that the oxidation of SO2 by H2O2 in the liquid water present in atmospheric aerosol particles can contribute to the missing sulfate source during severe haze episodes.

NH-HAZE: An image dehazing benchmark with non-homogeneous hazy and haze-free images

Abstract: Image dehazing is an ill-posed problem that has been extensively studied in the recent years. The objective performance evaluation of the dehazing methods is one of the major obstacles due to the lacking of a reference dataset. While the synthetic datasets have shown important limitations, the few realistic datasets introduced recently assume homogeneous haze over the entire scene. Since in many real cases haze is not uniformly distributed we introduce NH-HAZE, a non-homogeneous realistic dataset with pairs of real hazy and corresponding haze-free images. This is the first nonhomogeneous image dehazing dataset and contains 55 outdoor scenes. The non-homogeneous haze has been introduced in the scene using a professional haze generator that imitates the real conditions of hazy scenes. Additionally, this work presents an objective assessment of several state- of-the-art single image dehazing methods that were evaluated using NH-HAZE dataset.

Multi-Scale Deep Residual Learning-Based Single Image Haze Removal via Image Decomposition

Abstract: Images/videos captured from outdoor visual devices are usually degraded by turbid media, such as haze, smoke, fog, rain, and snow. Haze is the most common one in outdoor scenes due to the atmosphere conditions. In this paper, a novel deep learning-based architecture (denoted by MSRL-DehazeNet) for single image haze removal relying on multi-scale residual learning (MSRL) and image decomposition is proposed. Instead of learning an end-to-end mapping between each pair of hazy image and its corresponding haze-free one adopted by most existing learning-based approaches, we reformulate the problem as restoration of the image base component. Based on the decomposition of a hazy image into the base and the detail components, haze removal (or dehazing) can be achieved by both of our multi-scale deep residual learning and our simplified U-Net learning only for mapping between hazy and haze-free base components, while the detail component is further enhanced via the other learned convolutional neural network (CNN). Moreover, benefited by the basic building block of our deep residual CNN architecture and our simplified U-Net structure, the feature maps (produced by extracting structural and statistical features), and each previous layer can be fully preserved and fed into the next layer. Therefore, possible color distortion in the recovered image would be avoided. As a result, the final haze-removed (or dehazed) image is obtained by integrating the haze-removed base and the enhanced detail image components. Experimental results have demonstrated good effectiveness of the proposed framework, compared with state-of-the-art approaches.

Mutual promotion between aerosol particle liquid water and particulate nitrate enhancement leads to severe nitrate-dominated particulate matter pollution and low visibility

Abstract: . As has been the case in North America and western Europe, the SO2 emissions have substantially reduced in the North China Plain (NCP) in recent years. Differential rates of reduction in SO2 and NOx concentrations result in the frequent occurrence of particulate matter pollution dominated by nitrate ( p NO 3 - ) over the NCP. In this study, we observed a polluted episode with the particulate nitrate mass fraction in nonrefractory PM 1 (NR-PM 1 ) being up to 44 % during wintertime in Beijing. Based on this typical p NO 3 - -dominated haze event, the linkage between aerosol water uptake and p NO 3 - enhancement, further impacting on visibility degradation, has been investigated based on field observations and theoretical calculations. During haze development, as ambient relative humidity (RH) increased from ∼10 % to 70 %, the aerosol particle liquid water increased from ∼1 µg m−3 at the beginning to ∼75 µg m−3 in the fully developed haze period. The aerosol liquid water further increased the aerosol surface area and volume, enhancing the condensational loss of N2O5 over particles. From the beginning to the fully developed haze, the condensational loss of N2O5 increased by a factor of 20 when only considering aerosol surface area and volume of dry particles, while increasing by a factor of 25 when considering extra surface area and volume due to water uptake. Furthermore, aerosol liquid water favored the thermodynamic equilibrium of HNO3 in the particle phase under the supersaturated HNO3 and NH3 in the atmosphere. All the above results demonstrated that p NO 3 - is enhanced by aerosol water uptake with elevated ambient RH during haze development, in turn facilitating the aerosol take-up of water due to the hygroscopicity of particulate nitrate salt. Such mutual promotion between aerosol particle liquid water and particulate nitrate enhancement can rapidly degrade air quality and halve visibility within 1 d. Reduction of nitrogen-containing gaseous precursors, e.g., by control of traffic emissions, is essential in mitigating severe haze events in the NCP.

Source-Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown.

Abstract: The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles but coincided with Beijing experiencing "pandemic haze," raising the public concerns about the effectiveness of imposed traffic policies to improve the air quality. This paper explores the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown based on an integrated analysis framework, which combines a real-time on-road emission inventory, in situ air quality observations, and a localized numerical modeling system. We found that traffic emissions decreased substantially during the COVID-19 pandemic, but its imbalanced emission abatement of NOx (76%, 125.3 Mg/day) and volatile organic compounds (VOCs, 53%, 52.9 Mg/day) led to a significant rise of atmospheric oxidants in urban areas, resulting in a modest increase in secondary aerosols due to inadequate precursors, which still offset reduced primary emissions. Moreover, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which was transported into Beijing and mainly responsible for the aggravated haze pollution. We recommend that mitigation policies should focus on accelerating VOC emission reduction and synchronously controlling regional sources to release the benefits of local traffic emission control.

PM2.5 diminution and haze events over Delhi during the COVID-19 lockdown period: an interplay between the baseline pollution and meteorology.

Abstract: Delhi, a tropical Indian megacity, experiences one of the most severe air pollution in the world, linked with diverse anthropogenic and biomass burning emissions. First phase of COVID-19 lockdown in India, implemented during 25 March to 14 April 2020 resulted in a dramatic near-zeroing of various activities (e.g. traffic, industries, constructions), except the “essential services”. Here, we analysed variations in the fine particulate matter (PM2.5) over the Delhi-National Capital Region. Measurements revealed large reductions (by 40–70%) in PM2.5 during the first week of lockdown (25–31 March 2020) as compared to the pre-lockdown conditions. However, O3 pollution remained high during the lockdown due to non-linear chemistry and dynamics under low aerosol loading. Notably, events of enhanced PM2.5 levels (300–400 µg m−3) were observed during night and early morning hours in the first week of April after air temperatures fell close to the dew-point (~ 15–17 °C). A haze formation mechanism is suggested through uplifting of fine particles, which is reinforced by condensation of moisture following the sunrise. The study highlights a highly complex interplay between the baseline pollution and meteorology leading to counter intuitive enhancements in pollution, besides an overall improvement in air quality during the COVID-19 lockdown in this part of the world.

NH-HAZE: An Image Dehazing Benchmark with Non-Homogeneous Hazy and Haze-Free Images

Abstract: Image dehazing is an ill-posed problem that has been extensively studied in the recent years. The objective performance evaluation of the dehazing methods is one of the major obstacles due to the lacking of a reference dataset. While the synthetic datasets have shown important limitations, the few realistic datasets introduced recently assume homogeneous haze over the entire scene. Since in many real cases haze is not uniformly distributed we introduce NH-HAZE, a non-homogeneous realistic dataset with pairs of real hazy and corresponding haze-free images. This is the first non-homogeneous image dehazing dataset and contains 55 outdoor scenes. The non-homogeneous haze has been introduced in the scene using a professional haze generator that imitates the real conditions of hazy scenes. Additionally, this work presents an objective assessment of several state-of-the-art single image dehazing methods that were evaluated using NH-HAZE dataset.

Air pollution scenario over China during COVID-19

Abstract: The unprecedented slowdown in China during the COVID-19 period of November 2019 to April 2020 should have reduced pollution in smog-laden cities. However, moderate resolution imaging spectrometer (MODIS) satellite retrievals of aerosol optical depth (AOD) show a marked increase in aerosols over the Beijing–Tianjin–Hebei (BHT) region and most of Northeast and Central China, compared with the previous winter. Fine particulate (PM2.5) data from ground monitoring stations show an increase of 19.5% in Beijing during January and February 2020, and no reduction for Tianjin. In March and April 2020, a different spatial pattern emerges, with very high AOD levels observed over 50% of the Chinese mainland, and including peripheral regions in the northwest and southwest. At the same time, ozone monitoring instrument (OMI) satellite-derived NO2 concentrations fell drastically across China. The increase in PM2.5 while NO2 decreased in BTH and across China is likely due to enhanced production of secondary particulates. These are formed when reductions in NOx result in increased ozone formation, thus increasing the oxidizing capacity of the atmosphere. Support for this explanation is provided by ground level air quality data showing increased volume of fine mode aerosols throughout February and March 2020, and increased levels of PM2.5, relative humidity (RH), and ozone during haze episodes in the COVID-19 lockdown period. Backward trajectories show the origin of air masses affecting industrial centers of North and East China to be local. Other contributors to increased atmospheric particulates may include inflated industrial production in peripheral regions to compensate loss in the main population and industrial centers, and low wind speeds. Satellite monitoring of the extraordinary atmospheric conditions resulting from the COVID-19 shutdown could enhance understanding of smog formation and attempts to control it.

Trident Dehazing Network

Abstract: Most existing dehazing methods are not robust to nonhomogeneous haze. Meanwhile, the information of dense haze region is usually unknown and hard to estimate, leading to blurry in dehaze result for those regions. Focusing on these two issues, we propose a novel coarse-to-fine model, namely Trident Dehazing Network (TDN), to learn the hazy to hazy- free image mapping with automatic haze density recognition. In detail, TDN is composed of three sub-nets: the Encoder-Decoder Net (EDN) is the main net of TDN to reconstruct the coarse hazy-free feature; the Detail Refinement sub-Net (DRN) helps to refine the high frequency details that was easily lost in the pooling layers in the encoder; and the Haze Density Map Generation sub-Net (HDMGN) can automatically distinguish the thick haze region with thin one, to prevent over-dehazing or under-dehazing in regions of different haze density. Moreover, we propose a frequency domain loss function to make supervision of different frequency band more uniform. Extensive experimental results on synthetic and real datasets demonstrate that our proposed TDN outperforms the state-of-the-arts with better fidelity and perceptual, generalizing well on both dense haze and nonhomogeneous haze scene. Our method won the first place in NTIRE2020 nonhomogeneous dehazing challenge.

NTIRE 2020 challenge on nonhomogeneous dehazing

Abstract: This paper reviews the NTIRE 2020 Challenge on Non-Homogeneous Dehazing of images (restoration of rich details in hazy image). We focus on the proposed solutions and their results evaluated on NH-Haze, a novel dataset consisting of 55 pairs of real haze free and nonhomogeneous hazy images recorded outdoor. NH-Haze is the first realistic nonhomogeneous haze dataset that provides ground truth images. The nonhomogeneous haze has been produced using a professional haze generator that imitates the real conditions of haze scenes. 168 participants registered in the challenge and 27 teams competed in the final testing phase. The proposed solutions gauge the state-of-the-art in image dehazing.

Elevated levels of OH observed in haze events during wintertime in central Beijing

Abstract: Wintertime in situ measurements of OH, HO2 and RO2 radicals and OH reactivity were made in central Beijing during November and December 2016. Exceptionally elevated NO was observed on occasions, up to ∼250 ppbv. The daily maximum mixing ratios for radical species varied significantly day-to-day over the ranges 1–8×106 cm−3 (OH), 0.2–1.5×108 cm−3 (HO2) and 0.3–2.5×108 cm−3 (RO2). Averaged over the full observation period, the mean daytime peak in radicals was 2.7×106, 0.39×108 and 0.88×108 cm−3 for OH, HO2 and total RO2, respectively. The main daytime source of new radicals via initiation processes (primary production) was the photolysis of HONO (∼83 %), and the dominant termination pathways were the reactions of OH with NO and NO2, particularly under polluted haze conditions. The Master Chemical Mechanism (MCM) v3.3.1 operating within a box model was used to simulate the concentrations of OH, HO2 and RO2. The model underpredicted OH, HO2 and RO2, especially when NO mixing ratios were high (above 6 ppbv). The observation-to-model ratio of OH, HO2 and RO2 increased from ∼1 (for all radicals) at 3 ppbv of NO to a factor of ∼3, ∼20 and ∼91 for OH, HO2 and RO2, respectively, at ∼200 ppbv of NO. The significant underprediction of radical concentrations by the MCM suggests a deficiency in the representation of gas-phase chemistry at high NOx. The OH concentrations were surprisingly similar (within 20 % during the day) in and outside of haze events, despite j(O1D) decreasing by 50 % during haze periods. These observations provide strong evidence that gas-phase oxidation by OH can continue to generate secondary pollutants even under high-pollution episodes, despite the reduction in photolysis rates within haze.

Atmospheric Photosensitization: A New Pathway for Sulfate Formation

Abstract: Northern China is regularly subjected to intense wintertime "haze events", with high levels of fine particles that threaten millions of inhabitants. While sulfate is a known major component of these fine haze particles, its formation mechanism remains unclear especially under highly polluted conditions, with state-of-the-art air quality models unable to reproduce or predict field observations. These haze conditions are generally characterized by simultaneous high emissions of SO2 and photosensitizing materials. In this study, we find that the excited triplet states of photosensitizers could induce a direct photosensitized oxidation of hydrated SO2 and bisulfite into sulfate S(VI) through energy transfer, electron transfer, or hydrogen atom abstraction. This photosensitized pathway appears to be a new and ubiquitous chemical route for atmospheric sulfate production. Compared to other aqueous-phase sulfate formation pathways with ozone, hydrogen peroxide, nitrogen dioxide, or transition-metal ions, the results also show that this photosensitized oxidation of S(IV) could make an important contribution to aerosol sulfate formation in Asian countries, particularly in China.

Aerosol–photolysis interaction reduces particulate matter during wintertime haze events

Abstract: Aerosol-radiation interaction (ARI) plays a significant role in the accumulation of fine particulate matter (PM2.5) by stabilizing the planetary boundary layer and thus deteriorating air quality during haze events. However, modification of photolysis by aerosol scattering or absorbing solar radiation (aerosol-photolysis interaction or API) alters the atmospheric oxidizing capacity, decreases the rate of secondary aerosol formation, and ultimately alleviates the ARI effect on PM2.5 pollution. Therefore, the synergetic effect of both ARI and API can either aggravate or even mitigate PM2.5 pollution. To test the effect, a fully coupled Weather Research and Forecasting (WRF)-Chem model has been used to simulate a heavy haze episode in North China Plain. Our results show that ARI contributes to a 7.8% increase in near-surface PM2.5 However, API suppresses secondary aerosol formation, and the combination of ARI and API results in only 4.8% net increase of PM2.5 Additionally, API increases the solar radiation reaching the surface and perturbs aerosol nucleation and activation to form cloud condensation nuclei, influencing aerosol-cloud interaction. The results suggest that API reduces PM2.5 pollution during haze events, but adds uncertainties in climate prediction.

A new haze removal approach for sky/river alike scenes based on external and internal clues

Abstract: Sky/river alike areas are important parts of natural scenes. The haze of these areas will impact the vividness of natural scenes. More serious, once the haze occurs in navigation of flight and ship, it will threaten the safety. However, previous researches did not dehaze well for these areas. In this paper, a new haze removal approach is presented to improve the dehazing effect for the sky/river alike areas based on our new discovers. Inspired by the two discovers, we define two theoretical clues: the external boundary clue and the internal clue. And then a correction model is constructed to correct the dark channel values in the sky/river alike areas. Finally, an optimization solution is presented to solve this model. Both the visual experiment and the quantitative experiment show that proposed method outperforms the classical dark channel method and the deep learning method in sky/river alike areas.

Exploring wintertime regional haze in northeast China: role of coal and biomass burning

Abstract: . As one of the intense anthropogenic emission regions across the relatively high-latitude ( >40 ∘ N) areas on Earth, northeast China faces the serious problem of regional haze during the heating period of the year. Aerosols in polluted haze in northeast China are poorly understood compared with the haze in other regions of China such as the North China Plain. Here, we integrated bulk chemical measurements with single-particle analysis from transmission electron microscopy (TEM), nanoscale secondary ion mass spectrometry (NanoSIMS), and atomic force microscopy (AFM) to obtain morphology, size, composition, aging process, and sources of aerosol particles collected during two contrasting regional haze events (Haze-I and Haze-II) at an urban site and a mountain site in northeast China and further investigated the causes of regional haze formation. Haze-I evolved from moderate (average PM2.5 : 76–108 µ g m −3 ) to heavy pollution (151–154 µ g m −3 ), with the dominant PM2.5 component changing from organic matter (OM) (39–45 µ g m −3 ) to secondary inorganic ions (94–101 µ g m −3 ). Similarly, TEM observations showed that S-rich particles internally mixed with OM (named S-OM) increased from 29 % to 60 % by number at an urban site and 64 % to 74 % at a mountain site from the moderate Haze-I to heavy Haze-I events, and 75 %–96 % of Haze-I particles included primary OM. We found that change of wind direction caused Haze-I to rapidly turn into Haze-II (185–223 µ g m −3 ) with predominantly OM (98–133 µ g m −3 ) and unexpectedly high K+ (3.8 µ g m −3 ). TEM also showed that K-rich particles internally mixed with OM (named K-OM) increased from 4 %–5 % by number to 50 %–52 %. The results indicate that there were different sources of aerosol particles causing the Haze-I and Haze-II formation: Haze-I was mainly induced by accumulation of primary OM emitted from residential coal burning and further deteriorated by secondary aerosol formation via heterogeneous reactions; Haze-II was caused by long-range transport of agricultural biomass burning emissions. Moreover, abundant primary OM particles emitted from coal and biomass burning were considered to be one typical brown carbon, i.e., tar balls. Our study highlights that large numbers of light-absorbing tar balls significantly contribute to winter haze formation in northeast China and they should be further considered in climate models.

Stable Sulfur Isotopes Revealed a Major Role of Transition-Metal Ion-Catalyzed SO2 Oxidation in Haze Episodes

Abstract: Secondary sulfate aerosols played an important role in aerosol formation and aging processes, especially during haze episodes in China. Secondary sulfate was formed via atmospheric oxidation of SO2 by OH, O3, H2O2, and transition-metal-catalyzed (TMI) O2. However, the relative importance of these oxidants in haze episodes was strongly debated. Here, we use stable sulfur isotopes (δ34S) of sulfate aerosols and a Rayleigh distillation model to quantify the contributions of each oxidant during a haze episode in Nanjing, a megacity in China. The observed δ34S values of sulfate aerosols showed a negative correlation with sulfur oxidation ratios, which was attributed to the sulfur isotopic fractionations during the sulfate formation processes. Using the average fractionation factor calculated from our observations and zero-dimensional (0-D) atmospheric chemistry modeling estimations, we suggest that OH oxidation was trivial during the haze episode, while the TMI pathway contributed 49 ± 10% of the total sulfate production and O3/H2O2 oxidations accounted for the rest. Our results displayed good agreement with several atmospheric chemistry models that carry aqueous and heterogeneous TMI oxidation pathways, suggesting the role of the TMI pathway was significant during haze episodes.

Variation of size-segregated particle number concentrations in wintertime Beijing

Abstract: . The spatial and temporal variability of the number size distribution of aerosol particles is an indicator of the dynamic behavior of Beijing's atmospheric pollution cocktail. This variation reflects the strength of different primary and secondary sources, such as traffic and new particle formation, as well as the main processes affecting the particle population. In this paper, we report size-segregated particle number concentrations observed at a newly developed Beijing station during the winter of 2018. Our measurements covered particle number size distributions over the diameter range of 1.5 nm–1 µ m (cluster mode, nucleation mode, Aitken mode and accumulation mode), thus being descriptive of a major fraction of the processes taking place in the atmosphere of Beijing. Here we focus on explaining the concentration variations in the observed particle modes, by relating them to the potential aerosol sources and sinks, and on understanding the connections between these modes. We considered haze days and new particle formation event days separately. Our results show that during the new particle formation (NPF) event days increases in cluster mode particle number concentration were observed, whereas during the haze days high concentrations of accumulation mode particles were present. There was a tight connection between the cluster mode and nucleation mode on both NPF event and haze days. In addition, we correlated the particle number concentrations in different modes with concentrations of trace gases and other parameters measured at our station. Our results show that the particle number concentration in all the modes correlated with NOx , which reflects the contribution of traffic to the whole submicron size range. We also estimated the contribution of ion-induced nucleation in Beijing, and we found this contribution to be negligible.

China's emission control strategies have suppressed unfavorable influences of climate on wintertime PM 2.5 concentrations in Beijing since 2002

Abstract: . Severe wintertime PM 2.5 pollution in Beijing has been receiving increasing worldwide attention, yet the decadal variations remain relatively unexplored. Combining field measurements and model simulations, we quantified the relative influences of anthropogenic emissions and meteorological conditions on PM 2.5 concentrations in Beijing over the winters of 2002–2016. Between the winters of 2011 and 2016, stringent emission control measures resulted in a 21 % decrease in mean mass concentrations of PM 2.5 in Beijing, with 7 fewer haze days per winter on average. Given the overestimation of PM 2.5 by the model, the effectiveness of stringent emission control measures might have been slightly overstated. With fixed emissions, meteorological conditions over the study period would have led to an increase in haze in Beijing, but the strict emission control measures have suppressed the unfavorable influences of the recent climate. The unfavorable meteorological conditions are attributed to the weakening of the East Asia winter monsoon associated particularly with an increase in pressure associated with the Aleutian Low.