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This article presents the results of the Asia Pacific Metrology Programme (APMP) pilot comparison on high transmittance haze (TH), specifically TH >40 %. Various methods, including ASTM D1003, ISO 14782, the double beam method, and the double compensation method were employed. The results revealed that ASTM D1003 is still influenced by failure to compensate for sphere throughput, even in high TH artefacts. In contrast, the other methods exhibit good consistency, as expected. This article also analyses the total transmittance (TT) and diffuse transmittance (DT) obtained using the double compensation method, theoretically capable of determining accurate TT, DT, and TH, discussing the possibility of inconsistency in the reflectance between the sphere wall and the white plate affecting the agreement.

Sulfate aerosols exert profound impacts on human and ecosystem health, weather, and climate, but their formation mechanism remains uncertain. Atmospheric models consistently underpredict sulfate levels under diverse environmental conditions. From atmospheric measurements in two Chinese megacities and complementary laboratory experiments, we show that the aqueous oxidation of SO₂ by NO₂ is key to efficient sulfate formation but is only feasible under two atmospheric conditions: on fine aerosols with high relative humidity and NH₃ neutralization or under cloud conditions. Under polluted environments, this SO₂ oxidation process leads to large sulfate production rates and promotes formation of nitrate and organic matter on aqueous particles, exacerbating severe haze development. Effective haze mitigation is achievable by intervening in the sulfate formation process with enforced NH₃ and NO₂ control measures. In addition to explaining the polluted episodes currently occurring in China and during the 1952 London Fog, this sulfate production mechanism is widespread, and our results suggest a way to tackle this growing problem in China and much of the developing world.

Regional severe haze represents an enormous environmental problem in China, influencing air quality, human health, ecosystem, weather, and climate. These extremes are characterized by exceedingly high concentrations of fine particulate matter (smaller than 2.5 μm, or PM2.5) and occur with extensive temporal (on a daily, weekly, to monthly timescale) and spatial (over a million square kilometers) coverage. Although significant advances have been made in field measurements, model simulations, and laboratory experiments for fine PM over recent years, the causes for severe haze formation have not yet to be systematically/comprehensively evaluated. This review provides a synthetic synopsis of recent advances in understanding the fundamental mechanisms of severe haze formation in northern China, focusing on emission sources, chemical formation and transformation, and meteorological and climatic conditions. In particular, we highlight the synergetic effects from the interactions between anthropogenic emissions and atmospheric processes. Current challenges and future research directions to improve the understanding of severe haze pollution as well as plausible regulatory implications on a scientific basis are also discussed.

Haze clouds often form over the North China Plain (NCP) of eastern China, where large amounts of aerosol particles and their precursors are emitted. To obtain general insights into regional pollution, a large‐scale, long‐term study was conducted using A‐Train satellite observations, ground measurements, and meteorological data. Contrary to previous analyses, most of the haze clouds appeared to form abruptly (within 2–3 h). Case studies show that natural sources contribute significantly to the formation of regional haze. Dust plumes can mix with local pollutants, causing smog clouds to form abruptly, while moist airflows can cause widespread haze‐fog pollution. The combined observations revealed highly inhomogeneous haze clouds, in terms of both vertical and horizontal distribution, leading to clear discrepancies between site measurements near the surface and satellite observations at the top of the atmosphere. Surprisingly, prevailing dust plumes, which are closely connected with the haze clouds, were observed in winter. Airborne dust and water vapor transported from outside the region are the main drivers of regional haze over the NCP. Accumulation of local pollutants also leads to common occurrences of urban smog; however, the occurrence of most haze clouds shows no obvious correlation with local pollution. Local‐ and regional‐scale haze pollution are common over the NCP, but they have differing formation mechanisms, and contrasting chemical and physical properties. The present findings improve our understanding of heavy pollution over eastern China and its links to climate. Key Points Large‐scale and long‐term observation of haze clouds over eastern China Natural sources play a significant role in haze clouds over eastern China Local and regional haze are different in formation and their properties

Surface ozone is a severe air pollution problem in the North China Plain, which is home to 300 million people. Ozone concentrations are highest in summer, driven by fast photochemical production of hydrogen oxide radicals (HOₓ) that can overcome the radical titration caused by high emissions of nitrogen oxides (NOₓ) from fuel combustion. Ozone has been very low during winter haze (particulate) pollution episodes. However, the abrupt decrease of NOₓ emissions following the COVID-19 lockdown in January 2020 reveals a switch to fast ozone production during winter haze episodes with maximum daily 8-h average (MDA8) ozone concentrations of 60 to 70 parts per billion. We reproduce this switch with the GEOS-Chem model, where the fast production of ozone is driven by HOₓ radicals from photolysis of formaldehyde, overcoming radical titration from the decreased NOₓ emissions. Formaldehyde is produced by oxidation of reactive volatile organic compounds (VOCs), which have very high emissions in the North China Plain. This remarkable switch to an ozone-producing regime in January–February following the lockdown illustrates a more general tendency from 2013 to 2019 of increasing winter–spring ozone in the North China Plain and increasing association of high ozone with winter haze events, as pollution control efforts have targeted NOₓ emissions (30% decrease) while VOC emissions have remained constant. Decreasing VOC emissions would avoid further spreading of severe ozone pollution events into the winter–spring season.

Our analysis of fog and haze observations from the surface weather stations in China in recent 50 years （from 196l to 2011） shows that the number of fog days has experienced two-stage variations, with an increasing trend before 1980 and a decreasing trend after 1990. Especially, an obvious decreasing trend after 1990 can be clearly seen, which is consistent with the decreas- ing trend of the surface relative humidity. However, the number of haze days has demonstrated an increasing trend. As such, the role of reduction of atmospheric relative humidity in the transition process from fog into haze has been further investigated. It is estimated that the mean relative humidity of haze days is about 69%, lower than previously estimated, which implies that it is more difficult for the haze particles to transform into fog drops. This is possibly one of the major environmental factors leading to the reduction of number of fog days. The threshold of the relative humidity for transition from fog into haze is about 82%, also lower than previously estimated. Thus, the reduction of the surface relative humidity in China mainly due to the in- crease of the surface temperature and the saturation specific humidity may exert an obvious impact on the environmental con- ditions for the formations of fog and haze. In addition, our investigation of the relationship between haze and visibility reveals that with the increase of haze days, the visibility has declined markedly. Since 1961, the mean visibility has dropped from 4-10 to 2-4 kin, about a half of the previous horizontal distance of visibility.

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.

Recent in situ observations show that haze particles exist in a convection cloud chamber. The microphysics schemes previously used for large‐eddy simulations of the cloud chamber could not fully resolve haze particles and the associated processes, including their activation and deactivation. Specifically, cloud droplet activation was modeled based on Twomey‐type parameterizations, wherein cloud droplets were formed when a critical supersaturation for the available cloud condensation nuclei (CCN) was exceeded and haze particles were not explicitly resolved. Here, we develop and adapt haze‐capable bin and Lagrangian microphysics schemes to properly resolve the activation and deactivation processes. Results are compared with the Twomey‐type CCN‐based bin microphysics scheme in which haze particles are not fully resolved. We find that results from the haze‐capable bin microphysics scheme agree well with those from the Lagrangian microphysics scheme. However, both schemes significantly differ from those from a CCN‐based bin microphysics scheme unless CCN recycling is considered. Haze particles from the recycling of deactivated cloud droplets can strongly enhance cloud droplet number concentration due to a positive feedback in haze‐cloud interactions in the cloud chamber. Haze particle size distributions are more realistic when considering solute and curvature effects that enable representing the complete physics of the activation process. Our study suggests that haze particles and their interactions with cloud droplets may have a strong impact on cloud properties when supersaturation fluctuations are comparable to mean supersaturation, as is the case in the cloud chamber and likely is the case in the atmosphere, especially in polluted conditions. Plain Language Summary In atmospheric models, cloud droplet formation is usually simulated to occur when a submicron dry aerosol particle encounters supersaturated conditions. In reality, dry aerosol particles composed of water‐soluble compounds form aqueous haze particles first before they activate to cloud droplets. However, haze particles and the associated interactions with cloud droplets are usually not fully resolved in atmospheric models. In this study, we develop two types of microphysics schemes to explore haze‐cloud interactions in a convection cloud chamber. Our results show that recycling of deactivated cloud droplets through either dry aerosol or haze particles can significantly enhance the cloud droplet number concentration in the cloud chamber. Our study indicates that it is important to properly resolve haze particles and haze‐cloud interactions for cloud chamber simulations, which is likely also true for atmospheric cloud simulations, especially under polluted conditions. Key Points Bin and Lagrangian microphysics schemes with various levels of complexity are used to handle aerosol‐cloud interactions in a cloud chamber Simulations using haze‐capable bin and Lagrangian schemes capture the observed haze mode in the chamber Activation and deactivation rates are overestimated when using a CCN‐based bin scheme compared with haze‐capable schemes

A comprehensive in-situ dataset of low-level Arctic clouds was collected in the Fram Strait during the HALO-(AC)3 campaign in spring 2022 using the research aircraft Polar 6. The clouds observed at altitudes below 1000 m were frequently in a mixed-phase state. We demonstrate that despite comparable optical properties, classic mixed-phase clouds (MPC) and mixed-phase haze (MPH) can be distinguished on the basis of their microphysical properties, with MPH observed about 8 times more frequently than MPC. While the thermodynamic phases of the particles within the MPH are similar to those in the MPC, the supercooled droplets observed in MPC are replaced by large (> 3 µm) wet aerosol particles in MPH. Furthermore, the particle number concentration measured in MPH is reduced by approximately 3 orders of magnitude compared to MPC. MPH is observed in subsaturated air with respect to water, suggesting that the small liquid particles are haze droplets and are in equilibrium below the activation threshold to form cloud droplets. Chemical analysis suggested that the haze particles contained significant amounts of sea salt. Additional in-situ measurements with an optical particle counter indicated that their number concentration was 2 times larger over the sea ice compared to the open ocean. Furthermore, measurements of the vertical distribution of the thermodynamic phases in low-level Arctic clouds revealed a characteristic structure, with a liquid regime frequently occurring at the top of the atmospheric boundary layer, followed by MPCs, and an MPH layer below. The findings from this study enhance our understanding of the microphysical composition of clouds in mixed-phase conditions.

Because most dehazing methods use synthesized haze images for training, they may perform well on synthesized datasets. However, when these methods are applied to real-world scenes, their performance may significantly decrease due to domain shift. Therefore, we propose a dehazing network for real-world hazy scenes. This network includes a haze generation network that can utilize the hazy information of real haze images to generate images that are closer to real hazy scenes, generating training pairs to address the domain shift problem. The network also includes a dehazing network that integrates feature fusion attention mechanisms, which can achieve better dehazing performance.