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The planetary boundary layer is crucial for the turbulence mixing and exchange of heat flux, momentum, and atmospheric pollutants between the atmosphere and Earth's surface. Nevertheless, the estimated boundary layer height (BLH) varies greatly by data sources and algorithms. This paper seeks to characterize the convective BLHs from 1‐s radiosonde measurements of China Radiosonde Network (CRN) for the 2012–2020 period at 1400 Beijing time, by using eight well‐known algorithms, wherein the newly established Thorpe method is theoretically fundamental on turbulence analysis and is in remarkable agreement with the parcel and bulk Richardson number methods. BLHs obtained by eight methods, ranging from 1.2 to 2.5 km, strongly vary with methods based on different kinetic or thermodynamic theories. The significant offsets among methods motivate the present study to propose a merged algorithm, to minimize the spread of BLH estimate. The merged BLH contains more physical information than that retrieved from a single method and can significantly lower the uncertainty. The BLH climatology exhibits a spatial pattern of "Southwest‐High Southeast‐Low," ascending from 0.6 km over southeastern China to 2.3 km over southwestern China, which could be largely attributed to the variations in the integrated surface sensible heat flux, soil moisture, total cloud cover, land cover, synoptic forcing, and terrain‐induced flow. Of interest is that land surface properties could be the major driver for the development of CBL. Also noteworthy is that the smallest BLH is expected under the strongest synoptic forcing condition. Plain Language Summary: The planetary boundary layer (PBL), where the exchanges of heat, moisture, momentum, and mass mainly occur with a variety of physical and chemical processes involved, is the lowest part of the troposphere in direct contact with the ground surface. However, the determination of boundary layer height (BLH) tends to be dramatically influenced by the dataset and methods used. Few studies have been conducted to evaluate the discrepancy of nationwide daytime BLH over China originating from the methods used. In particular, eight well‐known methods, including the novel Thorpe method and seven other traditional methods, are applied to estimate BLHs from high‐resolution soundings from the China Radiosonde Network. However, BLH derived by eight methods vary from approximately 1.2 to 2.5 km, strongly depending on the method. Therefore, to compile a more convincing BLH dataset eight methods are selected and composed as a merged BLH. The climatology of the merged BLH for the period 2012–2020 shows a well‐defined "Southwest‐High Southeast‐Low " pattern, which could be attributed to the diversities in sensible heat flux, soil moisture, land cover, total cloud cover, synoptic forcing, and terrain‐induced flow across China. Key Points: The merged boundary layer height (BLH) is synthesized from eight methods and it carries more planetary boundary layer (PBL) information and can considerably lower the uncertaintiesThe "Southwest‐High Southeast‐Low" pattern of BLH could be attributed to land properties, synoptic forcing, and terrain‐induced flowUnder weak synoptic forcing condition the development of convective PBL is more susceptible to the variation of land surface properties [ABSTRACT FROM AUTHOR]

Studying the spatiotemporal variations of the urban heat island (UHI) effect and its cause is important towards understanding urban climate change, planning and green development, and disaster mitigation. In this paper, by using surface observations and reanalysis data with objective classification of synoptic weather patterns (SWPs), we analyze the associations between canopy UHI intensity (CUHI) and SWPs in the planetary boundary layer (PBL) and their potential drivers during wintertime of the period 2012–2017. Six dominant types of SWP are identified as follows: In the case of Types 3, 4, and 6, weak high‐pressure systems exist to the south of Beijing, resulting in weak southerly winds with low PBL height, large cloud coverage and high relative humidity (RH). These conditions are generally conducive to a strengthening of the CUHII. In contrast, under Types 1, 2, and 5, high‐pressure systems are located to the northwest of Beijing, and the associated strong northwesterly flows of dry and cold air strengthen the boundary layer mixing process, resulting in large wind speed and low RH. This is conducive to a weakening of the CUHII. In general, our work reveals the impacts of SWPs on the strength of CUHII mainly via the modulation of local weather conditions at diurnal and interannual scales, while spatial pattern of CUHII is largely dominated by local climate zones. Our findings have implications for CUHII forecasts, as well as impact assessments and policymaking in the context of UHI‐related energy conservation in winter over high‐density urban areas on the synoptic scale. Key Points: The wintertime CUHII in Beijing is sensitive to Synoptic Weather Patterns (SWPs) at diurnal and interannual scaleTemporal variation in the strength of CUHII is closely linked with SWPs, while spatial pattern of CUHII is mainly sharped by LCZsDaily amplitudes and peaks of CUHII vary under different SWPs [ABSTRACT FROM AUTHOR]

This paper investigates immersion mode ice‐nucleating particle (INP) concentrations measured with a continuous flow diffusion chamber at temperatures of −20°C, −25°C, and −30°C in Beijing from 4 May to 4 June 2018. Aerosol conditions in the experiment period are classified into four types: clean, light PM2.5 pollution, heavy PM2.5 pollution, and dust. The PM mass concentrations and the aerosol size distributions are distinctly different in the four aerosol conditions. INP concentration increases as temperature decreases from −20°C to −30°C for all the four aerosol conditions. At a given temperature, INP concentrations progressively increase as the aerosol condition changes from clean to light PM2.5 pollution and to heavy PM2.5 pollution condition. At −25°C and −30°C, the dust condition has a much higher INP concentration than the other aerosol conditions. The INP concentration is closely related to the number concentration of aerosols with diameters of 1.0–2.5 μm (n1.0 ${n}_{1.0}$). Using a similar method as in the previous parameterization of INP concentrations for global and fairly clean aerosol conditions, a new parameterization of the INP concentration based on n1.0 ${n}_{1.0}$ is provided for the complicated aerosol conditions with high aerosol number concentrations in Beijing. Plain Language Summary: The ice‐nucleating particle (INP) concentrations and the aerosol–INP relationship under conditions with high aerosol number concentrations including anthropogenic sources are not well understood. In this study, measurements of aerosols and INPs under various aerosol conditions in Beijing are used to investigate the aerosol–INP relationship. It is found that the immersion mode INP concentration in the experiment period is not only dependent on temperature but also substantially influenced by aerosol conditions. At temperatures between −20°C and −30°C, the condition with the heavier PM2.5 pollution has the higher INP concentrations, and the dust condition has the highest INP concentrations. The number concentration of aerosols with diameters of 1.0–2.5 μm is a better parameter for predicting the INP concentration than the number concentration of aerosols with diameters of 0.5–2.5 μm, which was proposed to predict the INP concentration in previous studies under relatively clean aerosol conditions. The new parameterization of aerosol–INP relationship provided in this study can be applicable for complicated aerosol conditions with high aerosol number concentrations including anthropogenic sources. Key Points: The immersion mode ice‐nucleating particle concentration progressively increases from clean to polluted aerosol conditionNumber concentration of aerosols with diameters of 1.0–2.5 μm is closely related to immersion mode ice‐nucleating particle concentrationParameterization of immersion mode ice‐nucleating particle concentration is provided for condition with high aerosol number concentration [ABSTRACT FROM AUTHOR]

Different adverse health effects of submicron (PM1) and fine particles (PM2.5) may be attributed to their chemical differences, requiring a better understanding of size‐resolved composition. Herein, extensive online measurements were conducted across seasons in Beijing by two aerosol mass spectrometers, one of which alternately sampled PM1 and PM2.5. Source apportionment of organic aerosol (OA) indicated that traffic‐ and cooking‐related OA together accounted for ∼20%−30% of the OA mass in PM2.5, showing insignificant seasonal variations. Coal‐combustion and biomass‐burning‐related OA had minor contributions. The two secondary OA (SOA) factors together accounted for 59%−73% of the OA mass in PM2.5. The mass distributions of particulate components in PM1 and PM2.5 varied greatly across seasons. Secondary formation played a key role in particle size growth during cold seasons. During severe hazes with high aerosol liquid water content (ALWC), the supermicron mass fraction (MF1−2.5) of secondary components reached ∼40%−50% while those for primary OA remained at ∼20%. Heterogeneous uptake, aqueous processing, and dissolution likely all contributed to the enhanced concentration of secondary components, and the former two were perhaps more important. The increase of MF1−2.5 for secondary components with increasing ALWC in spring was less than that in winter, possibly due to the shorter duration of stagnant conditions limiting secondary formation. Early autumn showed higher MF1−2.5 values than cold seasons with insignificant changes as ALWC varied, plausibly explained by intensive new particle formation hindering persistent particle growth. Our results highlight the importance of heterogeneous uptake and aqueous processing in distributing SOA in supermicron mode in polluted areas. Plain Language Summary: Recent studies have found that submicron (PM1) and fine particles (PM2.5) have different adverse health effects, which were likely due to their different chemical compositions. There may be large compositional differences between PM1 and PM2.5, especially in polluted areas with larger populations. Therefore, it is of great importance to explore their compositional differences and possible driving factors in polluted areas. We found that the mass distributions of different particulate components in the two size domains (<1 μm and 1–2.5 μm) largely varied across seasons. During cold seasons (i.e., winter and spring), aerosol‐water‐related secondary formation played a key role in particle size growth, including heterogeneous uptake and aqueous processes. Longer duration of stagnant conditions in cold seasons would favor the particles to grow larger. By contrast, aerosol water had a limited impact on particle size growth in early autumn, during which intensive new particle formation might hinder persistent particle growth. Our findings greatly contribute to an improved understanding of multiple factors that influence the compositional differences between PM1 and PM2.5 in polluted urban areas, thereby providing helpful insights into possible reasons for their different health effects. Key Points: The submicron‐to‐fine particles ratios vary greatly for different components in different seasonsHeterogeneous uptake and aqueous processing play important roles in the particle size growth during cold seasonsIntensive new particle formation in early autumn may hinder persistent size growth of local particles [ABSTRACT FROM AUTHOR]

Humic‐like substances (HULIS) are unresolved compounds isolated from organic matter in atmospheric aerosols. Understanding the chemical structures and sources that control the hygroscopicity of HULIS is important for predicting its environmental impacts and possibly useful for parameterization of the hygroscopicity of organic aerosol (OA). Here, the hygroscopic growth of HULIS from total suspended particles samples in Beijing was analyzed using a hygroscopicity tandem differential mobility analyzer. The hygroscopicity parameter of HULIS (κHULIS) was determined to be 0.06 ± 0.03, and was found to correlate positively with O:C and f44 from offline aerosol mass spectrometry. Additionally, κHULIS was correlated positively with oxygenated organic aerosol (OOA) and correlated negatively with cooking OA and biomass burning OA, for which the source‐related OA types were from mass‐spectral‐based positive matrix factorization analyses. Further analysis resolved substantial κ values of 0.09 and 0.22, respectively, for less‐oxidized and more‐oxidized OOA, in contrast to the low κ values for cooking OA and biomass burning OA. Extensions of O:C‐ and source‐based parameterizations reasonably estimated the hygroscopicity of total OA with a moderate contribution from HULIS. This result and the fact that the obtained OOA contributions to κ of OA were similar to those from different environments suggest the applicability of parameterizing the hygroscopicity for a wide range of OA in particular based on source‐related structural characteristics. Plain Language Summary: Humic‐like substances (HULIS) are ubiquitous components of atmospheric organic aerosol (OA). Understanding and parameterizing the hygroscopicity of HULIS is expected to facilitate predictions of aerosol budgets and related environmental impacts. In this study, the hygroscopicity parameters of HULIS were determined and found to be positively correlated with the oxygen‐to‐carbon elemental ratio (O:C). Furthermore, contributions from the sources of HULIS to their hygroscopicity were resolved, and a significant influence of oxygenated OA mass on the hygroscopicity of HULIS was revealed. The parameterization of hygroscopicity based on O:C or source information reconstructed the hygroscopicity of HULIS well, particularly for source‐based approach. These two parameterization approaches reasonably estimated the hygroscopicity of total OA in the studied aerosol, and the contributions from oxygenated OA masses were consistent with those in other environments, both of which suggest wide applicability of this parameterization method for OA fractions in addition to total OA. Key Points: The hygroscopicity parameter (κ) of Humic‐like substances (HULIS) was 0.06 ± 0.03, and it correlated positively with O:C and f44Organic mass assigned to the oxygenated organic aerosol (OA) controls the hygroscopicity of HULISSource‐based parameterization of the κ of OAs is applicable for different ranges of OA components [ABSTRACT FROM AUTHOR]

Heavy precipitation and associated flood hazards can cause enormous socioeconomic losses. The advances in atmospheric modeling enable great promise in accurately predicting precipitation. However, the representation of land‐atmosphere exchange processes in atmospheric models and its impacts on precipitation evolution remain high uncertainties. This study investigated the sensitivity of convective precipitation to land‐atmosphere exchanges and examined the improvements in precipitation simulations by a dynamic vegetation‐type‐dependent exchange scheme. We conducted 3‐km‐resolution convection‐permitting modeling for three heavy precipitation events that occurred over areas with different dominant land‐cover types. The results showed that land‐atmosphere exchange efficiency significantly altered the precipitation intensity as well as the onset and peak time of precipitation but hardly affected the precipitation pattern. Strong exchange simulations could agree better with the observed precipitation in the 21 July 2012 Beijing and the 19 June 2010 Jiangxi heavy precipitation events occurring over humid and semihumid zones, while weak exchange simulations could attain higher consistencies with the observations in the 30 July 2012 Ningxia heavy precipitation event occurring over arid and semiarid zones. As a more physical alternative, the dynamic exchange simulations could achieve the closest agreement with the field observations, especially the intensity and location of the heaviest rainfall. The dynamic scheme modifies land‐atmosphere exchange efficiency to match local land cover conditions and could provide promising applications in heavy precipitation modeling studies. Plain Language Summary: Over recent decades, the frequent occurrence of heavy precipitation events has caused devastating ecological and socioeconomic impacts, such as agriculture losses, infrastructure damage, and casualties. High‐resolution atmospheric modeling at a convection‐permitting grid spacing (≤4 km) provides valuable applications for predicting heavy precipitation. Precipitation can be strongly affected by the energy and moisture exchanges between land surface and atmosphere. However, the representation of land‐atmosphere interactions in atmospheric models and the responses of precipitation to land‐atmosphere exchange efficiency remain great uncertainties. This study performed 3‐km high‐resolution atmospheric modeling with a dynamic vegetation‐type‐dependent land‐atmosphere exchange scheme for three typical heavy precipitation events that occurred over areas with different dominant land‐cover types. The results showed that land‐atmosphere exchange efficiency mainly affected the precipitation intensity as well as the onset and peak time of precipitation. The dynamic exchange scheme modifies the efficiency of land‐atmosphere exchanges to match local land cover conditions and could reproduce well the field observations, especially the intensity and location of the heaviest rainfall which usually serve as the most concerned variable in a major rainstorm event. Our findings show that the dynamical scheme could help achieve more accurate precipitation simulations. Key Points: A dynamic vegetation‐type‐dependent land‐atmosphere exchange scheme was applied into convection‐permitting atmospheric modelsLand‐atmosphere exchange efficiency mainly affected the precipitation intensity as well as the onset and peak time of precipitationThe dynamic exchange simulations agreed well with the field observations, especially the intensity and location of the heaviest rainfall [ABSTRACT FROM AUTHOR]

Differentiating local‐scale precipitation (LP) and nonlocal‐scale precipitation (NLP) and understanding their corresponding prestorm environment are of importance for accurate severe weather analysis and forecasting. However, the difference in the transient prestorm environments of LP and NLP is largely undetermined, thereby fundamentally limiting the predictability of convective storms. The present study focuses on the precursor signals of LP and their differences from those of NLP based on explicit observational analyses using high‐resolution radiosonde measurements from the China radiosonde network with a vertical resolution of 5‐m, combined with 1‐min rain gauge data from the China rain gauge network during 2013–2020. LP and NLP can be recognized by most proximity sounding parameters. For example, the upcoming LP is characterized by larger most‐unstable convective available potential energy (MUCAPE), K index, and total precipitable water (TPW), and a lower lifting condensation level (LCL), compared to the NLP scenario. By taking proximity sounding parameters as inputs and precipitation types as learning targets, a nu‐support vector machine algorithm can effectively predict LP or NLP events, achieving an overall precision of 97%. However, the precision significantly drops by approximately 20% after removing the variable of low‐level wind shear, indicating the crucial role of wind observation when predicting the LP event. Furthermore, more intensive LPs are characterized by larger MUCAPE, K index, TPW, and moist static energy, and lower LCL. Among others, MUCAPE is the most important feature, according to the gradient boosting machine algorithm. Plain Language Summary: The prestorm environment of local‐scale precipitation (LP) and nonlocal‐scale precipitation (NLP) can be substantially different. However, the difference is currently not well understood or constrained by observation. This study uses high‐resolution radiosonde measurements from the China radiosonde network with a vertical resolution of 5‐m, combined with 1‐min rain gauge data from China rain gauge network during 2013–2020, to quantify the difference. Radiosonde balloons were released at 1315 Beijing time (BJT) and provided 12 parameters that represent the prestorm environment of LP or NLP, and the matched rainfall measurements were taken from the 1320–1520 BJT period. LP and NLP can be clearly distinguished by most radiosonde parameters, confirming the fact that LP is likely triggered by local thermal convection whereas NLP could be related to medium or large‐scale circulation. Moreover, LP and NLP events can be precisely classified by the nu‐support vector machine (NuSVM) algorithm. However, the precision of NuSVM significantly drops by 20% when removing the variable of low‐level wind shear. Furthermore, based on the training result from the gradient boosting machine algorithm, the most‐unstable convective available potential energy is the most important feature for the intensity of LP. Key Points: Most proximity sounding parameters of the forthcoming local‐scale precipitation (LP) and nonlocal‐scale precipitation are strikingly differentLow‐level wind measurements are indispensable for the classification of precipitation typesThe intensity and frequency of LP largely rely on the prestorm environment of the atmosphere, particularly the convective available potential energy value [ABSTRACT FROM AUTHOR]

The weekend effect of the canopy urban heat island (UHI) has been long recognized. However, how the UHI weekend effect (UWE) varies with the hour of day and season of year is still unclear; it remains largely unknown on how the UWE is regulated by various controls. To address these knowledge gaps, here we took Beijing, China as an example and investigated the detailed spatiotemporal UWE patterns and the major regulators with a 3‐year data set of in‐situ surface air temperatures. Our results indicate that the annual ΔIc (the UHI intensity difference on weekends and weekdays) is stronger at night (−0.13 ± 0.12 K; mean ± 1 STD) than during the day (−0.05 ± 0.10 K); at the seasonal scale, ΔIc reaches the strongest in winter (−0.14 K) and the weakest in summer (−0.05 K). The ΔIc is strongly regulated by anthropogenic heat flux (AHF), evidenced by a quasi‐synchronous diurnal pattern between ΔIc and ΔAHF (i.e., the AHF difference between weekends and weekdays). The nighttime ΔIc is intensely modulated by urban morphology, with a stronger modulation by the landscape shape index than by the distance of the station from the urban center. Weather conditions also modulate the ΔIc, with the ΔIc weakening with the increase of cloud coverage and wind speed level. We consider these findings deepen our understanding of the weekly rhythms of UHI as well as the underlying modulators. Key Points: A significant ΔIc (weekend‐weekday difference in canopy urban heat island) is observed in Beijing, ChinaΔIc is stronger at night than during the day and the two minima of diurnal ΔIc correspond well to morning and evening rush hoursVariations in weekday‐weekend contrasts in Ic and anthropogenic heat flux are synchronous yet ΔIc is also modulated by urban morphology and weather condition [ABSTRACT FROM AUTHOR]

Secondary particulate matter exerts adverse effects on air quality and human health. The production or reaction rate of secondary aerosols in polluted environments remains uncertain and is complicated by diverse emissions and meteorological conditions. By concurrently measuring the mass spectra of compounds in both particulate (using an aerosol mass spectrometer) and gas phases (using proton‐transfer‐reaction mass spectrometry) in suburban Beijing, we linked the secondary organic aerosol (OA) and volatile organic compounds (VOCs) to photochemical age (tage) and obtained their reaction or production rates. Factorization analysis of the mass spectra of OA and the 108 VOC species resolved three oxygenated OAs (OOA) and three secondary VOC factors at different oxidation levels. Primary organic aerosols and VOCs from traffic sources were determined to be important sources for secondary aerosol formation. At high pollution levels under the conditions of weaker solar radiation and higher relative humidity, moderately oxygenated OA (O/C = 0.61) and secondary inorganics were coproduced in combination with rapid consumption of all VOCs. At lower pollution levels, the intense solar radiation caused substantial and rapid production of OOA (O/C = 0.81) and intermediate VOCs (both in a high oxidation state) at a rate of 15.0% h−1 and 14.0% h−1, respectively. These results highlight the feedback effects between radiation and moisture in terms of altering the formation mechanism of secondary aerosols. In particular, highly oxygenated secondary airborne products under strong radiation should be considered in regard to their environmental impact. Plain Language Summary: In this study, the compositions of submicron aerosols and volatile organic compounds (VOCs) in suburban Beijing were concurrently characterized for their detailed mass spectra, and based on these spectra, the primary and secondary sources were apportioned to investigate their evolution and conversion. Our results demonstrate the contrasting phenomena of chemical evolution under the influence of solar radiation and moisture. Photo‐oxidation was observed to rapidly produce organic aerosol (OA) and secondary VOCs in a considerably high oxidation state, while higher relative humidity induced overall moderately oxygenated OA and secondary inorganic aerosols but resulted in more rapid consumption of all VOCs. Key Points: Mass spectra of organic compounds in both aerosols and gases were concurrently characterized in suburban BeijingThe production and consumption rates of organic aerosols (OAs) and gases were obtained under high radiation or moist conditionsHighly oxidized OAs and intermediate volatile gases are rapidly produced through photo oxidation under strong solar radiation [ABSTRACT FROM AUTHOR]

A sporadic case of noctilucent clouds (NLCs) was observed unexpectedly on the night of the 6–7 July 2020 in Beijing (40°2′N, 115°30′E). The noticeable wavy structures and observed ambient temperature (135.54K at the mesosphere and lower thermosphere [MLT]), both indicated that the increase in temperature oscillations could be the cold phase of gravity waves (GWs). The reasons for NLC formation were analyzed based on the observations and model data sets in our study. The real‐time synoptic analysis revealed that there were GWs originally generated by a squall line in the troposphere. Due to the blocked effect of a stable tropopause inversion layer (TIL), the GWs broke, leading to strong energy dissipation near the TIL. The reverse ray tracing analysis between the TIL and NLCs' layer revealed the travel distance (206.88 km) and time (49.91 min) of GWs. These findings show that the turbulence over the TIL (at approximately 14.64 km) excited secondary GWs, which propagated upwards toward the mesosphere and probably interacted with diurnal and semi‐diurnal tides. The cold phase of the larger‐amplitude waves can provide optimal conditions for NLCs forming. Our study highlights the significance of dynamic coupling mechanisms regarding the effects from troposphere to MLT thermal conditions and offers a case study for the increasing occurrences of NLCs at midlatitudes. Plain Language Summary: Noctilucent clouds (NLCs) are ice clouds forming at 80–86 km during summertime in the Northern Hemisphere. During the night of 6–7 July 2020, a Chinese photographer captured the occurrence of NLCs in Beijing (40°2′N, 115°30′E). The wavy structures in the photographs revealed that the occurrence of NLCs had a close relation with the atmospheric gravity waves (GWs), the significant transport of momentum and energy in the atmosphere. We used comprehensive data sets and models to locate the source of these GWs. The real‐time synoptic analysis in the troposphere revealed that the GWs were generated by a convective system, a squall line. However, a stable tropopause inversion layer inhibited the waves like a huge lid, resulting in strong energy dissipation and exciting new GWs propagating upwards. The secondary‐generation GWs can interact with large‐scale waves and cause severe cooling in the MLT, providing an ideal condition for the growth of ice particles in NLCs. These particles integrated the wave source at the tropopause and GWs that are visible in the NLCs for the first time at midlatitudes. The results inspired us to further explore the connection between the troposphere and the upper atmosphere in the future studies. Key Points: The mechanism of a sporadic case of formation of midlatitude noctilucent clouds (NLCs) in China is demonstratedThe interaction between gravity waves (GWs) and tidal waves substantially cooled the NLC layerTurbulence of the tropopause inversion layer excited secondary GWs which propagated upwards toward the mesosphere [ABSTRACT FROM AUTHOR]

Antimony (Sb) is a toxic heavy metal, and PM2.5‐bound Sb (SbPM2.5) in the air impacts human health via inhalation pathways. In this study, we analyzed multiyear measurements of ambient SbPM2.5 in Beijing to characterize its spatiotemporal distributions, identify main sources, and predict future trends. The results show that ambient SbPM2.5 has been decreasing with fluctuations from 2005 to 2012 and decreased rapidly after 2013, which was likely a result of the government's enhanced air pollution control plan that targeted main sources of industrial Sb. Across the city, average SbPM2.5 concentrations were relatively higher at nonemission locomotive traffic sampling sites and in densely populated areas (9.45–19.45 ng/m3) and lower in background areas (0.6–0.9 ng/m3). Regional‐scale emissions and local human activities both affected the spatial distributions of SbPM2.5. Notably, SbPM2.5 concentration increased by 58.3% from 2006 to 2013 in one suburban background area, indicating the changing emission distributions and intensities over the study period. A neural network model was developed and tested to predict future SbPM2.5 levels, results from which showed that with simulated massive reductions in coal supplies and a rapid boom in the waste incineration industry, SbPM2.5 concentration would vary in a smaller range (from 4.08 to 4.38 ng/m3) over the next decade as compared to the observed range during 2011–2018 (19.0–5.44 ng/m3). The impact of the continued expansion of the waste incineration industry on SbPM2.5 pollution needs to be considered in future emission control policies. Plain Language Summary: Long‐term exposure to antimony (Sb) and related compounds, such as through respiration of Sb containing atmospheric particles, can result in negative health impacts to human body. Knowledge of concentration levels and future trends of Sb in PM2.5 (SbPM2.5) especially in populated megacities is needed in assessing the potential risks of atmospheric Sb to human health. In this study, SbPM2.5 concentration data in Beijing over the past 15 years were aggregated to assess its past trends and predict its future levels. Benefited from the implementation of stringent air pollution control programs in this region, SbPM2.5 concentrations have been decreasing, but with fluctuations from 2005 to 2012, and at a faster rate after 2013. However, the decreasing trend will likely slowdown in the next decade due to the rapid development of the waste‐to‐energy conversion industry, which is an important source of atmospheric SbPM2.5 emission. Thus, future SbPM2.5 levels may still pose a threat to human health, especially to infants and children. Key Points: Characteristics of PM2.5‐bound antimony in Beijing have been summarized over 15 years and they predict future trendsThe aggressive reduction of antimony (Sb) pollution levels is mainly influenced by a comprehensive air pollution control program by the governmentThe Sb emissions from waste incineration are likely to replace coal combustion as the primary source in PM2.5 now and in the next decade [ABSTRACT FROM AUTHOR]

The impacts of anthropogenic heat emissions, urban land use, and aerosols on a snowfall event in Beijing were investigated by using the Weather Research and Forecasting model. The results show that urban land use and anthropogenic heat emissions can reduce the accumulation of snowfall by 17%–22% within the fifth ring road, which depends on the aerosol number concentration and size. The increase in aerosols (same land use and anthropogenic heat emissions) can increase the accumulated snowfall within fifth ring road, especially for accumulated and coarse mode. Urban land use, anthropogenic heat emissions, and aerosols have different effect on snowfall, which depend mainly on relatively humidity. Urban land use and anthropogenic heat emissions lead to the formation of an "urban heat and dry island," which is not favorable to snowfall processes during the initial snowfall processes and leads to a decrease in ice crystals and snow by 47% averaged. At this time, the increase in aerosol number concentrations has less impact (increase by 5% averaged) on snowfall because of higher supersaturation required for activation. With the development of snowfall processes, the feedback of cloud microphysics decrease temperature and increase relative humidity, which is favorable to snowfall process and increase snowfall slightly by 5% averaged. Meanwhile, the critical radius of aerosols that can be activated decrease, smaller particle aerosols are activated to form supercooled cloud water and further to form ice crystals and snow, which leads to an increase in accumulated snowfall by 11% averaged. Plain Language Summary: Urban are places where humans live, but human activities including urban land use changing, anthropogenic heat, and aerosols emissions can change local weather, especially local precipitation. It's important to know how human activities affect precipitation to avoid urban flooding and provide a theoretical basis for artificial impact weather. We analyzed the impact of urban land use, anthropogenic heat, and aerosols emissions on a snowfall over Beijing by using numerical simulation. Urban land use and anthropogenic heat emissions lead to the formation of the "urban heat and dry island," which leads to a decrease in the initial snowfall but slightly increase snowfall in the later period. The effect of aerosols on snowfall is related to number concentration and size. And the increase in aerosol number concentrations has less impact on snowfall at the initial period due to the lower supersaturation produced by the urban heat and dry island but increase snowfall in the later period due to higher supersaturation caused by the feedback of the cloud microphysics. Key Points: The interaction effects of urban environment, aerosol, large‐scale environment, and cloud microphysical processes reduce 16%–22% snowfallThe urban heat and dry island reduce 47% snowfall at the initial period and slightly increase 5% snowfall at the later periodThe increase of aerosols has the increase effects on snowfall, which increases about 5% and 11% at the different periods, respectively [ABSTRACT FROM AUTHOR]

Based on the long‐term observations of the Wuhan and Beijing Mesosphere‐Stratosphere‐Troposphere (MST) radars, the statistic characteristics of the mesospheric vertical winds at midlatitudes are investigated for the first time. The vertical wind data come from the Wuhan MST radar (29.51°N, 114.13°E) during 2012–2017 and from the Beijing MST radar (39.75°N, 116.96°E) during 2012–2014. The subdaily, seasonal, and annual variations of the mesospheric vertical winds at Wuhan and Beijing are presented. No obvious subdaily and seasonal variations are found and the annual variations of the mean vertical winds are downward in most of time. The mean vertical winds at Wuhan become smaller in summer and turn to upward at some heights, while those of Beijing only become smaller in summer. The difference of summer vertical winds over Wuhan and Beijing is closely related to the gravity wave activity. The Wuhan MST radar is located to the east side of the Qinghai‐Tibet plateau and also in the East Asian monsoon region, thus the mesospheric winds over Wuhan may experience more influence of gravity waves compared with those over Beijing. The possible bias sources in the vertical wind measurement of the two MST radars are carefully analyzed and the presented wind velocities are proved to be credible. The measured velocity magnitude is similar to other Very High Frequency radar observations, but much larger than that of the WACCM simulation. The Stokes drift, multicellular circulation structures, the wave influence on the radar echoes are raised as the potential sources for this discrepancy. Key Points: Wuhan and Beijing MST radars are used to study the statistical characteristics of the midlatitude mesospheric vertical windsEstimated mesospheric vertical winds at Wuhan and Beijing are generally downward all the year, and much larger than the model dataMuch more gravity wave activities are responsible for the summer difference of the mesospheric vertical winds [ABSTRACT FROM AUTHOR]

Nitrate (NO3−) is a major contributing species to haze formation in Northern China. So far, formation processes and source apportionments of nitrate aerosols during haze pollution have not yet been well understood. In this study, the PM2.5 samples were collected in Beijing from 13 November to 24 December 2018. In addition to water‐soluble ions, oxygen (δ18O‐NO3−) and nitrogen (δ15N‐NO3−) isotopes in particulate NO3− were also determined, in order to investigate the formation pathways and potential sources of NO3− aerosols. The results showed that NO3− was a dominant species (43%) of secondary inorganic aerosols during the sampling period. The δ18O‐NO3− and δ15N‐NO3− values averaged at 83.8 ± 13.4 and 11.5 ± 5.0‰, respectively. Combining isotope compositions and Bayesian isotope mixing model, we found that heterogeneous reaction and gas phase oxidation contributed equally to nitrate formation during the sampling period. However, the contribution of heterogeneous processes to nitrate increased from 39% during the clean period to 64% during the haze period. On average, coal combustion, biomass burning, vehicle emissions, and soil emission contributed 50%, 26%, 20%, and 4%, respectively, to nitrate aerosols during the sampling period. Compared to the result in 2013, the significant decrease (~21%) of relative contribution of coal combustion to nitrate was due to strict reduction of coal consumption in Beijing. Finally, the relative contribution of traffic emissions to nitrate increased from 18% during the clean period to 30% during the haze period, suggesting that control of traffic emissions would be an important way to decrease nitrate concentrations and improve the air quality in Beijing. Key Points: Nitrate aerosols in Beijing during the haze events were mainly produced by hydrolysis of N2O5 under high humidity conditionsThe contribution of coal combustion to atmospheric nitrate decreased significantly after clean air actions implemented by Chinese governmentStrict control of traffic emissions would be an important way to decrease nitrate concentrations and improve the air quality in Beijing [ABSTRACT FROM AUTHOR]

Beijing, China, is located in a region of complex terrain with high mountain ridges to the northwest and the Bohai Sea to the southeast. The origin of convective storms occurring on the plains can often be traced to the upstream mountains. Under weakly forced conditions, these convective storms most frequently evolve into squall lines (SL) and convective clusters (CC) when reaching the plains. In this study, we analyze 18 SL and 15 CC storm systems and assess their environmental and mesoscale differences between the two phenomena. By analyzing the frequency of convective occurrence for the two types of storms based on composite radar reflectivity, it is found that the high frequencies are located in the south of Beijing for SL and near the center of Beijing for CC. Using storm‐scale reanalysis data produced by a rapid update four‐dimensional variational analysis system that assimilates Doppler radar observations, distinct features of the SL and CC storms are revealed in terms of their convective environments and mesoscale structures, such as cold pool, horizontal wind convergence, and humidity distribution. It is found that low convective inhibition and high low‐level wind speed on the plains are common to both SL and CC, whereas higher vertical shear over the plains and stronger wind speed on both mountains and plains distinguishes SL from CC. We further show that the stronger wind and vertical shear in SL generate stronger and more organized downdrafts, producing a deeper cold pool, strong outflow and convergence, which explains the formation of the high‐frequency center in the south of Beijing. In contrast, the cold pool produced in CC is shallower and weaker, resulting in weaker outflow and convergence and convective activities that are located only in central Beijing. Key Points: Weakly forced mountain‐to‐plains precipitation systems (squall line and convective clusters) have distinct areas of high convective occurrenceThese two systems are associated with distinct convective environmentsDifferences in mesoscale features (cold pools, water vapor fields, and wind fields) explain the locations of convective activity [ABSTRACT FROM AUTHOR]

High‐impact poor air quality events, such as Beijing's so‐called "Airpocalypse" in January 2013, demonstrate that short‐lived poor air quality events can have significant effects on health and economic vitality. Poor air quality events result from the combination of the emission of pollutants and meteorological conditions favorable to their accumulation, which include limited scavenging, dispersion, and ventilation. The unprecedented nature of events such as the 2013 Airpocalypse, in conjunction with our nonstationary climate, motivate an assessment of whether climate change has altered the meteorological conditions conducive to poor winter air quality in Beijing. Using three indices designed to quantify the meteorological conditions that support poor air quality and drawing on the attribution methods of Diffenbaugh et al. (2017, https://doi.org/10.1073/pnas.1618082114), we assess (i) the contribution of observed trends to the magnitude of events, (ii) the contribution of observed trends to the probability of events, (iii) the return interval of events in the observational record, preindustrial model‐simulated climate and historical model‐simulated climate, (iv) the probability of the observed trend in the preindustrial and historical model‐simulated climates, and (v) the relative influences of anthropogenic forcing and natural variability on the observed trend. We find that anthropogenic influence has had a small effect on the probability of the January 2013 event in all three indices but has increased the probability of a long‐term positive trend in two out of three indices. This work provides a framework for both further understanding the role of climate change in air quality and expanding the scope of event attribution. Key Points: Extreme air quality conditions present in Beijing during January 2013 represented by three indices of air quality meteorologyNatural variability found to have a larger influence on extreme air quality events than anthropogenic forcingAnthropogenic forcing drove long‐term positive trends in two out of three indices, despite small effect on individual events [ABSTRACT FROM AUTHOR]