Heavy Pollution Episodes Research Articles

Understanding Meteorological Factors Influencing Heavy Air Pollution in Guwahati, India

Guwahati, Assam's largest city and the gateway to Northeast India faces rapid urbanization and increasing pollution. Although heavy air pollution has been frequent in recent decades, the exact reason behind this is still uncertain. During the study period from 2021 to 2023, we identified eight instances of heavy pollution events across the region, seven of which are aligned with a high-pressure system and influenced by westerly airflow at 700 hPa. Apart from that, temperature inversion, low boundary layer height, and low horizontal wind speeds in the lower troposphere help confine pollution, resulting in insufficient mixing and dispersion of pollutants in the atmosphere, which favors the development of heavy air pollution episodes. We investigated the impact of local and regional emissions on PM10 and PM2.5 concentrations over Guwahati City using the regional Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Our finding revealed that regional transport significantly contributes to PM10 (57.3 % to 75.5 %) and PM2.5 (56.9 % to 73.5 %) levels, highlighting the predominance of regionally transported pollutants. During high pollution days, local emissions increase due to stagnant air, limited dispersion from high-pressure systems, and temperature inversions, trapping pollutants in the region. This research offers valuable scientific knowledge to anticipate heavy air pollution episodes in Guwahati.

Regional source contributions to summertime ozone in the Yangtze River Delta

Ozone (O3) pollution is increasing in the Yangtze River Delta (YRD), with significant influences from regional transport during pollution events. However, the specific contributions of different regions remain imprecisely quantified. This study estimated the regional contributions of eight regions to summer O3 in the YRD using the Community Multiscale Air Quality (CMAQ) model with a source-tagged photochemical mechanism. Non-background O3 is attributed to nitrogen oxides (NOX) and volatile organic compounds (VOCs) from different regions. Background O3 is the predominant contributor with average ratios of 75.0%, 65.3%, 64.8% and 63.0% for Shanghai, Nanjing, Hangzhou and the entire YRD, respectively. Locally formed O3 are 39.9, 42.0, 39.6, and 36.9 parts per billion (ppb) by volume in the above areas. North Zhejiang and south Jiangsu are the primary sources of heavy pollution episodes as the maximum daily 8-h average (MDA8) O3 concentrations in these regions increase the most. NOX is the predominant contributor to heavy pollution episodes with the maximum increment attributed to NOX (O3N) of 14.3 ppb, while VOCs only contribute to 2.1 ppb (O3V) in Jiangsu. Relative humidity is crucial in heavy pollution episodes while high temperature, low planetary boundary layer (PBL) height and the wind field are associated with regional transport. Diurnal variation underscores the importance of understanding O3 formation in the afternoon (12:00–16:00), which is essential for devising effective mitigation policies.

Characterization, sources, and formation processes of dicarboxylic acids, oxocarboxylic acids and α-dicarbonyls in PM2.5 aerosols in New Delhi

Daytime and nighttime fine aerosol (PM2.5) samples were collected during a heavy pollution episode in November 2020, January 2021, and also during clean event (August 2020) in New Delhi. These samples (n = 20) were analyzed for water-soluble dicarboxylic acids (diacids) and related compounds, carbonaceous components, and inorganic ions to identify their sources and atmospheric processing in different episodes/seasons. Among the measured organics, oxalic acid (C2) was found to be the most abundant species followed by terephthalic (tPh), succinic (C4), phthalic (Ph), and azelaic (C9) acids. Such high abundance of tPh were different from those in other Asian cities where C3 is generally the second or third dominant species. tPh very well correlated with OC, Cl− and K+, indicating combustion of biomass and plastic-containing waste may be the possible sources. Significant high contents of diacids, oxoacids, and dicarbonyls were observed during heavy pollution episode, implying an enhanced emission and/or atmospheric processing of these species. Additionally, two important secondary formation pathways for C2 diacid were discussed in New Delhi, i.e. (i) biomass burning derived (biogenic) volatile organic precursors lead to formation of C2 diacid through transformation of oxoacids and dicarbonyls by oxidation, and (ii) oxidative degradation of the unsaturated fatty acids results in formation of C5 and C4 which subsequently decompose to C2 diacid. This study demonstrated that both primary emissions in clean event and secondary production during polluted event are important sources of aerosols in New Delhi.

Characteristics and Source Analysis of VOCs Pollution During Emergency Response in Tianjin

To elucidate the characteristics of VOCs chemical components during heavy pollution episodes, hourly online VOCs data derived from 11 heavy pollution events in Tianjin from 2019 to 2020 were employed. The positive matrix factorization （PMF） and conditional bivariate probability function （CBPF） were employed to analyze the sources of VOCs during heavy pollution episodes. The results indicated that the average VOCs volume fraction during these episodes was recorded at 35.7×10-9. Furthermore, it was observed that during the winter emergency response period, there was a discernible increase in the volume fraction of VOCs when compared to that during the autumn season. Specifically, there was a notable upswing of 48% in the olefins category, whereas alkanes registered a 4% increase. Additionally, the VOCs component structure changed significantly during the heavy pollution episodes. During the orange warning period, the proportion of alkanes increased by 36%, and the proportion of acetylene decreased by 32%. During the yellow warning period, the proportion of alkanes increased by 14%, and the proportion of acetylene decreased by 5%. During the emergency response period, motor vehicle emission sources, natural gas evaporative sources, and solvent use sources were the main contributors of VOCs in environmental receptors, contributing 17.5%, 15.4%, and 15.2%, respectively. Compared with that during the period antecedent to the emergency response, the contribution of vehicle emission sources and diesel volatile sources to VOCs in environmental receptors decreased by 2.0% to 5.5% and 2.1% to 6.6%, respectively, and the contribution of solvent use sources decreased by 0.2% to 2.4% during the yellow warning period. During the orange warning period, the contribution of motor vehicle emission sources was reduced by 0.1% to 8.3%, and the contribution of solvent use sources was reduced by 0.5% to 6.2%.

A long-term Doppler wind LiDAR study of heavy pollution episodes in western Yangtze River Delta region, China

Previous studies are primarily based on surface air pollution for a single event, leaving research on the temporal characteristics of aerosols and wind fields in the atmospheric boundary layer (ABL) and their associations unclear due to a lack of long-term vertical profile data. This study was the first to conduct long-term Doppler wind LiDAR measurements from Sep. 2019 to Aug. 2022 in Hefei in western Yangtze River Delta (YRD) region, China. The spatiotemporal characteristics of retrieved aerosol backscatter coefficient (β) and wind profiles were analyzed from the perspective of long-term statistics and typical heavy pollution episodes (HPEs). The seasonal profile of β showed a peak in the near-surface layer meanwhile the overall β profile (<0.5 km) was the highest in winter but lowest in summer. Combined with ground-based meteorological and air quality observations, 12 HPEs were identified and classified into dust-related events and fog-haze episodes. The results showed a consistency between hourly variations in PM10 (particulate matter smaller than 10 μm) concentration and β retrieved at 300 m during a high PM10 concentration (>150 μg/m3) period. Different roles of horizontal wind at different altitudes and its associated time delay effect on surface PM10 pollution were evaluated based on correlation coefficients (Ф) and air pollution diffusion conditions. Significant positive Ф values were noticed below 0.5 km during the entire dust-related EP4 and EP6, indicating that the higher wind speeds could exacerbate PM10 pollution. In contrast, large negative Ф values meant the removal of PM10 pollutants by strong winds below 0.8 km during 24 h after peak in EP3. Combining with backward trajectory analysis and meteorological condition, notable transboundary pollution with positive contributions from upper winds (>1.5 km) was discovered in dust-related EP1, EP4, EP7, EP9, and EP10. Time delay effect (1-h/2-h lag) of upper winds (>0.8 km) on surface PM10 pollution was explored in EP5, EP6, EP7, EP8, and EP9. In spring dust-related HPEs, surface PM10 pollution was mostly contributed by long-range transport of aerosol particles at higher altitudes (>1.5 km) from the northwest direction, driven by the Mongolian cyclone and the cold front system. Transboundary aerosols originated from the northern part of Anhui province and the YRD region in the middle altitudes (∼0.5 km) was the main contributor to fog-haze HPEs. The findings demonstrated the ability of the real-time Doppler wind LiDAR system to monitor transboundary air pollution and provided a scientific reference for policy makers.

Modal shift, environmental benefits and population exposure assessment on contingent transport policies

Transport policies targeting emission reduction and air quality improvement typically discourage private car use and promote shifts to mass transit (bus, metro). However, possible increase of travelers’ exposure while adapting to those policies have often been overlooked, which is addressed in this work via a case study of Heavy Pollution Episodes (HPEs) in Chengdu, China, using city-scale traffic camera and transit ridership data. By investigating traffic fluctuation and modal shift under prolonged license plate rationing for private cars and free or discounted fare for mass transit, we show that the reduction of small car traffic was marginal (up to 2.3 % in 24-hour periods), which, environmental benefits wise, is negligible according to air quality modelling. Meanwhile, over 3.23 % of car users switched to mass transit during Orange-level alerts, with a higher degree (by 19 %–39 %) of exposure to PM2.5. Our findings highlight the importance of exposure-centric decision making during HPEs.

Sources and formation of fine particles and organic aerosols during autumn-winter period in the southern edge of northern China plain

The North China Plain (NCP) experienced significant improvements in air quality in 2018–2022. However, severe pollution episodes still occur frequently during the cold season. The limitations of highly time-resolved measurements hinder understanding the sources and formation mechanisms of pollution episodes, especially the role of organic aerosols (OA). Therefore, we used a Time-of-Flight Aerosol Chemical Speciation Monitor to characterize the aerosol chemical species, variation, and sources of OA during autumn and winter in Luohe, a city in the southern part of the NCP. The results showed that nitrates and organics were the main species of fine particles (PM2.5), accounting for an average of 38.4% and 29.6% of its total mass, respectively. Furthermore, the positive matrix factorization model analyzed the OA in PM2.5 and identified three primary OA and secondary OA related to photochemistry. Primary OA was the dominant contributor throughout the study period (55%), increasing from 50% during the non-heating period to 59% during the heating period. The contribution of photochemically generated oxidized OA remained high (41%) during heavy pollution episodes in the heating period, indicating strong photochemical production during winter. Additionally, most aerosol species and OA factors showed distinct diurnal variations, with lower concentrations during the day, suggesting the influence of the planetary boundary layer and primary emissions. By analyzing the chemical species features of five heavy particulate matter pollution episodes during the study period, we identified three main driving mechanisms for severe pollution events: photochemical processing, photochemical and aqueous-phase production, and local emissions.

Moving beyond the Aerosol Climatology of WRF-Solar: A Case Study over the North China Plain

Abstract Numerical weather prediction (NWP), when accessible, is a crucial input to short-term solar power forecasting. WRF-Solar, the first NWP model specifically designed for solar energy applications, has shown promising predictive capability. Nevertheless, few attempts have been made to investigate its performance under high aerosol loading, which attenuates incoming radiation significantly. The North China Plain is a polluted region due to industrialization, which constitutes a proper testbed for such investigation. In this paper, aerosol direct radiative effect (DRE) on three surface shortwave radiation components (i.e., global, beam, and diffuse) during five heavy pollution episodes is studied within the WRF-Solar framework. Results show that WRF-Solar overestimates instantaneous beam radiation up to 795.3 W m−2 when the aerosol DRE is not considered. Although such overestimation can be partially offset by an underestimation of the diffuse radiation of about 194.5 W m−2, the overestimation of the global radiation still reaches 160.2 W m−2. This undesirable bias can be reduced when WRF-Solar is powered by Copernicus Atmosphere Monitoring Service (CAMS) aerosol forecasts, which then translates to accuracy improvements in photovoltaic (PV) power forecasts. This work also compares the forecast performance of the CAMS-powered WRF-Solar with that of the European Centre for Medium-Range Weather Forecasts model. Under high aerosol loading conditions, the irradiance forecast accuracy generated by WRF-Solar increased by 53.2% and the PV power forecast accuracy increased by 6.8%. Significance Statement Numerical weather prediction (NWP) is the “go-to” approach for achieving high-performance day-ahead solar power forecasting. Integrating time-varying aerosol forecasts into NWP models effectively captures aerosol direct radiation effects, thereby enhancing the accuracy of solar irradiance forecasts in heavily polluted regions. This work not only quantifies the aerosol effects on global, beam, and diffuse irradiance but also reveals the physical mechanisms of irradiance-to-power conversion by constructing a model chain. Using the North China Plain as a testbed, the performance of WRF-Solar on solar power forecasting on five severe pollution days is analyzed. This version of WRF-Solar can outperform the European Centre for Medium-Range Weather Forecasts model, confirming the need for generating high spatial–temporal NWP.

Designing regional joint prevention and control schemes of PM2.5 based on source apportionment of chemical transport model: A case study of a heavy pollution episode

Fine particular matter (PM2.5) pollution still occurs frequently in China. Despite recognizing the importance of regional joint prevention and control (RJPC) for mitigating haze pollution, there is still a limited understanding of scheme design and effectiveness. In this study, with the Fenhe Plain in China serving as the case, the Integrated Source Apportionment Method (ISAM), incorporated into the Community Multiscale Air Quality Modeling System (CMAQ), was used to quantitively identify PM2.5 sources during a typical heavy pollution episode from Jan. 20th to 25th, 2021. Informed by source apportionment, we designed and assessed multiple RJPC scenarios for eliminating heavy pollution, yielding recommended RJPC schemes. Source apportionment results revealed a substantial increase in the contribution percentage of regions within a 350-km radius during the pollution episode compared to the non-polluted period. Sulfate was predominantly contributed from long-distance transport, whereas nitrate was chiefly contributed from closer regions. Ammonium exhibited higher local contributions than nitrate from the Fenhe Plain. Moreover, Taiyuan and Linfen were identified as PM2.5 exporters, whereas Sanmenxia, Jinzhong, and Luliang served as PM2.5 importers, and Yuncheng acted as a comprehensive city. The proposed specific RJPC schemes aimed at eliminating heavy pollution for the Fenhe Plain emphasized the importance of controlling emissions of particulate matter, ammonia, nitrogen oxides, and volatile organic compounds in areas within an approximate 350-km radius outside the Fenhe Plain, in addition to strengthening the local emission control. Nevertheless, only through the comprehensive and in-depth implementation of emission control measures across a larger area can PM2.5 compliance be achieved.

Impact of traffic policy on travel population exposure during heavy pollution episodes: A Chengdu case study

Previous studies on exposure have often omitted the impact of travelers' response to policies during air pollution, particularly for multi-modal traffic system. To address this gap, we investigate the population exposure of three modes (cars, buses, and metro) during morning rush hour in Chengdu, China, amidst the implementation of contingent traffic-related policies during heavy pollution episodes with elevated background pollutant concentrations of PM2.5. We introduce a trip-based average population exposure model to evaluate travel population exposure. This model allows to calculate the exposure for all modes, and assess its changes owing to modal shifts. Additionally, we propose a traffic-modal exposure coefficient to quantify PM2.5 exposure disparities among traffic modals. The results indicate that: the population exposure of total travelers experiences a growth effect, influenced not only by increased pollutant concentration but also by modal shift. Lastly, the inside-to-outside ratio, bus waiting time, and attractiveness of active traveler are discussed for more policy implications. This study not only offers a quantitative model to uncover potential overestimation of the effect of policies on reducing exposure if failure to consider modal shift, but also provides valuable insights for managing exposure growth to safeguard health of urban residents and promote sustainable development of cities.

Modeling study of PM2.5 pollution episode of early spring 2019 in Hokkaido, Japan caused by biomass burning in Northeast China

Biomass burning (BB), in particular agricultural waste burning (Agri-BB), occurs at random locations, scales, and times. These factors make it challenging to detect Agri-BB accurately through satellite observations. Thus, the BB emission inventories using satellite observation data have uncertainties for their emission estimation approach and cause poor model performance for air pollutants including PM2.5. We utilized the two BB emission inventories, GFEDv4.1s and FINNv2.5 with the CMAQ model to simulate the PM2.5 heavy pollution episode in Hokkaido 2019. To estimate Agri-BB contributions, we conducted three simulation cases for each BB emission inventory: with and without Agri-BB emission, and the boosted Agri-BB emission cases. The baseline simulation failed to capture the temporal and spatial variation patterns of PM2.5. Meanwhile, the boosted Agri-BB case could show favorable performance for PM2.5 concentrations. These results indicated that the two BB emission inventories underestimated Agri-BB emissions. In the two boosted Agri-BB cases, the PM2.5 contributions from Agri-BB accounted for more than 50% during the episode. Moreover, high PM2.5 emissions were found in Northeast China and its surrounding regions similar to the two boosted Agri-BB cases. Consequently, the results revealed that Agri-BB emissions during the episode were significantly derived from the agricultural areas in Northeast China.

Attributions of emission-reduction and meteorological conditions to typical heavy pollution episodes in a cold metropolis, northeast China

Heavy pollution episodes frequently occurred in winter in northeast China due to the multiple anthropogenic emissions coupled with adverse meteorological conditions, which increased the difficulty of environmental pollution control. To better enact strategies for mitigating air pollution in the post-pandemic era, daily pollutant concentration monitoring and meteorological data were used to evaluate the changes and meteorological factors of air pollutants before (2019) and during (2020) the lockdown in Harbin City, northeast China. Moreover, typical pollution episodes under COVID-19 lockdown were identified, and their emission sources, meteorology conditions, and regional pollution transportation were analyzed. The results showed significant decreases in NO2, PM10 and CO, while O3 increased, and no differences in PM2.5 and SO2 during the lockdown compared with non-lockdown periods. It indicated that reduced activities of transportation resulted in reductions of NO2 concentrations by 16%, and stationary emission sources were less affected. Correlation between PM2.5 and O3 tended to change from positive to negative as the threshold of PM2.5 = 90 μg m−3, with the main controlling factor changed from their common gaseous precursors to meteorological conditions (temperature &amp;lt;0°C and wind speed &amp;lt;2 m s−1). Pollution days were concentrated in the COVID-19 lockdown period with PM2.5 as the primary pollutant. SO2 dominant pollution and PM2.5 dominant pollution were distinguished from six sustained heavy pollution events. PM2.5 and SO2 played essential roles in SO2 dominant pollution, which derived from local emissions of coal combustion and firework discharge. PM2.5 dominant pollution might be chemical transformed from coal burning, vehicle exhaust, and other secondary precursors, which was affected and aggravated by CO, NO2, high relative humidity and low wind speed affected by local emission and long-distance transport.

Measurement report: Dust and anthropogenic aerosols' vertical distributions over northern China dense aerosols gathered at the top of the mixing layer

Abstract. Over the past decades, northern China has been suffering from persistent air pollution caused by both fine and coarse atmospheric particles. Although there are plenty of theoretical and observational studies on aerosols in northern China, most of them only consider total aerosol concentrations and focus on heavy pollution episodes; the long-term vertical distributions of dust (coarse) and anthropogenic aerosols (fine) and their relationships with the mixing layer height (MLH) have not been revealed. In this study, the dust and anthropogenic aerosols' mass concentration and the MLH were retrieved by polarization Raman lidar over Beijing from May 2019 to February 2022. We found that large amounts of anthropogenic aerosols accumulate at the top of the mixing layer, which is most noticeable in summer, with monthly mean mass concentration up to 57 µg m−3. It is mainly influenced by the southward transport in the upper air, where the atmosphere is relatively stable and moist, favoring hygroscopic growth of particles. Dust mass concentration is discontinuous in the vertical direction, not only on the ground but also in lofted layers that reach up to several kilometers. The heights of these lofted dust layers exhibited apparent seasonal dependence, with the height of the main dust layer gradually ascending from 1.1 km to about 2.5 km from April to June and below 3 km from October to December. In addition, there is a significant negative correlation between bottom anthropogenic aerosols' mass concentration and the MLH, and an inverse function fit is more suitable to characterize this relationship, while the relationship between bottom dust mass concentration and the MLH is insignificant. These results will enhance our understanding of the sophisticated interactions between dust and anthropogenic aerosols, the MLH, and regional transport in northern China. It will also help to refine atmospheric chemistry models and improve surface prediction capabilities.

Assessment of the impacts of cloud chemistry on surface SO2 and sulfate levels in typical regions of China

Abstract. A regional online chemical weather model, Weather Research and Forecasting (WRF)/China Meteorological Administration Unified Atmospheric Chemistry Environment (CUACE), is used to assess the contributions of cloud chemistry to the SO2 and sulfate levels in typical regions of China. Upon comparison with several time series of in situ cloud chemical observations on Mountain Tai in Shandong Province of China, the CUACE cloud chemistry scheme is found to reasonably reproduce the observed cloud consumption of H2O2, O3, and SO2 and the production of sulfate, and it is consequently used in the regional assessment of a heavy pollution episode and monthly average of December 2016. During the cloudy period in the heavy pollution episode, sulfate production increased by 60 %–95 % and SO2 production reduced by over 80 %. The cloud chemistry mainly affects the middle and lower troposphere below 5 km as well as within the boundary layer, and it contributes significantly to the SO2 reduction and sulfate production in central-east China. Among these four typical regions in China, the Sichuan Basin (SCB) is the most affected by the cloud chemistry, with an average SO2 abatement of about 1.0–10.0 ppb and sulfate increase of about 10.0–70.0 µg m−3, followed by the Yangtze River Delta (YRD) and the southeast of the North China Plain (NCP), where SO2 abatement is about 1.0–5.0 ppb and sulfate increase is about 10.0–30.0 µg m−3. However, the cloud chemistry contributions to the Pearl River Delta (PRD) and the northwest of the NCP are not significant due to lighter pollution and less water vapor than the other regions.

Observations and explicit modeling of summer and autumn ozone formation in urban Beijing: Identification of key precursor species and sources

Due to the complexity and nonlinearity of the ozone (O3) production, it is vital to understand the detailed knowledge of ozone–precursor relationship for the formulation of effective mitigation of surface ozone pollution. In this study, continuous measurements of O3, volatile organic compounds (VOCs), and related parameters were conducted at an urban site of Beijing in the summer and autumn of 2019. The photochemical box model contained the Master Chemical Mechanism (MCMv3.3.1) was used to reveal the detailed information on the photochemical O3 formation. Results show that the average concentration of total VOCs (TVOC) was 31.2 ± 10.7 ppb and 37.8 ± 18.9 ppb during the summer and autumn campaign, respectively, with the largest contribution from alkanes in both seasons, which mainly originated from liquefied petroleum gas (LPG) usage (20.2%–22.6%), gasoline vehicular exhaust (21.0%–21.6%), diesel vehicular exhaust (18.1%–18.3%), solvent usage (20.4%–24.1%), and fuel evaporation (16.4%–17.4%) that identified by positive matrix factorization (PMF) model. Heavy ozone pollution episodes were observed and the net local O3 production rate during summer (EP1) and autumn (EP2) pollution episode was 9.87 ± 0.62 ppbv h−1, and 9.44 ± 1.18 ppbv h−1, respectively, which was both dominated by the reaction between HO2 with NO. The analysis of relative incremental reactivity (RIR) and O3-NOx-VOC isopleth shows that ozone formation was VOC-limited in urban Beijing, with alkenes and aromatics contributed the most to O3 formation in summer and autumn, respectively. In addition, modellings for various emission reduction scenarios were carried out, indicating the reduction of gasoline vehicles emissions in summer and both reduction of gasoline vehicles and solvent usage emissions in autumn is the best measures to efficiently reduce O3 pollution. These results improved our understanding of O3 precursors and their impact on ozone production and provided a more targeted reference for controlling ozone pollution in Beijing.

Characterizing near-ground-layer structure changes during a heavy air pollution episode in a remote urban area of northwest China

Characterizing near-ground-layer structure changes during a heavy air pollution episode in a remote urban area of northwest China

Relationship between atmospheric pollution and polycyclic aromatic hydrocarbons in fresh snow during heavy pollution episodes in a cold city, northeast China

Air quality index (AQI) and air pollutants during two typical pollution episodes, and polycyclic aromatic hydrocarbons (PAHs) in fresh snow after each episode in the winter 2019 across Harbin City in northeast China were investigated to explore the co-environmental behaviors. Significantly greater values of AQI and PAHs were found in the more serious atmospheric pollution episode (episode Ⅱ), demonstrating that PAHs in fresh snow is a robust indicator. PM2.5 was the primary air pollutant in both episodes based on PM2.5/PM10 ratios, which might be attributed to fine particulate converted from gas-to-particle process. PM2.5 and 4-ring PAHs significantly positive correlated, indicating that airborne particulate PAHs were co-emitted and co-transported with atmospheric fine particles released from coal combustion and vehicular emission under low temperature and high relative humidity. 3- and 4- rings PAHs were dominant in episode Ⅱ, while 5- and 6- rings PAHs were found the lowest in both episodes. These characteristics reflected that long-range transportation of coal and biomass burning were from the surrounding areas, while vehicle exhausts were mainly from local emissions. Except for the impact of local pollution source emissions, the regional transport could make a greater contribution in a more serious pollution event.

Variations of inhalation risks during different heavy pollution episodes based on 3-year measurement of toxic components in size-segregated particles

Toxic metals (TMs) and polycyclic aromatic hydrocarbons (PAHs) in size-segregated particles during common days (CD) and different heavy pollution (HP) episodes were measured during 2018–2021 in a Chinese megacity. The Multiple Path Particle Dosimetry Model (MPPD) was performed to estimate deposition efficiency, and then inhalation risks in the human pulmonary region during different types of HP were assessed and compared. The higher pulmonary deposition efficiency of PAHs and TMs during all types of HP than those during CD was confirmed. The accumulative incremental lifetime cancer risk (ILCR) of different HP were 2.42 × 10−5, 1.52 × 10−5, 1.39 × 10−5, 1.30 × 10−5 and 2.94 × 10−6 for HP4 (combustion sources HP), HP1 (ammonium nitrate HP), HP5 (mixed sources HP), HP3 (resuspended dust HP) and HP2 (ammonium sulfate HP), respectively. The accumulative hazard quotient (HQ) during different HP episodes decreased in the order of HP4 (0.32) > HP3 (0.24) > HP1 (0.22) > HP5 (0.18) > HP2 (0.05). The inhalation risks were dominated by Ni and Cr, what's more, the HQ of Ni and ILCR of Cr during the five HP episodes shared a similar size distribution pattern. However, the characteristic components during different HP episodes and their size distributions of them were distinctive. The size distribution of inhalation risks of the related components (Ni, Cr, BaP, and As) from the combustion process during HP4 peaked at fine mode (0.65–2.1 μm). The size distribution of inhalation risks of the dust-related components (Mn and V) and the components (As and BaP) that are likely to volatilize and re-distribution peaked at coarse mode (2.1–3.3 μm) during HP3. Notably, Mn and Co as catalysts at fine mode could increase the degree of secondary formation and toxicity.

Seasonal variation of particle hygroscopicity and its impact on cloud-condensation nucleus activation in the Beijing urban area

Hygroscopicity is a key parameter for characterizing the ability of particles to be activated as cloud-condensation nuclei (CCN). In this study, we present a 10-month size-resolved measurement of the hygroscopicity of particles with diameters of 50, 100 and 200 nm in the Beijing urban area using a Hygroscopicity-Tandem Differential Mobility Analyzer (H-TDMA). Compared with that in other studies conducted in China, the hygroscopicity parameter (κ) in this study was relatively higher than that in the Pearl River Delta region but lower than that in the Yangtze River Delta region. As the mass fraction of inorganic matter (especially nitrate) increased, the particles became more hygroscopic during spring and summer, as influenced by the chemical composition. Polluted southerly air masses also enhanced particle hygroscopicity. The CCN concentration was calculated based on κ-Köhler theory, with a moderate supersaturation of 0.4%. The critical diameter of particles as potential CCNs was smaller in spring than that in the other seasons. The critical diameters of aerosols in autumn, winter and spring were 142, 123 and 114 nm, respectively, with calculated CCN concentrations of 1683, 1909 and 1765 cm−3, respectively. Activation ratios, calculated as CCN divided by condensation nuclei (CN), were 0.13, 0.15 and 0.18 in autumn, spring and summer, respectively. During episodes of heavy pollution, the CCN concentration highly depended on the particle mass loading, as the accumulation mode dominated the particle number size distribution and the chemical composition was quasi-homogeneous. However, under other conditions, both particle size and chemical composition were important. This study revealed the relationship between particle hygroscopicity, CCN and air pollution level, and it will be useful for evaluating the environmental and climatic effects of aerosols.

Effects of local aerosol and transported dust pollution on the surface energy balance over farmland in eastern China during spring

Compared with the urban boundary layer, air pollution–surface energy budget interactions in farmland areas are relatively sparse. To investigate the roles of local aerosol and transported dust pollution on the surface energy balance over farmland, a field experiment was conducted during spring 2016 in eastern China. The heavy pollution episodes during the measurement period were typically accompanied by easterly winds, low wind speeds, and high relative humidity. On polluted days, relative to clean days, both downward and upward shortwave radiation decreased by 46%, while downward and upward longwave radiation increased by 4% and 1%. The combined effects of the four radiation components resulted in a 33% reduction in net radiation on polluted days, and thus, the surface energy budget changed. Polluted days had 15% (58%) less sensible (latent) heat flux than clean days. This resulted in a higher daytime Bowen ratio on polluted days (0.83) compared to clean days (0.44). In a case analysis of dust pollution, high wind speeds and continuous high pressure induced the outbreak of the dust pollution episodes. Compared to local pollution events, the latent (sensible) heat flux was reduced more (less) than that in transported dust pollution events. Generally, this work has important implications for understanding the surface energy balance across land–atmosphere interactions over farmland regions, which are experiencing frequent aerosol pollution from local emissions and transboundary dust events.