Aerosol Variability Research Articles

Spatial Gap-Filling of Himawari-8 Hourly AOD Products Using Machine Learning with Model-Based AOD and Meteorological Data: A Focus on the Korean Peninsula

Given the complex spatiotemporal variability of aerosols, high-frequency satellite observations are essential for accurately mapping their distribution. However, optical remote sensing encounters difficulties in detecting Aerosol Optical Depth (AOD) over cloud-covered regions, creating data gaps that limit comprehensive environmental analysis. This study introduces a spatial gap-filling method for Himawari-8/Advanced Himawari Imager (AHI) hourly AOD data, using a Random Forest (RF) model that integrates meteorological variables and model-based AOD data. Developed and validated over South Korea from 1 January to 31 December 2019, the model effectively improved data coverage from 6% to 100%. The approach demonstrated high performance in blind tests, achieving a root mean square error (RMSE) of 0.064 and a correlation coefficient (CC) of 0.966. Meteorological analysis indicated optimal model performance under cold, dry conditions (RMSE: 0.047, CC: 0.956), compared to humid conditions (RMSE: 0.105, CC: 0.921). Validation against Aerosol Robotic Network (AERONET) ground observations showed that, while the original Himawari-8 data exhibited higher accuracy (RMSE: 0.189, CC: 0.815, n = 346), the gap-filled dataset maintained reasonable precision (RMSE: 0.208, CC: 0.711) and significantly increased the number of valid data points (n = 4149). Furthermore, the gap-filled dataset successfully captured seasonal AOD patterns, with values ranging from 0.245–0.300 in winter to 0.381–0.391 in summer, providing a comprehensive view of aerosol dynamics across South Korea.

Peplospheric Influences on Local Greenhouse Gas and Aerosol Variability at the Lamezia Terme WMO/GAW Regional Station in Calabria, Southern Italy: A Multiparameter Investigation

Peplospheric Influences on Local Greenhouse Gas and Aerosol Variability at the Lamezia Terme WMO/GAW Regional Station in Calabria, Southern Italy: A Multiparameter Investigation

Indian Ocean temperature anomalies modulate the interannual variability of springtime smoke aerosols over the Indochina Peninsula

Abstract Smoke aerosols released through frequent springtime fire activity over the Indochina Peninsula (ICP) seriously affect regional air quality, climate, and human health. However, the mechanisms driving the interannual variability of these smoke aerosols are not well understood. By analyzing multi-source historical (1980–2020) smoke aerosols and meteorological reanalysis data, we explore the response of springtime smoke aerosol changes over the ICP to the interannual variability of the Indian Ocean (IO) sea-surface temperature (SST). Our findings show a positive correlation between the variability of springtime smoke aerosol loading and the preceding winter Southeast IO (SEIO) SST anomalies. Warmer SEIO SST tends to weaken the trans-equatorial flow (TEF) and the local Hadley circulation. This weakening of the TEF impede cyclones development in the Bay of Bengal (BOB), thereby reducing southwest water vapor transport. Simultaneously, enhanced westerly winds over the northern BOB are blocked by the northwestern mountains of ICP. These winds converge and rise on the windward slopes, while descending on the leeward side with diminished humidity. Collectively, these dynamics lead to drier and hotter local meteorological conditions that favored fire-induced smoke aerosol emissions. Our findings highlight the role of the SEIO in regulating smoke aerosol variability and provide a scientific basis for developing strategies to manage smoke aerosol emissions over the ICP.

Effect of Regional Anthropogenic Aerosols on Tropical Cyclone Frequency of Occurrence

AbstractPrevious studies have highlighted the distinct impacts of anthropogenic aerosols from the Western and Eastern Hemispheres on past multi‐decadal changes in tropical cyclone frequency of occurrence (TCF). However, the detailed effect of subregional aerosol variations remained unclear. Using idealized simulations with a dynamical climate model, this study reveals that reduced aerosol emissions from Europe and the U.S. since 1980 may have equally contributed to increased TCF over the North Atlantic, with Europe playing a major role in the decreased TCF in the South Indian Ocean and the U.S. contributing to the decrease in TCF in the South Pacific. Additionally, increased aerosol emissions from India since 1980 may have played a major role in decreasing TCF over the western North Pacific compared to increased emissions from China. TCFs are projected to decrease for most global tropics toward the end of this century due to the dominant effect of increasing greenhouse gases.

Significant annual variations of firework-impacted aerosols in Northeast China: Implications for rethinking the firework bans

Fireworks are banned in many Chinese cities but never eliminated, reflecting strong public demand on this traditional activity for festival celebrations. On the other hand, the assessment of firework contributions to air pollution remains vague, raising concerns on the necessity of the mandatory bans. Here we investigated the characteristics of firework episodes in a megacity in Northeast China, based on field campaigns conducted in four successive winters during 2018–2022. Although prohibited, the firework influences remained evident during the Chinese New Year periods, as suggested by the enhancements of water-soluble potassium (K+). In addition, significant annual variations were identified for the firework episodes, with the following features observed. First, the firework-induced enrichment ratios of K+ and chloride exhibited increasing trends across years, climbing from 4.4 to 8.6 and from 1.7 to 2.9, respectively. Second, the enrichment ratio of sulfate dropped from 2.8 to 1.6, indicating that the firework contributions to sulfate decreased but remained considerable. Third, fireworks turned into an unimportant source for organic carbon and nitrate in the most recent winter of 2021–2022, with enrichment ratios of ∼1 for both species. Fourth, the firework-driven increases in fine particle concentration were as high as ∼100% for the two winters during 2019–2021, whereas the increase dropped sharply to ∼30% for 2021–2022. These variations were in line with the promotion of environmentally friendly fireworks. Our results indicated that the air pollution caused by fireworks could be reduced substantially by advanced manufacturing technologies and thus it is time to rethink the firework bans.

Stark seasonal contrast of fine aerosol levels, composition, formation mechanism, and characteristics in a polluted megacity.

In this study, we investigated the temporal variation of organic and inorganic aerosol with its optical properties in Mumbai (India), an urban coastal region. Mean PM2.5concentrations during the sampling period were 175μg/m3 (winter) and 90μg/m3 (summer). During winter, the average concentrations of organic (OC), elemental (EC), and water-soluble organic carbon (WSOC) were three times higher than in summer. Secondary organic carbon (SOC) contribution in OC was higher in summer (78%) than in winter (53%), and strong solar radiation in summer likely caused this outcome. Aerosols were slightly acidic in both seasons, with an average pH of 5.7 (winter) and 6.0 (summer). A correlation was observed between SOC and the acidity of particles in summer (R2 = 0.6), indicating some amount of acid-catalysed SOC formation. In both seasons, the sulphate oxidation ratio (SOR) was higher than the nitrate oxidation ratio (NOR), which may reflect a preference for SO2 oxidation over NO2 or the difference in partitioning ammonium nitrate into ammonium sulphate under high RH. The dominant mechanism of SOC formation (gas vs aqueous phase oxidation) also showed seasonal variation. In winter, a relatively steep reduced major axis (RMA) slope of O3/CO suggests gas phase oxidation was the dominant mechanism of SOC production. Winter has more BrC fraction than summer, indicating higher absorbing aerosols, though the efficiency of absorbing the light was higher in summer. To assess the radiative forcing of PM2.5 on a local scale, an effective carbon ratio (ECR) was computed. The findings pointed to a local radiative heating impact caused by PM2.5. The spectral slope ratio and MAE at 250 to 300nm ratio (E2/E3) revealed a higher abundance of high molecular weight species in WSOC during summer than in winter.

On the Biases of MERRA-2 Reanalysis and Ground-Based Measurements of Black Carbon Aerosols Over India

The precise measurement of black carbon (BC) and assessment of involved biases are very important considering its serious health and climatic effects. MERRA-2 reanalysis data (modern-era retrospective analysis for research and applications, version 2) of surface black carbon (SBC) and ground measurements by optical photometers (mostly Aethalometer) have been used widely to study the temporal and spatial variation of BC aerosols over India. However, a significant bias (more than 70%) between MERRA-2 SBC concentration and ground measurements of BC (by Aethalometer, referred as MBC (AE)) was observed by Malik and Aggarwal, (2021). In the current study, the possible reasons for this bias are further evaluated by comparing the MERRA-2 SBC and Aethalometer measurements against a reference photometer, i.e., continuous soot monitoring system (COSMOS). Three-year (2020-2022) SBC concentrations of MERRA-2 reanalysis data are compared against simultaneous measurements of BC by COSMOS (MBC (COSMOS)). Additionally, the biases in ground measurements are further investigated by comparing one-month (March 2023) observations of Aethalometer (MBC (AE)). These comparison results revealed a 40% underestimation in MERRA-2 reanalysis during 2020-2022. The higher underestimation (50%) of SBC during increased biomass emissions months (October to May), in contrast to the 25% underestimation during conventional emissions months (June to September), emphasizes the underestimation of biomass emissions inputs in MERRA-2 SBC reanalysis. The initial large bias between raw data of Aethalometer (MBC (AE-raw) = 1.92-1.98 times MBC (COSMOS)) get reduced significantly when correction due to multiple scattering in the filter media and mass absorption cross-section (MAC) are incorporated to correct the Aethalometer data (MBC (AE-corr) = 1.15-1.18 times MBC (COSMOS)). The findings of this study underscore the need to harmonize the correction methods for multiple scattering and redefine the MAC values for Aethalometer measurements as well as updating the anthropogenic emission inventories in MERRA-2 SBC reanalysis.

Turbulent fluxes of aerosol and heat in a desertified area during intermittent emission of dust aerosol

Based on fluctuations measurement results in the components of wind speed, air temperature and concentration of aerosol particles on a desertified area in the Astrakhan region under conditions of intermittent emission of dust aerosol, vertical turbulent fluxes of dust aerosol and heat were determined. Using spectral analysis, the temporal variability of the horizontal and vertical components of wind speed, air temperature and concentration of dust aerosol particles was characterized. It is shown that the intermittent emission of the dust aerosol is determined by low-frequency convective-induced variations in the horizontal component of wind speed when the threshold saltation speed is exceeded. Significant differences in the spatiotemporal variability of vertical heat transfer and dust aerosol were revealed. The 30-minute average values of heat fluxes (90–158 W/m2) and dust aerosol (7.2–27.5 cm–2cm–1), as well as the rate of heat removal (14–21 cm/s) and dust aerosol (10–16 cm/s).

Impacts of meteorology and mixing height on radioactive and stable aerosols in Bratislava, Slovakia

This study investigated the variability of radioactive and stable aerosols (7Be, 210Pb, 137Cs, 40K, PM10, and PM2.5) in relation to mixing layer height (MLH) based on outdoor radon and meteorological factors in Bratislava, Slovakia from 2017 to 2021. Aerosol concentrations exhibit distinct seasonal patterns, with higher 7Be concentrations in summer and lower in winter, while 137Cs, 40K, 210Pb, PM10 and PM2.5 showed almost the opposite trends. Different statistical techniques, including Pearson's correlation analysis, multiple regression analysis (MRA), and canonical correlation analysis (CCA), were employed to elucidate the intricate relationships between aerosol concentrations, MLH, and meteorological parameters. The MRA identified a significant correlation between aerosol variability and specific predictors, while the CCA highlighted the differential influence of MLH and meteorological parameters on aerosol concentrations. The analysis revealed that temperature, MLH, and relative humidity are the primary factors influencing aerosol concentrations, underscoring their pivotal role in environmental dynamics.

Comparative analysis of winter composite-PM2.5 in Central Indo Gangetic Plain cities: Combined organic and inorganic source apportionment and characterization, with a focus on the photochemical age effect on secondary organic aerosol formation

To gain insights into air quality dynamics, a high-end instrument such as High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) alongside an Aethalometer was used to measure the Composite PM2.5 (C-PM2.5) in Lucknow and Kanpur during winter. It encompasses non-refractive PM2.5 (NR-PM2.5) and Black Carbon (BC) mass concentrations. Significant variation was noted in average C-PM2.5 concentrations at both sites, as 168.8 ± 61.3 μg m−3 in Lucknow and 90.7 ± 25.7 μg m−3 in Kanpur. Organics emerged as the predominant component, constituting ∼55%–65% of the C-PM2.5 mass, followed by inorganics (24% and 30%) and BC (20% and 8%). The present study employs Positive Matrix Factorization (PMF) on combined organic and inorganic source apportionment, resolving eight and seven source factors at Lucknow and Kanpur, respectively. Both sites exhibit significant contributions from solid-fuel combustion organic aerosol (SFC-OA), with ∼11% in Lucknow and 8% in Kanpur. However, SFC-OA mass concentration in Lucknow, at 24.67 μg m-³, is nearly double that in Kanpur (12.05 μg m-³). This was likely due to domestic coal burning in the nearby households, unregulated open burning, and burning of garbage on roadsides. The study shows that both sites were affected by oxidized biomass burning OA (O-BBOA) emissions, with increased concentration during the night due to dark oxidation by NO3 radicals. The diurnal variation of secondary organic aerosols (SOA), such as O-BBOA and semi-volatile oxygenated OA (SVOOA), shows increasing concentration during daytime hours. Therefore, the photochemical aging (ta) role in SOA formation was analyzed, and it was revealed that the formation might primarily be driven by photochemical oxidation. Additionally, two inorganic-rich factors, sulfate and nitrate-related OA (SO4-OA and NO3-OA) at both sites and additional ammonium chloride-related OA (NH4Cl-OA) resolved at Lucknow. Our study shows that NO3-OA and SO4-OA formation was dominated by aqueous phase processes due to high relative humidity and decline in concentration with increasing ta (ta > 30 h) during winter.

Anthropic-Induced Variability of Greenhouse Gasses and Aerosols at the WMO/GAW Coastal Site of Lamezia Terme (Calabria, Southern Italy): Towards a New Method to Assess the Weekly Distribution of Gathered Data

The key to a sustainable future is the reduction in humankind’s impact on natural systems via the development of new technologies and the improvement in source apportionment. Although days, years and seasons are arbitrarily set, their mechanisms are based on natural cycles driven by Earth’s orbital periods. This is not the case for weeks, which are a pure anthropic category and are known from the literature to influence emission cycles and atmospheric chemistry. For the first time since it started data gathering operations, CO (carbon monoxide), CO2 (carbon dioxide), CH4 (methane) and eBC (equivalent black carbon) values detected by the Lamezia Terme WMO/GAW station in Calabria, Southern Italy, have been evaluated via a two-pronged approach accounting for weekly variations in absolute concentrations, as well as the number of hourly averages exceeding select thresholds. The analyses were performed on seven continuous years of measurements from 2016 to 2022. The results demonstrate that the analyzed GHGs (greenhouse gasses) and aerosols respond differently to weekly cycles throughout the seasons, and these findings provide completely new insights into source apportionment characterization. Moreover, the results have been combined into a new parameter: the hereby defined WDWO (Weighed Distribution of Weekly Outbreaks) normalizes weekly trends in CO, CO2, CH4 and eBC on an absolute scale, with the scope of providing regulators and researchers alike with a new tool meant to better evaluate anthropogenic pollution and mitigate its effects on the environment and human health.

Can we achieve atmospheric chemical environments in the laboratory? An integrated model-measurement approach to chamber SOA studies.

Secondary organic aerosol (SOA), atmospheric particulate matter formed from low-volatility products of volatile organic compound (VOC) oxidation, affects both air quality and climate. Current 3D models, however, cannot reproduce the observed variability in atmospheric organic aerosol. Because many SOA model descriptions are derived from environmental chamber experiments, our ability to represent atmospheric conditions in chambers directly affects our ability to assess the air quality and climate impacts of SOA. Here, we develop an approach that leverages global modeling and detailed mechanisms to design chamber experiments that mimic the atmospheric chemistry of organic peroxy radicals (RO2), a key intermediate in VOC oxidation. Drawing on decades of laboratory experiments, we develop a framework for quantitatively describing RO2 chemistry and show that no previous experimental approaches to studying SOA formation have accessed the relevant atmospheric RO2 fate distribution. We show proof-of-concept experiments that demonstrate how SOA experiments can access a range of atmospheric chemical environments and propose several directions for future studies.

TAMU TRACER: Targeted Mobile Measurements to Isolate the Impacts of Aerosols and Meteorology on Deep Convection

Abstract Difficulty in using observations to isolate the impacts of aerosols from meteorology on deep convection often stems from the inability to resolve the spatiotemporal variations in the environment serving as the storm’s inflow region. During the U.S. Department of Energy (DOE) Tracking Aerosol Convection interactions Experiment (TRACER) in June–September 2022, a Texas A&M University (TAMU) team conducted a mobile field campaign to characterize the meteorological and aerosol variability in air masses that serve as inflow to convection across the ubiquitous mesoscale boundaries associated with the sea and bay breezes in the Houston, Texas, region. These boundaries propagate inland over the fixed DOE Atmospheric Radiation Measurement (ARM) sites. However, convection occurs on either or both the continental or maritime sides or along the boundary. The maritime and continental air masses serving as convection inflow may be quite distinct, with different meteorological and aerosol characteristics that fixed-site measurements cannot simultaneously sample. Thus, a primary objective of TAMU TRACER was to provide mobile measurements similar to those at the fixed sites, but in the opposite air mass across these moving mesoscale boundaries. TAMU TRACER collected radiosonde, lidar, aerosol, cloud condensation nuclei (CCN), and ice nucleating particle (INP) measurements on 29 enhanced operations days covering a variety of maritime, continental, outflow, and prefrontal air masses. This paper summarizes the TAMU TRACER deployment and measurement strategy, instruments, and available datasets and provides sample cases highlighting differences between these mobile measurements and those made at the ARM sites. We also highlight the exceptional TAMU TRACER undergraduate student participation in high-impact learning activities through forecasting and field deployment opportunities.

MAP-IO: an atmospheric and marine observatory program on board Marion Dufresne over the Southern Ocean

Abstract. This article is devoted to the presentation of the MAP-IO observation program. This program, launched in early 2021, has enabled the observation of nearly 700 d of measurements over the Indian and Southern Ocean with the equipment of 17 meteorological and oceanographic scientific instruments on board the ship Marion Dufresne. Several observational techniques have been developed to respond to the difficulties of observations on board the ship, in particular for passive remote sensing data, as well as for quasi-autonomous data acquisition and transfer. The first measurements made it possible to draw up unprecedented climatological data of the Southern Ocean regarding the size distribution and optical thickness of aerosols, the concentration of trace gases and greenhouse gases, UV, and integrated water vapor. High-resolution observations of phytoplankton in surface waters have also shown a great variability in latitude in terms of abundance and community structure (diversity). The operational success of this program and these unique scientific results together establish a proof of concept and underline the need to transform this program into a permanent observatory. The multi-year rotations over the Indian Ocean will enable us to assess the trends and seasonal variability of phytoplankton, greenhouse gases, ozone, and marine aerosols in a sensitive and poorly documented climatic region. Without being exhaustive, MAP-IO should make it possible to better understand and assess the biological carbon pump, to study the variability of gases and aerosols in a region that is remote in relation to the main anthropogenic sources, and to monitor the transport of stratospheric ozone by the Brewer–Dobson circulation. The meteorological MAP-IO data set is publicly available at https://www.aeris-data.fr/catalogue-map-io/ (last access: 26 August 2024) (atmospheric data) and at https://doi.org/10.17882/89505 (Thyssen et al., 2022a) (phytoplankton data).

The Influences of Indian Monsoon Phases on Aerosol Distribution and Composition over India

This study investigates the impacts of summer monsoon activity on aerosols over the Indian region. We analyze the variability of aerosols during active and break monsoon phases, as well as strong and weak monsoon years, using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Our findings show a clear distinction in aerosol distribution between active and break phases. During active phases, the Aerosol Optical Depth (AOD) and aerosol extinction are lower across the Indian region, while break phases are associated with higher AOD and extinction. Furthermore, we observed a significant increase in AOD over Central India during strong monsoon years, compared to weak monsoon years. Utilizing the vertical feature mask (VFM) data from CALIPSO, we identified polluted dust and dusty marine aerosols as the dominant types during both active/break phases and strong/weak monsoon years. Notably, the contributions of these pollutants are significantly higher during break phases compared to during active phases. Our analysis also reveals a shift in the origin of these aerosol masses. During active phases, the majority originate from the Arabian Sea; in contrast, break phases are associated with a higher contribution from the African region.

Tiny rain makers: How aerosols shape extreme rainfall simulation accuracy

Given the rapid spatiotemporal variability of aerosols and their complex impacts on the Earth system, investigating the role of aerosols in modelling extreme weather events, particularly various extreme rainfalls, remains limited. This study explored extreme rainfall simulation sensitivity to aerosol properties, transport and seasonality over the UK and Ireland during four seasons in 2020 by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model. Two sets of high-resolution simulations, one including aerosol direct and indirect effects and the other one without any aerosol effects, were conducted to investigate the improvements due to aerosol inputs. Meteorological results were verified using ground and satellite observations to examine the reliability of simulations. The 12 extreme rainfall events during the study months were classified by their backward trajectories from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, and their simulation accuracies were quantified through six spatiotemporal metrics and one overall score. By comprehensive analyses of the simulation performances under different conditions, it is found that the model performs better in simulating rainfall events driven by sea salt aerosols (SSA) compared to those promoted by anthropogenic aerosols. Air masses transported from the Arctic and North Atlantic Ocean also help achieve higher rainfall simulation accuracy than European air masses. Rainfall simulations for winter and autumn events outperform those for spring and summer events. When considering aerosol effects in simulations, almost half of the events showed improved performance, while an equal number experienced a decrease and a small proportion remained unchanged. The most remarkable improvements are observed in rainfall simulations with higher concentrations of SSA and the participation of anthropogenic aerosols, while simulations promoted only by anthropogenic aerosols all experience performance reductions. The aerosol effects also led to significant increases in monthly rainfalls, accompanied by great reductions of Cl in larger particle size aerosols and NO3 in smaller particle size aerosols.

Interdecadal variations of aerosol and its composition over the Fenwei Plain based on multi-source observations

Understanding the variations and potential source of air pollution is essential for implementing targeted mitigation actions. However, the distribution and long-term trends of Aerosol Optical Depth (AOD) and its components over the Fenwei Plain (FWP) have not been thoroughly investigated. Furthermore, the potential source contribution of AOD loading is still unclear. Thus, maximum synthesis and Mann-Kendall trend (MK) test with Sen's Slope methods are employed to reveal the spatiotemporal variation characteristics of AOD over the FWP. The Potential Source Contribution Function (PSCF) model was applied to analyze the potential source contribution of AOD over the FWP. Results demonstrated that the AOD in spatial pattern exhibited consistency with the topography. AOD over the FWP fluctuated annually from 2000 to 2020, with an increase in the previous decade followed by a gradual decline after 2011. There was a significant monthly variation in AOD with higher values in August (0.47±0.21) and lower in November (0.29±0.12). A positive AOD trend was confirmed from 2000 to 2010 yet a negative trend is identified from 2011 to 2020. The sulfate aerosol (AODSU) exhibited an increasing trend over an extended period. Clear-sky radiation shows a negative trend at the surface and the top of the atmosphere (TOA) from 2000 to 2010, which is consistent with the trend in AOD. The AOD in FWP was primarily influenced by local emissions, with contributions from northern and northwestern sources. This research offers an enhanced overarching comprehension of the distribution and regional climate effects of aerosols over the FWP.

Evidence of a dual African and Australian biomass burning influence on the vertical distribution of aerosol and carbon monoxide over the southwest Indian Ocean basin in early 2020

Abstract. During the 2020 austral summer, the pristine atmosphere of the southwest Indian Ocean (SWIO) basin experienced significant perturbations. This study examines the variability of aerosols and carbon monoxide (CO) over this remote oceanic region and investigates the underlying processes in the upper troposphere–lower stratosphere (UT-LS). Aerosol profiles in January and February 2020 revealed a multi-layer structure in the tropical UT-LS. Numerical models – the FLEXible PARTicle dispersion model (FLEXPART) and the Modèle Isentropique de transport Mésoéchelle de l'Ozone Stratosphérique par Advection (MIMOSA) – indicated that the lower-stratospheric aerosol content was influenced by the intense and persistent stratospheric aerosol layer generated during the 2019–2020 extreme Australian bushfire events. A portion of this layer was transported eastward by prevailing easterly winds, leading to increased aerosol extinction profiles over Réunion on 27 and 28 January. Analysis of advected potential vorticity revealed isentropic transport of air masses containing Australian biomass burning aerosols from extratropical latitudes to Réunion at the 400 K isentropic level on 28 January. Interestingly, we found that biomass burning (BB) activity in eastern Africa, though weak during this season, significantly influenced (contributed up to 90 % of) the vertical distribution of CO and aerosols in the upper troposphere over the SWIO basin. Ground-based observations at Réunion confirmed the simultaneous presence of African and Australian aerosol layers. This study provides the first evidence of African BB emissions impacting the CO and aerosol distribution in the upper troposphere over the SWIO basin during the convective season.

Evaluating the impact of control measures on sulfate-nitrate-ammonium aerosol variations and their formation mechanism in northern China during 2022 Winter Olympic Games

Sulfate, nitrate, and ammonium (SNA) significantly contribute to fine particulate matter (PM2.5). To ensure good air quality during 2022 Winter Olympic Games (WOG), stringent control measures were implemented in northern China. In this study, comprehensive atmospheric observations were conducted from 2022 January to March in four representative cities to investigate the changes in SNA and their formation mechanism in response to these control measures. The SNA concentrations obviously decreased (29.45%–42.83%) during the control periods in the four cities, but their proportion of PM2.5 remained relatively stable (>50%). SNA was the key factor driving the decrease and increase in the PM2.5 concentration during WOG, with nitrate making the most prominent contribution. The formation of SNA was largely dominated by aqueous heterogeneous chemistry instead of gas-phase oxidation. However, the aerosol liquid water content (ALWC) decreased while odd oxygen (OX) increased during the control periods. Such a variation influenced the role of aqueous heterogeneous and gas-phase reactions in SNA formation, with the former's dominant role being replaced by the latter. After the control periods, the aqueous heterogeneous reactions were enhanced again due to the increased ALWC. Among the cities in the study region, SNA formation became more intense from north to south with increased air temperature and relative humidity (RH). Moreover, ISORROPIA-II thermodynamic modelling revealed notable impacts of sulfate, ammonium, and nonvolatile cations (NVCs) on variations in particle acidity throughout WOG. These results provide a more comprehensive understanding of SNA responses to pollution control on a regional scale and insight into future conventional control.

Vulnerability assessment of aerosol and climate variability for rice and maize yield using EO datasets for sustainable agriculture over India.

Human-generated aerosol pollution gradually modifies the atmospheric chemical and physical attributes, resulting in significant changes in weather patterns and detrimental effects on agricultural yields. The current study assesses the loss in agricultural productivity due to weather and anthropogenic aerosol variations for rice and maize crops through the analysis of time series data of India spanning from 1998 to 2019. The average values of meteorological variables like maximum temperature (TMAX), minimum temperature (TMIN), rainfall, and relative humidity, as well as aerosol optical depth (AOD), have also shown an increasing tendency, while the average values of soil moisture and fraction of absorbed photosynthetically active radiation (FAPAR) have followed a decreasing trend over that period. This study's primary finding is that unusual variations in weather variables like maximum and minimum temperature, rainfall, relative humidity, soil moisture, and FAPAR resulted in a reduction in rice and maize yield of approximately (2.55%, 2.92%, 2.778%, 4.84%, 2.90%, and 2.82%) and (5.12%, 6.57%, 6.93%, 6.54%, 4.97%, and 5.84%), respectively. However, the increase in aerosol pollution is also responsible for the reduction of rice and maize yield by 7.9% and 8.8%, respectively. In summary, the study presents definitive proof of the detrimental effect of weather, FAPAR, and AOD variability on the yield of rice and maize in India during the study period. Meanwhile, a time series analysis of rice and maize yields revealed an increasing trend, with rates of 0.888 million tons/year and 0.561 million tons/year, respectively, due to the adoption of increasingly advanced agricultural techniques, the best fertilizer and irrigation, climate-resilient varieties, and other factors. Looking ahead, the ongoing challenge is to devise effective long-term strategies to combat air pollution caused by aerosols and to address its adverse effects on agricultural production and food security.