We describe the approach to estimating the atmospheric carbon dioxide (CO2) for the Aerosol and Carbon Detection Lidar (ACDL) onboard the Atmospheric Environment Monitoring Satellite (AEMS). The method estimates the optimal state vector by maximizing the measurement posterior probability under a given prior state vector probability distribution. A priori constraint considering the spatial correlation is used as regularization to solve the ill-posed problem. We ran a series of observing system simulation experiments to demonstrate the critical outcome and character percentage uncertainty reduction. The results show that the state vector uncertainty can be reduced by ∼ 10% near the surface for the single sounding. The CO2 column-averaged dry air mole fraction (XCO2) derived by this algorithm is more stable than that obtained by the conventional algorithm and enables the monitoring of concentration changes for the multiple soundings. Similar to the Total Carbon Column Observing Network (TCCON), the averaging kernel is also provided for the subsequent flux inversion. Our simulation experiments demonstrate that the structure of the prior error covariance plays an important role in revealing vertical information from observations. In addition, we applied this algorithm to an airborne ACDL experiment for the retrieval of atmospheric CO2 over Bohai Bay on March 14, 2019. AEMS’s observations with a small footprint will yield important information on the carbon cycle, especially for small but strong emission sources.

Kinetic studies of the reaction of Cl atoms with ethyl 2-chloroacetoacetate, CH3C(O)CHClC(O)OCH2CH3, (k1) and methyl 2-chloroacetoacetate, CH3C(O)CHClC(O)OCH3, (k2) have been developed for the first time using SPME/GC-FID and in situ FTIR spectroscopy at (298 ± 2) K and 1000 mbar in glass atmospheric chambers. Relative rate coefficients obtained by Fourier Transform Infrared Spectroscopy (FTIR) using different reference compounds, were the following (in cm3.molecule−1.s−1): kE2CAA-FTIR= (2.41 ± 0.57) × 10−10 and kM2CAA-FTIR= (2.16 ± 0.85) × 10−10. Similar and reproducible values were obtained using Gas Chromatography equipped with Flame Ionization Detection coupled with Solid Phase Micro Extraction (SPME), kE2CAA-GC-FID = (2.54 ± 0.81) × 10−10 and kM2CAA-GC-FID = (2.34 ± 0.87) × 10−10 all values in units of cm3.molecule−1.s−1. In addition, product studies were performed in similar conditions to the kinetic experiments to identify the reaction products and postulate their tropospheric degradation mechanisms. The reaction of Cl atoms with saturated esters initiates via H-atom abstraction from the alkyl groups of the molecule. Formyl chloride, chloroacetone, and acetyl chloride were positively identified as reaction products by FTIR. On the other hand, acetyl chloride, 1,1,1-trichloropropan-2-one, 1,1-dichloropropan-2-one, 1-chloropropan-2-one, ethyl chloroformate, and methyl chloroformate were identified by the GC-MS technique. Structure–Activity Relationship (SAR), calculations were also performed to estimate the more favorable reactions pathways in agreement with the products observed. The atmospheric implications of these reactions were assessed by the estimation of the residence times of the chloroesters studied as following: τCl-E2CAA = 1.47 days, and τCl-M2CAA = 1.57 days. Additionally, the possible impact of the emission of chloro acetoacetates in rain acidification was evaluated from the moderate Acidification Potentials (AP), 0.19, and 0.21 obtained for E2CAA and M2CAA, respectively.

At higher concentrations, tropospheric ozone can cause respiratory difficulties, premature human mortality and can harm vegetation by reducing photosynthesis and its growth. It is an oxidant and also an important greenhouse gas with positive feedback to temperature. It is produced as a byproduct of chemical reactions involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) in the presence of sunlight, rather than being emitted directly to the atmosphere. Here, we analyse the seasonal and inter-annual variability, long-term trends and radiative forcing of the tropospheric column ozone (TPO) in India for the period of 2005–2020 using satellite and ground-based data. The analysis shows very high annual averaged TPO in the Indo-Gangetic Plain (IGP) and North West India, about 45–50 DU. Our findings reveal a significant increase of TPO in India, with the highest trend in the peninsular region (0.295 ± 0.0617 DU/year) and the lowest in North West (0.179 ± 0.048 DU/year). The increase in tropospheric ozone reveals a warming of about 0.5 °C in the troposphere as there is an associated radiative forcing of about 0.2–0.5 W/m2 at the tropopause (125 hPa); indicating that the increasing tropospheric ozone is a great concern for regional warming, public health and ecosystem dynamics.

Elevated ozone (O3) concentration during the COVID-19 lockdown is a matter of great concern, but the changes of its sensitivities to key precursors remains unclear. This study utilized the Community Multiscale Air Quality (CMAQ) model coupled with the Higher-order Decoupled Direct Method in Three Dimensions (HDDM-3D) and the process analysis (PA) modules to reveal in detail the changes in O3-precursors sensitivities and the contribution of major chemical and physical processes to O3 formation/loss during the month-long COVID-19 lockdown in early 2020 over the Yangtze River Delta (YRD) region of China. The results indicate that the contributions (absolute value) of gas-phase chemistry to O3 and Ox (i.e., O3+NO2) were reduced by 35–50% and 8–24%, respectively, under lockdown-specific (LCD) scenario compared with the business-as-usual (BAU) scenario in the highly urbanized areas of eastern and central YRD. Under the BAU (LCD) scenario, the first-order and second-order O3-NOx sensitivities averaged about −25 (−36) μg/m3 and about 8 (28) μg/m3, respectively. These 1st- and 2nd-order sensitivities of O3 to NOx were both intensified due to COVID-19 lockdown, which potentially contributed to O3 increases of between 5 and 10 μg/m3. In other words, the concentration of O3 and its rate of increase were both amplified due to COVID-19 lockdown. Overall, this study highlighted a significant wintertime “NOx reduction disbenefit” phenomenon over YRD because of both strong 1st-order (negative) and 2nd-order (positive) O3 sensitivities to NOx emissions, which were further reinforced due to COVID-19 lockdown.

A novel approach for parametrization of the cloud effect on ultraviolet (UV) sun wavelengths is proposed. Diagnostic and observational studies show that solar reflectance at 0.65 μm (R0.65μm) could be a proxy for cloud optical depth, and it can be applied to parametrize the cloud modification factor (CMF), which is often applied to estimate the UV index. For all sky conditions, a linear relation between broadband CMF (0.2–0.4 μm) and R0.65μm is derived, given by CMF(theory) = 1.09–1.19·R0.65μm using a radiative transfer model, which is close to CMF(observed) = 1.15 − 1.55 Rch1 based on ground-based radiation measurements and geostationary satellite channel 1 reflectance data (Rch1). The observationally derived CMF versus Rch1 fitting was applied for four different cloud classes from the satellite scene classification products: cirrus, cumulus, stratus and deep convective clouds. CMF varies with Rch1 from 1 for optically thin clouds to 0.05 for stratus and convective clouds, while CMF >0.7 denotes cirrus clouds. These values differ significantly from the constant CMF values suggested in the literature, particularly for convective clouds. The parameterization found here for each cloud is assessed by comparing the UVI estimated using the novel CMF function to UVI ground-based observations during a four-year period in São Paulo, Brazil. Because of high temporal and spatial satellite data availability, the parametrized CMF in terms of Rch1 is well suited for incorporation into operational weather services, estimating UVI under cloudy conditions with high correlation (r > 0.8) and low errors (root mean square error <2.0) when compared to ground data. In addition, CMF parametrization provides a better IUV cloud effect than the CMF given in the literature. The findings shown here enable better UVI estimation under overcast skies over tropical climates, allowing for more realistic information regarding health and sun exposure to be communicated to the public.

The air quality of Northeast Asia cannot be improved by the individual national efforts because of the proximity of countries. To foster understanding of this problem, the Fine Particle Research Initiative in East Asia considering National Differences (FRIEND) Project was launched in 2020. During the first FRIEND campaign conducted from December 15, 2020 to January 15, 2021, gaseous and aerosol components were monitored simultaneously with high temporal resolution at the following key sites in Northeast Asia: Ulaanbaatar, Mongolia; Beijing, China; Seosan and Seoul, Republic of Korea; and Noto, Japan. The chemical components of PM1.0 were monitored with Aerosol Chemical Speciation Monitors (ACSMs) at the Beijing, Seoul, and Noto sites. Over the upwind region of Northeast Asia (Beijing and Seoul), sulfate aerosol (SO42−) was a high as a fraction of PM1.0 and nitrate aerosol (NO3−) was high, whereas over the downwind region (Noto), SO42− was high and NO3− was low. We used regional numerical modeling to clarify the reason for these distinctive PM1.0 differences over the upwind and downwind regions. The model also reproduced higher NO3− in the upwind region and higher SO42− in the downwind region, and captured the ACSMs measurements based on the statistical analyses. The conversion ratio from SO2 to SO42− (FS) indicated lower oxidation over the Asian continent and increased oxidation toward the downwind region. The OH radical and cloud fraction suggested that the gas- and aqueous-phase SO2 oxidation processes were inactive over the Asian continent. In contrast to FS, the conversion ratio from HNO3 to NO3− (FN) indicated a higher production ratio over the Asian continent and a strong decline toward the downwind region. HNO3 concentration in northeastern China was close to zero, whereas NH3 concentration was high, suggesting NH3-rich conditions where HNO3 was fully neutralized to form NO3−, whereas the conditions were NH3-poor toward the downwind region. Therefore, these factors govern the transformation process of PM1.0 during long-range transport from the upwind to downwind region in Northeast Asia and determine the distinctive features of inorganic PM1.0.

Low-cost air quality monitors are growing in popularity among both researchers and community members to understand variability in pollutant concentrations. Several studies have produced calibration approaches for these sensors for ambient air. These calibrations have been shown to depend primarily on relative humidity, particle size distribution, and particle composition, which may be different in indoor environments. However, despite the fact that most people spend the majority of their time indoors, little is known about the accuracy of commonly used devices indoors. This stems from the fact that calibration data for sensors operating in indoor environments are rare. In this study, we sought to evaluate the accuracy of the raw data from PurpleAir fine particulate matter monitors and for published calibration approaches that vary in complexity, ranging from simply applying linear corrections to those requiring co-locating a filter sample for correction with a gravimetric concentration during a baseline visit. Our data includes PurpleAir devices that were co-located in each home with a gravimetric sample for 1-week periods (265 samples from 151 homes). Weekly-averaged gravimetric concentrations ranged between the limit of detection (3 μg/m3) and 330 μg/m3. We found a strong correlation between the PurpleAir monitor and the gravimetric concentration (R > 0.91) using internal calibrations provided by the manufacturer. However, the PurpleAir data substantially overestimated indoor concentrations compared to the gravimetric concentration (mean bias error ≥ 23.6 μg/m3 using internal calibrations provided by the manufacturer). Calibrations based on ambient air data maintained high correlations (R ≥ 0.92) and substantially reduced bias (e.g. mean bias error = 10.1 μg/m3 using a US-wide calibration approach). Using a gravimetric sample from a baseline visit to calibrate data for later visits led to an improvement over the internal calibrations, but performed worse than the simpler calibration approaches based on ambient air pollution data. Furthermore, calibrations based on ambient air pollution data performed best when weekly-averaged concentrations did not exceed 30 μg/m3, likely because the majority of the data used to train these models were below this concentration.

Cis-3-hexenyl acetate (cis-HXAC) is a major green leaf volatile released by plants, and its atmospheric degradation by O3 may play an important role in the formation of secondary organic aerosol (SOA). In this study, indoor smog chamber experiments were carried out to investigate the effects of particle acidity and SO2 on the formation of secondary organic aerosols (SOA) from the ozonolysis of cis-HXAC. Particle formation and growth were characterized using a scanning mobility particle sizer, and the chemical composition of the particles was analyzed by thermal-desorption gas chromatography mass spectrometry, with the main products and reaction pathways of cis-HXAC ozonolysis being identified. The results revealed that acidic seed particles inhibited SOA formation compared to non-acidic seed particles, and SO2 was considered to play a catalytic role in cis-HXAC ozonolysis, showing a good positive correlation with SOA generation. The results of this study provide new information on the ozonolysis of cis-HXAC, confirm the important role of anthropogenic pollution, and help to further elucidate the potential of green leaf volatiles ozonolysis to generate SOA under complex pollution conditions.

Air quality issues caused by PM2.5-induced persistent extreme haze episodes have become increasingly serious in urban environments in recent years. Secondary water-soluble inorganic sulfate (SO42−), nitrate (NO3−) and ammonium (NH4+) ions are the major components of PM2.5. However, the contributions of inorganic nitrogen species, especially nitrate, to PM2.5 have greatly increased during haze episodes in many cities in China. Therefore, better understanding of their emission sources and formation pathways holds the key to controlling urban PM2.5 pollution more efficiently and effectively. In this study, water-soluble ionic characteristics and isotopic compositions and sources of NH4+ and NO3−, as well as NO3− formation pathways were determined in PM2.5 aerosol samples collected in Guangzhou, China, during 2015–2018. The PM2.5 concentrations varied from 30.5 to 189.8 μg⋅m−3 and their mean values were highest in spring (111.1 μg⋅m−3) and lowest in summer (63.5 μg⋅m−3). The δ15N–NH4+ and δ15N–NO3- values ranged from +4.5 to +20.2‰ and from +4.8 to +14.8‰, respectively, with their mean values being highest in winter (14.0‰ and 9.5‰, respectively) and lowest in summer (10.4‰ and 7.1‰, respectively). The seasonal δ15N variability was mainly attributed to isotopic equilibrium fractionation, and partly due to the changes in NH3 and NOx sources. The average δ18O–NO3- value of 63.0‰, ranging seasonally from +58.6‰ in summer to +68.0‰ in spring, suggests that NO2 +⋅OH pathway played a vital role (70.3–85.9%) in NO3− formation. The Bayesian isotope mixing model results revealed fossil fuel combustion sources as dominant sources of atmospheric NH3 and NOx. This study suggests that more effort should be devoted to reduce NH3 and NOx from combustion-related processes and highlights the importance of δ18O–NO3- analysis for exploring variations of nitrate formation pathways in urban atmospheres.

A nested GEOS-Chem atmosphere transport model has been set up for the Indian monsoon region (40° E-110° E & 15° S–45° N at 0.250X0.3125°) spatial resolution to study the variability of the tropospheric CO2 over India and surrounding oceans during 2012–2020. The model has been constrained by the influxes of CO2 at its four lateral boundaries derived from the GEOS-Chem global simulations and surface fluxes of CO2 over the land and oceans based on historical databases. It is initialized from a known state and driven by the GEOS reanalysis's meteorological forcing. Model simulations were evaluated at three in situ measurement locations and with respect to the satellite retrievals from OCO-2 and GOSAT. Model parameters were tuned to have reasonable solutions to resolve observed latitudinal gradient and seasonal and inter-annual variability. Three additional model runs were made to evaluate the role of long-range transport, net terrestrial ecosystem exchange, air-sea fluxes, and regional emissions in controlling seasonal oscillations of tropospheric CO2 over the study region. It revealed that the net terrestrial ecosystem exchanges are responsible for 35% control in the surface layer CO2 seasonal tendency for India and the Bay of Bengal domains, and 10% for the Arabian Sea. The air-sea fluxes have 8% control on the CO2 seasonal tendency for the Arabian Sea and Bay of Bengal and 5% for India. The anthropogenic emissions have 4% control for India and <1% for the Arabian Sea, and 9% for the Bay of Bengal. The long-range transport, as the residual, is responsible for 60% variability in the seasonal cycle of CO2 over India and the Bay of Bengal and 75% for the Arabian Sea domain.

In recent years, the rapid pollution emission reductions significantly decreased the PM2.5, which weakened the aerosol radiation feedback effect and in turn influenced the changes of PM2.5 and O3. To promote our understanding of this effect, we used an online-coupled meteorology-chemistry model (WRF-Chem) to investigate the influence of aerosol direct effects (ADE) on PM2.5 and O3 responding to different pollutant emissions reduction for a summer PM2.5-O3 compound pollution month in Beijing-Tian-Hebei region (BTH) and surrounding area. We performed scenario simulations with turning on/off both aerosol influences on the meteorology (ADE_MET) and photolysis (ADE_PHO), and turning on only ADE_PHO with different reduction ratios for primary PM2.5 (100%), SO2 (80%) and NOx (40%) emissions. Our results showed that total reduction of primary PM2.5, SO2 and NOx emissions led to overall declines of surface PM2.5 in BTH and surrounding area. The SO2 and NOx emission reductions both furtherly decreased PM2.5 via the changed ADE, while the primary PM2.5 emission reduction increased the PM2.5 by its induced ADE. Different from PM2.5, O3 significantly increased in BTH after cutting the three types of emissions. The primary PM2.5 emission reduction led to O3 increase over the whole region mostly by the induced ADE, while the NOx emission reduction directly enhanced O3 in the plain areas mainly due to incompatible reduction of NOx and VOCs emissions. The O3 enhanced by emission-reduction-induced ADE accounted for 56.1% of the total increase. The ADE_PHO caused by PM2.5 primary emissions reduction was the dominant contribution to the total ADE induced increases of PM2.5 and O3, which enhanced the photolysis of gases and led to overall increase of oxidants that strengthened secondary aerosol formation, and also promoted the production of O3 via photochemical processes. The results implicate that with the continuously strengthened abatement of PM2.5 primary emissions, it may offset part of the reduction effect on PM2.5 decrease by the changed ADE, and also increase O3 over the whole region. The results also suggested that while controlling both PM2.5 and O3 in BTH in summer, not only the cooperative emission reduction of NOx and VOCs is essential, the induced ADE effect by PM2.5 primary emissions reduction should also be considered.

Shortcomings and uncertainties in the model representation of atmospheric transformations (the aging) of organic aerosol (OA) have long been identified as one of the potential sources of considerable uncertainty in OA simulations with both global and regional models. However, the impact of this uncertainty on predictions of radiative and climate effects of both anthropogenic and biomass burning (BB) aerosol yet needs to be understood. This study examines the importance of the model representation of OA for simulating the direct radiative effect (DRE) of Siberian BB aerosol in the eastern Arctic. We employ a regional coupled chemistry-meteorology model and a global fire emission database to simulate the optical properties and DRE of BB aerosol emitted from intense Siberian fires in July 2016 and compare the DRE estimates that were obtained using two alternative representations of Siberian BB OA. One of them is a “default” OA representation that predicts very little secondary OA (SOA), and another involves a simple original OA parameterization that has been developed previously within the volatility basis set (VBS) framework and features a strong production of SOA. The simulations of the aerosol optical properties are evaluated against satellite observations of the aerosol optical depth (AOD) in Siberia and the Arctic as well as against values of the single scattering albedo derived from in situ observations of the aerosol absorption and scattering coefficients at four Arctic sites. While the simulations with the default OA representation are found to strongly underestimate AOD both in Siberia and the eastern Arctic, the use of the VBS parameterization considerably improves the agreement between the AOD simulations and observations in both regions. Simulations of the single scattering albedo are found to be overall rather adequate with both representations. Differences in the OA representations are found to result in major differences in the estimates of the DRE of Siberian BB aerosol in the eastern Arctic. Specifically, although the simulations with both representations predict that the DRE is predominantly negative at the top of the atmosphere (TOA), the magnitude of the mean DRE is found to be more than twice as large (6.0 W m−2) with the VBS parameterization than with the default OA representation (2.8 W m−2). An even larger difference (by a factor of 3.5) is found between the estimates of the DRE over the snow- or ice-covered areas. The different treatments of the BB OA evolution are associated also with considerably different contributions of black and brown carbon to the DRE estimates. Overall, our results indicate that model estimates of the DRE of Siberian BB aerosol in the eastern Arctic are strongly sensitive to the assumptions regarding the evolution of OA in Siberian BB plumes and that the SOA formation in these plumes is one of the major factors determining the magnitude of the radiative effects of Siberian BB aerosol in the real atmosphere.

This work presents a methodology to identify the fuel sulphur content (FSC) violations of ongoing vessels, using CFD RANS modelling by implementing the SST k-omega turbulence parameterization to predict the CO2 and SO2 concentrations of plume dispersion. Gaseous pollutants measurements and meteorological data from a ship emission monitoring station in the approach to the port of Hamburg, Germany, have been used for the evaluation of the methodology. Gaseous pollutants concentration, meteorology, identity, and position of passing ships (AIS signal) are the main parameters of the modelling approach. Five ships have been selected to demonstrate and evaluate the method developed. The vessels had different installed power, geometry, and fuel sulphur content. A virtual monitoring station is created for collecting concentration data from the simulated plume and producing concentration time-series. The comparison between modelling and measurements is being performed with integrated numerical values that were produced from the concentration time-series. Modelling, in comparison to measurements for all case studies, provides results for CO2 and SO2 that are in the same order of magnitude, which constitutes the main criterion of validity. In the methodology, the uncertainties are separated into three categories. The first one is related to ambient conditions such as turbulence and temperature profiles. The second concerns ships’ funnel exit characteristics considering the estimation of funnel exit concentration and exhaust mass flow. The third considers the uncertainties that are related to measurements. All details above were used to produce expressions considering the relationship between the FSC and SO2 measuring instruments. The outcome of this work can contribute in finding optimum monitoring location and in estimating plume dispersion close to the water level, e.g. for studying pollutants exchange in the air-water interface.

Scavenging of anthropogenic aerosols by mineral dust in polluted environment was investigated in this work based on comprehensive observations of a long durative dust event from March 15 to 18, 2021 over north China. Combined observations of a Raman-depolarization lidar (355 nm) and a micro-pulse lidar (532 nm) show that dust particles become more spherical after mixing with anthropogenic pollutants in a polluted environment, likely due to mixing with anthropogenic aerosols. A sharply decease in anthropogenic aerosol in PM2.5 during dust event, especially for inorganic components (e.g., nitrate (NO3−), sulfate (SO42+), ammonium (NH4+)), supports the above viewpoint. The mass concentration of anthropogenic aerosol in PM2.5 decreased by 78% in late period of dust event. Further analyses suggest that such a decrease of anthropogenic aerosol in PM2.5 is caused by the coating of fine anthropogenic aerosols on coarse dust particles, rather than enhanced atmospheric diffusion capacity or weakened chemical reactions. Dust particles own high deposition velocity due to their coarse size. Hence, the coating of anthropogenic aerosols on dust particles enhance the scavenging of anthropogenic aerosols.

Combined air pollution prevails in the Pearl River Delta (PRD) region in recent years; large amounts of aerosols have caused a significant attenuation of actinic radiation. Solar radiation is the driving energy for photochemical reactions and plays an important role in the ozone formation. In this study, characteristics of actinic radiation and atmospheric composition in the PRD region have been analyzed based on long-term observation. The radiation transfer model (SBDART) is used to quantitatively estimate the direct radiation effect and actinic radiation effect of aerosol. Results indicate that PM2.5 concentration and atmospheric extinction coefficient have shown a downward trend. Meanwhile, ozone and Single Scattering Albedo (SSA) have increased. The average value of SSA is 0.914 ± 0.041, attaining the highest level in spring, followed by autumn and summer, and the lowest is found in winter. A linear relationship between UVA/UVB of actinic radiation flux and solar shortwave radiation has been revealed. Through the conversion formula proposed in the article, conventional radiation data can be converted into actinic radiation flux and species photolysis rate. The actinic radiation and radiation attenuation caused by aerosols shows an overall downward trend at the surface. In the ultraviolet to visible wavelength range (280–670 nm), the annual average attenuation of aerosol direct radiation and actinic radiation is 61.6 ± 31.8 W/m2 and 120.1 ± 59.7 W/m2, respectively. The radiation attenuation caused by aerosols is the largest in spring, with little difference in summer, autumn and winter, which are 92.9 ± 42.1 W/m2, 53.7 ± 21.3 W/m2, 48.0 ± 13.7 W/m2 and 52.1 ± 15.8 W/m2, respectively. The attenuation of actinic radiation caused by aerosol is the largest in spring, followed by winter, and there is little difference between summer and autumn, which are 174.8 ± 78.4 W/m2, 111.1 ± 33.1 W/m2, 98.3 ± 38.4 W/m2 and 96.7 ± 26.9 W/m2, respectively. The direct radiation effect of aerosol and the actinic radiation effect have opposite trends with increasing height. Below the aerosol scale height, the larger SSA is corresponding with greater radiant flux, and it is opposite above the aerosol scale height. SSA has the same effect on the actinic radiant flux of the entire layer: The larger SSA is in accordance with greater actinic radiant flux.

Climate change may aggravate air pollution through altering emissions, ventilation, chemical production, and deposition. Under a warming climate, persistent weather patterns are likely to increase in both number and intensity, yet their implications on future air quality have been less explored. Here we use ground-level observations of air pollutants and meteorological reanalysis dataset to explore how persistence of weather conditions would affect extremes of wintertime PM2.5 and summertime O3 in China. Associated changes in the shapes of their distributions are discussed also with contrasting weather conditions. As air stagnation days persist, median summertime O3 significantly increases, with 0.07, 0.12 and 0.19 standard deviation per day (about 1.97, 3.12 and 4.63 ppb per day) for the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions, respectively. As high temperature days continue, significant increases in median (about 0.31 ppb per day) and 90th percentile (about 0.78 ppb per day) of summertime O3 is found only in the YRD region, although the highest probability of O3 extreme (90th percentile) is identified on the last day of four-day high temperature events for both the BTH and YRD regions. In contrast, persistent stagnation causes a significant increase in the 90th percentile of PM2.5 of about 17.87 and 10.88 μg/m3 per day for BTH and YRD regions, rather than the median. Stagnation events lasting for five, four and five days are the best indicators for PM2.5 extreme (90th percentile) in the BTH, YRD and PRD regions, respectively. Analysis on contrasting monthly weather conditions suggests that summertime O3 extreme is amplified by higher mean daily maximum air temperature (T) in the BTH region and co-occurrences of high T and stagnation in the YRD region, while wintertime PM2.5 extreme is significantly amplified by stronger stagnation. These results suggest that megacities with relatively high emissions are more vulnerable to a hotter and more stable future.

Temporal variation in cloud cover and surface conditions greatly affects estimation errors associated with reference surface reflectance and atmospheric composition retrievals. In this study, to determine an optimal temporal window for clear-sky composition methods that are used to identify surface reflectance for the retrieval of atmospheric properties, we analyzed temporal variation in surface reflectance and cloud fractions using long-term daily observations from the Moderate Resolution Imaing Spectroradiometer (MODIS) satellite. For the temporal variation in surface reflectance, gridded pixels with a standard deviation less than 0.025 represented 87.0%, 84.5%, 80.5%, and 77.3% of the total pixels for periods of 15, 20, 30, and 40 days, respectively. The temporal variability of surface reflectance was lowest in summer and highest in winter due to vegetation and snow cover changes over land surface in East Asia. For the temporal variation in cloud fractions, pixels with a cloud fraction <10% ranged from 91.2% (15-day) to 98.1% (40-day). Only temporal windows of 30 and 40 days satisfied the criterion of 95% cumulative distribution in the 10% cloud fraction range. Thus, and appropriate temporal window for clear-sky composition methods must be selected in consideration of the seasonal dependency of surface types and cloud cover variation. The temporal window for the clear-sky composition must be longer than 30 days considering the temporal variability of cloud cover, and shorter than 30 days considering that of surface reflectance. However, seasonal dependencies of surface reflectance and cloud fraction are also additionally considered to select the appropriated temporal window for the clear-sky composition.

Total ozone column (TOC) measurements are retrieved from the Ozone Monitoring Instrument (OMI) onboard the NASA Earth Observing System (EOS) Aura satellite at the three Norwegian sites: Oslo (59.9°N 10.7°E, 1 m a.s.l.), Trondheim (63.4°N 10.4°E, 3 m a.s.l.) and Andøya (69.1°N 15.7°E, 32 m a.s.l.). TOC data have been analysed from 2005 to 2021, in order to detect annual and multi-years total ozone variability. The relationship between geopotential height (GPH) at 250 hPa and total ozone column has been evaluated after showing that monthly anomalies in GPH and TOC are correlated amongst the three sites. The influence of the three Northern Hemisphere Tele Connection (TC) indices (North Atlantic Oscillation, Arctic Oscillation and Scandinavia) on TOC variability has been investigated. It is found that Scandinavia index plays a prominent role for the northernmost latitudes of Andøya and Trondheim while North Atlantic Oscillation and Arctic Oscillation indices are weakly correlated (negatively) to TOC and (positively) to GPH at Oslo. The response of TOC variability to the solar activity at the three sites is also explored and it is noticed that in the period of increasing variation of solar activity, significant TOC anomaly events are only observed in Andøya and Trondheim.

Although chlorofluorocarbons (CFCs), CH3Br and chlorinated solvents such as CH3Cl3 and CCl4 have been entirely phased out in the Pearl River Delta (PRD) region, these compounds still exist chronically in atmosphere. In this study, ambient air samples were collected at twenty sites in the PRD region in winter (November to December 2019) and summer (August 2020) to characterize the spatio-seasonal variation of ozone-depleting substances (ODS), including CFC-11, CFC-12, CFC-113, CFC-114, CH3CCl3, CCl4, and CH3Br, and to estimate their emissions. Our observation showed that the average mixing ratios of the target ODS in the PRD region were 16.5%–92.5% lower compared with their reported levels in 2001 except for CFC-114, which basically remained at a constant level. Among the seven ODS, the average mixing ratio of CH3CCl3 declined most rapidly. The mixing ratios of the target ODS were higher in summer than in winter. Higher mixing ratios of the target ODS were observed in the two PRD urban background sites than the northern hemisphere background level, suggesting the existence of local emission sources. The spatial distribution indicated that the Foshan–Guangzhou–Dongguan–Shenzhen corridor area had the highest mixing ratios of the target ODS. Based on the CO-tracer ratio method, the estimated emissions of CFC-11, CFC-12, CFC-113, CFC-114, CH3Br, CH3CCl3 and CCl4 were 1.2, 0.8, 0.3, 0.2, 0.1, 0.1 and 0.4 kt/year, respectively. CFCs showed a very slow reduction in emission since 2008 in general, and the estimated emissions of CH3CCl3 and CCl4 gradually declined from the high value reported in 2004 while CH3Br kept the same level. The findings of this study can help to get a better understanding of the emissions status of ODS in the PRD region and provide valuable information for further reduction processes.

Peroxides (H2O2, ROOR, ROOH) play an important atmospheric role in both the gas and particle phases. Several techniques are available in the literature for their quantification, although current techniques are very expensive or time-consuming. In the present work, a new fast and sensitive iodometric-spectrophotometric method, based on the traditional one, has been developed for the trace SOA (Secondary Organic Aerosols)-bound peroxides of laboratory-generated samples. The proposed method is based on the acceleration by microwave radiation of the reaction of peroxides with potassium iodide in acid medium. Iodine is liberated and in the presence of excess of iodide forms I3− that could be monitored at three different wavelengths (288, 351 and 420 nm). The linear range of concentrations of the method is at least 1–35 μM. The limit of detection of the method was 1 μM without degasification and decreased to 0.25 μM with degasification, respectively. The optimum conditions and other analytical parameters were evaluated for H2O2, tert-butyl hydroperoxide and cumene hydroperoxide. The main advantages of the new method in comparison with the traditional method are: it is less time consuming, it is applicable even in the presence of oxygen, it has a lower limit of detection (for 1 cm pathlength cell) and there are no sensitivity differences between different peroxides types.The proposed method has been successfully applied and compared with the traditional method for the determination of peroxides in SOA generated in laboratory by the gas phase ozonolysis of α-pinene.