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Oxidative stress is an important cause of respiratory diseases associated with exposure to PM 2.5 . Accordingly, acellular methods for assessing the oxidative potential (OP) of PM 2.5 have been evaluated extensively for use as indicators of oxidative stress in living organisms. However, OP-based assessments only reflect the physicochemical properties of particles and do not consider particle-cell interactions. Therefore, to determine the potency of OP under various PM 2.5 scenarios, oxidative stress induction ability (OSIA) assessments were performed using a cell-based method, the heme oxygenase-1 (HO-1) assay, and the findings were compared with OP measurements obtained using an acellular method, the dithiothreitol assay. For these assays, PM 2.5 filter samples were collected in two cities in Japan. To quantitatively determine the relative contribution of the quantity of metals and subtypes of organic aerosols (OA) in PM 2.5 to the OSIA and the OP, online measurements and offline chemical analysis were also performed. The findings showed a positive relationship between the OSIA and OP for water-extracted samples, confirming that the OP is generally well suited for use as an indicator of the OSIA. However, the correspondence between the two assays differed for samples with a high water-soluble (WS)-Pb content, which had a higher OSIA than would be expected from the OP of other samples. The results of reagent-solution experiments showed that the WS-Pb induced the OSIA, but not the OP, in 15-min reactions, suggesting a reason for the inconsistent relationship between the two assays across samples. Multiple linear regression analyses and reagent-solution experiments showed that WS transition metals and biomass burning OA accounted for approximately 30-40% and 50% of the total OSIA or the total OP of water-extracted PM 2.5 samples, respectively. This is the first study to evaluate the association between cellular oxidative stress assessed by the HO-1 assay and the different subtypes of OA., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

COVID-19 related restrictions lowered particulate matter and trace gas concentrations across cities around the world, providing a natural opportunity to study effects of anthropogenic activities on emissions of air pollutants. In this paper, the impact of sudden suspension of human activities on air pollution was analyzed by studying the change in satellite retrieved NO 2 concentrations and top-down NOx emission over the urban and rural areas around Delhi. NO 2 was chosen for being the most indicative of emission intensity due to its short lifetime of the order of a few hours in the planetary boundary layer. We present a robust temporal comparison of Ozone Monitoring Instrument (OMI) retrieved NO 2 column density during the lockdown with the counterfactual baseline concentrations, extrapolated from the long-term trend and seasonal cycle components of NO 2 using observations during 2015 to 2019. NO 2 concentration in the urban area of Delhi experienced an anomalous relative change ranging from 60.0% decline during the Phase 1 of lockdown (March 25-April 13, 2020) to 3.4% during the post-lockdown Phase 5. In contrast, we find no substantial reduction in NO 2 concentrations over the rural areas. To segregate the impact of the lockdown from the meteorology, weekly top-down NOx emissions were estimated from high-resolution TROPOspheric Monitoring Instrument (TROPOMI) retrieved NO 2 by accounting for horizontal advection derived from the steady state continuity equation. NOx emissions from urban Delhi and power plants exhibited a mean decline of 72.2% and 53.4% respectively in Phase 1 compared to the pre-lockdown business-as-usual phase. Emission estimates over urban areas and power-plants showed a good correlation with activity reports, suggesting the applicability of this approach for studying emission changes. A higher anomaly in emission estimates suggests that comparison of only concentration change, without accounting for the dynamical and photochemical conditions, may mislead evaluation of lockdown impact. Our results shall also have a broader impact for optimizing bottom-up emission inventories.

Delhi, a tropical Indian megacity, experiences one of the most severe air pollution in the world, linked with diverse anthropogenic and biomass burning emissions. First phase of COVID-19 lockdown in India, implemented during 25 March to 14 April 2020 resulted in a dramatic near-zeroing of various activities (e.g. traffic, industries, constructions), except the "essential services". Here, we analysed variations in the fine particulate matter (PM 2.5 ) over the Delhi-National Capital Region. Measurements revealed large reductions (by 40-70%) in PM 2.5 during the first week of lockdown (25-31 March 2020) as compared to the pre-lockdown conditions. However, O 3 pollution remained high during the lockdown due to non-linear chemistry and dynamics under low aerosol loading. Notably, events of enhanced PM 2.5 levels (300-400 µg m -3 ) were observed during night and early morning hours in the first week of April after air temperatures fell close to the dew-point (~ 15-17 °C). A haze formation mechanism is suggested through uplifting of fine particles, which is reinforced by condensation of moisture following the sunrise. The study highlights a highly complex interplay between the baseline pollution and meteorology leading to counter intuitive enhancements in pollution, besides an overall improvement in air quality during the COVID-19 lockdown in this part of the world.

Aerosol particles emitted from various human activities deteriorate air quality and are suggested to increase public health risk. Numerous studies have emphasized the relationship between the mass and/or number concentration of aerosols (or commonly known as particulate matter (PM)) in the atmosphere and the incidence of respiratory and cardiovascular diseases, while very few have examined the deposition efficiency of inhaled particles in the respiratory tract. We present the first examination of particles deposition based on, detailed simulation of aerosol physico-chemical properties by a recently developed particle-resolved aerosol model and the mixing state dependent hygrosocpic growth and deposition computed at particle-level by deposition model. Furthermore, we elucidate the impact of mixing state on deposition efficiency by using a recently introduced aerosol mixing state index. We find that without considering mixing-state-dependent hygroscopic growth of particles leads to overestimation of deposition efficiency; whereas considering an average mixing state leads to underestimation of 5% to 20% of soot particle deposition efficiency in human alveoli. We conclude that aerosol mixing state, which evolves during the interaction between atmospheric chemistry and meteorology, is important for the comprehensive evaluation of air quality and its implication to public health requires further investigation.

The source-receptor relationship analysis of PAH deposition in Northeast Asia was investigated using an Eulerian regional-scale aerosol chemical transport model. Dry deposition (DD) of PAH was controlled by wind flow patterns, whereas wet deposition (WD) depended on precipitation in addition to wind flow patterns. The contribution of WD was approximately 50-90% of the total deposition, except during winter in Northern China (NCHN) and Eastern Russia (ERUS) because of the low amount of precipitation. The amount of PAH deposition showed clear seasonal variation and was high in winter and low in summer in downwind (South Korea, Japan) and oceanic-receptor regions. In the downwind region, the contributions from NCHN (WD 28-52%; DD 54-55%) and Central China (CCHN) (WD 43-65%; DD 33-38%) were large in winter, whereas self-contributions (WD 20-51%; DD 79-81%) were relatively high in summer. In the oceanic-receptor region, the deposition amount decreased with distance from the Asian continent. The amount of DD was strongly influenced by emissions from neighboring domains. The contributions of WD from NCHN (16-20%) and CCHN (28-35%) were large. The large contributions from China in summer to the downwind region were linked to vertical transport of PAHs over the Asian continent associated with convection.

We analyzed the source-receptor relationships for particulate polycyclic aromatic hydrocarbon (PAH) concentrations in northeastern Asia using an aerosol chemical transport model. The model successfully simulated the observed concentrations. In Beijing (China) benzo[a]pyren (BaP) concentrations are due to emissions from its own domain. In Noto, Oki and Tsushima (Japan), transboundary transport from northern China (>40 °N, 40-60%) and central China (30-40 °N, 10-40%) largely influences BaP concentrations from winter to spring, whereas the relative contribution from central China is dominant (90%) in Hedo. In the summer, the contribution from Japanese domestic sources increases (40-80%) at the 4 sites. Contributions from Japan and Russia are additional source of BaP over the northwestern Pacific Ocean in summer. The contribution rates for the concentrations from each domain are different among PAH species depending on their particulate phase oxidation rates. Reaction with O3 on particulate surfaces may be an important component of the PAH oxidation processes., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

In response to increasing trends in sulfur deposition in Northeast Asia, three countries in the region (China, Japan, and Korea) agreed to devise abatement strategies. The concepts of critical loads and source-receptor (S-R) relationships provide guidance for formulating such strategies. Based on the Long-range Transboundary Air Pollutants in Northeast Asia (LTP) project, this study analyzes sulfur deposition data in order to optimize acidic loads over the three countries. The three groups involved in this study carried out a full year (2002) of sulfur deposition modeling over the geographic region spanning the three countries, using three air quality models: MM5-CMAQ, MM5-RAQM, and RAMS-CADM, employed by Chinese, Japanese, and Korean modeling groups, respectively. Each model employed its own meteorological numerical model and model parameters. Only the emission rates for SO(2) and NO(x) obtained from the LTP project were the common parameter used in the three models. Three models revealed some bias from dry to wet deposition, particularly the latter because of the bias in annual precipitation. This finding points to the need for further sensitivity tests of the wet removal rates in association with underlying cloud-precipitation physics and parameterizations. Despite this bias, the annual total (dry plus wet) sulfur deposition predicted by the models were surprisingly very similar. The ensemble average annual total deposition was 7,203.6 ± 370 kt S with a minimal mean fractional error (MFE) of 8.95 ± 5.24 % and a pattern correlation (PC) of 0.89-0.93 between the models. This exercise revealed that despite rather poor error scores in comparison with observations, these consistent total deposition values across the three models, based on LTP group's input data assumptions, suggest a plausible S-R relationship that can be applied to the next task of designing cost-effective emission abatement strategies.

This study provides comparisons of aerosol representation methods incorporated into a regional-scale nonhydrostatic meteorology–chemistry model (NHM-Chem). Three options for aerosol representations are currently available: the five-category non-equilibrium (Aitken, soot-free accumulation, soot-containing accumulation, dust, and sea salt), three-category non-equilibrium (Aitken, accumulation, and coarse), and bulk equilibrium (submicron, dust, and sea salt) methods. The three-category method is widely used in three-dimensional air quality models. The five-category method, the standard method of NHM-Chem, is an extensional development of the three-category method and provides improved predictions of variables relating to aerosol–cloud–radiation interaction processes by implementing separate treatments of light absorber and ice nuclei particles, namely, soot and dust, from the accumulation- and coarse-mode categories (implementation of aerosol feedback processes to NHM-Chem is still ongoing, though). The bulk equilibrium method was developed for operational air quality forecasting with simple aerosol dynamics representations. The total CPU times of the five-category and three-category methods were 91 % and 44 % greater than that of the bulk method, respectively. The bulk equilibrium method was shown to be eligible for operational forecast purposes, namely, the surface mass concentrations of air pollutants such as O3 , mineral dust, and PM2.5. The simulated surface concentrations and depositions of bulk chemical species of the three-category method were not significantly different from those of the five-category method. However, the internal mixture assumption of soot/soot-free and dust/sea salt particles in the three-category method resulted in significant differences in the size distribution and hygroscopicity of the particles. The unrealistic dust/sea salt complete mixture of the three-category method induced significant errors in the prediction of the mineral dust-containing cloud condensation nuclei (CCN), which alters heterogeneous ice nucleation in cold rain processes. The overestimation of soot hygroscopicity by the three-category method induced errors in the BC-containing CCN, BC deposition, and light-absorbing aerosol optical thickness (AAOT). Nevertheless, the difference in AAOT was less pronounced with the three-category method because the overestimation of the absorption enhancement was compensated by the overestimation of hygroscopic growth and the consequent loss due to in-cloud scavenging. In terms of total properties, such as aerosol optical thickness (AOT) and CCN, the results of the three-category method were acceptable. [ABSTRACT FROM AUTHOR]

The Model Inter-Comparison Study for Asia (MICS-Asia) phase III was conducted to promote understanding of regional air quality and climate change in Asia, which have received growing attention due to the huge amount of anthropogenic emissions worldwide. This study provides an overview of acid deposition. Specifically, dry and wet deposition of the following species was analyzed: S (sulfate aerosol, sulfur dioxide (SO2), and sulfuric acid (H2SO4)), N (nitrate aerosol, nitrogen monoxide (NO), nitrogen dioxide (NO2), and nitric acid (HNO3)), and A (ammonium aerosol and ammonia (NH3)). The wet deposition simulated by a total of nine models was analyzed and evaluated using ground observation data from the Acid Deposition Monitoring Network in East Asia (EANET). In the phase III study, the number of observation sites was increased from 37 in the phase II study to 54, and southeast Asian countries were newly added. Additionally, whereas the analysis period was limited to representative months of each season in MICS-Asia phase II, the phase III study analyzed the full year of 2010. The scope of this overview mainly focuses on the annual accumulated deposition. In general, models can capture the observed wet deposition over Asia but underestimate the wet deposition of S and A, and show large differences in the wet deposition of N. Furthermore, the ratio of wet deposition to the total deposition (the sum of dry and wet deposition) was investigated in order to understand the role of important processes in the total deposition. The general dominance of wet deposition over Asia and attributions from dry deposition over land were consistently found in all models. Then, total deposition maps over 13 countries participating in EANET were produced, and the balance between deposition and anthropogenic emissions was calculated. Excesses of deposition, rather than of anthropogenic emissions, were found over Japan, northern Asia, and southeast Asia, indicating the possibility of long-range transport within and outside of Asia, as well as other emission sources. To improve the ability of models to capture the observed wet deposition, two approaches were attempted, namely, ensemble and precipitation adjustment. The ensemble approach was effective at modulating the differences in performance among models, and the precipitation-adjusted approach demonstrated that the model performance for precipitation played a key role in better simulating wet deposition. Finally, the lessons learned from the phase III study and future perspectives for phase IV are summarized. [ABSTRACT FROM AUTHOR]

Satellite sensors are powerful tools to monitor the spatiotemporal variations of air pollutants in large scales, but it has been challenging to detect surface O3 due to the presence of abundant stratospheric and upper tropospheric O3. East Asia is one of the most polluted regions in the world, but anthropogenic emissions such as NOx and SO2 began to decrease in 2010s. This trend was well observed by satellites, but the spatiotemporal impacts of these emission trends on O3 have not been well understood. Recent advancement in a retrieval method for the Ozone Monitoring Instrument (OMI) sensor enabled detection of lower tropospheric O3 and its legitimacy has been validated. In this study, we investigated the statistical significance for the OMI sensor to detect the lower tropospheric O3 responses to the future emission reduction of the O3 precursor gases over East Asia in summer, by utilizing a regional chemistry model. The emission reduction of 10, 25, 50, and 90% resulted in 4.4, 11, 23, and 53% decrease of the areal and monthly mean daytime simulated satellite-detectable O3 (ΔO3), respectively. The fractions of significant areas are 55, 84, 93, and 96% at a one-sided 95% confidence interval. Because of the recent advancement of satellite sensor technologies (e.g., TROPOMI), study on tropospheric photochemistry will be rapidly advanced in the near future. The current study proved the usefulness of such satellite analyses on the lower tropospheric O3 and its perturbations due to the precursor gas emission controls. [ABSTRACT FROM AUTHOR]

A total of 14 chemical transport models (CTMs) participated in the first topic of the Model Inter-Comparison Study for Asia (MICS-Asia) phase III. These model results are compared with each other and an extensive set of measurements, aiming to evaluate the current CTMs' ability in simulating aerosol concentrations, to document the similarities and differences among model performance, and to reveal the characteristics of aerosol components in large cities over East Asia. In general, these CTMs can well reproduce the spatial–temporal distributions of aerosols in East Asia during the year 2010. The multi-model ensemble mean (MMEM) shows better performance than most single-model predictions, with correlation coefficients (between MMEM and measurements) ranging from 0.65 (nitrate, NO3-) to 0.83 (PM 2.5). The concentrations of black carbon (BC), sulfate (SO42-), and PM 10 are underestimated by MMEM, with normalized mean biases (NMBs) of -17.0 %, - 19.1 %, and - 32.6 %, respectively. Positive biases are simulated for NO3- (NMB = 4.9 %), ammonium (NH4+) (NMB = 14.0 %), and PM 2.5 (NMB = 4.4 %). In comparison with the statistics calculated from MICS-Asia phase II, frequent updates of chemical mechanisms in CTMs during recent years make the intermodel variability of simulated aerosol concentrations smaller, and better performance can be found in reproducing the temporal variations of observations. However, a large variation (about a factor of 2) in the ratios of SNA (sulfate, nitrate, and ammonium) to PM 2.5 is calculated among participant models. A more intense secondary formation of SO42- is simulated by Community Multi-scale Air Quality (CMAQ) models, because of the higher SOR (sulfur oxidation ratio) than other models (0.51 versus 0.39). The NOR (nitric oxidation ratio) calculated by all CTMs has larger values (∼0.20) than the observations, indicating that overmuch NO3- is simulated by current models. NH3 -limited condition (the mole ratio of ammonium to sulfate and nitrate is smaller than 1) can be successfully reproduced by all participant models, which indicates that a small reduction in ammonia may improve the air quality. A large coefficient of variation (CV > 1.0) is calculated for simulated coarse particles, especially over arid and semi-arid regions, which means that current CTMs have difficulty producing similar dust emissions by using different dust schemes. According to the simulation results of MMEM in six large Asian cities, different air-pollution control plans should be taken due to their different major air pollutants in different seasons. The MICS-Asia project gives an opportunity to discuss the similarities and differences of simulation results among CTMs in East Asian applications. In order to acquire a better understanding of aerosol properties and their impacts, more experiments should be designed to reduce the diversities among air quality models. [ABSTRACT FROM AUTHOR]

We analyzed the ozone (O 3 ) profile product (PROFOZ) derived from Ozone Monitoring Instrument(OMI) ultraviolet (UV) spectra to reveal spatial and temporal variations in O 3 distributions over China. Although discriminating vertical O 3 in the lower troposphere is a challenge for satellite-borne measurements, previous research has confirmed the reliability of the lowermost layer O 3 of the PROFOZ product, corresponding to 0–3 km, under the high O 3 condition over China by comparison with the airborne measurements. In the present study, we focus on the seasonal variation of O 3 obtained in the lowermost layer over China. We track the O 3 enhancement under polluted conditions by using the ozone anomaly (ΔO 3 ), defined as the difference between the retrieval values and a priori values, because our focus is the temporally high O 3 level compared with the background level. We divide the 25–40° N and 100–135° E region into clusters according to the similarity of the seasonal variation in ΔO 3 at the lowermost layer corresponding to approximately 0–3 km in altitude. Using this cluster analysis, we distinguish the areas in which ΔO 3 has outstanding seasonality with high values in summer, particularly in June, and low values in winter over the North China Plain and Sichuan basin. The areas with these anomalous ΔO 3 values correspond to high NO 2 emission areas. We compare the results with model simulations from the Meteorological Research Institute–Chemistry Climate Model (MRI-CCM2) and meteorological data. The areas showing outstanding seasonality also correspond to those of high chemical production rates in June. Along the coastal area, ΔO 3 values tend to drop to negative in August, which can be attributed to the inflow of clean oceanic air to inland regions. The results presented here again demonstrate the reliability of the lower tropospheric O 3 data from the OMI PROFOZ product and suggest good capability of UV satellite sensors for monitoring O 3 pollution that will be launched in the near future. [ABSTRACT FROM AUTHOR]

In recent years, high fine particulate (PM2.5) pollution episodes with high ozone (O3) levels have been observed in Shanghai from time to time. However, their occurrence and characteristics remain poorly understood. Meanwhile, as a major precursor of tropospheric hydroxyl radical (OH) that initiates the formation of hydroperoxyl and organic peroxy radicals, HONO would inevitably affect the formation of O3, but its role in the formation of O3 during the double high-level PM2.5 and O3 pollution episodes remains unclear. In this study, the characteristics of the double high pollution episodes and the role of HONO in O3 formation in these episodes were investigated based on field observation in urban Shanghai from 2014 to 2016. Results showed that high PM2.5 pollution and high O3 pollution could occur simultaneously. The cases with data of double high O3 and PM2.5 concentrations accounted for about 1.0% of the whole sampling period. During the double high pollution episodes, there still existed active photochemical processes, while the active photochemical processes at high PM2.5 concentration were conductive to the production and accumulation of O3 under a VOC-limited regime and a calm atmospheric condition including high temperature, moderately high relative humidity, and low wind speed, which in turn enhanced the conversions of SO2 and NO2 and the formation and accumulation of secondary sulfate and nitrate aerosols and further promoted the increase of PM2.5 concentration and the deterioration of air pollution. Further analysis indicated that the daytime HONO concentration could be strongly negatively correlated with O3 concentration in most of the double high pollution episodes, revealing the dominant role of HONO in O3 formation during these pollution episodes. This study provides important field measurement-based evidence for understanding the significant contribution of daytime HONO to O3 formation, and helps to clarify the formation and coexistence mechanisms of the double high-level O3 and PM2.5 pollution episodes. [ABSTRACT FROM AUTHOR]

We report the results of year-long PM2.5 (particulate matter less than 2.5 µm in diameter) simulations over Northeast Asia for the base year of 2013 under the framework of the Long-range Transboundary Air Pollutants in Northeast Asia (LTP) project. LTP is a tripartite project launched by China, Japan, and Korea for cooperative monitoring and modeling of the long-range transport (LRT) of air pollutants. In the modeling aspect in the LTP project, each country's modeling group employs its own original air quality model and options. The three regional air quality models employed by the modeling groups are WRF-CAMx, NHM-RAQM2, and WRF-CMAQ. PM2.5 concentrations were simulated in remote exit-and-entrance areas associated with the LRT process over China, Japan, and Korea. The results showed apparent bias that remains unexplored due to a series of uncertainties from emission estimates and inherent model limitations. The simulated PM10 levels at seven remote exit-and-entrance sites were underestimated with the normalized mean bias of 0.4 ± 0.2. Among the four chemical components of PM2.5 (SO42−, NO3−, organic carbon (OC), and elemental carbon (EC)), the largest inter-model variability was in OC, with the second largest discrepancy in NO3−. Our simulation results also indicated that under considerable SO42− levels, favorable environments for ammonium nitrate formation were found in exit-and-entrance areas between China and Korea, and gas-aerosol partitioning for semi-volatile species of ammonium nitrate could be fully achieved prior to arrival at the entrance areas. Other chemical characteristics, including NO3−/SO42− and OC/EC ratios, are discussed to diagnose the LRT characteristics of PM2.5 in exit-and-entrance areas associated with transboundary transport over China, Japan, and Korea. [ABSTRACT FROM AUTHOR]