Overlooked significance of iodic acid in new particle formation in the continental atmosphere

New particle formation (NPF) substantially affects the global radiation balance and climate. Iodic acid (IA) is a key marine NPF driver that recently has also been detected inland. However, its impact on continental particle nucleation remains unclear. Here, we provide molecular-level evidence that IA greatly facilitates clustering of two typical land-based nucleating precursors: dimethylamine (DMA) and sulfuric acid (SA), thereby enhancing particle nucleation. Incorporating this mechanism into an atmospheric chemical transport model, we show that IA-induced enhancement could realize an increase of over 20% in the SA-DMA nucleation rate in iodine-rich regions of China. With declining anthropogenic pollution driven by carbon neutrality and clean air policies in China, IA could enhance nucleation rates by 1.5 to 50 times by 2060. Our results demonstrate the overlooked key role of IA in continental NPF nucleation and highlight the necessity for considering synergistic SA-IA-DMA nucleation in atmospheric modeling for correct representation of the climatic impacts of aerosols.

Perspective on Theoretical and Experimental Advances in Atmospheric Photochemistry

Research that explores the chemistry of Earth's atmosphere is central to the current understanding of global challenges such as climate change, stratospheric ozone depletion, and poor air quality in urban areas. This research is a synergistic combination of three established domains: earth observation, for example, using satellites, and in situ field measurements; computer modeling of the atmosphere and its chemistry; and laboratory measurements of the properties and reactivity of gas-phase molecules and aerosol particles. The complexity of the interconnected chemical and photochemical reactions which determine the composition of the atmosphere challenges the capacity of laboratory studies to provide the spectroscopic, photochemical, and kinetic data required for computer models. Here, we consider whether predictions from computational chemistry using modern electronic structure theory and nonadiabatic dynamics simulations are becoming sufficiently accurate to supplement quantitative laboratory data for wavelength-dependent absorption cross-sections, photochemical quantum yields, and reaction rate coefficients. Drawing on presentations and discussions from the CECAM workshop on Theoretical and Experimental Advances in Atmospheric Photochemistry held in March 2024, we describe key concepts in the theory of photochemistry, survey the state-of-the-art in computational photochemistry methods, and compare their capabilities with modern experimental laboratory techniques. From such considerations, we offer a perspective on the scope of computational (photo)chemistry methods based on rigorous electronic structure theory to become a fourth core domain of research in atmospheric chemistry.

Global variability in atmospheric new particle formation mechanisms

A key challenge in aerosol pollution studies and climate change assessment is to understand how atmospheric aerosol particles are initially formed1,2. Although new particle formation (NPF) mechanisms have been described at specific sites3-6, in most regions, such mechanisms remain uncertain to a large extent because of the limited ability of atmospheric models to simulate critical NPF processes1,7. Here we synthesize molecular-level experiments to develop comprehensive representations of 11 NPF mechanisms and the complex chemical transformation of precursor gases in a fully coupled global climate model. Combined simulations and observations show that the dominant NPF mechanisms are distinct worldwide and vary with region and altitude. Previously neglected or underrepresented mechanisms involving organics, amines, iodine oxoacids and HNO3 probably dominate NPF in most regions with high concentrations of aerosols or large aerosol radiative forcing; such regions include oceanic and human-polluted continental boundary layers, as well as the upper troposphere over rainforests and Asian monsoon regions. These underrepresented mechanisms also play notable roles in other areas, such as the upper troposphere of the Pacific and Atlantic oceans. Accordingly, NPF accounts for different fractions (10-80%) of the nuclei on which cloud forms at 0.5% supersaturation over various regions in the lower troposphere. The comprehensive simulation of global NPF mechanisms can help improve estimation and source attribution of the climate effects of aerosols.

Diurnal emission variation of ozone precursors: Impacts on ozone formation during Sep. 2019

With the issue of ozone (O3) pollution having increasingly gained visibility and prominence in China, the Chinese government explored various policies to mitigate O3 pollution. In some provinces and cities, diurnal regulations of O3 precursor were implemented, such as shifting O3 precursor emission processes to nighttime and offering preferential refueling at night. However, the effectiveness of these policies remains unverified, and their impact on the O3 generation process requires further elucidation. In this study, we utilized a regional climate and air quality model (WRF-Chem, v4.5) to test three scenarios aimed at exploring the impact of diurnal industry emission variation of O3 precursors on O3 formation. Significant O3 variations were observed mainly in urban areas. Shifting volatile organic compounds (VOCs) to nighttime have slight decreased daytime O3 levels while moving nitrogen oxides (NOx) to nighttime elevates O3 levels. Simultaneously moving both to nighttime showed combined effects. Process analysis indicates that the diurnal variation in O3 was mainly attributed to chemical process and vertical mixing in urban areas, while advection becomes more important in non-urban areas, contributing to the changes in O3 and O3 precursors levels through regional transportation. Further photochemical analysis reveals that the O3 photochemical production in urban areas was affected by reduced daytime O3 precursors emissions. Specifically, decreasing VOCs lowered the daytime O3 production by reducing the ROx radicals (ROx = HO + HO˙2 + RO˙2), whereas decreasing NOx promoted the daytime O3 production by weakening ROx radical loss. Our results demonstrate that diurnal regulation of O3 precursors will disrupt the ROx radical and O3 formation in local areas, resulting in a change in O3 concentration and atmospheric oxidation capacity, which should be considered in formulating new relevant policies.

Tethered balloon system and High-Resolution Mass Spectrometry Reveal Increased Organonitrates Aloft Compared to the Ground Level

Atmospheric particles play critical roles in climate. However, significant knowledge gaps remain regarding the vertically resolved organic molecular-level composition of atmospheric particles due to aloft sampling challenges. To address this, we use a tethered balloon system at the Southern Great Plains Observatory and high-resolution mass spectrometry to, respectively, collect and characterize organic molecular formulas (MF) in the ground level and aloft (up to 750 m) samples. We show that organic MF uniquely detected aloft were dominated by organonitrates (139 MF; 54% of all uniquely detected aloft MF). Organonitrates that were uniquely detected aloft featured elevated O/C ratios (0.73 ± 0.23) compared to aloft organonitrates that were commonly observed at the ground level (0.63 ± 0.22). Unique aloft organic molecular composition was positively associated with increased cloud coverage, increased aloft relative humidity (∼40% increase compared to ground level), and decreased vertical wind variance. Furthermore, 29% of extremely low volatility organic compounds in the aloft sample were truly unique to the aloft sample compared to the ground level, emphasizing potential oligomer formation at higher altitudes. Overall, this study highlights the importance of considering vertically resolved organic molecular composition (particularly for organonitrates) and hypothesizes that aqueous phase transformations and vertical wind variance may be key variables affecting the molecular composition of aloft organic aerosol.

Volatility Basis Set Distributions and Viscosity of Organic Aerosol Mixtures: Insights from Chemical Characterization Using Temperature-Programmed Desorption-Direct Analysis in Real-Time High-Resolution Mass Spectrometry

Quantitative assessment of gas-particle partitioning of individual components within complex atmospheric organic aerosol (OA) mixtures is critical for predicting and comprehending the formation and evolution of OA particles in the atmosphere. This investigation leverages previously documented data obtained through a temperature-programmed desorption-direct analysis in real-time, high-resolution mass spectrometry (TPD-DART-HRMS) platform. This methodology facilitates the bottom-up construction of volatility basis set (VBS) distributions for constituents found in three biogenic secondary organic aerosol (SOA) mixtures produced through the ozonolysis of α-pinene, limonene, and ocimene. The apparent enthalpies (ΔH*, kJ mol-1) and saturation mass concentrations (CT*, μg·m-3) of individual SOA components, determined as a function of temperature (T, K), facilitated an assessment of changes in VBS distributions and gas-particle partitioning with respect to T and atmospheric total organic mass loadings (tOM, μg·m-3). The VBS distributions reveal distinct differences in volatilities among monomers, dimers, and trimers, categorized into separate volatility bins. At the ambient temperature of T = 298 K, only monomers efficiently partition between gas and particle phases across a broad range of atmospherically relevant tOM values of 1-100 μg·m-3. Partitioning of dimers and trimers becomes notable only at T > 360 K and T > 420 K, respectively. The viscosity of SOA mixtures is assessed using a bottom-up calculation approach, incorporating the input of elemental formulas, ΔH*, CT*, and particle-phase mass fractions of the SOA components. Through this approach, we are able to accurately estimate the variations in SOA viscosity that result from the evaporation of its components. These variations are, in turn, influenced by atmospherically relevant changes in tOM and T. Comparison of the calculated SOA viscosity and diffusivity values with literature reported experimental results shows close agreement, thereby validating the employed calculation approach. These findings underscore the significant potential for TPD-DART-HRMS measurements in enabling the untargeted analysis of organic molecules within OA mixtures. This approach facilitates quantitative assessment of their gas-particle partitioning and allows for the estimation of their viscosity and condensed-phase diffusion, thereby contributing valuable insights to atmospheric models.

Hotspot driven air pollution during crop residue burning season in the Indo-Gangetic Plain, India

Intensive crop residue burning (CRB) in northern India triggers severe air pollution episodes over the Indo-Gangetic Plain (IGP) each year during October and November. We have quantified the contribution of hotspot districts (HSDs) and total CRB to poor air quality over the IGP. Initially, we investigated the spatiotemporal distribution of CRB fire within the domain and pinpointed five HSD in each Punjab and Haryana. Furthermore, we have simulated air quality and quantified the impact of CRB using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), incorporating recent anthropogenic emissions (EDGAR v5) and biomass burning emissions (FINN v2.4) inventories, along with MOZART-MOSAIC chemistry. The key finding is that HSDs contributed ∼80% and ∼50% of the total fire counts in Haryana and Punjab, respectively. The model effectively captured observed PM₂.₅ concentrations, with a normalized mean bias (NMB) below 0.2 and R-squared (R2) exceeding 0.65 at the majority of validation sites. However, some discrepancies were observed at a few sites in Delhi, Punjab, Haryana, and West Bengal. The National Capital Region experienced the highest PM₂.₅ concentrations, followed by Punjab, Haryana, Uttar Pradesh, Bihar, and West Bengal. Moreover, HSDs were responsible for about 70% of the total increase in CRB-induced PM₂.₅ in the western, central, and eastern cities, and around 50% in the northern cities. By eliminating CRB emissions across the domain, we could potentially save approximately 18,000 lives annually. Policymakers, scientists, and institutions can leverage the framework to address air pollution at national and global scales by targeting source-specific hotspots. This approach, coupled with appropriate technological and financial solutions, can contribute to achieving climate change and sustainable development goals.

Uniformly elevated future heat stress in China driven by spatially heterogeneous water vapor changes

The wet bulb temperature (Tw) has gained considerable attention as a crucial indicator of heat-related health risks. Here we report south-to-north spatially heterogeneous trends of Tw in China over 1979-2018. We find that actual water vapor pressure (Ea) changes play a dominant role in determining the different trend of Tw in southern and northern China, which is attributed to the faster warming of high-latitude regions of East Asia as a response to climate change. This warming effect regulates large-scale atmospheric features and leads to extended impacts of the South Asia high (SAH) and the western Pacific subtropical high (WPSH) over southern China and to suppressed moisture transport. Attribution analysis using climate model simulations confirms these findings. We further find that the entire eastern China, that accommodates 94% of the country's population, is likely to experience widespread and uniform elevated thermal stress the end of this century. Our findings highlight the necessity for development of adaptation measures in eastern China to avoid adverse impacts of heat stress, suggesting similar implications for other regions as well.

Direct Observation of Particle-To-Particle Variability in Ambient Aerosol pH Using a Novel Analytical Approach Based on Surface-Enhanced Raman Spectroscopy

The pH of atmospheric aerosols is a key characteristic that profoundly influences their impacts on climate change, human health, and ecosystems. Despite widely performed aerosol pH research, determining the pH levels of individual atmospheric aerosol particles has been a challenge. This study presents a novel analytical technique that utilizes surface-enhanced Raman spectroscopy to assess the pH of individual ambient PM2.5-10 aerosol particles in conjunction with examining their hygroscopic behavior, morphology, and elemental compositions. The results revealed a substantial pH variation among simultaneously collected aerosol particles, ranging from 3.3 to 5.7. This variability is likely related to each particle's unique reaction and aging states. The extensive particle-to-particle pH variability suggests that atmospheric aerosols present at the same time and location can exhibit diverse reactivities, reaction pathways, phase equilibria, and phase separation properties. This pioneering study paves the way for in-depth investigations into particle-to-particle variability, size dependency, and detailed spatial and temporal variations of aerosol pH, thus deepening our understanding of atmospheric chemistry and its environmental implications.

Dominant physical and chemical processes impacting nitrate in Shandong of the North China Plain during winter haze events

Nitrate has been a dominant component of PM2.5 since the stringent emission control measures implemented in China in 2013. Clarifying key physical and chemical processes influencing nitrate concentrations is crucial for eradicating heavy air pollution in China. In this study, we explored dominant processes impacting nitrate concentrations in Shandong of the North China Plain during three haze events from 9 to 25 December 2021, named cases P1 (94.46 (30.85) μg m-3 for PM2.5 (nitrate)), P2 (148.95 (50.12) μg m-3) and P3 (88.03 (29.21) μg m-3), by using the Weather Research and Forecasting/Chemistry model with an integrated process rate analysis scheme and updated heterogeneous hydrolysis of dinitrogen pentoxide on the wet aerosol surface (HET-N2O5) and additional nitrous acid (HONO) sources (AS-HONO). The results showed that nitrate increases in the three cases were attributed to aerosol chemistry, whereas nitrate decreases were due mainly to the vertical mixing process in cases P1 and P2 and to the advection process in case P3. HET-N2O5 (the reaction of OH + NO2) contributed 45 % (51 %) of the HNO3 production rate during the study period. AS-HONO produced a nitrate enhancement of 24 % in case P1, 12 % in case P2 and 19 % in case P3, and a HNO3 production rate enhancement of 0.79- 0.97 (0.18- 0.60) μg m-3 h-1 through the reaction of OH + NO2 (HET-N2O5) in the three cases. This study implies that using suitable parameterization schemes for heterogeneous reactions on aerosol and ground surfaces and nitrate photolysis is vital in simulations of HONO and nitrate, and the MOSAIC module for aerosol water simulations needs to be improved.

Air quality modeling in the metropolitan area of São Paulo, Brazil: A review

Numerous studies have used air quality models to estimate pollutant concentrations in the Metropolitan Area of São Paulo (MASP) by using different inputs and assumptions. Our objectives are to summarize these studies, compare their performance, configurations, and inputs, and recommend areas of further research. We examined 29 air quality modeling studies that focused on ozone (O3) and fine particulate matter (PM2.5) performed over the MASP, published from 2001 to 2023. The California Institute of Technology airshed model (CIT) was the most used offline model, while the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was the most used online model. Because the main source of air pollution in the MASP is the vehicular fleet, it is commonly used as the only anthropogenic input emissions. Simulation periods were typically the end of winter and during spring, seasons with higher O3 and PM2.5 concentrations. Model performance for hourly ozone is good with half of the studies with Pearson correlation above 0.6 and root mean square error (RMSE) ranging from 7.7 to 27.1 ppb. Fewer studies modeled PM2.5 and their performance is not as good as ozone estimates. Lack of information on emission sources, pollutant measurements, and urban meteorology parameters is the main limitation to perform air quality modeling. Nevertheless, researchers have used measurement campaign data to update emission factors, estimate temporal emission profiles, and estimate volatile organic compounds (VOCs) and aerosol speciation. They also tested different emission spatial disaggregation approaches and transitioned to global meteorological reanalysis with a higher spatial resolution. Areas of research to explore are further evaluation of models' physics and chemical configurations, the impact of climate change on air quality, the use of satellite data, data assimilation techniques, and using model results in health impact studies. This work provides an overview of advancements in air quality modeling within the MASP and offers practical approaches for modeling air quality in other South American cities with limited data, particularly those heavily impacted by vehicle emissions.

Modeling the Formation of Organic Compounds across Full Volatility Ranges and Their Contribution to Nanoparticle Growth in a Polluted Atmosphere

Nanoparticle growth influences atmospheric particles' climatic effects, and it is largely driven by low-volatility organic vapors. However, the magnitude and mechanism of organics' contribution to nanoparticle growth in polluted environments remain unclear because current observations and models cannot capture organics across full volatility ranges or track their formation chemistry. Here, we develop a mechanistic model that characterizes the full volatility spectrum of organic vapors and their contributions to nanoparticle growth by coupling advanced organic oxidation modeling and kinetic gas-particle partitioning. The model is applied to Nanjing, a typical polluted city, and it effectively captures the volatility distribution of low-volatility organics (with saturation vapor concentrations <0.3 μg/m3), thus accurately reproducing growth rates (GRs), with a 4.91% normalized mean bias. Simulations indicate that as particles grow from 4 to 40 nm, the relative fractions of GRs attributable to organics increase from 59 to 86%, with the remaining contribution from H2SO4 and its clusters. Aromatics contribute much to condensable organic vapors (∼37%), especially low-volatility vapors (∼61%), thus contributing the most to GRs (32-46%) as 4-40 nm particles grow. Alkanes also contribute 19-35% of GRs, while biogenic volatile organic compounds contribute minimally (<13%). Our model helps assess the climatic impacts of particles and predict future changes.

Wintertime Formation of Large Sulfate Particles in China and Implications for Human Health

Outdoor air pollution causes millions of premature deaths annually worldwide. Sulfate is a major component of particulate pollution. Winter sulfate observations in China show both high concentrations and an accumulation mode with a modal size >1 μm. However, we find that this observed size distribution cannot be simulated using classical gaseous and aqueous phase formation (CSF) or proposed aerosol-processing formation (APF) mechanisms. Specifically, the CSF simulation underestimates sulfate concentrations by 76% over megacities in China and predicts particle size distributions with a modal size of ∼0.35 μm, significantly smaller than observations. Although incorporating the APF mechanism in the atmospheric chemical model notably improves sulfate concentration simulation with reasonable parameters, the simulated sulfate particle size distribution remains similar to that using the CSF mechanism. We further conduct theoretical analyses and show that particles with diameters <0.3 μm grow rapidly (2-3 s) to 1 μm through the condensation of sulfuric acid in fresh high-temperature exhaust plumes, referred to as in-source formation (ISF). An ISF sulfate source equivalent to 15% of sulfur emissions from fossil fuel combustion largely explains both observed size distributions and mass concentrations of sulfate particles. The findings imply that ISF is a major source of wintertime micron-sized sulfate in China and underscore the importance of considering the size distribution of aerosols for accurately assessing the impacts of inorganic aerosols on radiative forcing and human health.

The influence of dust on extreme precipitation at a large city in North China

In recent decades, the Beijing-Tianjin-Hebei city cluster is experiencing rapid urbanization along with economic booming. Meanwhile, these cities are suffering the influence of extreme precipitation and dust storms. In this study, the impact of dust aerosol on extreme precipitation that occurred in Beijing during 19-21 July 2016 is investigated using both satellite retrievals and Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model simulations. Results reveal that the dust particles can increase extreme precipitation by promoting the formation of ice clouds and enhancing convections. The dust is lifted into the upper troposphere (>10 km) via strong convection and affects the physical process of precipitation after long-range transport. It further transforms the supercooled water into the middle and high levels of ice nuclei (IN). These promote the formation of ice clouds according to the decreased effective radius of IN and increased ice water path, respectively. Along with sufficient water vapor transport and strong convergence, the formation of IN could release more latent heat and further strengthen convection development. Thus, the precipitation amount in southern Beijing is almost enhanced by 40 % (>80 mm). This study will provide a deep insight into understanding the causes of urban extreme precipitation.

Increasing Nonfossil Fuel Contributions to Atmospheric Nitrate in Urban China from Observation to Prediction

China's nitrogen oxide (NOx) emissions have undergone significant changes over the past few decades. However, nonfossil fuel NOx emissions are not yet well constrained in urban environments, resulting in a substantial underestimation of their importance relative to the known fossil fuel NOx emissions. We developed an approach using machine learning that is accurate enough to generate a long time series of the nitrogen isotopic composition (δ15N) of atmospheric nitrate using high-level accuracies of air pollutants and meteorology data. Air temperature was found to be the critical driver of the variation of nitrate δ15N at daily resolution based on this approach, while significant reductions of aerosol and its precursor emissions played a key role in the change of nitrate δ15N on the yearly scale. Predictions from this model found a significant decrease in nitrate δ15N in Chinese megacities (Beijing and Guangzhou as representative cities in the north and south, respectively) since 2013, implying an enhanced contribution of nonfossil fuel NOx emissions to nitrate aerosols (up to 22%-26% in 2021 from 18%-22% in 2013 quantified by an isotope mixing model), as confirmed by the Weather Research and Forecasting model coupled with online chemistry (WRF-Chem) simulation. Meanwhile, the declining contribution in coal combustion (34%-39% in 2013 to 31%-34% in 2021) and increasing contribution of natural gas combustion (11%-14% in 2013 to 14%-17% in 2021) demonstrated the transformation of China's energy structure from coal to natural gas. This approach provides missing records for exploring long-term variability in the nitrogen isotope system and may contribute to the study of the global reactive nitrogen biogeochemical cycle.

Nonequilibrium Behavior in Isoprene Secondary Organic Aerosol

Recent studies have shown that instantaneous gas-particle equilibrium partitioning assumptions fail to predict SOA formation, even at high relative humidity (∼85%), and photochemical aging seems to be one driving factor. In this study, we probe the minimum aging time scale required to observe nonequilibrium partitioning of semivolatile organic compounds (SVOCs) between the gas and aerosol phase at ∼50% RH. Seed isoprene SOA is generated by photo-oxidation in the presence of effloresced ammonium sulfate seeds at <1 ppbv NOx, aged photochemically or in the dark for 0.3-6 h, and subsequently exposed to fresh isoprene SVOCs. Our results show that the equilibrium partitioning assumption is accurate for fresh isoprene SOA but breaks down after isoprene SOA has been aged for as short as 20 min even in the dark. Modeling results show that a semisolid SOA phase state is necessary to reproduce the observed particle size distribution evolution. The observed nonequilibrium partitioning behavior and inferred semisolid phase state are corroborated by offline mass spectrometric analysis on the bulk aerosol particles showing the formation of organosulfates and oligomers. The unexpected short time scale for the phase transition within isoprene SOA has important implications for the growth of atmospheric ultrafine particles to climate-relevant sizes.

Summertime Urban Ammonia Emissions May Be Substantially Underestimated in Beijing, China

Ammonia (NH3) is critical to the nitrogen cycle and PM2.5 formation, yet a great deal of uncertainty exists in its urban emission quantifications. Model-underestimated NH3 concentrations have been reported for cities, yet few studies have provided an explanation. Here, we explore reasons for severe WRF-Chem model underestimations of NH3 concentrations in Beijing in August 2018, including simulated gas-particle partitioning, meteorology, regional transport, and emissions, using spatially refined (3 km resolution) NH3 emission estimates in the agricultural sector for Beijing-Tianjin-Hebei and in the traffic sector for Beijing. We find that simulated NH3 concentrations are significantly lower than ground-based and satellite observations during August in Beijing, while wintertime underestimations are much more moderate. Further analyses and sensitivity experiments show that such discrepancies cannot be attributed to factors other than biases in NH3 emissions. Using site measurements as constraints, we estimate that both agricultural and non-agricultural NH3 emission totals in Beijing shall increase by ∼5 times to match the observations. Future research should be performed to allocate underestimations to urban fertilizer, power, traffic, or residential sources. Dense and regular urban NH3 observations are necessary to constrain and validate bottom-up inventories and NHx simulation.

Modeling Impacts of Urbanization on Winter Boundary Layer Meteorology and Aerosol Pollution in the Central Liaoning City Cluster, China

The influence of urbanization on the frequent winter aerosol pollution events in Northeast China is not fully understood. The Weather Research and Forecasting Model with Chemistry (WRF-Chem) coupled with urban canopy (UC) models was used to simulate the impact of urbanization on an aerosol pollution process in the Central Liaoning city cluster (CLCC), China. To investigate the main mechanisms of urban expansion and UC on the winter atmospheric environment and the atmospheric diffusion capacity (ADC) in the CLCC, three simulation cases were designed using land-use datasets from different periods and different UC schemes. A comparative analysis of the simulation results showed that the land-use change (LU) and both LU and UC (LUUC) effects lead to higher surface temperature and lower relative humidity and wind speed in the CLCC by decreasing surface albedo, increasing sensible heat flux, and increasing surface roughness, with a spatial distribution similar to the distribution of LU. The thermal effect leads to an increase in atmospheric instability, an increase in boundary layer height and diffusion coefficient, and an increase in the ADC. The LU and LUUC effects lead to a significant decrease in near-surface PM2.5 concentrations in the CLCC due to changes in meteorological conditions and ADC within the boundary layer. The reduction in surface PM2.5 concentrations due to the LU effect is stronger at night than during daytime, while the LUUC effect leads to a greater reduction in surface PM2.5 concentrations during the day, mainly due to stronger diffusion and dilution caused by the effect of urban turbulence within different levels caused by the more complex UC scheme. In this study, the LU and LUUC effects result in greater thermal than dynamic effects, and both have a negative impact on surface PM2.5 concentrations, but redistribute pollutants from the lower urban troposphere to higher altitudes.

Air pollution and associated health impact and economic loss embodied in inter-provincial electricity transfer in China

As the largest producer and consumer of coal in the world, China heavily relies on coal resources for thermal power generation. Owing to the unbalanced distribution of energy resources, electricity transfer among regions in China plays a key role in promoting economic growth and ensuring energy safety. However, little is known about air pollution and the related health impacts resulting from electricity transfer. This study assessed PM_2.5 pollution and related health and economic losses attributable to the inter-provincial electricity transfer in mainland China in 2016. The results show that a large amount of virtual air pollutant emissions were transferred from energy-abundant northern, western and central China to well-developed and populated eastern coastal regions. Correspondingly, the inter-provincial electricity transfer dramatically reduced the atmospheric levels of PM_2.5 and related health and economic losses in eastern and southern China, while increasing those in northern, western and central China. The health benefits attributable to inter-provincial electricity transfer were mainly found in Guangdong, Liaoning, Jiangsu and Shandong, whereas the extra health loss is concentrated in Hebei, Shanxi, Inner Mongolia, and Heilongjiang. Overall, the inter-provincial electricity transfer led to an extra increase of 3600 (95 % CI: 3200-4100) PM_2.5-related deaths and 345 (95 % CI: 294-389) million USD of economic loss in China in 2016. The results could assist air pollution mitigation strategies for the thermal power sector in China by strengthening the cooperation between suppliers and consumers of electricity.

Optimal reactive nitrogen control pathways identified for cost-effective PM2.5 mitigation in Europe

Excess reactive nitrogen (Nr), including nitrogen oxides (NO_x) and ammonia (NH₃), contributes strongly to fine particulate matter (PM_2.5) air pollution in Europe, posing challenges to public health. Designing cost-effective Nr control roadmaps for PM_2.5 mitigation requires considering both mitigation efficiencies and implementation costs. Here we identify optimal Nr control pathways for Europe by integrating emission estimations, air quality modeling, exposure-mortality modeling, Nr control experiments and cost data. We find that phasing out Nr emissions would reduce PM_2.5 by 2.3 ± 1.2 μg·m^-3 in Europe, helping many locations achieve the World Health Organization (WHO) guidelines and reducing PM_2.5-related premature deaths by almost 100 thousand in 2015. Low-ambition NH₃ controls have similar PM_2.5 mitigation efficiencies as NO_x in Eastern Europe, but are less effective in Western Europe until reductions exceed 40%. The efficiency for NH₃ controls increases at high-ambition reductions while NO_x slightly decreases. When costs are considered, strategies for both regions uniformly shift in favor of NH₃ controls, as NH₃ controls up to 50% remain 5-11 times more cost-effective than NO_x per unit PM_2.5 reduction, emphasizing the priority of NH₃ control policies for Europe.

Impact of coronavirus-driven reduction in aerosols on precipitation in the western United States

Among the many impacts of COVID-19, the pandemic led to improved air quality conditions in the countries under quarantine due to the shutdown of industries, drastically reduced traffic, and lockdowns. Meanwhile, the western United States, particularly the coastal areas from Washington to California, received much less precipitation than normal during early 2020. Is it possible that this reduction in precipitation was driven by the reduced aerosols due to the coronavirus? Here we show that the reduction in aerosols resulted in higher temperatures (up to ∼0.5 °C) and generally lower snow amounts but cannot explain the observed low precipitation amounts over this region. In addition to an assessment of the effects of the coronavirus-related reduction in aerosols on precipitation across the western United States, our findings also provide basic information on the potential impacts different mitigation efforts aimed at reducing anthropogenic aerosols would have on the regional climate.

The underlying mechanisms of PM2.5 and O3 synergistic pollution in East China: Photochemical and heterogeneous interactions

The rapid development of Chinese cities is accompanied by air pollution. Although the implementation of air pollution control strategies in recent years has alleviated PM_2.5 pollution, O₃ pollution and the synergistic pollution of PM_2.5 and O₃ have become more serious. To understand the underlying chemical interaction mechanisms between PM_2.5 and O₃, we applied the modified Weather Research and Forecasting model with Chemistry (WRF-Chem) to study the effects of aerosol-photolysis feedback and heterogeneous reactions on the two pollutants and revealed the contribution of different mechanisms in different seasons and regions in Yangtze River Delta (YRD) in eastern China. We found that, through the aerosol-photolysis feedback, PM_2.5 decreased the surface photolysis rates J_NO2 and J_O1D, resulting in a decrease in O₃ concentration in the VOC-sensitive area and a slight increase in the NO_x-sensitive area. The heterogeneous reactions reduced O₃ concentration in the YRD in spring, autumn and winter by consuming H_xO_y. While in summer, the heterogeneous absorption of NO_x decreased O₃ in the NO_x-sensitive areas and increased O₃ in the VOC-sensitive areas. Heterogeneous reactions also promoted the secondary formation of fine sulfate and nitrate aerosols, especially in winter. Through the combined effect of two chemical processes, PM_2.5 can lead to a decrease in O₃ concentration of -3.3 ppb (-7.6 %), -2.2 ppb (-4.0 %), -2.9 ppb (-6.3 %), and - 5.9 ppb (-18.7 %), in spring, summer, autumn and winter in YRD. Therefore, if the PM_2.5 concentration decreases, the weakening effect of PM_2.5 on the ozone concentration will be reduced, resulting in the aggravation of ozone pollution. This study is important for understanding the synergistic pollution mechanism and provides a scientific basis for the coordinated control of urban air pollution.

Unified theoretical framework for black carbon mixing state allows greater accuracy of climate effect estimation

Black carbon (BC) plays an important role in the climate system because of its strong warming effect, yet the magnitude of this effect is highly uncertain owing to the complex mixing state of aerosols. Here we build a unified theoretical framework to describe BC's mixing states, linking dynamic processes to BC coating thickness distribution, and show its self-similarity for sites in diverse environments. The size distribution of BC-containing particles is found to follow a universal law and is independent of BC core size. A new mixing state module is established based on this finding and successfully applied in global and regional models, which increases the accuracy of aerosol climate effect estimations. Our theoretical framework links observations with model simulations in both mixing state description and light absorption quantification.

Exploring drivers of the aggravated surface O3 over North China Plain in summer of 2015-2019: Aerosols, precursors, and meteorology

Continuous aggravated surface O₃ over North China Plain (NCP) has attracted widely public concern. Herein, we evaluated the effects of changes in aerosols, precursor emissions, and meteorology on O₃ in summer (June) of 2015-2019 over NCP via 8 scenarios with WRF-Chem model. The simulated mean MDA8 O₃ in urban areas of 13 major cities in NCP increased by 17.1%∼34.8%, which matched well with the observations (10.8%∼33.1%). Meanwhile, the model could faithfully reproduce the changes in aerosol loads, precursors, and meteorological conditions. A relatively-even O₃ increase (+1.2%∼+3.9% for 24-h O₃ and +1.0%∼+3.8% for MDA8 O₃) was induced by PM_2.5 dropping, which was consistent with the geographic distribution of regional PM_2.5 reduction. Meanwhile, the NO₂ reduction coupled with a near-constant VOCs led to the elevated VOCs/NO_x ratios, and then caused O₃ rising in the areas under VOCs-limited regimes. Therein, the pronounced increases occurred in Handan, Xingtai, Shijiazhuang, Tangshan, and Langfang (+10.7%∼+13.6% for 24-h O₃ and +10.2%∼+12.2% for MDA8 O₃); while the increases in other cities were 5.7%∼10.5% for 24-h O₃ and 4.9%∼9.2% for MDA8 O₃. Besides, the meteorological fluctuations brought about the more noticeable O₃ increases in northern parts (+12.5%∼+13.5% for 24-h O₃ and +11.2%∼+12.4% for MDA8 O₃) than those in southern and central parts (+3.2%∼+9.3% for 24-h O₃ and +3.7%∼+8.8% for MDA8 O₃). The sum of the impacts of the three drivers reached 16.7%∼21.9%, which were comparable to the changes of the observed O₃. Therefore, exploring reasonable emissions-reduction strategies is essential for the ozone pollution mitigation over this region.

Effect of agricultural soil wind erosion on urban PM2.5 concentrations simulated by WRF-Chem and WEPS: A case study in Kaifeng, China

Dust emission induced by agricultural soil wind erosion is one of the main sources of atmospheric particulate matter (PM) in dryland areas. However, most current air quality models do not consider this emission source, resulting in large uncertainties in PM simulations. Here we estimated the agricultural PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) emission around Kaifeng, a prefecture-level city in central China, using the Wind Erosion Prediction System (WEPS), with the MEIC (Multi-resolution Emission Inventory for China) as an anthropogenic emission source. We then plugged these estimates into the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to simulate an air pollution episode in Kaifeng, China. Results showed that the addition of agricultural soil PM_2.5 emissions significantly improved the ability of WRF-Chem to accurately simulate PM_2.5 concentrations. The PM_2.5 concentration mean bias and correlation coefficient of not considered and considered agricultural dust emission were -72.35 μg m^-‍3 and 3.31 μg m^-‍3 and 0.3 and 0.58, respectively. The PM_2.5 emitted by the agricultural soil wind erosion contributed around 37.79% of the PM_2.5 in the Kaifeng municipal district during this pollution episode. This study confirmed that the dust emission caused by agricultural soil wind erosion can significantly impact urban PM_2.5 concentrations which surrounded by large areas of farmland, and also indicated that coupling dust emissions from farmland with anthropogenic air pollutant emissions can improve the accuracy of air quality models.

Molecular Imaging Reveals Two Distinct Mixing States of PM2.5 Particles Sampled in a Typical Beijing Winter Pollution Case

Mixing states of aerosol particles are crucial for understanding the role of aerosols in influencing air quality and climate. However, a fundamental understanding of the complex mixing states is still lacking because most traditional analysis techniques only reveal bulk chemical and physical properties with limited surface and 3-D information. In this research, 3-D molecular imaging enabled by ToF-SIMS was used to elucidate the mixing states of PM_2.5 samples obtained from a typical Beijing winter haze event. In light pollution cases, a thin organic layer covers separated inorganic particles; while in serious pollution cases, ion exchange and an organic-inorganic mixing surface on large-area particles were observed. The new results provide key 3-D molecular information of mixing states, which is highly potential for reducing uncertainty and bias in representing aerosol-cloud interactions in current Earth System Models and improving the understanding of aerosols on air quality and human health.

Sensitivity of WRF/Chem simulated PM2.5 to initial/boundary conditions and planetary boundary layer parameterization schemes over the Indo-Gangetic Plain

The ability of a chemical transport model to simulate accurate meteorological and chemical processes depends upon the physical parametrizations and quality of meteorological input data such as initial/boundary conditions. In this study, weather research and forecasting model coupled with chemistry (WRF-Chem) is used to test the sensitivity of PM_2.5 predictions to planetary boundary layer (PBL) parameterization schemes (YSU, MYJ, MYNN, ACM2, and Boulac) and meteorological initial/boundary conditions (FNL, ERA-Interim, GDAS, and NCMRWF) over Indo-Gangetic Plain (Delhi, Punjab, Haryana, Uttar Pradesh, and Rajasthan) during the winter period (December 2017 to January 2018). The aim is to select the model configuration for simulating PM_2.5 which shows the lowest errors and best agreement with the observed data. The best results were achieved with initial/boundary conditions from ERA and GDAS datasets and local PBL parameterization (MYJ and MYNN). It was also found that PM_2.5 concentrations are relatively less sensitive to changes in initial/boundary conditions but in contrast show a stronger sensitivity to changes in the PBL scheme. Moreover, the sensitivity of the simulated PM_2.5 to the choice of PBL scheme is more during the polluted hours of the day (evening to early morning), while that to the choice of the meteorological input data is more uniform and subdued over the day. This work indicates the optimal model setup in terms of choice of initial/boundary conditions datasets and PBL parameterization schemes for future air quality simulations. It also highlights the importance of the choice of PBL scheme over the choice of meteorological data set to the simulated PM_2.5 by a chemical transport model.

Which aerosol type dominate the impact of aerosols on ozone via changing photolysis rates?

The impact of aerosols on ozone via influencing photolysis rates is a combined effect of absorbing aerosols (AA) and scattering aerosols (SA). However, AA and SA show different optical properties and influence photolysis rates differently, which then cause different impacts on ozone. Till now, the dominate factor is disconfirmed, which is largely due to the impact of SA on ozone not reaching to a consistent conclusion. In this study, the WRF-Chem model was implemented to simulate the air pollutants over the North China Plain (NCP). The impacts of AA and SA on ozone via influencing photolysis rates were quantitatively isolated and analyzed. Our results also demonstrated the decreasing effect of AA on ozone within planet boundary layer (PBL) which is consistent with the conclusions of previous studies. But for SA, it decreased the ozone chemical contribution (CHEM) near surface but increased which in the upper layers of PBL, that enlarge the ozone vertical gradients. In this case, more vertical exchanges of ozone would occur with the effect of vertical mixing motion of atmosphere, then the opposite CHEM variations were counteracted with each other and finally led to very slight changes in ozone within PBL. Thus, it can be summarized that AA dominate this impact of aerosols on ozone. Reducing AA could cause a general increase in ozone (ΔO3) over the NCP. Based on the aerosol levels of this case, ΔO3 would be seen over 86 % of the areas in the NCP when reducing AA by 3/4 and ΔO3 was more significant in the megacities. Our study highlights the different relationships between ozone and aerosol types, which suggests that more attentions should be paid on aerosol types, especially AA, when making the synergetic control strategy of aerosols and ozone in China.

Secondary PM2.5 dominates aerosol pollution in the Yangtze River Delta region: Environmental and health effects of the Clean air Plan

The Clean Air Plan has been active in China since 2013 to mitigate severe PM_2.5 pollution. In this study, we applied the air quality model WRF-Chem to simulate PM_2.5 in the Yangtze River Delta (YRD) region of China in 2017, with the aim of assessing the air quality improvement and its associated health burden in the final year of the Clean Air Plan. To better describe the fate of various PM_2.5 compositions, we updated the chemical mechanisms in the model beforehand, including heterogeneous sulfate reactions, aqueous secondary organic aerosol (SOA) uptake, and volatility basis set (VBS) based SOA production. Both the observation and simulation results agreed that the stringent clear air action effectively reduced the PM_2.5 pollution levels by ∼ 30 %. The primary PM_2.5 (-6 ∼  - 16 % yr^-1) showed a more significant decreasing trend than the secondary PM_2.5 (-2 ∼  - 8 % yr^-1), which was mainly caused by the directivity of the clear air actions and the worsening ozone pollution in the recent years. The inconsistent decreasing trends of PM_2.5 components subsequently led to an increasing proportion of secondary PM_2.5. Nitrate particles, higher in the central and western YRD region, have replaced sulfate and have become the largest component of secondary inorganic aerosols year-round, except in summer, when strong ammonium nitrate evaporation occurs. In addition, SOA remains an important component (21 ∼ 22 %) especially in summer, most of which is produced from the oxidation and ageing of semi/intermediate volatile organic compounds (S/IVOC). Furthermore, we quantified the associated health impacts and found that the Clean Air Plan has largely reduced premature mortality due to PM_2.5 exposure in the YRD region from 399.1 thousand to 295.7 thousand. Our study highlights the benefits of the Clean Air Plan and suggests that subsequent PM_2.5 improvement should be geared more towards controlling secondary pollutants.

Maize yield reduction and economic losses caused by ground-level ozone pollution with exposure- and flux-response relationships in the North China Plain

Ground-level ozone (O₃) has negative effects on agricultural crops. Maize is an important grain crop in China. The North China Plain (NCP) serves as the major crops' production area of China and experiences severe ozone pollution. Using the ground-level ozone simulated by an atmospheric chemistry transport model (WRF-Chem), we quantified the yield reduction and economic losses of maize during 2015-2018 over NCP based on exposure-response AOT40 (accumulation of hourly O₃ concentration exceed 40 ppb) and flux-response POD₆ (phytotoxic dose of ozone over 6 nmol m^-2 s^-1). Results showed that the ozone concentration, AOT40, and POD₆ clearly increased from 2015 to 2018 in growing season of maize over NCP. The four-year annual mean ozone concentration, AOT40, and POD₆ were 0.055 ppm, 18.02 ppm h, and 5.02 mmol m^-2, respectively. At county level, the relative loss of maize yield (MRYL) based on AOT40 and POD₆ had clearly spatio-temporal differences in NCP. The average MRYLs of AOT40 and of POD₆ from 2015 to 2018 were 10.4% and 21.4%, respectively, and these reductions were associated with 2399 million and 5637 million US dollars, respectively. This study suggests that surface ozone increased the yield losses of maize, and indicates that further reductions in ozone concentrations can enhance the food security in China.

Achieving Brazil's Deforestation Target Will Reduce Fire and Deliver Air Quality and Public Health Benefits

Climate, deforestation, and forest fires are closely coupled in the Amazon, but models of fire that include these interactions are lacking. We trained machine learning models on temperature, rainfall, deforestation, land-use, and fire data to show that spatial and temporal patterns of fire in the Amazon are strongly modified by deforestation. We find that fire count across the Brazilian Amazon increases by 0.44 percentage points for each percentage point increase in deforestation rate. We used the model to predict that the increased deforestation rate in the Brazilian Amazon from 2013 to 2020 caused a 42% increase in fire counts in 2020. We predict that if Brazil had achieved the deforestation target under the National Policy on Climate Change, there would have been 32% fewer fire counts across the Brazilian Amazon in 2020. Using a regional chemistry-climate model and exposure-response associations, we estimate that the improved air quality due to reduced smoke emission under this scenario would have resulted in 2,300 fewer deaths due to reduced exposure to fine particulate matter. Our analysis demonstrates the air quality and public health benefits that would accrue from reducing deforestation in the Brazilian Amazon.

South Asian black carbon is threatening the water sustainability of the Asian Water Tower

Long-range transport of black carbon from South Asia to the Tibetan plateau and its deposition on glaciers directly enhances glacier melt. Here we find South Asian black carbon also has an indirect effect on the plateau's glaciers shrinkage by acting to reduce the water supply over the southern Tibetan plateau. Black carbon enhances vertical convection and cloud condensation, which results in water vapor depletion over the Indian subcontinent that is the main moisture flux source for the southern Tibetan plateau. Increasing concentrations of black carbon causes a decrease in summer precipitation over the southern Tibetan plateau, resulting in 11.0% glacier deficit mass balance on average from 2007 to 2016; this loss rises to 22.1% in the Himalayas. The direct (accelerated melt) and indirect (mass supply decrease) effects of black carbon are driving the glacial mass decline of the so-called "Asian Water Tower".

Co-Benefits of Energy Structure Transformation and Pollution Control for Air Quality and Public Health until 2050 in Guangdong, China

In order to mitigate global warming and improve air quality, the transformation of regional energy structures is the most important development pathway. China, as a major global consumer of fossil fuels, will face great pressure in this regard. Aiming toward achieving the global 2 °C warming target in China, this study takes one of the most developed regions of China, Guangdong Province, as the research area in order to explore a future development pathway and potential air quality attainment until 2050, by developing two energy structure scenarios (BAU_Energy and 2Deg_Energy) and three end-of-pipe scenarios (NFC, CLE, and MTFR), and simulating future air quality and related health impacts for the different scenarios using the WRF-Chem model. The results show that under the energy transformation scenario, total energy consumption in Guangdong rises from 296 Mtce (million tons of coal equivalent) in 2015 to 329 Mtce in 2050, with electricity and clean energy accounting for 45% and 35%. In 2050, the transformation of the energy structure leads to 64%, 75%, and 46% reductions in the emissions of CO₂, NOx, and SO₂ compared with those in 2015. Together with the most stringent end-of-pipe control measures, the emissions of VOCs and primary PM_2.5 are effectively reduced by 66% and 78%. The annual average PM_2.5 and MDA8 (daily maximum 8 h O₃) concentrations in Guangdong are 33.8 and 85.9 μg/m³ in 2015, with 63.4 thousand premature deaths (95% CI: 57.1-70.8) due to environmental exposure. Under the baseline scenario, no improvement is gained in air quality or public health by 2050. In contrast, the PM_2.5 and MDA8 concentrations decline to 21.7 and 75.5 μg/m³ under the scenario with energy structure transformation, and total premature deaths are reduced to 35.5 thousand (31.9-39.5). When further combined with the most stringent end-of-pipe control measures, the PM_2.5 concentrations decrease to 16.5 μg/m³, but there is no significant improvement for ozone, with premature deaths declining to 20.6 thousand (18.5-23.0). This study demonstrates that the transformation of energy structure toward climate goals could be effective in mitigating air pollution in Guangdong and would bring significant health benefits. Compared with the end-of-pipe control policies, transformation of the energy structure is a more effective way to improve regional air quality in the long term, and synergistic promotion of both is crucial for regional development.

Notable impact of wildfires in the western United States on weather hazards in the central United States

Wildfires have intensified in both frequency and burned areas in recent decades in the United States and constitute a significant threat to life and property. Sensible heat and aerosols produced by wildfires may affect severe storms and weather hazards downstream. Here, we show that wildfires in the western United States can lead to more severe hazardous weather in the central United States, notably increasing occurrences of heavy precipitation rates and large hail. Both heat and aerosols from wildfires play an important role. As wildfires are projected to be more severe in a warmer climate, the influence of wildfires on severe weather in downstream regions may become increasingly important.

Increased wildfire events constitute a significant threat to life and property in the United States. Wildfire impact on severe storms and weather hazards is another pathway that threatens society, and our understanding of which is very limited. Here, we use unique modeling developments to explore the effects of wildfires in the western US (mainly California and Oregon) on precipitation and hail in the central US. We find that the western US wildfires notably increase the occurrences of heavy precipitation rates by 38% and significant severe hail (≥2 in.) by 34% in the central United States. Both heat and aerosols from wildfires play an important role. By enhancing surface high pressure and increasing westerly and southwesterly winds, wildfires in the western United States produce (1) stronger moisture and aerosol transport to the central United States and (2) larger wind shear and storm-relative helicity in the central United States. Both the meteorological environment more conducive to severe convective storms and increased aerosols contribute to the enhancements of heavy precipitation rates and large hail. Moreover, the local wildfires in the central US also enhance the severity of storms, but their impact is notably smaller than the impact of remote wildfires in California and Oregon because of the lessened severity of the local wildfires. As wildfires are projected to be more frequent and severe in a warmer climate, the influence of wildfires on severe weather in downwind regions may become increasingly important.

Impacts of TROPOMI-Derived NO X Emissions on NO2 and O3 Simulations in the NCP during COVID-19

NO₂ and O₃ simulations have great uncertainties during the COVID-19 epidemic, but their biases and spatial distributions can be improved with NO₂ assimilations. This study adopted two top-down NO _X inversions and estimated their impacts on NO₂ and O₃ simulation for three periods: the normal operation period (P1), the epidemic lockdown period following the Spring Festival (P2), and back to work period (P3) in the North China Plain (NCP). Two TROPOspheric Monitoring Instrument (TROPOMI) NO₂ retrievals came from the Royal Netherlands Meteorological Institute (KNMI) and the University of Science and Technology of China (USTC), respectively. Compared to the prior NO _X emissions, the two TROPOMI posteriors greatly reduced the biases between simulations with in situ measurements (NO₂ MREs: prior 85%, KNMI -27%, USTC -15%; O₃ MREs: Prior -39%, KNMI 18%, USTC 11%). The NO _X budgets from the USTC posterior were 17-31% higher than those from the KNMI one. Consequently, surface NO₂ levels constrained by USTC-TROPOMI were 9-20% higher than those by the KNMI one, and O₃ is 6-12% lower. Moreover, USTC posterior simulations showed more significant changes in adjacent periods (surface NO₂: P2 vs P1, -46%, P3 vs P2, +25%; surface O₃: P2 vs P1, +75%, P3 vs P2, +18%) than the KNMI one. For the transport flux in Beijing (BJ), the O₃ flux differed by 5-6% between the two posteriori simulations, but the difference of NO₂ flux between P2 and P3 was significant, where the USTC posterior NO₂ flux was 1.5-2 times higher than the KNMI one. Overall, our results highlight the discrepancies in NO₂ and O₃ simulations constrained by two TROPOMI products and demonstrate that the USTC posterior has lower bias in the NCP during COVD-19.

Multi-scale three-dimensional variational data assimilation for high-resolution aerosol observations: Methodology and application

With an increasing number of air quality monitoring stations installed around the Chinese mainland, high-resolution aerosol observations become available, allowing improvements in air pollution monitoring and aerosol forecasting. However, the multi scales (especially small-scale) information included in high-resolution aerosol observations could not be effectively utilized by the traditional three-dimensional variational method (3DVAR). This study attempted to extend the traditional 3DVAR to a multi-scale 3DVAR with two iteration steps, two-scale-3DVAR (TS-3DVAR), to improve the effectiveness of assimilating high-resolution observations. In TS-3DVAR, the large-scale and small-scale components of observation information were decomposed from the original high-resolution observations using a Gaussian smoothing method and then assimilated using the corresponding large-scale or small-scale background error covariances which were derived from the partitioned background error samples. The data assimilation (DA) analysis field generated by TS-3DVAR is more accurate than 3DVAR in reproducing the field’s multi-scale characteristics, which could thus be used as the initial chemical field of the air quality model to improve aerosol forecasting. Particulate matter with an aerodynamic diameter of less than 2.5 μm (PM_2.5) and 10.0 μm (PM₁₀) from the surface air quality monitoring stations from November 01 to November 30, 2018 at 00:00 were assimilated daily to verify the effects of TS-3DVAR and 3DVAR on the aerosol analysis and forecast accuracy. The results showed that TS-3DVAR better constrained both large-scale and small-scale, especially the spatial wavelengths in a range of 54–216 km and those above 351 km. The average power spectra of the TS-3DVAR assimilation increment in the two wavelength ranges were 71.70% and 35.33% higher than those of 3DVAR. As a result, the TS-3DVAR was more effective than 3DVAR in improving the accuracy of the initial chemical field, and thereby the forecasting capability for PM_2.5. In the initial chemical field, the 30-day average correlation coefficient (Corr) of PM_2.5 of TS-3DVAR was 0.052 (6.12%) higher than that of 3DVAR, and the root mean square error (RMSE) of TS-3DVAR was 3.446 μg m⁻³ (16.4%) lower than that of 3DVAR. For the forecasting capability for PM_2.5 mass concentration, the 30-day average Corr of TS-3DVAR during the 0–24 hour forecast period was 0.025 (5.08%) higher than that of 3DVAR, and the average RMSE was 2.027 μg m⁻³ (4.85%) lower. The positive effect of TS-3DVAR on the improvement of forecasting capability can last for more than 24 h.

Numerical study of the amplification effects of cold-front passage on air pollution over the North China Plain

Cold-front systems provide scavenging mechanisms for air pollution in the North China Plain (NCP), but the transport of pollutants with cold fronts aggravates air quality downstream. The impact of cold fronts on PM_2.5 concentrations over the NCP during 8-14 December 2019 was studied using the WRF-Chem model. Results indicate that cold fronts directly influence PM_2.5 concentration through regional transport of pollutants and adjustment of meteorological systems, and they indirectly affect air quality by influencing aerosol-radiation interaction. Pollutants affecting downstream areas may be transported to altitudes of ~3 km along the frontal surface, with near-surface PM_2.5 concentrations increasing temporarily at up to 15 μg·m^-3·h^-1 behind the surface frontal line owing to the inversion layer triggered by the oblique frontal surface. The transport process plays an essential role in affecting air pollution levels, more than vertical mixing and chemical reaction processes. Changes in the meteorological system (eastward shift of the high-pressure center) occurring with the passage of cold fronts facilitate the accumulation and transport of pollutants in the NCP, reducing air quality in the western and northern NCP. Cold fronts may also indirectly exacerbate near-surface pollutant diffusion conditions by affecting solar radiation incidence, with a reduction of the 2-m temperature by as much as 1 °C, increasing near-surface (<1 and 0.5 km agl on the pre- and post-frontal sides, respectively) PM_2.5 concentrations by up to 40 μg·m^-3, while reducing upper-layer concentrations by up to 30 μg·m^-3. This study emphasizes the amplification effect of cold fronts on air pollution, with inter-regional cooperation being essential in improving air quality in the NCP region.

The striking effect of vertical mixing in the planetary boundary layer on new particle formation in the Yangtze River Delta

New particle formation (NPF) induces a sharp increase in ultrafine particle number concentrations and potentially acts as an important source of cloud condensation nuclei (CCN). As the densely populated area of China, the Yangtze River Delta (YRD) region shows a high frequency of observed NPF events at the ground level, especially in spring. Although recent observational studies suggested a possible connection between NPF at the higher altitudes and ground level, the role played by vertical mixing, particularly in the planetary boundary layer (PBL) is not fully understood. Here we integrate measurements in Nanjing on 15-20 April 2018, and the NPF-explicit Weather Research and Forecast coupled with chemistry (WRF-Chem) model simulations to better understand the governing mechanisms of the NPF and CCN. Our results indicate that newly formed particles at the boundary layer top could be transported downward by vertical mixing as the PBL develops. A numerical sensitivity simulation created by eliminating aerosol vertical mixing suppresses both the downward transport of particles formed at a higher altitude and the dilution of particles at the ground level. The resulting higher Fuchs surface area at the ground level, together with the lack of downward transport, yields a sharp weakening of NPF strength and delayed start of NPF therein. The aerosol vertical mixing, therefore, leads to a more than double increase of surface CN_10-40 and a one third decrease of boundary layer top CN_10-40. Additionally, the continuous growth of nucleated ultrafine particles at the boundary layer top is strongly steered by the upward transport of condensable gases, with close to half increase of particle number concentrations in Aitken mode and CCN at a supersaturation rate of 0.75%. The findings may bridge the gap in understanding the complex interaction between PBL dynamics and NPF events, reducing the uncertainty in assessing the climate impact of aerosols.

Long-term PM0.1 exposure and human blood lipid metabolism: New insight from the 33-community study in China

Ambient particles with aerodynamic diameter <0.1 μm (PM_0.1) have been suggested to have significant health impact. However, studies on the association between long-term PM_0.1 exposure and human blood lipid metabolism are still limited. This study was aimed to evaluate such association based on multiple lipid biomarkers and dyslipidemia indicators. We matched the 2006-2009 average PM_0.1 concentration simulated using the neural-network model following the WRF-Chem model with the clinical and questionnaire data of 15,477 adults randomly recruited from 33 communities in Northeast China in 2009. After controlling for social demographic and behavior confounders, we assessed the association of PM_0.1 concentration with multiple lipid biomarkers and dyslipidemia indicators using generalized linear mixed-effect models. Effect modification by various social demographic and behavior factors was examined. We found that each interquartile range increase in PM_0.1 concentration was associated with a 5.75 (95% Confidence interval, 3.24-8.25) mg/dl and a 6.05 (2.85-9.25) mg/dl increase in the serum level of total cholesterol and LDL-C, respectively. This increment was also associated with an odds ratio of 1.25 (1.10-1.42) for overall dyslipidemias, 1.41 (1.16, 1.73) for hypercholesterolemia, and 1.90 (1.39, 2.61) for hyperbetalipoproteinemia. Additionally, we found generally greater effect estimates among the younger participants and those with lower income or with certain behaviors such as high-fat diet. The deleterious effect of long-term PM_0.1 exposure on lipid metabolism may make it an important toxic chemical to be targeted by future preventive strategies.

Unexpected response of nitrogen deposition to nitrogen oxide controls and implications for land carbon sink

Terrestrial ecosystems in China receive the world’s largest amount of reactive nitrogen (N) deposition. Recent controls on nitrogen oxides (NO_x = NO + NO₂) emissions in China to tackle air pollution are expected to decrease N deposition, yet the observed N deposition fluxes remain almost stagnant. Here we show that the effectiveness of NO_x emission controls for reducing oxidized N (NO_y = NO_x + its oxidation products) deposition is unforeseen in Eastern China, with one-unit reduction in NO_x emission leading to only 55‒76% reductions in NO_y-N deposition, as opposed to the high effectiveness (around 100%) in both Southern China and the United States. Using an atmospheric chemical transport model, we demonstrate that this unexpected weakened response of N deposition is attributable to the enhanced atmospheric oxidizing capacity by NO_x emissions reductions. The decline in N deposition could bear a penalty on terrestrial carbon sinks and should be taken into account when developing pathways for China’s carbon neutrality.

Recent vigorous controls in anthropogenic nitrogen oxide emissions in China cannot result in proportionate decreases in regional atmospheric nitrogen deposition. Enhanced atmospheric oxidizing capacity offsets those reductions of precursor emissions.

Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China Using Machine Learning Emulation

Machine learning models can emulate chemical transport models, reducing computational costs and enabling more experimentation. We developed emulators to predict annual-mean fine particulate matter (PM_2.5) and ozone (O₃) concentrations and their associated chronic health impacts from changes in five major emission sectors (residential, industrial, land transport, agriculture, and power generation) in China. The emulators predicted 99.9% of the variance in PM_2.5 and O₃ concentrations. We used these emulators to estimate how emission reductions can attain air quality targets. In 2015, we estimate that PM_2.5 exposure was 47.4 μg m^-3 and O₃ exposure was 43.8 ppb, associated with 2,189,700 (95% uncertainty interval, 95UI: 1,948,000-2,427,300) premature deaths per year, primarily from PM_2.5 exposure (98%). PM_2.5 exposure and the associated disease burden were most sensitive to industry and residential emissions. We explore the sensitivity of exposure and health to different combinations of emission reductions. The National Air Quality Target (35 μg m^-3) for PM_2.5 concentrations can be attained nationally with emission reductions of 72% in industrial, 57% in residential, 36% in land transport, 35% in agricultural, and 33% in power generation emissions. We show that complete removal of emissions from these five sectors does not enable the attainment of the WHO Annual Guideline (5 μg m^-3) due to remaining air pollution from other sources. Our work provides the first assessment of how air pollution exposure and disease burden in China varies as emissions change across these five sectors and highlights the value of emulators in air quality research.

Emission Sector Impacts on Air Quality and Public Health in China From 2010 to 2020

Anthropogenic emissions and ambient fine particulate matter (PM_2.5) concentrations have declined in recent years across China. However, PM_2.5 exposure remains high, ozone (O₃) exposure is increasing, and the public health impacts are substantial. We used emulators to explore how emission changes (averaged per sector over all species) have contributed to changes in air quality and public health in China over 2010-2020. We show that PM_2.5 exposure peaked in 2012 at 52.8 μg m^-3, with contributions of 31% from industry and 22% from residential emissions. In 2020, PM_2.5 exposure declined by 36% to 33.5 μg m^-3, where the contributions from industry and residential sources reduced to 15% and 17%, respectively. The PM_2.5 disease burden decreased by only 9% over 2012 where the contributions from industry and residential sources reduced to 15% and 17%, respectively 2020, partly due to an aging population with greater susceptibility to air pollution. Most of the reduction in PM_2.5 exposure and associated public health benefits occurred due to reductions in industrial (58%) and residential (29%) emissions. Reducing national PM_2.5 exposure below the World Health Organization Interim Target 2 (25 μg m^-3) would require a further 80% reduction in residential and industrial emissions, highlighting the challenges that remain to improve air quality in China.

Process-Level Modeling Can Simultaneously Explain Secondary Organic Aerosol Evolution in Chambers and Flow Reactors

Secondary organic aerosol (SOA) data gathered in environmental chambers (ECs) have been used extensively to develop parameters to represent SOA formation and evolution. The EC-based parameters are usually constrained to less than one day of photochemical aging but extrapolated to predict SOA aging over much longer timescales in atmospheric models. Recently, SOA has been increasingly studied in oxidation flow reactors (OFRs) over aging timescales of one to multiple days. However, these OFR data have been rarely used to validate or update the EC-based parameters. The simultaneous use of EC and OFR data is challenging because the processes relevant to SOA formation and evolution proceed over very different timescales, and both reactor types exhibit distinct experimental artifacts. In this work, we show that a kinetic SOA chemistry and microphysics model that accounts for various processes, including wall losses, aerosol phase state, heterogeneous oxidation, oligomerization, and new particle formation, can simultaneously explain SOA evolution in EC and OFR experiments, using a single consistent set of SOA parameters. With α-pinene as an example, we first developed parameters by fitting the model output to the measured SOA mass concentration and oxygen-to-carbon (O:C) ratio from an EC experiment (<1 day of aging). We then used these parameters to simulate SOA formation in OFR experiments and found that the model overestimated SOA formation (by a factor of 3-16) over photochemical ages ranging from 0.4 to 13 days, when excluding the abovementioned processes. By comprehensively accounting for these processes, the model was able to explain the observed evolution in SOA mass, composition (i.e., O:C), and size distribution in the OFR experiments. This work suggests that EC and OFR SOA data can be modeled consistently, and a synergistic use of EC and OFR data can aid in developing more refined SOA parameters for use in atmospheric models.

Is Urban Greening an Effective Solution to Enhance Environmental Comfort and Improve Air Quality?

Urban greening has often been proposed as a cost-effective solution to improve environmental comfort, but may also deteriorate air quality. Quantifying these two opposing effects of urban greening is necessary to develop successful environmental policies for specific mega-city clusters. In this study, a high-resolution regional climate and air quality model (WRF-Chem, v4.0.3) was employed to test three scenarios aimed at quantifying the impact of land-use change and biogenic emissions from urban greening on regional climate and air quality. It was found that urban greening could effectively decrease the near-surface temperature by up to 0.45 °C, but the increased biogenic volatile organic compound (BVOC) emissions offset some of this cooling effect (by up to 65%). Land-use change due to urban greening dominated the improvement in human comfort but worsened diffusion conditions to result in the convergence of fine particulate matter in specific areas. The selection of low-emission tree species may be imperative, although increased emissions from urban greening will not change the sensitivity of ozone to precursors under the current scenario of anthropogenic emissions. This is because BVOC emissions due to urban greening will become a more important source of pollution with the development of clean energy and the popularity of low-carbon lifestyles.

The Dynamical Role of the Chesapeake Bay on the Local Ozone Pollution Using Mesoscale Modeling—A Case Study

This study investigated the dynamic influence of the Chesapeake Bay (CB) on local ozone (O3) concentration and distribution using a weather forecasting model. The Weather Research and Forecasting model coupled with Chemistry (WRF–Chem) was employed to simulate O3 production and transportation near the CB. Baseline (water) as well as sensitivity (nowater) model experiments of bay circulation were carried out with and without bay water by changing the water surface from water to land (loam). First, the model performance simulating O3 was evaluated using the baseline experiment results and AirNow surface wind and O3 observations. The results showed that the model overestimates surface O3 by up to 20–30%. Further, the comparisons of the baseline and sensitivity experiments revealed higher O3 mixing ratios, primarily due to the resulting bay breeze circulation. These increases, after considering model overestimation, represent a mean bay dynamics circulation-induced contribution of up to 10% at night and 5% during the day. Furthermore, the boundary layer over northern CB, where it is at its narrowest width, was higher (by 1.2 km on average) during daytime due to higher surface temperatures observed. The boundary layer depth difference between the northern, central, and southern regions of the bay leads to a differential in the role of bay circulation dynamics in the observed O3 increase. The relatively wider swath of water surface over southern CB resulted in a lower boundary layer depth and stronger breeze circulation and this circulation contributed to O3 concentrations. Moreover, since the case selected has a minimal bay breeze circulation, the associated surface ozone enhancements represent what is expected at least at a minimum.

The Independent Impacts of PM2.5 Dropping on the Physical and Chemical Properties of Atmosphere over North China Plain in Summer during 2015–2019

Great changes occurred in the physical and chemical properties of the atmosphere in the North China Plain (NCP) in summer caused by PM2.5 dropping from 58 μg/m3 in 2015 to 36.0 μg/m3 in 2019. In this study, we first applied the WRF-Chem model to quantify the impact of PM2.5 reduction on shortwave radiation reaching the ground (SWDOWN), planetary boundary layer height (PBLH), and the surface concentration of air pollutants (represented by CO). Simulation results obtained an increase of 15.0% in daytime SWDOWN and 9.9% in daytime PBLH, and a decrease of −5.0% in daytime CO concentration. These changes were induced by the varied PM2.5 levels. Moreover, the variation in SWDOWN further led to a rise in the NO2 photolysis rate (JNO2) over this region, by 1.82 × 10−4~1.91 × 10−4 s−1 per year. Afterwards, we employed MCM chemical box model to explore how the JNO2 increase and the precursor decrease (CO, VOCs, and NOx) influenced O3 and HOx radicals. The results revealed that the photolysis rate (J) increase would individually cause a change on daytime surface O3, OH, and HO2 radicals by +9.0%, +18.9%, and +23.7%; the corresponding change induced by the precursor decrease was −2.5%, +1.9%, and −2.3%. At the same time, the integrated impacts of the change in J and precursors cause an increase of +6.3%, +21.1%, and +20.9% for daytime surface O3, OH, and HO2. Generally, the atmospheric oxidation capacity significantly enhanced during summer in NCP due to the PM2.5 dropping in recent years. This research can help understand atmosphere changes caused by PM2.5 reduction comprehensively.

Projection of the Near-Future PM2.5 in Northern Peninsular Southeast Asia under RCP8.5

Throughout the year, particularly during the dry season, the northern peninsula of Southeast Asia struggles with air pollution from PM2.5. In this study, we used the Nested Regional Climate and Chemistry Model (NRCM-Chem) to predict the PM2.5 concentrations over Southeast Asia’s northern peninsula during the years 2020–2029 under the Representative Concentration Pathway (RCP)8.5. In general, the model reasonably shows a good result, including temperature, precipitation, and PM2.5 concentration, compared to the observation with an Index of Agreement (IOA) in the range of 0.63 to 0.80. However, there were some underestimations for modeled precipitation and temperature and an overestimation for modeled PM2.5 concentration. As a response to changes in climatic parameters and the emission of PM2.5’s precursors, PM2.5 concentrations tend to increase across the region in the range of (+1) to (+35) µg/m3 during the dry season (November to April) and decline in the range of (−3) to (−30) µg/m3 during the wet season (May to October). The maximum increase in PM2.5 concentrations were found in March by >40 µg/m3.

Role of anthropogenic aerosols in affecting different-grade precipitation over eastern China: A case study

Atmospheric aerosols play an important role in affecting clouds and precipitation by serving as condensation/ice nuclei. However, how to quantify the contribution of anthropogenic aerosols to the alteration of clouds and precipitation remains unknown. In this study, using a Weather Research and Forecasting-Chemistry (WRF-Chem) model, we quantified the impacts of anthropogenic aerosols on cloud water properties under different precipitation grades during a single rainfall event over eastern China. The results of this study show that anthropogenic aerosols have varying effects on hourly precipitation with heavy (greater than 1.04 mm/h), moderate (0.41-1.04 mm/h), and light (less than 0.41 mm/h) grades. Due to the presence of anthropogenic aerosols, heavy precipitation is intensified by 70.96%; however, moderate and light precipitation is further weakened by 24.87% and 86.43%, respectively. For heavy precipitation, the addition of anthropogenic aerosols induces an enhancement in upward motion, increases the cloud water path and effective radius through the aerosol-radiation interaction (ARI) effect, which is the main reason for the intensification of heavy-grade precipitation. In addition, the weakened upward motion and decreased ice water path caused by ARI and aerosol-cloud interaction (ACI) effects play common roles in reducing moderate and light precipitation. Studying anthropogenic aerosols' impacts on precipitation is of great importance for understanding the influence of anthropogenic pollution on the weather and climate and even for promoting precipitation forecasting and prediction.

Responses of surface O3 and PM2.5 trends to changes of anthropogenic emissions in summer over Beijing during 2014-2019: A study based on multiple linear regression and WRF-Chem

Owing to the implementation of air pollution control actions, anthropogenic emissions in Beijing have changed in recent years. Understanding the impact of changes in anthropogenic emissions on O₃ and PM_2.5 trends is helpful for developing air quality management strategies. Herein, we investigated the variations of air pollutants in summer over Beijing using long-term data sets from 2014 to 2019, and explored the responses of O₃ and PM_2.5 trends to changes in anthropogenic emissions based on multiple linear regression (MLR) analysis and WRF-Chem model. The results indicated a significant decrease in PM_2.5, but a near constant level of O₃ during 2014-2019. The decrease rate of PM_2.5, which was lower than that of SO₂, might be due to the effect of NO₂ on atmospheric PM_2.5. Both the slightly increasing correlations between PM_2.5 and NO₂ and the WRF-Chem model simulations implied that atmospheric PM_2.5 in Beijing is trending to be more sensitive to NO_x than SO₂. The emissions of NO_x and VOCs from industry and transportation were found to make great contribution to O₃ production in Beijing. Due to the titration of NO_x in VOC-limited regime, the relatively low emission ratios of NO_x and VOCs from industry and transportation in Beijing provided convincing evidence for the persistently high O₃ concentrations during 2014-2019. However, the noticeable increase of the O₃ trends in other areas (e.g., Hebei, Tianjin) could be explained by the significant decline in the emission ratios of NO_x and VOCs from anthropogenic emissions especially industry during 2014-2019. Controlling the emission of NO_x can substantially reduce PM_2.5 pollution, but may aggravate O₃ pollution, and thus effective VOC emission control strategies need to be considered for simultaneously controlling O₃ and PM_2.5 pollution in Beijing and other regions of China.

Impact of Wildfires on Meteorology and Air Quality (PM2.5 and O3) over Western United States during September 2017

In this study, we investigated the impact of wildfires on meteorology and air quality (PM2.5 and O3) over the western United States during the September 2017 period. This is done by using Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate scenarios with wildfires (base case) and without wildfires (sensitivity case). Our analysis performed during the first half of September 2017 (when wildfire activity was more intense) reveals a reduction in modelled daytime average shortwave surface downward radiation especially in locations close to wildfires by up to 50 W m−2, thus resulting in the reduction of the diurnal average surface temperature by up to 0.5 °C and the planetary boundary layer height by up to 50 m. These changes are mainly attributed to aerosol-meteorology feedbacks that affect radiation and clouds. The model results also show mostly enhancements for diurnally averaged cloud optical depth (COD) by up to 10 units in the northern domain due to the wildfire-related air quality. These changes occur mostly in response to aerosol–cloud interactions. Analysis of the impact of wildfires on chemical species shows large changes in daily mean PM2.5 concentrations (exceeding by 200 μg m−3 in locations close to wildfires). The 24 h average surface ozone mixing ratios also increase in response to wildfires by up to 15 ppbv. The results show that the changes in PM2.5 and ozone occur not just due to wildfire emissions directly but also in response to changes in meteorology, indicating the importance of including aerosol-meteorology feedbacks, especially during poor air quality events.