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Pile–slab retaining walls, as innovative rockfall protection structures, have been extensively utilized in the western mountainous regions of China. With their characteristics of a small footprint, high interception height, and ease of construction, these structures demonstrate promising potential for application in mountainous regions worldwide, such as the Himalayas, Andes, and Alps. However, their dynamic response upon impact and impact resistance energy remain ambiguous due to the intricate composite nature of the structures. To elucidate this, an exhaustive dynamic analysis of a four-span pile–slab retaining wall with a cantilever section of 6 m under various impact scenarios was conducted utilizing the finite-element numerical simulation method. The rationality of the selected material constitutive models and the numerical algorithm was validated by reproducing two physical model tests. The simulation results reveal the following. (1) The lateral displacement of the pile at the ground surface and the concrete damage under the pile at the impact center are greater than those under the slab at the impact center, implying that the impact location has a significant influence on the stability of the structure. (2) There is a positive correlation between the response indexes (impact force, interaction force, lateral deformation of pile and slab, concrete damage) and the impact velocities. (3) The rockfall peak impact force, the ratio of the peak impact force to the peak interaction force, and lateral displacement of the pile at the ground surface had strong linear relationships with rockfall energy. (4) Relative to the bending moment, shear force, and damage degree, the lateral displacement of the pile at the ground surface is the first to reach its limit value. Taking the lateral displacement of the pile at the ground surface as the controlling factor, the estimated maximum impact energy that the pile–slab retaining wall can withstand is 905 kJ in this study when the structure top is taken as the impact point. In cases where the impact energy of falling rocks exceeds 905 kJ, it is recommended to optimize the mechanical properties of the cushion layer, improve the elastic modulus of concrete, increase the reinforcement ratio of longitudinal tension bars, enlarge the section size of piles at ground level, or add anchoring measures to enhance the bending resistance of the retaining structure.

The Chlorophyll-a (Chla) concentration is an important parameter characterizing the water quality of rivers and lakes. Satellite remote sensing provides new opportunities for the quantitative monitoring of Chla concentration in large-scale water bodies. In this study, Sentinel-2 satellite remote sensing data integrated on the Google Earth Engine (GEE) remote sensing big data platform are employed, along with hourly measured water quality site data, to establish a quantitative inversion model for Chla concentration water quality parameters in Jiujiang City within Jiangxi Province, China. The Chla concentration is estimated for each quarter from 2020 to 2022, and the spatial distribution is analyzed, revealing the changing trend of Chla concentration over the past three years. The key findings are as follows: (1) The quantitative inversion model for Chla concentration has been validated with measured data, achieving a model accuracy of 0.53; (2) The spatial inversion results of Chla concentration exhibit an increasing trend that is consistent with actual measurement site results; (3) Owing to the influence of human activities and the peak-low water level of rivers and lakes, Chla concentration shows a discernible seasonal variation pattern. This methodology offers a new perspective for analyzing the seasonal variation characteristics of Chla concentration in rivers and lakes, providing valuable insights for the sustainable management of river and lake water quality.

Urban lakes serve an indispensable role in maintaining the ecological balance of cities, ensuring flood safety, and providing recreational spaces for tourism. With the development of human activities and economic, the extent of urban lakes are inevitably influenced. Currently, the ability to detect detailed temporal changes in urban lake areas using high resolution data still has limitations. This study proposed a novel method by combining time series Gaofen-1 (GF-1) remote sensing data and random forest machine learning algorithm to explore the urban lakes change Zhushan Lake located in Wuhan. The research conducted the extraction of surface water for Zhushan Lake and its surrounding pit-ponds from 2013 to 2020. And then, a quantitative analysis of the characteristics and driving factors of lake changes is conducted. We find that (1) the accuracy of surface water extraction using the random forest classification method consistently exceeded 96%. The Kappa coefficient ranges from a minimum of 0.86 to a maximum of 0.99. (2) A noticeable decline was observed in the water areas of Zhushan Lake and its surrounding pit-ponds, predominantly along the northwestern shoreline and in the eastern pond regions. This decline is primarily attributed to pressures from building construction. The methodology proposed in this study is suitable for the area management of lakes in urban areas.

In the context of global warming, an increase in atmospheric aridity and global dryland expansion under the future climate has been expected in previous studies. However, this conflicts with observed greening over drylands and the insignificant increase in hydrological and ecological aridity from the ecohydrology perspective. Combining climatic, hydrological, and vegetation data, this study evaluated global dryland aridity changes at meteorological stations from 2003 to 2019. A decoupling between atmospheric, hydrological, and vegetation aridity was found. Atmospheric aridity represented by the vapor pressure deficit (VPD) increased, hydrological aridity indicated by machine-learning-based precipitation minus evapotranspiration (P − ET) data did not change significantly, and ecological aridity represented by the leaf area index (LAI) decreased. P − ET showed nonsignificant changes in most of the dominant combinations of the VPD, LAI, and P − ET. This study highlights the added value of using station-scale data to assess dryland change as a complement to results based on coarse-resolution reanalysis data and land surface models.

Using statistical methods that do not directly represent the causality between variables to attribute climate and plant traits as controlling ecosystem functions may lead to biased perceptions. We revisited this issue using a causal graphical model, the Bayesian network (BN), capable of quantifying causality by conditional probability tables. Based on expert knowledge and climate, vegetation, and ecosystem function data from the FLUXNET flux stations, we constructed a BN representing the causal relationship of climate–plant-trait–ecosystem functions. Based on the sensitivity analysis function of the BN, we attributed the control of climate and plant traits over ecosystem functions and compared the results with those based on random forests and correlation analysis. The main conclusions of this study include the following: BN can be used for the quantification of causal relationships between complex ecosystems in response to climate change and enables the analysis of indirect effects among variables. The causality reflected in the BN is as good as the expert knowledge of the causal links. Compared to BN, the feature importance difference between “mean vapor pressure deficit and cumulative soil water index” and “maximum leaf area index and maximum vegetation height” reported by random forests is higher and can be overestimated. With the causality relation between correlated variables constructed, a BN-based sensitivity analysis can reduce the uncertainty in quantifying the importance of correlated variables. The understanding of the mechanism of indirect effects of climate variables on ecosystem functions through plant traits can be deepened by the chain casuality quantification in BNs.

Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by the difference between PM10 and PM2.5. Coarse PM concentrations in 2015 averaged 52 µg m−3 in the North China Plain (NCP) and 23 µg m−3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM10. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21 % from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the Korea–United States Air Quality (KORUS-AQ) campaign over the SMA in May–June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations for 2015–2019 show that decreasing anthropogenic coarse PM directly increases PM2.5 nitrate in summer, offsetting 80 % the effect of nitrogen oxide and ammonia emission controls, while in winter the presence of coarse PM increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the lack of decrease in wintertime PM2.5 nitrate observed in the NCP and the SMA over the 2015–2021 period despite decreases in nitrogen oxide and ammonia emissions. Continuing decrease of fugitive dust pollution means that more stringent nitrogen oxide and ammonia emission controls will be required to successfully decrease PM2.5 nitrate.

Fine particulate matter (PM2.5) pollution is a severe problem in China. Research on the sources of Chinese PM2.5 pollution has focused on the contributions of China's domestic emissions. However, the impact of foreign anthropogenic emissions has typically been simplified or neglected, partly due to the perception that the short lifetime of PM2.5 (a few days) does not allow long-distance transport. Here we explore the role of foreign anthropogenic emissions in Chinese PM2.5 pollution in 2015 using the GEOS-Chem chemical transport model. We validate the model simulations with a comprehensive set of observations of PM2.5 and its composition, including sulfate, nitrate, ammonium, black carbon, and primary organic aerosols, over China and its surrounding regions. We find that 8 % of PM2.5 (5 µg m−3) and 19 % of nitrate (2.6 µg m−3) over eastern China in 2015 was contributed by foreign anthropogenic emissions. The contributions were the highest in January (6.9 µg m−3 PM2.5, with 68 % nitrate) and the lowest in July (2.7 µg m−3 PM2.5, with 11 % nitrate). Yet, only 30 % of such foreign contributions in January were through direct atmospheric transport. The majority (70 %) were instead through chemical interactions between foreign-transported aerosol precursors and China's domestic emissions of pollutants. Specifically, the transport of non-methane volatile organic compounds (NMVOCs) from foreign countries enhanced the atmospheric oxidizing capacity and facilitated the oxidation of Chinese nitrogen oxides (NOx) to form nitric acid (HNO3) over eastern China. The abundance of Chinese ammonia (NH3) further partitioned nearly all HNO3 gas to particulate nitrate, leading to considerable foreign contributions of nitrate and PM2.5 to eastern China. Over southwestern China, foreign anthropogenic emissions contributed 4.9 µg m−3 PM2.5 concentrations (18 % of total PM2.5 mass) to Yunnan Province, with 37 % as organics and 27 % as sulfate. Our findings suggest that foreign anthropogenic emissions play an important role in Chinese PM2.5 pollution because of direct aerosol transport and, more importantly, chemical interactions between transported pollutants and China's local emissions. Thus, foreign emission reductions will be very beneficial for improving Chinese air quality.

While formation and growth of particles in the troposphere have been extensively studied in the past two decades, very limited efforts have been devoted to understanding these in the stratosphere. Here we use both Cosmics Leaving OUtdoor Droplets (CLOUD) laboratory measurements taken under very low temperatures (205–223 K) and Atmospheric Tomography Mission (ATom) in situ observations of particle number size distributions (PNSDs) down to 3 nm to constrain nucleation mechanisms and to evaluate model-simulated particle size distributions in the lowermost stratosphere (LMS). We show that the binary homogenous nucleation (BHN) scheme used in most of the existing stratospheric aerosol injection (a proposed method of solar radiation modification) modeling studies overpredicts the nucleation rates by 3–4 orders of magnitude (when compared to CLOUD data) and particle number concentrations in the background LMS by a factor ∼ 2–4 (when compared to ATom data). Based on a recently developed kinetic nucleation model, which gives rates of both ion-mediated nucleation (IMN) and BHN at low temperatures in good agreement with CLOUD measurements, both BHN and IMN occur in the stratosphere. However, IMN rates are generally more than 1 order of magnitude higher than BHN rates and thus dominate nucleation in the background stratosphere. In the Southern Hemisphere (SH) LMS with minimum influence of anthropogenic emissions, our analysis shows that ATom-measured PNSDs generally have four apparent modes. The model captures reasonably well the two modes (Aitken mode and the first accumulation mode) with the highest number concentrations and size-dependent standard deviations. However, the model misses an apparent second accumulation mode peaking around 300–400 nm, which is in the size range important for aerosol direct radiative forcing. The bimodal structure of accumulation mode particles has also been observed in the stratosphere well above tropopause and in the volcano-perturbed stratosphere. We suggest that this bimodal structure may be caused by the effect of charges on coagulation and growth, which is not yet considered in any existing models and may be important in the stratosphere due to high ionization rates and the long lifetime of aerosols. Considering the importance of accurate PNSDs for projecting a realistic radiation forcing response to stratospheric aerosol injection (SAI), it is essential to understand and incorporate such potentially important processes in SAI model simulations and to carry out further research to find out what other processes the present models might have missed.

With the rapid accumulation of water flux observations from global eddy-covariance flux sites, many studies have used data-driven approaches to model water fluxes, with various predictors and machine learning algorithms used. However, it is unclear how various model features affect prediction accuracy. To fill this gap, we evaluated this issue based on records of 139 developed models collected from 32 such studies. Support vector machines (SVMs; average R-squared = 0.82) and RF (random forest; average R-squared = 0.81) outperformed other evaluated algorithms with sufficient sample size in both cross-study and intra-study (with the same data) comparisons. The average accuracy of the model applied to arid regions is higher than in other climate types. The average accuracy of the model was slightly lower for forest sites (average R-squared = 0.76) than for croplands and grasslands (average R-squared = 0.8 and 0.79) but higher than for shrubland sites (average R-squared = 0.67). Using Rn/Rs, precipitation, Ta, and the fraction of absorbed photosynthetically active radiation (FAPAR) improved the model accuracy. The combined use of Ta and Rn/Rs is very effective, especially in forests, while in grasslands the combination of Ws and Rn/Rs is also effective. Random cross-validation showed higher model accuracy than spatial cross-validation and temporal cross-validation, but spatial cross-validation is more important in spatial extrapolation. The findings of this study are promising to guide future research on such machine-learning-based modeling.

The mission of WEST (tungsten-W Environment in Steady-state Tokamak) is to explore long pulse operation in a full tungsten (W) environment for preparing next-step fusion devices (ITER and DEMO) with a focus on testing the ITER actively cooled W divertor in tokamak conditions. Following the successful completion of phase 1 (2016-2021), phase 2 started in December 2022 with the lower divertor made entirely of actively cooled ITER-grade tungsten mono-blocks. A boronization prior the first plasma attempt allowed for a smooth startup with the new divertor. Despite the reduced operating window due to tungsten, rapid progress has been made in long pulse operation, resulting in discharges with a pulse length of 100 s and an injected energy of around 300 MJ per discharge. Plasma startup studies were carried out with equatorial boron nitride limiters to compare them with tungsten limiters, while Ion Cyclotron Resonance Heating assisted startup was attempted. High fluence operation in attached regime, which was the main thrust of the first campaigns, already showed the progressive build up of deposits and appearance of dust, impacting the plasma operation as the plasma fluence increased. In total, the cumulated injected energy during the first campaigns reached 43 GJ and the cumulated plasma time exceeded 5 h. Demonstration of controlled X-Point Radiator regime is also reported, opening a promising route for investigating plasma exhaust and plasma-wall interaction issues in more detached regime. This paper summarises the lessons learned from the manufacturing and the first operation of the ITER-grade divertor, describing the progress achieved in optimising operation in a full W environment with a focus on long pulse operation and plasma wall interaction.

Net ecosystem exchange (NEE) is an important indicator of carbon cycling in terrestrial ecosystems. Many previous studies have combined flux observations and meteorological, biophysical, and ancillary predictors using machine learning to simulate the site-scale NEE. However, systematic evaluation of the performance of such models is limited. Therefore, we performed a meta-analysis of these NEE simulations. A total of 40 such studies and 178 model records were included. The impacts of various features throughout the modeling process on the accuracy of the model were evaluated. Random forests and support vector machines performed better than other algorithms. Models with larger timescales have lower average R2 values, especially when the timescale exceeds the monthly scale. Half-hourly models (average R2 = 0.73) were significantly more accurate than daily models (average R2 = 0.5). There are significant differences in the predictors used and their impacts on model accuracy for different plant functional types (PFTs). Studies at continental and global scales (average R2 = 0.37) with multiple PFTs, more sites, and a large span of years correspond to lower R2 values than studies at local (average R2 = 0.69) and regional (average R2 = 0.7) scales. Also, the site-scale NEE predictions need more focus on the internal heterogeneity of the NEE dataset and the matching of the training set and validation set.

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea–United States Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by −64 % but overestimates nitrate by +36 %. The largest underestimate in sulfate occurs during the pollution event, for which models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of 5 increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape, resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model's inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model, which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation, implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally produced sulfate increased from 1 % to 25 % of locally produced PM2.5, implying that local emissions controls could have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction, which affects the aerosol liquid water abundance and chemistry driving sulfate–nitrate–ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and this results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate + nitrate + ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

As one of the most abundant atmospheric aerosols and effective ice nuclei, mineral dust affects clouds and precipitation in the Earth system. Here numerical experiments are carried out to investigate the impacts of dust aerosols on summertime convective clouds and precipitation over the mountainous region of Taiwan by acting as ice-nucleating particles. We run the Weather Research and Forecasting model (WRF) with the Morrison two-moment and spectral-bin microphysics (SBM) schemes at 3 km resolution, using dust number concentrations from a global chemical transport model (GEOS-Chem-APM). The case study indicates that the long-range-transported mineral dust, with relatively low number concentrations, can notably affect the properties of convective clouds (ice and liquid water contents, cloud top height, and cloud coverage) and precipitation (spatial pattern and intensity). The effects of dust are evident during strong convective periods, with significantly increased ice water contents in the mixed-phase regime via the enhanced heterogeneous freezing. With both the Morrison and SBM schemes, we see the invigoration effects of dust aerosols on the convective intensity through enhanced condensation and deposition latent heating. The low-altitude dust particles are uplifted to the freezing level by updrafts, which, in turn, enhance the convective cloud development through immersion freezing and convective invigoration. Compared to the Morrison scheme, the SBM scheme predicts more realistic precipitation and different invigoration effects of dust. The differences are partially attributed to the saturation adjustment approach utilized in the bulk scheme, which leads to a stronger enhancement of condensation at midlatitudes to low altitudes and a weaker deposition increase at the upper level.

Geostationary satellite measurements of aerosol optical depth (AOD) over East Asia from the Geostationary Ocean Color Imager (GOCI) and Advanced Himawari Imager (AHI) instruments can augment surface monitoring of fine particulate matter (PM2.5) air quality, but this requires better understanding of the AOD–PM2.5 relationship. Here we use the GEOS-Chem chemical transport model to analyze the critical variables determining the AOD–PM2.5 relationship over East Asia by simulation of observations from satellite, aircraft, and ground-based datasets. This includes the detailed vertical aerosol profiling over South Korea from the KORUS-AQ aircraft campaign (May–June 2016) with concurrent ground-based PM2.5 composition, PM10, and AERONET AOD measurements. The KORUS-AQ data show that 550 nm AOD is mainly contributed by sulfate–nitrate–ammonium (SNA) and organic aerosols in the planetary boundary layer (PBL), despite large dust concentrations in the free troposphere, reflecting the optically effective size and high hygroscopicity of the PBL aerosols. We updated SNA and organic aerosol size distributions in GEOS-Chem to represent aerosol optical properties over East Asia by using in situ measurements of particle size distributions from KORUS-AQ. We find that SNA and organic aerosols over East Asia have larger size (number median radius of 0.11 µm with geometric standard deviation of 1.4) and 20 % larger mass extinction efficiency as compared to aerosols over North America (default setting in GEOS-Chem). Although GEOS-Chem is successful in reproducing the KORUS-AQ vertical profiles of aerosol mass, its ability to link AOD to PM2.5 is limited by under-accounting of coarse PM and by a large overestimate of nighttime PM2.5 nitrate. The GOCI–AHI AOD data over East Asia in different seasons show agreement with AERONET AODs and a spatial distribution consistent with surface PM2.5 network data. The AOD observations over North China show a summer maximum and winter minimum, opposite in phase to surface PM2.5. This is due to low PBL depths compounded by high residential coal emissions in winter and high relative humidity (RH) in summer. Seasonality of AOD and PM2.5 over South Korea is much weaker, reflecting weaker variation in PBL depth and lack of residential coal emissions.

The previous comparative studies on watersheds were mostly based on the comparison of dispersive characteristics, which lacked systemicity and causality. We proposed a causal structure-based framework for basin comparison based on the Bayesian network (BN) and focus on the basin-scale water–energy–food–ecology (WEFE) nexus. We applied it to the Syr Darya River basin (SDB) and the Amu Darya River basin (ADB), of which poor water management caused the Aral Sea disaster. The causality of the nexus was effectively compared and universality of this framework was discussed. In terms of changes in the nexus, the sensitive factor for the water supplied to the Aral Sea changed from the agricultural development during the Soviet Union period to the disputes in the WEFE nexus after the disintegration. The water–energy contradiction of the SDB is more severe than that of the ADB, partly due to the higher upstream reservoir interception capacity. It further made management of the winter surplus water downstream of the SDB more controversial. Due to this, the water–food–ecology conflict between downstream countries may escalate and turn into a long-term chronic problem. Reducing water inflow to depressions and improving the planting structure prove beneficial to the Aral Sea ecology, and this effect of the SDB is more significant. The construction of reservoirs on the Panj River of the upstream ADB should be cautious to avoid an intense water–energy conflict such as the SDB's. It is also necessary to promote the water-saving drip irrigation and to strengthen the cooperation.

The global oxidation capacity, defined as the tropospheric mean concentration of the hydroxyl radical (OH), controls the lifetime of reactive trace gases in the atmosphere such as methane and carbon monoxide (CO). Models tend to underestimate the methane lifetime and CO concentrations throughout the troposphere, which is consistent with excessive OH. Approximately half of the oxidation of methane and non-methane volatile organic compounds (VOCs) is thought to occur over the oceans where oxidant chemistry has received little validation due to a lack of observational constraints. We use observations from the first two deployments of the NASA ATom aircraft campaign during July–August 2016 and January–February 2017 to evaluate the oxidation capacity over the remote oceans and its representation by the GEOS-Chem chemical transport model. The model successfully simulates the magnitude and vertical profile of remote OH within the measurement uncertainties. Comparisons against the drivers of OH production (water vapor, ozone, and NOy concentrations, ozone photolysis frequencies) also show minimal bias, with the exception of wintertime NOy. The severe model overestimate of NOy during this period may indicate insufficient wet scavenging and/or missing loss on sea-salt aerosols. Large uncertainties in these processes require further study to improve simulated NOy partitioning and removal in the troposphere, but preliminary tests suggest that their overall impact could marginally reduce the model bias in tropospheric OH. During the ATom-1 deployment, OH reactivity (OHR) below 3 km is significantly enhanced, and this is not captured by the sum of its measured components (cOHRobs) or by the model (cOHRmod). This enhancement could suggest missing reactive VOCs but cannot be explained by a comprehensive simulation of both biotic and abiotic ocean sources of VOCs. Additional sources of VOC reactivity in this region are difficult to reconcile with the full suite of ATom measurement constraints. The model generally reproduces the magnitude and seasonality of cOHRobs but underestimates the contribution of oxygenated VOCs, mainly acetaldehyde, which is severely underestimated throughout the troposphere despite its calculated lifetime of less than a day. Missing model acetaldehyde in previous studies was attributed to measurement uncertainties that have been largely resolved. Observations of peroxyacetic acid (PAA) provide new support for remote levels of acetaldehyde. The underestimate in both model acetaldehyde and PAA is present throughout the year in both hemispheres and peaks during Northern Hemisphere summer. The addition of ocean sources of VOCs in the model increases cOHRmod by 3 % to 9 % and improves model–measurement agreement for acetaldehyde, particularly in winter, but cannot resolve the model summertime bias. Doing so would require 100 Tg yr−1 of a long-lived unknown precursor throughout the year with significant additional emissions in the Northern Hemisphere summer. Improving the model bias for remote acetaldehyde and PAA is unlikely to fully resolve previously reported model global biases in OH and methane lifetime, suggesting that future work should examine the sources and sinks of OH over land.

Formation of new particles in the atmosphere has important implications for air quality and climate. Recently, we have developed a kinetically based H2SO4–H2O–NH3-ion nucleation model which well captures the absolute values of nucleation rates as well as dependencies of nucleation rates on NH3 and H2SO4 concentrations, ionization rates, temperature, and relative humidity observed in the well-controlled Cosmics Leaving Outdoor Droplets (CLOUD) measurements. Here we employ the aforementioned recently developed kinetic nucleation model to generate nucleation rate lookup tables for H2SO4–H2O binary homogenous nucleation (BHN), H2SO4–H2O–NH3 ternary homogeneous nucleation (THN), H2SO4–H2O-ion binary ion-mediated nucleation (BIMN), and H2SO4–H2O–NH3-ion ternary ion-mediated nucleation (TIMN). A comparison of nucleation rates calculated using the lookup tables with CLOUD measurements of BHN, BIMN, THN, and TIMN is presented. The lookup tables cover a wide range of key parameters controlling binary, ternary, and ion-mediated nucleation in the Earth's atmosphere and are a cost-efficient solution for multidimensional modeling. The lookup tables and FORTRAN codes, made available through this work, can be readily used in 3-D modeling. The lookup tables can also be used by experimentalists involved in laboratory and field measurements for a quick assessment of nucleation involving H2SO4, H2O, NH3, and ions.

Wet processes, including aqueous-phase chemistry, wet scavenging, and wet surface uptake during dry deposition, are important for global modeling of aerosols and aerosol precursors. In this study, we improve the treatments of these wet processes in the Goddard Earth Observing System with chemistry (GEOS-Chem) v12.6.0, including pH calculations for cloud, rain, and wet surfaces, the fraction of cloud available for aqueous-phase chemistry, rainout efficiencies for various types of clouds, empirical washout by rain and snow, and wet surface uptake during dry deposition. We compare simulated surface mass concentrations of aerosols and aerosol precursors with surface monitoring networks over the United States, European, Asian, and Arctic regions, and show that model results with updated wet processes agree better with measurements for most species. With the implementation of these updates, normalized mean biases (NMBs) of surface nitric acid, nitrate, and ammonium are reduced from 78 %, 126 %, and 45 % to 0.9 %, 15 %, and 4.1 % over the US sites, from 107 %, 127 %, and 90 % to −0.7 %, 4.2 %, and 16 % over European sites, and from 121 %, 269 %, and 167 % to −21 %, 37 %, and 86 % over Asian remote region sites. Comparison with surface measured SO2, sulfate, and black carbon at four Arctic sites indicated that those species simulated with the updated wet processes match well with observations except for a large underestimate of black carbon at one of the sites. We also compare our model simulation with aircraft measurement of nitric acid and aerosols during the Atmospheric Tomography Mission (ATom)-1 and ATom-2 periods and found a significant improvement of modeling skill of nitric acid, sulfate, and ammonium in the Northern Hemisphere during wintertime. The NMBs of these species are reduced from 163 %, 78 %, and 217 % to −13 %, −1 %, and 10 %, respectively. The investigation of impacts of updated wet process treatments on surface mass concentrations indicated that the updated wet processes have strong impacts on the global means of nitric acid, sulfate, nitrate, and ammonium and relative small impacts on the global means of sulfur dioxide, dust, sea salt, black carbon, and organic carbon.

Atmospheric particles can act as cloud condensation nuclei (CCN) and modify cloud properties and precipitation and thus indirectly impact the hydrological cycle and climate. New particle formation (NPF or nucleation), frequently observed at locations around the globe, is an important source of ultrafine particles and CCN in the atmosphere. In this study, wintertime NPF over the Northeastern United States (NEUS) is simulated with WRF-Chem coupled with a size-resolved (sectional) advanced particle microphysics (APM) model. Model-simulated variations in particle number concentrations during a 2-month period (November–December 2013) are in agreement with corresponding measurements taken at Pinnacle State Park (PSP), New York, and Appalachian State University (APP), North Carolina. We show that, even during wintertime, regional nucleation occurs and contributes significantly to ultrafine-particle and CCN number concentrations over the NEUS. The model shows that, due to low biogenic emissions during this period, wintertime regional nucleation is solely controlled by inorganic species and the newly developed ternary ion-mediated nucleation scheme is able to capture the variations in observed particle number concentrations (ranging from ∼200 to 20 000 cm−3) at both PSP and APP. Total particle and CCN number concentrations dramatically increase following NPF events and have the highest values over the Ohio Valley region, where elevated [SO2] is sustained by power plants. Secondary particles dominate particle number abundance over the NEUS, and their fraction increases with altitude from ≳85 % near the surface to ≳95 % in the upper troposphere. The secondary fraction of CCN also increases with altitude, from 20 %–50 % in the lower boundary layer to 50 %–60 % in the middle troposphere to 70 %–85 % in the upper troposphere.

The working environment in hot dry rock boreholes, encountered in deep geothermal investigation drilling and ultra-deep geological drilling (up to 5000 m), is very difficult at the present stage. We have developed a drilling trajectory measuring instrumentation (DTMI), which is based on the interference fiber-optic gyro (FOG). This can work continuously, for 4 h, in an environment where the ambient temperature does not exceed 270 ∘C and the pressure does not exceed 120 MPa. The DTMI is mainly divided into three parts: an external confining tube, a metal vacuum flask, and a FOG measurement probe. Here, we focus on the mechanical design, strength, and pressure field simulation analysis for the external tube, the structural design and temperature field simulation analysis for the vacuum flask, and the FOG Shupe error analysis and compensation in the temperature field. Finally, through the engineering applications of the SK-2 east borehole of the China Continental Scientific Drilling (CCSD) project and the geothermal well of Xingreguan-2, the data measurements of the drilling trajectory were used to analyze the stability of the DTMI. The instrument realizes long-duration, high-stability work in the process of making trajectory measurements in an ultra-deep hole. The instrument has the characteristic of anti-electromagnetic interference and enables work to be carried out in the blind zone of existing technologies and instrumentation. Therefore, DTMI has great potential in the promotion and development of geological drilling technology.

The outputs of four global climate models (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR and MIROC5), which were statistically downscaled and bias corrected, were used to drive four hydrological models (Hydrologiska Byråns, HBV; Soil and Water Assessment Tool, SWAT; Soil and Water Integrated Model, SWIM; and Variable Infiltration Capacity, VIC) to simulate the daily discharge at the Cuntan hydrological station in the upper Yangtze River from 1861 to 2299. As the performances of hydrological models in various climate conditions could be different, the models were first calibrated in the period from 1979 to 1990. Then, the models were validated in the comparatively wet period, 1967–1978, and in the comparatively dry period, 1991–2002. A multi-objective automatic calibration programme using a univariate search technique was applied to find the optimal parameter set for each of the four hydrological models. The Nash–Sutcliffe efficiency (NSE) of daily discharge and the weighted least-squares function (WLS) of extreme discharge events, represented by high flow (Q10) and low flow (Q90), were included in the objective functions of the parameterization process. In addition, the simulated evapotranspiration results were compared with the GLEAM evapotranspiration data for the upper Yangtze River basin. For evaluating the performances of the hydrological models, the NSE, modified Kling–Gupta efficiency (KGE), ratio of the root-mean-square error to the standard deviation of the measured data (RSR) and Pearson's correlation coefficient (r) were used. The four hydrological models reach satisfactory simulation results in both the calibration and validation periods. In this study, the daily discharge is simulated for the upper Yangtze River under the preindustrial control (piControl) scenario without anthropogenic climate change from 1861 to 2299 and for the historical period 1861–2005 and for 2006 to 2299 under the RCP2.6, RCP4.5, RCP6.0 and RCP8.5 scenarios. The long-term daily discharge dataset can be used in the international context and water management, e.g. in the framework of Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) by providing clues to what extent human-induced climate change could impact streamflow and streamflow trend in the future. The datasets are available at: https://doi.org/10.4121/uuid:8658b22a-8f98-4043-9f8f-d77684d58cbc (Gao et al., 2019).

Reactive oxygen species (ROS) mediate multiple physiological functions; however, the over-accumulation of ROS causes premature aging and/or death and is associated with various inflammatory conditions. Nevertheless, there are limited clinical treatment options that are currently available. The good news is that owing to the considerable advances in nanoscience, multiple types of nanomaterials with unique ROS-scavenging abilities that influence the temporospatial dynamic behaviors of ROS in biological systems have been developed. This has led to the emergence of next-generation nanomaterial-controlled strategies aimed at ameliorating ROS-related inflammatory conditions. Accordingly, herein we reviewed recent progress in research on nanotherapy based on ROS scavenging. The underlying mechanisms of the employed nanomaterials are emphasized. Furthermore, important issues in developing cross-disciplinary nanomedicine-based strategies for ROS-based inflammatory conditions are discussed. Our review of this increasing interdisciplinary field will benefit ongoing studies and clinical applications of nanomedicine based on ROS scavenging.

The widely used community model GEOS-Chem 12.0.0 and previous versions have been recognized to significantly overestimate the concentrations of gaseous nitric acid, aerosol nitrate, and aerosol ammonium over the United States. The concentrations of nitric acid are also significantly overpredicted in most global models participating in a recent model intercomparison study. In this study, we show that most or all of this overestimation issue appears to be associated with wet scavenging processes. The replacement of constant in-cloud condensation water (ICCW) assumed in GEOS-Chem standard versions with one varying with location and time from the assimilated meteorology significantly reduces mass loadings of nitrate and ammonium during the wintertime, while the employment of an empirical washout rate for nitric acid significantly decreases mass concentrations of nitric acid and ammonium during the summertime. Compared to the standard version, GEOS-Chem with updated ICCW and washout rate significantly reduces the simulated annual mean mass concentrations of nitric acid, nitrate, and ammonium at surface monitoring network sites in the US from 2.04 to 1.03, 1.89 to 0.88, and 1.09 to 0.68 µg m−3, respectively, in much better agreement with corresponding observed values of 0.83, 0.70, and 0.60 µg m−3, respectively. In addition, the agreement of model-simulated seasonal variations of corresponding species with measurements is also improved. The updated wet scavenging scheme improves the skill of the model in predicting nitric acid, nitrate, and ammonium concentrations, which are important species for air quality and climate.

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters >50 and >120 nm, as well as −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations ( %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −13 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (∂Nd/∂Na) and to updraft velocity (∂Nd/∂w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂Nd/∂Na and ∂Nd/∂w; models may be predisposed to be too “aerosol sensitive” or “aerosol insensitive” in aerosol–cloud–climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.

New particle formation (NPF) is known to be an important source of atmospheric particles that impacts air quality, hydrological cycle, and climate. Although laboratory measurements indicate that ammonia enhances NPF, the physicochemical processes underlying the observed effect of ammonia on NPF are yet to be understood. Here we present a comprehensive kinetically based H2SO4–H2O–NH3 ternary ion-mediated nucleation (TIMN) model that is based on the thermodynamic data derived from both quantum-chemical calculations and laboratory measurements. NH3 was found to reduce nucleation barriers for neutral, positively charged, and negatively charged clusters differently, due to large differences in the binding strength of NH3, H2O, and H2SO4 to small clusters of different charging states. The model reveals the general favor of nucleation of negative ions, followed by nucleation on positive ions and neutral nucleation, for which higher NH3 concentrations are needed, in excellent agreement with Cosmics Leaving OUtdoor Droplets (CLOUD) measurements. The TIMN model explicitly resolves dependences of nucleation rates on all the key controlling parameters and captures the absolute values of nucleation rates as well as the dependence of TIMN rates on concentrations of NH3 and H2SO4, ionization rates, temperature, and relative humidity observed in the well-controlled CLOUD measurements well. The kinetic model offers physicochemical insights into the ternary nucleation process and provides a physics-based approach to calculate TIMN rates under a wide range of atmospheric conditions.

Amines have received increasing attention in recent years because of their potential role in new particle formation in the atmosphere and their impact on aerosol chemistry. High concentrations of amines are expected to be limited to the vicinity of source regions due to their short lifetime, highlighting the necessity of having a better understanding of contributions of emissions from different source types. This study presents the first high-resolution model simulation of concentrations of methylamines on a regional scale over the Yangtze River Delta region in East China. The WRF-Chem with nested grids is used in model simulations. In contrast to the very limited existing modeling studies that assumed a fixed ratio (FR) of amines to total ammonia emission, we derive source-dependent ratios (SDR) that distinguish C1-amine (CH3NH2), C2-amines (C2H7N), C3-amines (C3H9N) emissions from five different source types (agriculture, residential, transportation, chemical industry, and other industry). The amines-to-ammonia mass emission ratios, estimated from previous measurements, are 0.026, 0.0015, 0.0011, 0.0011, and 0.0011 for C1-amine; 0.007, 0.0018, 0.0015, 0.01, and 0.0009 for C2-amines; and 0.0004, 0.0005, 0.00043, 0.0006, and 0.0004 for C3-amines for chemical–industrial, other industrial, agricultural, residential, and transportational sources, respectively. The simulated concentrations of C1-, C2-, and C3-amines, based on both FR and SDR, have been compared with field measurements at a suburban site in Nanjing and at an urban site in Shanghai, China. SDR substantially improves the ability of the model in capturing the observed concentrations of methylamines. Concentrations of C1-, C2-, and C3-amines in the surface layer in the Yangtze River Delta region are generally in the range of 2–20, 5–50, and 0.5–4 pptv. Vertically, the concentrations of C1-, C2-, and C3-amines decrease quickly with altitude, dropping by a factor of ∼ 10 from the surface to ∼ 900 hPa. Results from the present study are critical to evaluating potential roles of amines in nucleation and chemical processes in polluted air.

Atmospheric aerosols from anthropogenic and natural sources reach the polar regions through long-range transport and affect the local radiation balance. Such transport is, however, poorly constrained in present-day global climate models, and few multi-model evaluations of polar anthropogenic aerosol radiative forcing exist. Here we compare the aerosol optical depth (AOD) at 550 nm from simulations with 16 global aerosol models from the AeroCom Phase II model intercomparison project with available observations at both poles. We show that the annual mean multi-model median is representative of the observations in Arctic, but that the intermodel spread is large. We also document the geographical distribution and seasonal cycle of the AOD for the individual aerosol species: black carbon (BC) from fossil fuel and biomass burning, sulfate, organic aerosols (OAs), dust, and sea-salt. For a subset of models that represent nitrate and secondary organic aerosols (SOAs), we document the role of these aerosols at high latitudes.The seasonal dependence of natural and anthropogenic aerosols differs with natural aerosols peaking in winter (sea-salt) and spring (dust), whereas AOD from anthropogenic aerosols peaks in late spring and summer. The models produce a median annual mean AOD of 0.07 in the Arctic (defined here as north of 60° N). The models also predict a noteworthy aerosol transport to the Antarctic (south of 70° S) with a resulting AOD varying between 0.01 and 0.02. The models have estimated the shortwave anthropogenic radiative forcing contributions to the direct aerosol effect (DAE) associated with BC and OA from fossil fuel and biofuel (FF), sulfate, SOAs, nitrate, and biomass burning from BC and OA emissions combined. The Arctic modelled annual mean DAE is slightly negative (−0.12 W m−2), dominated by a positive BC FF DAE in spring and a negative sulfate DAE in summer. The Antarctic DAE is governed by BC FF. We perform sensitivity experiments with one of the AeroCom models (GISS modelE) to investigate how regional emissions of BC and sulfate and the lifetime of BC influence the Arctic and Antarctic AOD. A doubling of emissions in eastern Asia results in a 33 % increase in Arctic AOD of BC. A doubling of the BC lifetime results in a 39 % increase in Arctic AOD of BC. However, these radical changes still fall within the AeroCom model range.

Although some scholars have studied soil erosion in karst landforms, analyses of the spatial and temporal evolution of soil erosion and correlation analyses with spatial elements have been insufficient. The lack of research has led to an inaccurate assessment of environmental effects, especially in the mountainous area of Wuling in China. Soil erosion and rocky desertification in this area influence the survival and sustainability of a population of 0.22 billion people. This paper analyzes the spatiotemporal evolution of soil erosion and explores its relationship with rocky desertification using GIS technology and the revised universal soil loss equation (RUSLE). Furthermore, this paper analyzes the relationship between soil erosion and major natural elements in southern China. The results are as follows: (1) from 2000 to 2013, the proportion of the area experiencing micro-erosion and mild erosion was at increasing risk in contrast to areas where moderate and high erosion are decreasing. The area changes in this time sequence reflect moderate to high levels of erosion tending to convert into micro-erosion and mild erosion. (2) The soil erosion area on the slope, at 15–35°, accounted for 60.59 % of the total erosion area, and the corresponding soil erosion accounted for 40.44 %. (3) The annual erosion rate in the karst region decreased much faster than in the non-karst region. Soil erosion in all of the rock outcrop areas indicates an improving trend, and dynamic changes in soil erosion significantly differ among the various lithological distribution belts. (4) The soil erosion rate decreased in the rocky desertification regions, to below moderate levels, but increased in the severe rocky desertification areas. The temporal and spatial variations in soil erosion gradually decreased in the study area. Differences in the spatial distribution between lithology and rocky desertification induced extensive soil loss. As rocky desertification became worse, the erosion modulus decreased and the decreasing rate of annual erosion slowed.

Secondary particles formed via new particle formation (NPF) dominate cloud condensation nuclei (CCN) abundance in most parts of the troposphere and are important for aerosol indirect radiative forcing (IRF). Laboratory measurements have shown that certain organic compounds can significantly enhance the binary nucleation of sulfuric acid and H2O. According to our recent study comparing particle size distributions measured in nine forest areas in North America with those predicted by a global size-resolved aerosol model, current H2SO4–organics nucleation parameterizations appear to significantly overpredict NPF and particle number concentrations in summer. The lack of temperature dependence in the current H2SO4–organics nucleation parameterization has been suggested to be a possible reason for the observed overprediction. In this work, H2SO4–organics clustering thermodynamics from quantum chemical studies has been employed to develop a scheme to incorporate temperature dependence into H2SO4–organics nucleation parameterization. We show that temperature has a strong impact on H2SO4–organics nucleation rates and may reduce the nucleation rate by ∼ 1 order of magnitude per 10 K of temperature increase. The particle number concentrations in summer over North America based on the revised scheme is a factor of more than 2 lower, which is in much better agreement with the observations. With the temperature-dependent H2SO4–organics nucleation parameterization, the summer CCN concentrations in the lower troposphere in the Northern Hemisphere are about 10–30 % lower compared to the temperature-independent parameterization. This study highlights the importance of the temperature effect and its impacts on NPF in the global modeling of aerosol number abundance.

In practical projects, suitable high-precision control points are often added in the adjustment calculation so as to accurately recover the relationships between different light beams at the time of photography and finally obtain the results of high-precision oblique photography data. This paper studies the layout of control points of oblique photography data, and provides certain theoretical and practical guidance to the data processing application of actual oblique photography projects under the circumstance that there is no corresponding specification as the guidance for data processing of oblique photography at present.

The key technologies in the real scene 3D modeling of oblique photography mainly include the data acquisition of oblique photography, layout and surveying of photo control points, oblique camera calibration, aerial triangulation, dense matching of multi-angle image, building of triangulation irregular network (TIN) and TIN simplification and automatic texture mapping, among which aerial triangulation is the core and the results of aerial triangulation directly affect the later model effect and the corresponding data accuracy. Starting from this point of view, this paper aims to study the practical technologies of aerial triangulation for real scene 3D modeling with oblique photography and finally proposes a technical method of aerial triangulation with oblique photography which can be put into practice.

The vertical profile of aerosol is important for its radiative effects, but weakly constrained by observations on the global scale, and highly variable among different models. To investigate the controlling factors in one particular model, we investigate the effects of individual processes in HadGEM3–UKCA and compare the resulting diversity of aerosol vertical profiles with the inter-model diversity from the AeroCom Phase II control experiment. In this way we show that (in this model at least) the vertical profile is controlled by a relatively small number of processes, although these vary among aerosol components and particle sizes. We also show that sufficiently coarse variations in these processes can produce a similar diversity to that among different models in terms of the global-mean profile and, to a lesser extent, the zonal-mean vertical position. However, there are features of certain models' profiles that cannot be reproduced, suggesting the influence of further structural differences between models. In HadGEM3–UKCA, convective transport is found to be very important in controlling the vertical profile of all aerosol components by mass. In-cloud scavenging is very important for all except mineral dust. Growth by condensation is important for sulfate and carbonaceous aerosol (along with aqueous oxidation for the former and ageing by soluble material for the latter). The vertical extent of biomass-burning emissions into the free troposphere is also important for the profile of carbonaceous aerosol. Boundary-layer mixing plays a dominant role for sea salt and mineral dust, which are emitted only from the surface. Dry deposition and below-cloud scavenging are important for the profile of mineral dust only. In this model, the microphysical processes of nucleation, condensation and coagulation dominate the vertical profile of the smallest particles by number (e.g. total CN > 3 nm), while the profiles of larger particles (e.g. CN > 100 nm) are controlled by the same processes as the component mass profiles, plus the size distribution of primary emissions. We also show that the processes that affect the AOD-normalised radiative forcing in the model are predominantly those that affect the vertical mass distribution, in particular convective transport, in-cloud scavenging, aqueous oxidation, ageing and the vertical extent of biomass-burning emissions.

Recent laboratory chamber studies indicate a significant role for highly oxidized low-volatility organics in new particle formation (NPF), but the actual role of these highly oxidized low-volatility organics in atmospheric NPF remains uncertain. Here, particle size distributions (PSDs) measured in nine forest areas in North America are used to characterize the occurrence and intensity of NPF and to evaluate model simulations using an empirical formulation in which formation rate is a function of the concentrations of sulfuric acid and low-volatility organics from alpha-pinene oxidation (Nucl-Org), and using an ion-mediated nucleation mechanism (excluding organics) (Nucl-IMN). On average, NPF occurred on ~ 70 % of days during March for the four forest sites with springtime PSD measurements, while NPF occurred on only ~ 10 % of days in July for all nine forest sites. Both Nucl-Org and Nucl-IMN schemes capture the observed high frequency of NPF in spring, but the Nucl-Org scheme significantly overpredicts while the Nucl-IMN scheme slightly underpredicts NPF and particle number concentrations in summer. Statistical analyses of observed and simulated ultrafine particle number concentrations and frequency of NPF events indicate that the scheme without organics agrees better overall with observations. The two schemes predict quite different nucleation rates (including their spatial patterns), concentrations of cloud condensation nuclei, and aerosol first indirect radiative forcing in North America, highlighting the need to reduce NPF uncertainties in regional and global earth system models.

Gaseous amines have attracted increasing attention due to their potential role in enhancing particle nucleation and growth and affecting secondary organic aerosol formation. Here we study with a chemistry transport model the global distributions of the most common and abundant amines in the air: monomethylamine (MMA), dimethylamine (DMA), and trimethylamine (TMA). We show that gas phase oxidation and aerosol uptakes are dominant sinks for these methylamines. The oxidation alone (i.e., no aerosol uptake) leads to methylamine lifetimes of 5–10 h in most parts of low and middle latitude regions. The uptake by secondary species with uptake coefficient (γ) of 0.03 (corresponding to the uptake by sulfuric acid particles) reduces the lifetime by ~30% over oceans and much more over the major continents, resulting in a methylamine lifetime of less than 1–2 h over central Europe, eastern Asia, and eastern US. With the estimated global emission flux, from the literature, our simulations indicate that [DMA] in the model surface layer over major continents is generally in the range of 0.1–2 ppt (parts per trillion) when γ = 0.03 and 0.2–10 ppt when γ = 0, and decreases quickly with altitude. [DMA] over oceans is below 0.05 ppt and over polar regions it is below 0.01 ppt. The simulated [MMA] is about a factor of ~2.5 higher while [TMA] is a factor of ~8 higher than [DMA]. The modeled concentrations of methylamines are substantially lower than the limited observed values available, with normalized mean bias ranging from −57 (γ = 0) to −88% (γ = 0.03) for MMA and TMA, and from −78 (γ = 0) to −93% (γ = 0.03) for DMA.

The combined effects of drought, warming and the changes in land cover have caused severe land degradation for several decades in the extremely arid desert oases of southern Xinjiang, northwest China. Land cover classifications of Landsat images in 1990, 2000 and 2008 were performed based on the multistage supervised classification scheme using the maximum likelihood classifier integrated with conventional vegetation and soil indexes, which improved overall accuracies by 4–5% compared to the standard classification method. Based on the detection of changes in land cover during 1990–2008 using remote sensing (RS) and a geographic information system (GIS), it can be found that the oasis significantly (+35%) increased, while the area of ecotone decreased (−43%). The major trends of the land cover changes were the notable growth of the oasis and the reduction of the desert–oasis ecotone. These changes were mainly a result of the intensified human activities such as land and water exploitation as well as overgrazing. The results of this study indicate that the oasis environment will be deteriorated by increase in potential areas of land degradation if the trend of desert moving further inward and the shrinking of the ecotone continues over the next decades.

This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

The effects of yeast-derived protein (YP) on growth performance, intestinal health, and oxidative status of weanling piglets were investigated. A total of 80 weaned piglets (PIC 327 × 1050, 26 ± 2 days old, 6.20 ± 0.10 kg) were randomly allocated into 2 groups, 5 pens per each group and 8 piglets per each pen, receiving control diet and diet with inclusion of 4% YP at the expenses of fish meal (YP diet) for a period of 28 days. The diets were formulated to contain similar nutrient levels. Compared with control, piglets fed YP diet had markedly higher overall average daily growth (+14%, P < 0.05) and lower final feed conversion ratio (-8%, P < 0.01). Concentrations of serum serine, cystathionine, histidine, hydroxyproline, and urea were decreased in piglets fed YP diet (P < 0.05), whereas alanine and aspartate were increased (P < 0.01). Moreover, serum antioxidant enzyme activity (glutathione peroxidase) was markedly increased (+19%, P < 0.01) in piglets fed YP diet relative to piglets fed control diet. In addition, feeding YP diet considerably (P < 0.05) increased the copy numbers of lactobacilli and total bacteria in the colon of piglets at the end of the experiment. Furthermore, the mRNA abundance of innate immunity-related genes (TLR4, NF-κB1, and IL-6) was increased (P < 0.06) in the ileum of piglets fed YP diet. Collectively, results of this study indicated that diet with the inclusion of YP improved growth performance and partially enhanced anti-oxidative capability as well as intestinal innate immunity of weaning piglets.

Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.

We report on the AeroCom Phase II direct aerosol effect (DAE) experiment where 16 detailed global aerosol models have been used to simulate the changes in the aerosol distribution over the industrial era. All 16 models have estimated the radiative forcing (RF) of the anthropogenic DAE, and have taken into account anthropogenic sulphate, black carbon (BC) and organic aerosols (OA) from fossil fuel, biofuel, and biomass burning emissions. In addition several models have simulated the DAE of anthropogenic nitrate and anthropogenic influenced secondary organic aerosols (SOA). The model simulated all-sky RF of the DAE from total anthropogenic aerosols has a range from −0.58 to −0.02 Wm−2, with a mean of −0.27 Wm−2 for the 16 models. Several models did not include nitrate or SOA and modifying the estimate by accounting for this with information from the other AeroCom models reduces the range and slightly strengthens the mean. Modifying the model estimates for missing aerosol components and for the time period 1750 to 2010 results in a mean RF for the DAE of −0.35 Wm−2. Compared to AeroCom Phase I (Schulz et al., 2006) we find very similar spreads in both total DAE and aerosol component RF. However, the RF of the total DAE is stronger negative and RF from BC from fossil fuel and biofuel emissions are stronger positive in the present study than in the previous AeroCom study. We find a tendency for models having a strong (positive) BC RF to also have strong (negative) sulphate or OA RF. This relationship leads to smaller uncertainty in the total RF of the DAE compared to the RF of the sum of the individual aerosol components. The spread in results for the individual aerosol components is substantial, and can be divided into diversities in burden, mass extinction coefficient (MEC), and normalized RF with respect to AOD. We find that these three factors give similar contributions to the spread in results.

A clear understanding of particle formation mechanisms is critical for assessing aerosol indirect radiative forcing and associated climate feedback processes. Recent studies reveal the importance of ion-mediated nucleation (IMN) in generating new particles and cloud condensation nuclei (CCN) in the atmosphere. Here we implement the IMN scheme into the Community Atmosphere Model version 5 (CAM5). Our simulations show that, compared to globally averaged results based on H2SO4-H2O binary homogeneous nucleation (BHN), the presence of ionization (i.e., IMN) halves H2SO4 column burden, but increases the column integrated nucleation rate by around one order of magnitude, total particle number burden by a factor of ~3, CCN burden by ~10% (at 0.2% supersaturation) to 65% (at 1.0% supersaturation), and cloud droplet number burden by ~18%. Compared to BHN, IMN increases cloud liquid water path by 7.5%, decreases precipitation by 1.1%, and increases total cloud cover by 1.9%. This leads to an increase of total shortwave cloud radiative forcing (SWCF) by 3.67 W m−2 (more negative) and longwave cloud forcing by 1.78 W m−2 (more positive), with large spatial variations. The effect of ionization on SWCF derived from this study (3.67 W m−2) is a factor of ~3 higher that of a previous study (1.15 W m−2) based on a different ion nucleation scheme and climate model. Based on the present CAM5 simulation, the 5-yr mean impacts of solar cycle induced changes in ionization rates on CCN and cloud forcing are small (~−0.02 W m−2) but have larger inter-annual (from −0.18 to 0.17 W m−2) and spatial variations.

Mixing of Asian mineral dust with anthropogenic pollutants allows pollutants (e.g. sulfate and nitrate) to be transported over longer distances (e.g. to the northern Pacific, even to North America) along with dust particles. This mixing therefore affects the atmospheric and oceanic environment at local, regional and even continental scales. In this study, we used a three-dimensional regional chemical transport model (Nested Air Quality Predicting Modeling System, NAQPMS) to examine the degree of mixing between Asian mineral dust and anthropogenic pollutants in a super-duststorm event during 19–22 March 2010. Influences of the mixing processes on regional atmospheric environmental and oceanic biogeochemical cycles were also investigated. A comparison with measurements showed that the model reproduced well the trajectory of long-range dust transport, the vertical dust profile, and the chemical evolution of dust particles. We found that along-path mixing processes during the long-range transport of Asian dust led to increasingly polluted particles. As a result, ~60% of the sulfate and 70–95% of the nitrate in the downwind regions was derived from active mixing processes of minerals with pollutants sourced from the North China Plain and enhanced by transport over South China. This mixing had a significant impact on the regional-scale atmospheric composition and oceanic biogeochemical cycle. Surface HNO3, SO2 and O3 were decreased by up to 90%, 40% and 30%, respectively, due to the heterogeneous reactions on dust particles. Fe solubility rose from ~0.5% in the Gobi region to ~3–5% in the northwestern Pacific, resulting from oxidization of SO2 on dust particles. Total Fe(II) deposition in the ocean region of East Asia reached 327 tons during the 4-day dust event, and created a calculated primary productivity of ~520 mgC m−2 d−1 in the Kuril Islands, which can support almost 100% of the observed mean marine primary productivity in spring in this region (526 mgC m−2 d−1).

There exist large uncertainties in the present modeling of physical, chemical, and optical properties of atmospheric particles. We have recently incorporated an advanced particle microphysics (APM) model into a global chemistry transport model (GEOS-Chem) and a regional weather forecasting and chemistry model (WRF-Chem). Here we develop a scheme for calculating regional and global aerosol optical depth (AOD) from detailed aerosol information resolved by the APM model. According to GEOS-Chem-APM simulations, in most parts of the globe, the mass of secondary species resides mainly within secondary particles (60–90%), but in certain regions a large fraction (up to 50–80%) can become coated on various primary particles. Secondary species coated on black carbon and primary organic carbon particles significantly increase the size and hygroscopicity of these particles and thus impact their optical properties. The GEOS-Chem-APM model captures the global spatial distributions of AOD derived from AERONET, MODIS, and MISR measurements, generally within a factor of ~2. Our analysis indicates that modeled annual mean AODs at all sky and clear sky conditions differ by ~20% globally averaged and by >50% in some regions. The time series of WRF-Chem-APM predicted AOD over the northeastern United States in June 2008 have been compared to those from seven AERONET sites. Overall, the model mostly captures the absolute values as well as the variations of AOD at the AERONET sites (including dramatic changes associated with the crossing of high AOD plumes). Both GEOS-Chem and WRF-Chem simulations indicate that AOD over the northeastern US is dominated by secondary particles and have large spatiotemporal variations.

Aerosol direct radiative forcing (DRF) plays an important role in global climate change but has a large uncertainty. Here we investigate aerosol DRF with GEOS-Chem-APM, a recently developed global aerosol microphysical model that is designed to capture key particle properties (size, composition, coating of primary particles by volatile species, etc.). The model, with comprehensive chemistry, microphysics and up-to-date emission inventories, is driven by assimilated meteorology, which is presumably more realistic compared to the model-predicted meteorology. For this study, the model is extended by incorporating a radiation transfer model. Optical properties are calculated using Mie theory, where the core-shell configuration could be treated with the refractive indices from the recently updated values available in the literature. The surface albedo is taken from MODIS satellite retrievals for the simulation year, in which the data set for the 8-day mean at 0.05° (5600 m) resolution for 7 wavebands is provided. We derive the total and anthropogenic aerosol DRF, mainly focus on the results of anthropogenic aerosols, and then compare with those values reported in previous studies. In addition, we examine the anthropogenic aerosol DRF's dependence on several key factors, including the particle size of black carbon (BC) and primary organic carbon (POC), the density of BC and the mixing state. Our studies show that the anthropogenic aerosol DRF at top of atmosphere (TOA) for all sky is −0.41 W m−2. However, the sensitivity experiments suggest that the magnitude could vary from −0.08 W m−2 to −0.61 W m−2, depending on assumptions regarding the mixing state, size and density of particles.

New particle formation contributes significantly to the number concentration of condensation nuclei (CN) as well as cloud CN (CCN), a key factor determining aerosol indirect radiative forcing of the climate system. Using a physics-based nucleation mechanism that is consistent with a range of field observations of aerosol formation, it is shown that projected increases in global temperatures could significantly inhibit new particle, and CCN, formation rates worldwide. An analysis of CN concentrations observed at four NOAA ESRL/GMD baseline stations since the 1970s and two other sites since 1990s reveals long-term decreasing trends that are consistent in sign with, but are larger in magnitude than, the predicted temperature effects. The possible reasons for larger observed long-term CN reductions at remote sites are discussed. The combined effects of rising temperatures on aerosol nucleation rates and other chemical and microphysical processes may imply substantial decreases in future tropospheric particle abundances associated with global warming, delineating a potentially significant feedback mechanism that increases Earth's climate sensitivity to greenhouse gas emissions. Further research is needed to quantify the magnitude of such a feedback process.

Aerosol nucleation events, widely observed at various locations around the globe, are a significant source of cloud condensation nuclei (CCN) which determines aerosol indirect radiative forcing. In this study, a size-resolved, computationally efficient, advanced particle microphysics (APM) model, which has been previously incorporated into a global chemistry transport model (GEOS-Chem), is integrated into the Weather Research and Forecast model coupled with Chemistry (WRF-Chem) to study new particle formation and its contribution to particle number concentration and CCN abundance over the Eastern United States. Size- and composition-resolved aerosol properties from GEOS-Chem + APM simulations are used to initialize and provide boundary conditions for the WRF-Chem + APM model. The modeling results have been evaluated with the relevant measurements obtained during the INTEX-A field campaign in the summer of 2004. Model simulation captures the high concentrations of SO2 and CN10 at surface layer and source regions but underpredicts the values in the upper troposphere. The particle formation and number concentrations simulated by WRF-Chem + APM are generally consistent with those based on GEOS-Chem + APM over the Eastern United States, but the WRF-Chem + APM simulation has a much higher spatial resolution and can reveal urban and even plume scale processes. Our simulations show that high values of nucleation rates are largely confined to the regions of high SO2 emissions and that aerosol nucleation dominates the spatial and temporal distributions of condensation nuclei lager than 10 nm (CN10). Similarly, high concentrations of CCN at supersaturation of 0.4% (CCN0.4) are generally confined to SO2 source regions, with the highest monthly (July) mean CCN0.4 value exceeding 1600 # cm−3 in the lower troposphere over Indiana and Ohio. Nucleation and subsequent growth of secondary particles are important sources of CCN0.4, accounting for more than 80% in most parts of the Eastern United States.

The impact of primary sulfate emissions on cloud condensation nuclei (CCN) concentrations, one of the major uncertainties in global CCN predictions, depends on the fraction of sulfur mass emitted as primary sulfate particles (fsulfate), the fraction of primary sulfate mass distributed into the nucleation mode particles (fnucl), and the nucleation and growth processes in the ambient atmosphere. Here, we use a global size-resolved aerosol microphysics model recently developed to study how the different parameterizations of primary sulfate emission affect particle properties and CCN abundance. Different from previous studies, we use the ion-mediated nucleation scheme to simulate tropospheric particle formation. The kinetic condensation of low volatile secondary organic gas (SOG) (in addition to H2SO4 gas) on nucleated particles is calculated based on our new scheme that considers the SOG volatility changes arising from the oxidation aging. Our simulations show a compensation effect of nucleation to primary sulfate emission. We find that the change of fnucl from 5% to 15% has a more significant impact on the simulated particle number budget than that of fsulfate within the range of 2.5–5%. Based on our model configurations, an increase of fsulfate from 0% to 2.5% (with fnucl = 5%) does not improve the agreement between simulated and observed annual mean number concentrations of particles >10 nm at 21 stations but further increase of either fsulfate from 2.5% to 5% (with fnucl = 5%) or fnucl from 5% to 15% (with fsulfate = 2.5%) substantially deteriorates the agreement. For fsulfate of 2.5%–5% and fnucl of 5%, our simulations indicate that the global CCN at supersaturation of 0.2% increases by 8–11% in the boundary layer and 3–5% in the whole troposphere (compared to the case with fsulfate=0).

A numerical evaluation of global oceanic emissions of α-pinene and isoprene based on both "bottom-up" and "top-down" methods is presented. We infer that the global "bottom-up" oceanic emissions of α-pinene and isoprene are 0.013 TgC yr−1 and 0.32 TgC yr−1, respectively. By constraining global chemistry model simulations with the shipborne measurement of Organics over the Ocean Modifying Particles in both Hemispheres summer cruise, we derived the global "top-down" oceanic α-pinene source of 29.5 TgC yr−1 and isoprene source of 11.6 TgC yr−1. Both the "bottom-up" and "top-down" values are subject to large uncertainties. The incomplete understanding of the in-situ phytoplankton communities and their range of emission potentials significantly impact the estimated global "bottom-up" oceanic emissions, while the estimated total amounts of the global "top-down" oceanic sources can be influenced by emission parameterizations, model and input data spatial resolutions, boundary layer mixing processes, and the treatments of chemical reactions. The global oceanic α-pinene source and its impact on organic aerosol formation is significant based on "top-down" method, but is negligible based on "bottom-up" approach. Our research highlights the importance of carrying out further research (especially measurements) to resolve the large offset in the derived oceanic organic emission based on two different approaches.

An advanced particle microphysics model with a number of computationally efficient schemes has been incorporated into a global chemistry transport model (GEOS-Chem) to simulate particle number size distributions and cloud condensation nuclei (CCN) concentrations in the atmosphere. Size-resolved microphysics for secondary particles (i.e., those formed from gaseous species) and sea salt has been treated in the present study. The growth of nucleated particles through the condensation of sulfuric acid vapor and equilibrium uptake of nitrate, ammonium, and secondary organic aerosol is explicitly simulated, along with the scavenging of secondary particles by primary particles (dust, black carbon, organic carbon, and sea salt). We calculate secondary particle formation rate based on ion-mediated nucleation (IMN) mechanism and constrain the parameterizations of primary particle emissions with various observations. Our simulations indicate that secondary particles formed via IMN appear to be able to account for the particle number concentrations observed in many parts of the troposphere. A comparison of the simulated annual mean concentrations of condensation nuclei larger than 10 nm (CN10) with those measured values show very good agreement (within a factor of two) in near all 22 sites around the globe that have at least one full year of CN10 measurements. Secondary particles appear to dominate the number abundance in most parts of the troposphere. Calculated CCN concentration at supersaturation of 0.4% (CCN0.4) and the fraction of CCN0.4 that is secondary (fsecCCN) have large spatial variations. Over the middle latitude in the Northern Hemisphere, zonally averaged CCN0.4 decreases from ~400–700 cm−3 in the boundary layer (BL) to below 100 cm−3 above altitude of ~4 km, the corresponding fsecCCN values change from 50–60% to above ~70%. In the Southern Hemisphere, the zonally averaged CCN0.4 is below 200 cm−3 and fsecCCN is generally above 60% except in the BL over the Southern Ocean.

Aerosol nucleation events have been observed at a variety of locations worldwide, and may have significant climatic and health implications. While ions have long been suggested as favorable nucleation embryos, their significance as a global source of particles has remained uncertain. Here, an ion-mediated nucleation (IMN) mechanism, which incorporates new thermodynamic data and physical algorithms, has been integrated into a global chemical transport model (GEOS-Chem) to study ion-mediated particle formation in the global troposphere. The simulated annual mean results have been compared to a comprehensive set of data relevant to particle nucleation around the globe. We show that predicted annual spatial patterns of particle formation agree reasonably well with land-, ship-, and aircraft-based observations. Our simulations show that, globally, IMN in the boundary layer is largely confined to two broad latitude belts: one in the northern hemisphere (~20° N–70° N), and one in the southern hemisphere (~30° S–90° S). In the middle latitude boundary layer over continents, the annual mean IMN rates are generally above 104 cm−3day−1, with some hot spots reaching 105 cm−3day−1. The zonally-averaged vertical distribution of IMN rates indicates that IMN is significant in the tropical upper troposphere, the entire middle latitude troposphere, and over Antarctica. Comparing the relative strengths of particle sources due to IMN and due to primary particle emissions demonstrates that IMN is significant on a global scale. Further research is needed to reduce modeling uncertainties and to understand the ultimate contribution of freshly nucleated particles to the abundance of cloud condensation nuclei.

We theoretically investigate the spin injection from a ferromagnetic silicene to a normal silicene (FS/NS), where the magnetization in the FS is assumed from the magnetic proximity effect. Based on a silicene lattice model, we demonstrated that the pure spin injection could be obtained by tuning the Fermi energy of two spin species, where one is in the spin orbit coupling gap and the other one is outside the gap. Moreover, the valley polarity of the spin species can be controlled by a perpendicular electric field in the FS region. Our findings may shed light on making silicene-based spin and valley devices in the spintronics and valleytronics field.