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Our understanding of aerosol optical depth (AOD) in Antarctica remains limited due to the scarcity of ground observation stations and limited daylight days. Utilizing data from the CE318-T photometer spanning January 2020 to April 2023 at Zhongshan Station, we analyzed the seasonal, monthly, and diurnal variations in AOD and the Ångström exponent (AE). AOD median values increased from spring (0.033) to winter (0.115), while AE peaked during summer (1.010) and autumn (1.034), declining in winter (0.381), indicating a transition in dominant aerosol particle size from fine to coarse mode between summer and winter. Monthly mean AOD variation closely paralleled the proportion of AE < 1, suggesting fluctuations in coarse-mode particle proportions drive AOD variation. The high AOD values during winter and spring were associated with an increased contribution of coarse-mode particles, while high AOD values during summer and autumn were associated with the growth of fine-mode particles. We observed a peak in AOD (∼ 0.06) at 14:00 local time (LT) at Zhongshan Station, possibly associated with a slight decrease in boundary layer height (BLH). Additionally, higher (lower) wind speeds corresponded to lower (higher) AOD values, indicating the diffusion (accumulation) effect. The temperature and AOD showed an insignificant positive correlation (R = 0.22, p = 0.40), and relative humidity exhibited a significant negative correlation with AOD (R = −0.59, p = 0.02). Backward trajectory analysis revealed that coarse particles from the ocean predominantly contributed to high AOD daily mean values, while fine particles on low-AOD days originated mainly from the air mass over the Antarctic Plateau. This study enhances the understanding of the optical properties and seasonal behaviors of aerosols in the coastal Antarctic. Specifically, AOD measurements during the polar night address the lack of validation data for winter AOD simulations. Additionally, we revealed that lower wind speeds, higher temperatures, and lower relative humidity contribute to increased AOD at Zhongshan Station, and air masses from the ocean significantly impact local AOD levels. These findings help us infer AOD variation patterns in the coastal Antarctic based on meteorological changes, providing valuable insights for climate modeling in the context of global climate change.

Aerosol hygroscopicity plays a vital role in aerosol radiative forcing. One key parameter describing hygroscopicity is the scattering enhancement factor, f(RH), defined as the ratio of the scattering coefficient at humidified relative humidity (RH) to its dry value. Here, we utilize the f(80 %) from ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) 2016 and 2018 airborne measurements to investigate the hygroscopicity of aerosols, its vertical distribution, its relationship with chemical composition, and its sensitivity to organic aerosol (OA) hygroscopicity over the southeast Atlantic (SEA) Ocean during the biomass burning (BB) season. We found that aerosol hygroscopicity remains steady above 2 km, with a mean f(80 %) of 1.40 ± 0.17. Below 2 km, aerosol hygroscopicity increases with decreasing altitude, with a mean f(80 %) of 1.51 ± 0.22, consistent with higher values of BB aerosol hygroscopicity found in the literature. The hygroscopicity parameter of OA (κOA) is retrieved from the Mie model with a mean value of 0.11 ± 0.08, which is in the middle to upper range compared to the literature. Higher OA hygroscopicity is related to aerosols that are more aged, oxidized, and present at lower altitudes. The enhanced biomass burning aerosol (BBA) hygroscopicity at lower altitudes is mainly due to a lower OA fraction, increased sulfate fraction, and greater κOA at lower altitudes. We propose a parameterization that quantifies f(RH) with chemical composition and κOA based on Mie simulation of internally mixed OA–(NH4)2SO4–BC mixtures. The good agreement between the predictions and the ORACLES measurements implies that the aerosols in the SEA during the BB season can be largely represented by the OA–(NH4)2SO4–BC internal mixture with respect to the f(RH) prediction. The sensitivity of f(RH) to κOA indicates that applying a constant κOA is only suitable when the OA fraction is low and κOA shows limited variation. However, in situations deviating these two criteria, κOA can notably impact scattering coefficients and aerosol radiative effect; therefore, accounting for κOA variability is recommended.

Black carbon (BC) plays an important role in air quality, public health, and climate, but its long-term variations in emissions and health effects have been insufficiently understood for China. Here, we present the spatiotemporal evolution of BC emissions and the associated premature mortality in China during 2000–2020 based on an integrated framework combining satellite observations from the Ozone Monitoring Instrument (OMI), an extreme gradient boosting (XGBoost) algorithm, a “top-down” inversion approach, and an exposure–response model. We found that the “bottom-up” approach most likely underestimated BC emissions, particularly in less developed western and remote areas. Pollution controls were estimated to reduce the annual BC emissions by 26 % during 2010–2020, reversing the 8 % growth during 2000–2010. BC emissions in the main coal-producing provinces declined by 2010 but rebounded afterwards. By contrast, provinces with higher economic and urbanization levels experienced emission growth (0.05–0.10 Mg km−2 yr−1) by 2010 and declined greatly (0.07–0.23 Mg km−2 yr−1) during 2010–2020. The national annual BC-associated premature mortality ranged between 733 910 (95 % confidence interval: 676 790–800 250) and 937 980 cases (864 510–1 023 400) for different years. The changing BC emissions contributed to an increase of 78 590 cases (72 520–85 600) during 2000–2005 and a decrease of 133 360 cases (123 150–145 180) during 2010–2015. Strategies differentiated by region are needed for further reducing BC emissions and their health and climate impacts.

Nucleophilic high molecular-weight organic compounds (HMWOCs) are sensitive to protons (H+) in Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) analysis. A comprehensive evaluation of the diurnal evolution of nucleophilic HMWOCs was performed. HMWOCs aged significantly in daily cycles, accompanied by functionality shifts, particularly oxygenated and reduced nitrogen (CHON and CHN) as well as oxygenated organics. The intensities of high molecular-weight (HMW) oxygenated compounds increased during both daytime and nighttime. The daytime evolution produced more nitrogen-containing compounds with carboxylic group (–COOH) homologues with molecular weights greater than 300, while the nighttime evolution produced mostly small CHON compounds (molecular weights < 300). During evolution, nighttime CHON removals were observed; meanwhile, carboxylation was also identified in CHON groups. The daytime evolution produced significantly more reduced-nitrogen-containing compounds; a day- and nighttime increase in CHN compounds with five members was also observed. This study can provide insights into the aging of less polar organic aerosols.

Although China's air quality has substantially improved in recent years due to the vigorous emissions reduction, the Beijing–Tianjin–Hebei (BTH) region, especially its central and southern plains at the eastern foot of the Taihang Mountains, has been the most polluted area in China, with persistent and severe haze in winter. Combining meteorology–chemistry coupled model simulations and multiple observations, this study explored the causes of several heavy haze events in this area in January 2017, focusing on local circulations related to mountain terrain. The study results showed that on the weather scale, the configuration of the upper, middle, and lower atmosphere provided favorable weather and water vapor transport conditions for the development of haze pollution. Under the weak weather-scale systems, local circulation played a dominant role in the regional distribution and extreme values of PM2.5. Influenced by the Taihang and Yanshan mountains, vertical circulations and wind convergence zone were formed between the plain and mountain slopes. The vertical distribution of pollutants strongly depended on the intensity and location of the circulation. The circulation with high intensity and low altitude was more unfavorable for the vertical and horizontal diffusion of near-surface pollutants. More importantly, we found that the aerosol–radiation interaction (ARI) significantly amplified the impacts of local vertical circulations on heavy haze by two mechanisms. First, the ARI strengthened the vertical circulations at the lower levels, with the zonal wind speeds increasing by 0.3–0.8 m s−1. Meanwhile, the ARI could cause a substantial downward shift in the vertical circulations (∼ 100 m). Second, the ARI weakened the horizontal diffusion of pollutants by reducing the westerly winds and enhancing wind convergence and southerly winds. Under these two mechanisms, pollutants could only recirculate in a limited space. This superposition of the typical local circulation and the ARI eventually contributed to the accumulation of pollutants and the consequent deterioration of haze pollution in the region.

Data assimilation techniques are one of the most important ways to reduce the uncertainty in atmospheric chemistry model input and improve the model forecast accuracy. In this paper, an ensemble optimal interpolation assimilation (EnOI) system for a regional online chemical weather numerical forecasting system (GRAPES_Meso5.1/CUACE) is developed for operational use and efficient updating of the initial fields of chemical components. A heavy haze episode in eastern China was selected, and the key factors affecting EnOI, such as localization length scale, ensemble size, and assimilation moment, were calibrated by sensitivity experiments. The impacts of assimilating ground-based PM2.5 observations on the model chemical initial field PM2.5 and visibility forecasts were investigated. The results show that assimilation of PM2.5 reduces the uncertainty in the initial PM2.5 field considerably. Using only 50 % of observations in the assimilation, the root mean square error (RMSE) of initial PM2.5 for independent verification sites in mainland China decreases from 73.7 to 46.4 µg m−3, and the correlation coefficient increases from 0.58 to 0.84. An even larger improvement appears in northern China. For the forecast fields, assimilation of PM2.5 improves PM2.5 and visibility forecasts throughout the time window of 24 h. The PM2.5 RMSE can be reduced by 10 %–21 % within 24 h, and the assimilation effect is the most remarkable in the first 12 h. Within the same assimilation time, the assimilation efficiency varies with the discrepancy between model forecasts and observations at the moment of assimilation, and the larger the deviation, the higher the efficiency. The assimilation of PM2.5 further contributes to the improvement of the visibility forecast. When the PM2.5 increment is negative, it corresponds to an increase in visibility, and when the PM2.5 analysis increment is positive, visibility decreases. It is worth noting that the improvement of visibility forecasting by assimilating PM2.5 is more obvious in the light-pollution period than in the heavy-pollution period. The results of this study show that EnOI may provide a practical and cost-effective alternative to the ensemble Kalman filter (EnKF) for the applications where computational cost is the main limiting factor, especially for real-time operational forecast.

Mineral dust is a major natural atmospheric aerosol that impacts the Earth's radiation balance. The significant scavenging process of fine particles by the strong wind during the dust episodes provided a relatively clean environment that was favourable for new particle formation (NPF) occurrence. In this study, the NPF occurred following the dust episodes (dust-related NPF), and other cases under clean and polluted conditions were classified based on the long-term particle number size distribution (PNSD) in urban Beijing in spring from 2017 to 2021. It was found that the observed formation (Jobs) and growth rate (GR) of dust-related NPF events were approximately 50 % and 30 % lower than the values of other NPF days, respectively. A typical severe dust storm that originated from Mongolia and swept over northern China on 15–16 March 2021 was analysed, to illustrate how the dust storm influences the NPF event. The maximum hourly mean PM10 mass concentration reached 8000 µg m−3 during this dust storm. The occurrence of an NPF event after a dust storm was facilitated due to the low condensation sink (∼ 0.005 s−1) caused by the strong dilution process of pre-existing particles. However, a downward trend of particle hygroscopicity was found during dust storm and NPF event as compared with the polluted episode, resulting in an increasing trend of the critical diameter at different supersaturations (ss), where aerosols are activated as cloud condensation nuclei (CCN), although the NPF event occurred when dust faded. The critical diameter was elevated by approximately 6 %–10 % (ss = 0.2 % and 0.7 %) during the dust storm, resulting in a lower CCN activation ratio, especially at low supersaturation. Modifications of the nucleation and growth process, as well as the particle-size distribution and hygroscopicity of the dust particles, provide valuable information that reveals the underlying climate and air quality effects of Asian mineral dust.

Non-methane short-lived climate forcers (SLCFs), including aerosols, ozone, and their precursors, are important climate forcings and primary air pollutants. Future stringent SLCF emissions controls to mitigate air pollution will substantially impact regional climate change. Here, we investigate the changes in future climate extremes and resulting population exposure risks in Asia during 2031–2050 in response to non-methane SLCF emissions reductions using multi-model ensemble (MME) simulations under two shared socioeconomic pathway (SSP) scenarios with the same greenhouse gas (GHG) emissions but weak (SSP3-7.0) and strong (SSP3-7.0-lowNTCF) air quality control measures from the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP), which is endorsed by the Coupled Model Intercomparison Project phase 6 (CMIP6). The MME results show that future reductions in non-methane SLCF emissions lead to an increase of 0.23 ± 0.16 W m−2 in global annual mean effective radiative forcing, thereby magnifying the GHG-induced global surface warming by 0.19 ± 0.1 K during 2031–2050. In terms of the entire study area of Asia, the additional warming caused by the non-methane SLCF reductions increases the temperature of the hottest days (TXx) by 0.3 ± 0.1 K, the percentage of warm days (TX90p) by 4.8 ± 2.2 %, the number of tropical nights (TR) by 1.7 ± 0.8 d, the warm-spell duration (WSDI) by 1.0 ± 0.4 d, the number of heavy precipitation days (R10) by 1.0 ± 0.5 d, the maximum consecutive 5 d precipitation (RX5day) by 1.0 ± 0.3 mm, and the total wet-day precipitation (R95p) by 16.4 ± 7.3 mm during 2031–2050. In terms of sub-regional changes in temperature extremes, the largest regional increases in TXx, TX90p, and WSDI occur in northern India (NIN) and northern China (NC). Relatively large increases in TR are projected in NC and the Sichuan Basin (SCB), reaching 5.1 ± 2.5 d and 4.9 ± 3.3 d, respectively. For precipitation extremes, the regional changes are greatest in southern China (SC), particularly southwestern China (SWC), where reductions in non-methane SLCF emissions increase R10 by 2.5 ± 1.9 d, RX5day by 2.5 ± 1.5 mm, and R95p by 37.5 ± 22.6 mm. Moreover, the populations exposed to temperature and precipitation extremes increase most sharply in NIN, reaching (32.2 ± 11.4) × 107 person-days and (4.6 ± 6.1) × 106 person-days during 2031–2050, respectively, followed by NC and SCB. Our results highlight the significant impacts of non-methane SLCF reductions on future climate extremes and related exposure risks in eastern and southern Asia, which are comparable to the impact associated with increased GHG forcing in some regions.

The representation of aerosol–cloud interaction (ACI) and its impacts in the current climate or weather model remains a challenge, especially for severely polluted regions with high aerosol concentration, which is even more important and worthy of study. Here, ACI is first implemented in the atmospheric chemistry model GRAPES_Meso5.1/CUACE by allowing for real-time aerosol activation in the Thompson cloud microphysics scheme. Two experiments are conducted focusing on a haze pollution case with coexisting high aerosol and stratus cloud over the Jing–Jin–Ji region in China to investigate the impact of ACI on the mesoscale numerical weather prediction (NWP). Study results show that ACI increases cloud droplet number concentration, water mixing ratio, liquid water path (CLWP), and optical thickness (COT), as a result improving the underestimated CLWP and COT (reducing the mean bias by 21 % and 37 %, respectively) over a certain subarea by the model without ACI. A cooling in temperature in the daytime below 950 hPa occurs due to ACI, which can reduce the mean bias of 2 m temperature in the daytime by up to 14 % (∼ 0.6 ∘C) in the subarea with the greatest change in CLWP and COT. The 24 h cumulative precipitation in this subarea corresponding to moderate-rainfall events increases, which can reduce the mean bias by 18 %, depending on the enhanced melting of the snow by more cloud droplets. In other areas or periods with a slight change in CLWP and COT, the impact of ACI on NWP is not significant, suggesting the inhomogeneity of ACI. This study demonstrates the critical role of ACI in the current NWP model over the severely polluted region and the complexity of the ACI effect.

Endothelial dysfunction is a hallmark of cardiovascular diseases, contributing to impaired vasodilation, altered hemodynamics, and atherosclerosis progression. Trimetazidine, traditionally used for angina pectoris, exhibits diverse therapeutic effects on endothelial dysfunction. This review aims to elucidate the mechanisms underlying trimetazidine’s actions and its potential as a therapeutic agent for endothelial dysfunction and associated cardiovascular disorders. Trimetazidine enhances vasodilation and hemodynamic function by modulating endothelial nitric oxide synthase activity, nitric oxide production, and endothelin-1. It also ameliorates metabolic parameters, including reducing blood glucose, mitigating oxidative stress, and dampening inflammation. Additionally, trimetazidine exerts antiatherosclerotic effects by inhibiting plaque formation and promoting its stability. Moreover, it regulates apoptosis and angiogenesis, fostering endothelial cell survival and neovascularization. Understanding trimetazidine’s multifaceted mechanisms underscores its potential as a therapeutic agent for endothelial dysfunction and associated cardiovascular disorders, warranting further investigation for clinical translation.

The semi-permanent stratocumulus clouds over the south-eastern Atlantic Ocean (SEA) can act as an “air conditioner” to the regional and global climate system. The interaction of aerosols and clouds becomes important in this region and can lead to negative radiative effects, partially offsetting the positive radiative forcing of greenhouse gases. A key pathway by which aerosols affect cloud properties is by acting as cloud condensation nuclei (CCN). In this paper, we use the United Kingdom Earth System Model (UKESM1) to investigate the sources of CCN (from emissions and atmospheric processes) in the SEA as well as the response of the cloud droplet number concentration (CDNC), the cloud liquid water path (LWP), and radiative forcing to these sources during 2016 and 2017. Overall, free and upper troposphere nucleated aerosols are the dominant source of the boundary layer CCN concentration at 0.2 % supersaturation (CCN0.2 %), contributing an annual average of ∼ 41 % as they subside and entrain into the marine boundary layer, which is consistent with observations highlighting the important role of nucleation in the boundary layer CCN concentration. In terms of emission sources, anthropogenic emissions (from energy, industry, agriculture, etc.) contribute the most to the annual average CCN0.2 % in the marine boundary layer (∼ 26 %), followed by biomass burning (BB, ∼ 17 %). In the cloud layer, BB contributes about 34 % of the annual CCN0.2 %, midway between the contributions from aerosol nucleation (36 %) and anthropogenic sources (31 %). The contribution of aerosols from different sources to the CDNC is consistent with their contribution to CCN0.2 % within the marine boundary layer, with free and upper troposphere aerosol nucleation being the most important source of the CDNC overall. In terms of emission sources, anthropogenic sources are also the largest contributors to the annual average CDNC, closely followed by BB. However, during the BB season, BB and free and upper troposphere aerosol nucleation are equally the most important sources of the CDNC. The contribution of BB to the CDNC is more significant than its increase to CCN0.2 %, mainly because BB aerosols are mostly located directly above the inversion layer in the model; thus, they can increase the in-cloud CDNC by enhancing the supersaturation through the dynamical feedback due to short-wave absorption. An aerosol source that shows an increase in the CDNC also shows an increase in the LWP resulting from a reduction in autoconversion. Due to the absorption effect, BB aerosol can enhance existing temperature inversions and reduce the entrainment of sub-saturated air, leading to a further increase in the LWP. As a result, the contribution of BB to the LWP is second only to aerosol nucleation on annual averages. These findings demonstrate that BB is not the dominant source of CCN within the marine boundary layer from an emission source perspective. However, as most BB aerosols are located directly above the inversion layer, their effect on clouds increases due to their absorption effect (about the same as anthropogenic sources for the CDNC and more than anthropogenic sources for the LWP), highlighting the crucial role of their radiative effect on clouds. The results on the radiative effects of aerosols show that BB aerosol exhibits an overall positive RFari (radiative forcing associated with aerosol–radiation interactions), but its net effective radiative forcing remains negative due to its effect on clouds (mainly due to its absorbing effect). By quantifying aerosol and cloud properties affected by different sources, this paper provides a framework for understanding the effects of aerosol sources on marine stratocumulus clouds and radiation in the SEA.

This study characterizes single-particle aerosol composition from filters collected during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) and CLoud–Aerosol–Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017) campaigns. In particular the study describes aged biomass burning aerosol (BBA), its interaction with the marine boundary layer and the influence of biomass burning (BB) air on marine aerosol. The study finds evidence of BBA influenced by marine boundary layer processing as well as sea salt influenced by BB air. Secondary chloride aerosols were observed in clean marine air as well as in BB-influenced air in the free troposphere. Higher-volatility organic aerosol appears to be associated with increased age of biomass burning plumes, and photolysis or oxidation may be a mechanism for the apparent increased volatility. Aqueous processing and interaction with the marine boundary layer air may be a mechanism for the presence of sodium on many aged potassium salts. By number, biomass burning potassium salts and modified sea salts are the most observed particles on filter samples. The most commonly observed BC coatings are inorganic salts. These results suggest that atmospheric processes such as photolysis, oxidation and cloud processing are key drivers in the elemental composition and morphology of aged BBA. Fresh BBA inorganic salt content, as it has an important role in the particles' ability to uptake water, may be a key driver in how aqueous processing and atmospheric aging proceed.

From June to October, southern Africa produces one-third of the global biomass burning (BB) emissions by widespread fires. BB aerosols are transported westward over the south-eastern Atlantic with the mid-tropospheric winds, resulting in significant radiative effects. Ascension Island (ASI) is located midway between Africa and South America. From June 2016 to October 2017, a 17-month in situ observation campaign on ASI found a low single-scattering albedo (SSA) as well as a high mass absorption cross-section of black carbon (MACBC), demonstrating the strong absorbing marine boundary layer in the south-eastern Atlantic. Here we investigate the monthly variations of critical optical properties of BB aerosols, i.e. SSA and MACBC, during the BB seasons and the driving factors behind these variations. Both SSA and MACBC increase from June to August and decrease in September and October. The average SSA during the BB seasons is 0.81 at 529 nm wavelength, with the highest mean ∼ 0.85 in October and the lowest ∼ 0.78 in August. The absorption enhancement (Eabs) derived from the MACBC shows similar trends with SSA, with the average during the whole of the BB seasons at ∼ 1.96 and ∼ 2.07 in 2016 and 2017, respectively. As the Eabs is higher than the ∼ 1.5 commonly adopted value by climate models, this result suggests the marine boundary layer in the south-eastern Atlantic is more absorbing than model simulations. We find the enhanced ratio of BC to CO (ΔBC/ΔCO, equal to BC/ΔCO as the BC background concentration is considered to be 0) is well correlated with SSA and MACBC, providing a simple way to estimate the aerosol optical characteristics in the south-eastern Atlantic. The exponential function we proposed can approximate SSA and MACBC with BC/ΔCO, and when BC/ΔCO is small it can capture the rapid growth of SSA as BC/ΔCO decreases. BC/ΔCO is influenced by combustion conditions and aerosol scavenging. From the analysis of the location of BB, the primary source fuel, the water content in the fuel, combined with the mean cloud cover and precipitation in the transport areas of the BB plume, we conclude that the increase in BC/ΔCO from June to August is likely to be caused by burning becoming more flaming. The reduction in the water content of fuels may be responsible for the change in the burning conditions from June to August. The decrease in BC/ΔCO in September and October may be caused by two factors, one being a lower proportion of flaming conditions, possibly associated with a decrease in mean surface wind speed in the burning area, and the other being an increase in precipitation in the BB transport pathway, leading to enhanced aerosol scavenging, which ultimately results in an increase in SSA and MACBC.

Fine particulate matter (PM2.5) has altered the radiation balance on Earth and raised environmental and health risks for decades but has only been monitored widely since 2013 in China. Historical long-term PM2.5 records with high temporal resolution are essential but lacking for both research and environmental management. Here, we reconstruct a site-based PM2.5 dataset at 6 h intervals from 1960 to 2020 that combines long-term visibility, conventional meteorological observations, emissions, and elevation. The PM2.5 concentration at each site is estimated based on an advanced machine learning model, LightGBM, that takes advantage of spatial features from 20 surrounding meteorological stations. Our model's performance is comparable to or even better than those of previous studies in by-year cross validation (CV) (R2=0.7) and spatial CV (R2=0.76) and is more advantageous in long-term records and high temporal resolution. This model also reconstructs a 0.25∘ × 0.25∘, 6-hourly, gridded PM2.5 dataset by incorporating spatial features. The results show PM2.5 pollution worsens gradually or maintains before 2010 from an interdecadal scale but mitigates in the following decade. Although the turning points vary in different regions, PM2.5 mass concentrations in key regions decreased significantly after 2013 due to clean air actions. In particular, the annual average value of PM2.5 in 2020 is nearly the lowest since 1960. These two PM2.5 datasets (publicly available at https://doi.org/10.5281/zenodo.6372847, Zhong et al., 2022) provide spatiotemporal variations at high resolution, which lay the foundation for research studies associated with air pollution, climate change, and atmospheric chemical reanalysis.

The study presents a climatology of aerosol composition concentrations obtained by a recently developed algorithm approach, namely the Generalized Retrieval of Atmosphere and Surface Properties (GRASP)/Component. It is applied to the whole archive of observations from the POLarization and Directionality of the Earth's Reflectances (POLDER-3). The conceptual specifics of the GRASP/Component approach is in the direct retrieval of aerosol speciation (component fraction) without intermediate retrievals of aerosol optical characteristics. Although a global validation of the derived aerosol component product is challenging, the results obtained are in line with general knowledge about aerosol types in different regions. In addition, we compare the GRASP-derived black carbon (BC) and dust components with those of the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) product. Quite a reasonable general agreement was found between the spatial and temporal distribution of the species provided by GRASP and MERRA-2. The differences, however, appeared in regions known for strong biomass burning and dust emissions; the reasons for the discrepancies are discussed. The other derived components, such as concentrations of absorbing (BC, brown carbon (BrC), iron-oxide content in mineral dust) and scattering (ammonium sulfate and nitrate, organic carbon, non-absorbing dust) aerosols, represent scarce but imperative information for validation and potential adjustment of chemical transport models. The aerosol optical properties (e.g., aerosol optical depth (AOD), Ångström exponent (AE), single-scattering albedo (SSA), fine- and coarse-mode aerosol optical depth (AODF AND AODC)) derived from GRASP/Component were found to agree well with the Aerosol Robotic Network (AERONET) ground reference data, and were fully consistent with the previous GRASP Optimized, High Precision (HP) and Models retrieval versions applied to POLDER-3 data. Thus, the presented extensive climatology product provides an opportunity for understanding variabilities and trends in global and regional distributions of aerosol species. The climatology of the aerosol components obtained in addition to the aerosol optical properties provides additional valuable, qualitatively new insight about aerosol distributions and, therefore, demonstrates advantages of multi-angular polarimetric (MAP) satellite observations as the next frontier for aerosol inversion from advanced satellite observations. The extensive satellite-based aerosol component dataset is expected to be useful for improving global aerosol emissions and component-resolved radiative forcing estimations. The GRASP/Component products are publicly available (https://www.grasp-open.com/products/, last access: 15 March 2022) and the dataset used in the current study is registered under https://doi.org/10.5281/zenodo.6395384 (Li et al., 2022b).

Biomass burning emissions often contain brown carbon (BrC), which represents a large family of light-absorbing organics that are chemically complex, thus making it difficult to estimate their absorption of incoming solar radiation, resulting in large uncertainties in the estimation of the global direct radiative effect of aerosols. Here we investigate the contribution of BrC to the total light absorption of biomass burning aerosols over the South-East Atlantic Ocean with different optical models, utilizing a suite of airborne measurements from the ORACLES 2018 campaign. An effective refractive index of black carbon (BC), meBC=1.95+ikeBC, that characterizes the absorptivity of all absorbing components at 660 nm wavelength was introduced to facilitate the attribution of absorption at shorter wavelengths, i.e. 470 nm. Most values of the imaginary part of the effective refractive index, keBC, were larger than those commonly used for BC from biomass burning emissions, suggesting contributions from absorbers besides BC at 660 nm. The TEM-EDX single-particle analysis further suggests that these long-wavelength absorbers might include iron oxides, as iron is found to be present only when large values of keBC are derived. Using this effective BC refractive index, we find that the contribution of BrC to the total absorption at 470 nm (RBrC,470) ranges from ∼8 %–22 %, with the organic aerosol mass absorption coefficient (MACOA,470) at this wavelength ranging from 0.30±0.27 to 0.68±0.08 m2 g−1. The core–shell model yielded much higher estimates of MACOA,470 and RBrC,470 than homogeneous mixing models, underscoring the importance of model treatment. Absorption attribution using the Bruggeman mixing Mie model suggests a minor BrC contribution of 4 % at 530 nm, while its removal would triple the BrC contribution to the total absorption at 470 nm obtained using the AAE (absorption Ångström exponent) attribution method. Thus, it is recommended that the application of any optical properties-based attribution method use absorption coefficients at the longest possible wavelength to minimize the influence of BrC and to account for potential contributions from other absorbing materials.

Although a remarkable reduction in the frequency of sand and dust storms (SDSs) in the past several decades has been reported over northern China (NC), two unexpected mega SDSs occurred on 15–20 and 27–29 March 2021 (abbreviated as the “3.15” and “3.27” SDS events), which has reawakened widespread concern. This study characterizes the optical, microphysical, and radiative properties of aerosols and their meteorological drivers during these two SDS events using the Sun photometer observations in Beijing and a comprehensive set of multiple satellite (including MODIS, VIIRS, CALIOP, and Himawari-8) and ground-based observations (including the CMA visibility network and AD-Net) combined with atmospheric reanalysis data. Moreover, a long-term (2000–2021) dust optical depth (DOD) dataset retrieved from MODIS measurements was also utilized to evaluate the historical ranking of the dust loading in NC during dust events. During the 3.15 and 3.27 events, the invasion of dust plumes greatly degraded the visibility over large areas of NC, with extreme low visibility of 50 and 500 m recorded at most sites on 15 and 28 March, respectively. Despite the shorter duration of the 3.27 event relative to the 3.15 event, sun photometer and satellite observations in Beijing recorded a larger peak AOD (∼2.5) in the former than in the latter (∼2.0), which was mainly attributed to the short-term intrusion of coarse-mode dust particles with larger effective radii (∼1.9 µm) and volume concentrations (∼2.0 µm3 µm−2) during the 3.27 event. The shortwave direct aerosol radiative forcing induced by dust was estimated to be −92.1 and −111.4 W m−2 at the top of the atmosphere, −184.7 and −296.2 W m−2 at the surface, and +92.6 and +184.8 W m−2 in the atmosphere in Beijing during the 3.15 and 3.27 events, respectively. CALIOP observations show that during the 3.15 event the dust plume was lifted to an altitude of 4–8 km, and its range of impact extended from the dust source to the eastern coast of China. In contrast, the lifting height of the dust plume during the 3.27 event was lower than that during the 3.15 event, which was also confirmed by ground-based lidar observations. The MODIS-retrieved DOD data registered these two massive SDS events as the most intense episode in the same period in history over the past 2 decades. These two extreme SDS events were associated with both atmospheric circulation extremes and local meteorological anomalies that favored enhanced dust emissions in the Gobi Desert (GD) across southern Mongolia and NC. Meteorological analysis revealed that both SDS events were triggered by an exceptionally strong Mongolian cyclone generated at nearly the same location (along the central and eastern plateau of Inner Mongolia) in conjunction with a surface-level cold high-pressure system at the rear, albeit with differences in magnitude and spatial extent of impact. In the GD, the early melting of spring snow caused by near-surface temperature anomalies over dust source regions, together with negative soil moisture anomalies induced by decreased precipitation, formed drier and barer soil surfaces, which allowed for increased emissions of dust into the atmosphere by strongly enhanced surface winds generated by the Mongolian cyclone.

This research explores the application of Proportional-Integral-Derivative (PID) controllers and Variable Steering Ratio (VSR) control strategies within a Steer-by-Wire (SbW) system, utilizing a comprehensive 14 Degrees of Freedom (DOF) full vehicle dynamic model. The study aims to advance vehicle dynamics and control through SbW technology. This research addresses the challenge of optimizing steering control by integrating an SbW system with PID and VSR strategies to overcome the limitations of traditional steering mechanisms and enhance vehicle responsiveness and stability. The SbW system, using a PID-based controller, was rigorously tested and validated using MATLAB Simulink and Hardware-in-the-Loop System (HiLS) method. The performance of the system was assessed through four distinct signal tests: step, sine, square, and sawtooth inputs. These tests confirmed the precision of the PID controller in position tracking. To improve the practical applicability of the SbW system, a 14-DOF vehicle dynamic model was developed and validated before integration with the SbW system. The integrated system accurately replicated conventional steering behavior, as validated by Step Steer Input (SSI) and Double Lane Change (DLC) tests, demonstrating less than 11% RMS percentage error - well within the acceptable threshold of less than 15%. Additionally, the study proposed and validated VSR control strategies through the DLC test. Results indicate that the PID controller effectively tracked desired signals, while the VSR strategy reduced driver workload and improved steering stability. This research offers valuable insights into enhancing SbW system performance and lays a foundation for future advancements in vehicle control systems. [ABSTRACT FROM AUTHOR]

This research delves into how Model Reference Adaptive Control (MRAC) can be applied in an independent Steer-by-Wire (SBW) system, utilising a detailed 14 Degrees of Freedom (DOF) full-vehicle model. This study is all about pushing forward vehicle dynamics and control using SBW technology. This study also has come up with some cutting-edge control algorithms that allow each wheel to be steered independently, which seriously boosts how manoeuvrable and responsive the vehicle is. Through simulations, the study shows that MRAC is a big improvement over traditional control methods where quantitative analysis shows that MRAC reduces yaw rate errors by up to 66.67% compared to Proportional-Integral-Derivative (PID) and 50% compared to Multi-order PID (MOPID). Additionally, in lateral acceleration and sideslip angle controls, MRAC demonstrates a similar reduction in errors, significantly outperforming PID and MOPID with errors maintained well below 10%, proving its worth in predictive control and real-time adaptability to various road conditions and driver intentions. The key finding from this study is that MRAC greatly enhances manoeuvrability and responsiveness compared to standard methods which offer flexibility according to the different driving scenarios. There are notable advancements in vehicle steering systems, which contribute to safer and more efficient driving. In essence, this work marks a significant step forward in automotive steering technology, opening the door to safer and more efficient modern vehicles. [ABSTRACT FROM AUTHOR]

To investigate how magnetic reconnection (MR) accelerates electrons to a power-law energy spectrum in solar flares, we explore the scaling of a kinetic model proposed by Che & Zank (CZ) and compare it to observations. Focusing on thin current sheet MR particle-in-cell (PIC) simulations, we analyze the impact of domain size on the evolution of the electron Kelvin–Helmholtz instability (EKHI). We find that the duration of the growth stage of the EKHI ( ${t}_{G}\sim {{\rm{\Omega }}}_{e}^{-1}$ ) is short and remains nearly unchanged because the electron gyrofrequency Ω _e is independent of domain size. The quasi-steady stage of the EKHI ( t _MR ) dominates the electron acceleration process and scales linearly with the size of the simulations as L / v _A0 , where v _A0 is the Alfvén speed. We use the analytical results obtained by CZ to calculate the continuous temporal evolution of the electron energy spectra from PIC simulations and linearly scale them to solar flare observational scales. For the first time, an electron acceleration model predicts the sharp two-stage transition observed in typical soft–hard–harder electron energy spectra, implying that the electron acceleration model must be efficient with an acceleration timescale that is a small fraction of the duration of solar flares. Our results suggest that we can use PIC MR simulations to investigate the observational electron energy spectral evolution of solar flares if the ratio t _MR / t _G is sufficiently small, i.e., ≲10%.

An evaluation of aerosol microphysical, optical and radiative properties measured with a multiwavelength photometer named CW193 was performed in this study. The instrument has a highly integrated design, smart control performance and is composed of three parts (the optical head, robotic drive platform and stents system). Based on synchronous measurements, the CW193 products were validated using reference data from the AERONET CE318 photometer. The results show that the raw digital counts from CW193 agree well with the counts from AERONET (R>0.989), with daily average triplets of around 1.2 % to 3.0 % for the ultraviolet band and less than 2.0 % for the visible and infrared bands. Good aerosol optical depth agreement (R>0.997, 100 % within expected error) and root mean square error (RMSE) values ranging from 0.006 (for the 870 nm band) to 0.016 (for the 440 nm band) were obtained, with the relative mean bias (RMB) ranging from 0.922 to 1.112 and the aerosol optical depth bias within ±0.04. The maximum deviation of the peak value for fine-mode particles varied from about 8.9 % to 77.6 %, whereas the variation for coarse-mode particles was about 13.1 % to 29.1 %. The deviation variations of the single scattering albedo were approximately 0.1 %–1.8 %, 0.6 %–1.9 %, 0.1 %–2.6 % and 0.8 %–3.5 % for the 440, 675, 870 and 1020 nm bands, respectively. For the aerosol direct radiative forcing, deviations of approximately 4.8 %–12.3 % were obtained at the earth's surface and 5.4 %–15.9 % for the top of the atmosphere. In addition, the water vapor retrievals showed satisfactory accuracy, characterized by a high R value (∼0.997), a small RMSE (∼0.020) and a good expected error distribution (100 % within expected error). The water vapor RMB was about 0.979, and the biases mostly varied within ±0.04, whereas the mean values were concentrated within ±0.02.

Under intense industry competition, decision makers must ensure that products demanded by consumers can be quickly produced with minimum production cost. However, because uncertainties are unavoidable and inevitably affect decision makers, numerous studies have discussed how to control uncertainties or minimize their effects. Multiple uncertainties that interact simultaneously may cause a combined effect in actual systems. Therefore, this study presents a robust optimization model with two uncertainties, extending the method of robust optimization with one uncertainty. To demonstrate the applicability of the proposed model with two uncertainties, this study uses the supplier selection problem with component purchase quantity allocation in supply chain management as an analysis case. This considers the reliability of production and transportation and develops a multi-objective robust optimization model with two uncertainties. In addition, a nondominated sorting genetic algorithm is proposed for solving the proposed multi-objective robust optimization model. The relationship between price of robustness and budget parameters is explored by considering the robust optimization model with production and transportation uncertainties proposed in this study. Finally, there is a comparative analysis between the results for price of robustness in the proposed two-uncertainty model and in the one-uncertainty model. First published online 15 December 2022

Globally gridded aerosol extinction data from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) during 2007–2019 are utilized to investigate the three-dimensional (3D) climatological distribution of tropospheric type-dependent aerosols and to identify the trends in column aerosol optical depth (AOD), partitioned within different altitude regimes, and their meteorological drivers. Using detection samples of layer aerosols, we also yield a 3D distribution of the frequency of occurrence (FoO) of aerosol subtypes classified by CALIOP. The results show that the aerosol extinction coefficient (AEC) shows contrasting vertical distribution patterns over land and ocean, with the former possessing significant geographical dependence, while the enhancement of AEC in the latter is mainly located below 1 km. The vertical structures of the type-dependent AECs, however, are strongly dependent on altitude. When the total AOD (TAOD) is partitioned into the planetary boundary layer (PBL) and the free troposphere (FT), results demonstrate that the PBL and FT contribute 62.08 % and 37.92 %, respectively, of the global tropospheric TAOD averaged over daytime and nighttime. Yet this CALIOP-based partitioning of the different aerosol subtypes in the PBL and FT varies significantly. Among all 12 typical regions of interest analyzed, more than 50 % of TAOD is located in the lower troposphere (0–2 km), while the contribution is less than 2 % above 6 km. In global average terms, we found the aerosol FoO averaged over all layers is 4.45 %, with the largest contribution from “clean marine” (1.79 %) and the smallest from “clean continental” (0.05 %). Overall, the FoO vertical structures of the aerosol layer exhibit a distribution pattern similar to that of AEC. The resulting trend analyses show that CALIOP accurately captures significant regional anomalies in TAOD, as observed in other satellite measurements and aerosol reanalysis. Our correlation analysis between meteorological factors and TAOD suggests the interannual variability of TAOD is related to the variability of precipitation (PPT), volumetric soil moisture (VSM), and wind speed (WS) in the particular regions. For instance, the positive TAOD trend over the equatorial central Pacific is mainly attributable to the increased PPT and decreased WS. In contrast, in dry convective regions dominated by dust and smoke, the interannual variability/trend in TAOD is largely modified by the VSM driven by the PPT. Additionally, we further found that these significant regional correlations are more robust within the PBL and significantly weakened or even reversed within the FT. This highlights the superiority of using the TAOD partitioned within the PBL as a proxy variable for the widely applied TAOD to explore the relationships between atmospheric pollution and meteorology.

The study was carried out to evaluate the impact of seasonal variations on the hematological responses of goats in Malaysia. Fifty-two goats (24 bucks and 28 does), aged between 1 to 2 years old were used in the study. The goats were fed on commercial concentrate and forage, access to mineral salt and water was ad libitum. Blood samples were obtained from each goat in January, May and September to analyze hematology blood constitute during the study. The results showed that red blood cell (RBC) levels in Anglo-Nubian females rose dramatically in January and May while the Saanen breed remains without diversity. In all seasons, high hemoglobin (Hb) concentration of Anglo-Nubian males was unlike Saanen breed. For Saanen females, mean corpuscular volume (MCV) increased significant-ly, whereas in Saanen males, mean corpuscular hemoglobin (MCH) and MCH concentration (MCHC) were increased. High packed cell volume (PCV) concentration of Anglo females compared to others during September. In conclusion, variations in breed and sex of goats reflect the distinct ability of trop-ical changes that have been formed during seasonal effects on hematological responses between the two breeds of goats.

The contribution of meteorology and emissions to long-term PM2.5 trends is critical for air quality management but has not yet been fully analyzed. Here, we used the combination of a machine learning model, statistical method, and chemical transport model to quantify the meteorological impacts on PM2.5 pollution during 2000–2018. Specifically, we first developed a two-stage machine learning PM2.5 prediction model with a synthetic minority oversampling technique to improve the satellite-based PM2.5 estimates over highly polluted days, thus allowing us to better characterize the meteorological effects on haze events. Then we used two methods to examine the meteorological contribution to PM2.5: a generalized additive model (GAM) driven by the satellite-based full-coverage daily PM2.5 retrievals and the Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) modeling system. We found good agreements between GAM estimations and the CMAQ model estimations of the meteorological contribution to PM2.5 on a monthly scale (correlation coefficient between 0.53–0.72). Both methods revealed the dominant role of emission changes in the long-term trend of PM2.5 concentration in China during 2000–2018, with notable influence from the meteorological condition. The interannual variabilities in meteorology-associated PM2.5 were dominated by the fall and winter meteorological conditions, when regional stagnant and stable conditions were more likely to happen and when haze events frequently occurred. From 2000 to 2018, the meteorological contribution became more unfavorable to PM2.5 pollution across the North China Plain and central China but were more beneficial to pollution control across the southern part, e.g., the Yangtze River Delta. The meteorology-adjusted PM2.5 over eastern China (denoted East China in figures) peaked in 2006 and 2011, mainly driven by the emission peaks in primary PM2.5 and gas precursors in these years. Although emissions dominated the long-term PM2.5 trends, the meteorology-driven anomalies also contributed −3.9 % to 2.8 % of the annual mean PM2.5 concentrations in eastern China estimated from the GAM. The meteorological contributions were even higher regionally, e.g., −6.3 % to 4.9 % of the annual mean PM2.5 concentrations in the Beijing-Tianjin-Hebei region, −5.1 % to 4.3 % in the Fenwei Plain, −4.8 % to 4.3 % in the Yangtze River Delta, and −25.6 % to 12.3 % in the Pearl River Delta. Considering the remarkable meteorological effects on PM2.5 and the possible worsening trend of meteorological conditions in the northern part of China where air pollution is severe and population is clustered, stricter clean air actions are needed to avoid haze events in the future.

Studies on self-driving vehicles have become a trend in recent years, and many systems have been developed to enable autonomous manoeuvre. Various methods have been used to improve path-tracking algorithms which increase vehicle performance, including tracking accuracy and stability. Path tracking is one of the primary problems for autonomous vehicles where the vehicle deviates from target paths, which leads to unnecessary counter-correction. Conventional front wheel steering is unable to satisfy the manoeuvre with a high lateral acceleration since the front steering angle is limited in accurately responding to vehicle dynamics. Moreover, the characteristics of front wheel steering vehicles affect handling stability due to the fact that the turning radius is larger than the vehicle itself. This disadvantageous can compromise safety during understeer and over-steer situations. The main objective of this preliminary study is to investigate the performance of a four-wheel steering system (4WS) in path tracking for autonomous vehicles using a classical model predictive controller (MPC). Conventional two-wheel steering (2WS) tracking performance following the desired driving system with the same MPC controller is compared with 4WS vehicles. The driving system is developed using Driving Scenario Designer to extract the desired yaw angle and lateral position for controller references constructed in Matlab Simulink. Fixed MPC constraint, prediction, control horizon, yaw angle and lateral position weights were used to compare the performance between 2WS and 4WS vehicles. The simulation results show that 4WS is three times better than 2WS vehicles in tracking predetermined paths. 4WS vehicle show 74.55% better performance in lateral position tracking and 68.75% better performance in trailing predetermined yaw angle value. The simulation data from the preliminary study will be used as a guideline to develop an advanced controller of 4WS vehicles. [ABSTRACT FROM AUTHOR]

The development of chemical transport models with advanced physics and chemical schemes could improve air-quality forecasts. In this study, the China Meteorological Administration Unified Atmospheric Chemistry Environment (CUACE) model, a comprehensive chemistry module incorporating gaseous chemistry and a size-segregated multicomponent aerosol algorithm, was coupled to the Weather Research and Forecasting (WRF) framework with chemistry (WRF-Chem) using an interface procedure to build the WRF/CUACE v1.0 model. The latest version of CUACE includes an updated aerosol dry deposition scheme and the introduction of heterogeneous chemical reactions on aerosol surfaces. We evaluated the WRF/CUACE v1.0 model by simulating PM2.5, O3, NO2, and SO2 concentrations for January, April, July, and October (representing winter, spring, summer and autumn, respectively) in 2013, 2015, and 2017 and comparing them with ground-based observations. Secondary inorganic aerosol simulations for the North China Plain (NCP), Yangtze River Delta (YRD), and Sichuan Basin (SCB) were also evaluated. The model captured well the variations of PM2.5, O3, and NO2 concentrations in all seasons in eastern China. However, it is difficult to accurately reproduce the variations of air pollutants over SCB, due to its deep basin terrain. The simulations of SO2 were generally reasonable in the NCP and YRD with the bias at −15.5 % and 24.55 %, respectively, while they were poor in the Pearl River Delta (PRD) and SCB. The sulfate and nitrate simulations were substantially improved by introducing heterogeneous chemical reactions into the CUACE model (e.g., change in bias from −95.0 % to 4.1 % for sulfate and from 124.1 % to 96.0 % for nitrate in the NCP). Additionally, The WRF/CUACE v1.0 model was revealed with better performance in simulating chemical species relative to the coupled Fifth-Generation Penn State/NCAR Mesoscale Model (MM5) and CUACE model. The development of the WRF/CUACE v1.0 model represents an important step towards improving air-quality modeling and forecasts in China.

The representations of clouds, aerosols, and cloud–aerosol–radiation impacts remain some of the largest uncertainties in climate change, limiting our ability to accurately reconstruct past climate and predict future climate. The south-east Atlantic is a region where high atmospheric aerosol loadings and semi-permanent stratocumulus clouds are co-located, providing an optimum region for studying the full range of aerosol–radiation and aerosol–cloud interactions and their perturbations of the Earth's radiation budget. While satellite measurements have provided some useful insights into aerosol–radiation and aerosol–cloud interactions over the region, these observations do not have the spatial and temporal resolution, nor the required level of precision to allow for a process-level assessment. Detailed measurements from high spatial and temporal resolution airborne atmospheric measurements in the region are very sparse, limiting their use in assessing the performance of aerosol modelling in numerical weather prediction and climate models. CLARIFY-2017 was a major consortium programme consisting of five principal UK universities with project partners from the UK Met Office and European- and USA-based universities and research centres involved in the complementary ORACLES, LASIC, and AEROCLO-sA projects. The aims of CLARIFY-2017 were fourfold: (1) to improve the representation and reduce uncertainty in model estimates of the direct, semi-direct, and indirect radiative effect of absorbing biomass burning aerosols; (2) to improve our knowledge and representation of the processes determining stratocumulus cloud microphysical and radiative properties and their transition to cumulus regimes; (3) to challenge, validate, and improve satellite retrievals of cloud and aerosol properties and their radiative impacts; (4) to improve the impacts of aerosols in weather and climate numerical models. This paper describes the modelling and measurement strategies central to the CLARIFY-2017 deployment of the FAAM BAe146 instrumented aircraft campaign, summarizes the flight objectives and flight patterns, and highlights some key results from our initial analyses.

The south-eastern Atlantic Ocean (SEA) is semi-permanently covered by one of the most extensive stratocumulus cloud decks on the planet and experiences about one-third of the global biomass burning emissions from the southern Africa savannah region during the fire season. To get a better understanding of the impact of these biomass burning aerosols on clouds and the radiation balance over the SEA, the latest generation of the UK Earth System Model (UKESM1) is employed. Measurements from the CLARIFY and ORACLES flight campaigns are used to evaluate the model, demonstrating that the model has good skill in reproducing the biomass burning plume. To investigate the underlying mechanisms in detail, the effects of biomass burning aerosols on the clouds are decomposed into radiative effects (via absorption and scattering) and microphysical effects (via perturbation of cloud condensation nuclei – CCN – and cloud microphysical processes). July–August means are used to characterize aerosols, clouds, and the radiation balance during the fire season. Results show that around 65 % of CCN at 0.2 % supersaturation in the SEA can be attributed to biomass burning. The absorption effect of biomass burning aerosols is the most significant on clouds and radiation. Near the continent, it increases the supersaturation diagnosed by the activation scheme, while further from the continent it reduces the altitude of the supersaturation. As a result, the cloud droplet number concentration responds with a similar pattern to the absorption effect of biomass burning aerosols. The microphysical effect, however, decreases the supersaturation and increases the cloud droplet concentration over the ocean, although this change is relatively small. The liquid water path is also significantly increased over the SEA (mainly caused by the absorption effect of biomass burning aerosols) when biomass burning aerosols are above the stratocumulus cloud deck. The microphysical pathways lead to a slight increase in the liquid water path over the ocean. These changes in cloud properties indicate the significant role of biomass burning aerosols for clouds in this region. Among the effects of biomass burning aerosols on the radiation balance, the semi-direct radiative effects (rapid adjustments induced by the radiative effects of biomass burning aerosols) have a dominant cooling impact over the SEA, which offset the warming direct radiative effect (radiative forcing from biomass burning aerosol–radiation interactions) and lead to an overall net cooling radiative effect in the SEA. However, the magnitude and the sign of the semi-direct effects are sensitive to the relative location of biomass burning aerosols and clouds, reflecting the critical task of the accurate modelling of the biomass burning plume and clouds in this region.

Previous observational evidence and numerical simulations have revealed that the surface sensible heating in spring (March–April–May, MAM) over the Tibetan Plateau (TPSH) can affect the Asian regional hydrological cycle, surface energy balance, and climate through altering atmospheric heat source of the Tibetan Plateau (TP). This study aims to investigate the impacts of MAM TPSH on the interannual variability of East Asian dust cycle by using CAM4-BAM (version 4 of the Community Atmosphere Model coupled to a bulk aerosol model), MERRA-2 (version 2 of the Modern-Era Retrospective analysis for Research and Applications) surface dust concentration, and TPSH measurements. Our simulations show that the surface dust concentrations over the East Asian (EA) dust source region and over the northwestern Pacific (NP) in MAM are significantly positively correlated with TPSH, with regionally averaged correlation coefficients of 0.49 for EA and 0.44 for NP. Similar positive correlations are also shown between the MAM TPSH measurements averaged over the 73 observation sites and the surface dust concentration from MERRA-2. Simulation-based comparisons between strongest and weakest TPSH years reveal that, the MAM surface dust concentration in the strongest TPSH years increases with relative differences of 13.1 % over EA and 36.9 % over NP. These corresponding differences are found in MERRA-2 with 22.9 % and 13.3 % over EA and NP, respectively. Further simulated results show that the processes of whole dust cycles (e.g., dust loading, emission, and transport, as well as dust deposition) are also significantly enhanced during the strongest TPSH years over EA and NP. Through enhancing the TP heat source, stronger TPSH in MAM generates an anticyclonic anomaly in middle and upper troposphere over the TP and over the downstream Pacific region, respectively. These atmospheric circulation anomalies induced by the increased TPSH result in increasing the westerly winds over both EA and NP, which in turn increases dust emissions over the dust source, and dust transport over these two regions, as well as the regional dust cycles. These results suggest that addressing the East Asian dust changes in the future climates requires considering not only increasing greenhouse gas emissions but also the variations of the TP's heat source under global warming.

This paper is an overview of the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. A formula was proposed for estimating the accuracy of the sky radiometer calibration constant F0 using the improved Langley (IL) method, which was found to be a good approximation to observed monthly mean uncertainty in F0, around 0.5 % to 2.4 % at the Tokyo and Rome sites and smaller values of around 0.3 % to 0.5 % at the mountain sites at Mt. Saraswati and Davos. A new cross IL (XIL) method was also developed to correct an underestimation by the IL method in cases with large aerosol retrieval errors. The root-mean-square difference (RMSD) in aerosol optical thickness (AOT) comparisons with other networks took values of less than 0.02 for λ≥500 nm and a larger value of about 0.03 for shorter wavelengths in city areas and smaller values of less than 0.01 in mountain comparisons. Accuracies of single-scattering albedo (SSA) and size distribution retrievals are affected by the propagation of errors in measurement, calibrations for direct solar and diffuse sky radiation, ground albedo, cloud screening, and the version of the analysis software called the Skyrad pack. SSA values from SKYNET were up to 0.07 larger than those from AERONET, and the major error sources were identified as an underestimation of solid viewing angle (SVA) and cloud contamination. Correction of these known error factors reduced the SSA difference to less than 0.03. Retrievals of other atmospheric constituents by the sky radiometer were also reviewed. Retrieval accuracies were found to be about 0.2 cm for precipitable water vapor amount and 13 DU (Dobson Unit) for column ozone amount. Retrieved cloud optical properties still showed large deviations from validation data, suggesting a need to study the causes of the differences. It is important that these recent studies on improvements presented in the present paper are introduced into the existing operational systems and future systems of the International SKYNET Data Center.

Rapid urbanization and industrialization have led to deterioration of air quality in the Beijing–Tianjin–Hebei (BTH) region due to high loadings of PM2.5. Heavy aerosol pollution frequently occurs in winter, in close relation to the planetary boundary layer (PBL) meteorology. To unravel the physical processes that influence PBL structure and aerosol pollution in BTH, this study combined long-term observational data analyses, synoptic pattern classification, and meteorology–chemistry coupled simulations. During the winter of 2017 and 2018, Beijing and Tangshan often experienced heavy PM2.5 pollution simultaneously, accompanied by strong thermal inversion aloft. These concurrences of pollution in different cities were primarily regulated by the large-scale synoptic conditions. Using principal component analysis with geopotential height fields at the 850 hPa level during winter, two typical synoptic patterns associated with heavy pollution in BTH were identified. One pattern is characterized by a southeast-to-north pressure gradient across BTH, and the other is associated with high pressure in eastern China. Both synoptic types feature warmer air temperature at 1000 m a.g.l., which could suppress the development of the PBL. Under these unfavorable synoptic conditions, aerosols can modulate PBL structure through the radiative effect, which was examined using numerical simulations. The aerosol radiative effect can significantly lower the daytime boundary layer height through cooling the surface layer and heating the upper part of the PBL, leading to the deterioration of air quality. This PBL–aerosol feedback is sensitive to the aerosol vertical structure, which is more effective when the synoptic pattern can distribute more aerosols to the upper PBL.

This study analyzed the aerosol optical properties derived by SKYRAD.pack versions 5.0 and 4.2 (referred to as V5.0 and V4.2) using the radiometer measurements over Qionghai and Yucheng in China, two new sites of the sky radiometer network (SKYNET). As V5.0 uses an a priori size distribution function (SDF) of a bimodal log-normal function, the volume size distribution retrieved by V5.0 presented bimodal patterns with a 0.1–0.2 µm fine particle mode and a 3.0–6.0 µm coarse particle mode both over Qionghai and Yucheng. The differences in the volume size distributions between the two versions were very large for the coarse mode with a radius of over 5 µm. The single scattering albedos (SSAs) by V5.0 correlated with SSAs by V4.2 with R=0.88, 0.87, 0.90, 0.88, and 0.92 at wavelengths of 400, 500, 670, 870, and 1020 nm over Qionghai, respectively. The correlation coefficients were around 0.95, 0.95, 0.96, 0.94, and 0.91 at the five channels in Yucheng. An error of ±5 % for the solid view angle (SVA) introduced about ±2 % differences in retrieved SSA values both by V4.2 and V5.0. An error of ±50 % for ground surface albedo (Ag) caused about 1 % averaged differences in retrieved SSA values by the two versions. With the atmospheric pressure (PRS) increased by 1 %, 2 %, 3 %, and 4 %, the averaged changes in SSAs did not exceed 0.8 % both by V4.2 and V5.0. The SSA differences at 500 nm between the two versions decreased, while aerosol optical depths (AODs) increased over both sites. The seasonal variability of the aerosol properties over Qionghai and Yucheng was investigated based on SKYRAD.pack V5.0. The seasonal averaged AOD over Qionghai had higher values in spring, winter, and autumn and lower values in summer. The AOD averages were commonly higher in summer and spring than in winter and autumn in Yucheng. The lowest seasonal averaged SSAs were both observed in winter at the two sites. The fraction of the fine aerosol particles was much smaller in summer than in other seasons over Qionghai; the volume fraction of the coarse-mode particle in Yucheng had much larger values compared to the fine-mode particle in all seasons. The validation results provide valuable references for continued improvement of the retrieval algorithms of SKYNET and other aerosol observational networks.

This study explores the opinions of Malaysian clinical specialists on the antibiotic prophylaxis against infective endocarditis (IE) as described in the 2008 National Institute for Health and Care Excellence (NICE) guideline. This cross-sectional study was performed from September 2017 to March 2019. The self-administered questionnaire comprised two sections: background information of the specialists and their opinions on the NICE guideline. The questionnaire was distributed to 794 potential participants, and 277 responded (response rate of 34.9%). In general, 49.8% of the respondents believed that clinicians should adhere to the guideline, although the majority of oral and maxillofacial surgeons (54.5%) actually disagreed with this view. The dental procedures that were perceived as presented moderate-to-high risk for IE were minor surgery for an impacted tooth with a recent episode of infection, dental implant surgery, periodontal surgery and dental extraction in patients with poor oral hygiene. The cardiac conditions that were strongly recommended for antibiotic prophylaxis were severe mitral valve stenosis or regurgitation and previous IE. Less than half of Malaysian clinical specialists agreed with the changes in the 2008 NICE guideline, contributing to their insistence that antibiotic prophylaxis is still needed for high-risk cardiac conditions and selected invasive dental procedures.

Public safety-related problems exist in all countries, causing the public to fear for their personal safety and that of their property. Maintaining public safety, providing citizens with safe living environments, and realizing sustainable social development are issues that concern not only the public but also local and central governments. Accordingly, this study proposed a measurement model that combines the analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to obtain public safety ratings. First, this study used the AHP to analyze the contributions of public safety-related criteria, and the relative weights of the criteria were calculated. Subsequently, TOPSIS was used to calculate the relative closeness coefficients between public safety performance and positive-ideal solutions to evaluate public safety performance. The measurement model proposed in this study was used to rate the public safety performance of 22 cities and counties in Taiwan. The results showed that the criterion weights matched the perceptions of the public, and Lienchiang County, Taitung County, and Penghu County had the best public safety performance. The applicability of the proposed measurement model has been confirmed using real-world data. Thus, it can be used to help decision-makers make complex public safety-related decisions.

Small-amplitude fluctuations in the magnetized solar wind are measured typically by a single spacecraft. In the magnetohydrodynamics (MHD) description, fluctuations are typically expressed in terms of the fundamental modes admitted by the system. An important question is how to resolve an observed set of fluctuations, typically plasma moments such as the density, velocity, pressure, and magnetic field fluctuations, into their constituent fundamental MHD modal components. Despite its importance in understanding the basic elements of waves and turbulence in the solar wind, this problem has not yet been fully resolved. Here, we introduce a new method that identifies between wave modes and advected structures such as magnetic islands or entropy modes and computes the phase information associated with the eligible MHD modes. The mode-decomposition method developed here identifies the admissible modes in an MHD plasma from a set of plasma and magnetic field fluctuations measured by a single spacecraft at a specific frequency and an inferred wavenumber k _m . We present data from three typical intervals measured by the Wind and Solar Orbiter spacecraft at ∼1 au and show how the new method identifies both propagating (wave) and nonpropagating (structures) modes, including entropy and magnetic island modes. This allows us to identify and characterize the separate MHD modes in an observed plasma parcel and to derive wavenumber spectra of entropic density, fast and slow magnetosonic, Alfvénic, and magnetic island fluctuations for the first time. These results help identify the fundamental building blocks of turbulence in the magnetized solar wind.

The long-term temporal–spatial variations in the aerosol optical properties over the Tibetan Plateau (TP) and the potential long-range transport from surrounding areas to the TP were analyzed in this work, by using multiple years of sun photometer measurements (CE318) at five stations in the TP, satellite aerosol products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), back-trajectory analysis from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) and model simulations from the Goddard Earth Observing System (GEOS)-Chem chemistry transport model. The results from the ground-based observations showed that the annual aerosol optical depth (AOD) at 440 nm at most TP sites increased in recent decades with trends of 0.001±0.003 yr−1 at Lhasa, 0.013±0.003 yr−1 at Mt_WLG, 0.002±0.002 yr−1 at NAM_CO and 0.000±0.002 yr−1 at QOMS_CAS. The increasing trend was also found for the aerosol extinction Ångström exponent (EAE) at most sites with the exception of the Mt_WLG site. Spatially, the AOD at 550 nm observed from MODIS showed negative trends at the northwest edge close to the Taklimakan Desert and to the east of the Qaidam Basin and slightly positive trends in most of the other areas of the TP. Different aerosol types and sources contributed to a polluted day (with CE318 AOD at 440 nm > 0.4) at the five sites on the TP: dust was the dominant aerosol type in Lhasa, Mt_WLG and Muztagh with sources in the Taklimakan Desert, but fine-aerosol pollution was dominant at NAM_CO and QOMS_CAS with transport from South Asia. A case of aerosol pollution at Lhasa, NAM_CO and QOMS_CAS during 28 April–3 May 2016 revealed that the smoke aerosols from South Asia were lifted up to 10 km and transported to the TP, while the dust from the Taklimakan Desert could climb the north slope of the TP and then be transported to the central TP. The long-range transport of aerosol thereby seriously impacted the aerosol loading over the TP.

This study presents a novel methodology for the remote monitoring of aerosol components over large spatial and temporal domains. The concept is realized within the GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm to directly infer aerosol components from the measured radiances. The observed aerosols are assumed to be mixtures of hydrated soluble particles embedded with black carbon, brown carbon, iron oxide, and other (non-absorbing) insoluble inclusions. The complex refractive indices of the dry components are fixed a priori (although the refractive index of the soluble host is allowed to vary with hydration), and the complex refractive indices of the mixture are computed using mixing rules. The volume fractions of these components are derived along with the size distribution and the fraction of spherical particles, as well as the spectral surface reflectance in cases when the satellite data are inverted. The retrieval is implemented as a statistically optimized fit in a continuous space of solutions. This contrasts with most conventional approaches in which the type of aerosol is either associated with a pre-assumed aerosol model that is included in a set of look-up tables, or determined from the analysis of the retrieved aerosol optical parameters (e.g., single scattering albedo, refractive index, among others, provided by the AERONET retrieval algorithm); here, we retrieve the aerosol components explicitly. The approach also bridges directly to the quantities used in global chemical transport models. We first tested the approach with synthetic data to estimate the uncertainty, and then applied it to real ground-based AERONET and spaceborne POLDER/PARASOL observations; thus, the study presents a first attempt to derive aerosol components from satellite observations specifically tied to global chemical transport model quantities. Our results indicate aerosol optical characteristics that are highly consistent with standard products (e.g., R of ∼0.9 for aerosol optical thickness) and demonstrate an ability to separate intrinsic optical properties of fine- and coarse-sized aerosols. We applied our method to POLDER/PARASOL radiances on the global scale and obtained spatial and temporal patterns of the aerosol components that agree well with existing knowledge on aerosol sources and transport features. Finally, we discuss limitations and perspectives of this new technique.

Land surface albedo plays an important role in climate change research. Satellite remote sensing has the characteristic of wide observation range, and it can make repeated observations on the same area. Therefore, using the remote sensing data to retrieve surface albedo becomes a main method to obtain the surface albedo in a wide range or even on a global scale. However, the time resolution of existing albedo products is usually low, which has a great impact on the analysis of rapid changes in surface vegetation and the climate change research. The Deep Space Climate Observatory (DSCOVR) was launched to a sun-earth first Lagrange point (L1) orbit, which is a new and unique vantage point to observe the continuously full, sunlit disk of Earth. DSCOVR can provide observation data with high time resolution, therefore, it is necessary to explore the feasibility of the new sensor DSCOVR/EPIC inversion of the daily albedo product. The relationship between the surface broadband albedo and the surface reflectance was established, and then the surface albedo with high temporal resolution was calculated using the DSCOVR/EPIC data. The Inner Mongolia Autonomous Region and parts of the Sahara Desert were selected to verify the accuracy of DSCOVR albedo compared with MODIS albedo. The results show that the correlation coefficients between DSCOVR albedo and MODIS albedo are greater than 0.7 and RMSE are less than 0.05 both in visible band and shortwave band. It can be seen that this method can be used for the albedo retrieval using DSCOVR/EPIC data.

Aerosols play an important role in climate changes and environmental changes as well as on human health. ADV v3.11, ORAC v4.10, and SU v4.32 was three new versions of Advanced Along-Track Scanning Radiometer (AATSR) aerosol datasets which are published on Climate Change Initiative (CCI). In order to evaluate the accuracy of three AATSR aerosol optical depth (AOD) datasets, and to improve the spatial coverage and accuracy of AATSR AOD dataset, this study completed two works: the first part is validated the accuracy of three AOD datasets; the second part is fused three AATSR AOD datasets based on uncertainty of each dataset. After comparing with AERONET and CARSNET ground-based data over China, results show that the root-mean-square error (RMSE) for ADV v3.11, ORAC v4.10, SU v4.32 and fused AOD are 0.22, 0.17, 0.18, 0.17 respectively.

Facility Management (FM) has becoming a crucial aspect in providing better service to the client/tenant or public as well as to minimize the maintenance cost. Group of buildings bounded by a defined boundary/spatial space such as a college, university, city or even a country have to manage their assets and space systematically with maximum potential/usage and minimum maintenance cost. Incorporating GIS plays innovative and effective role in asset and space FM especially. There are a lot of research and suggestions for it, but implementation is still average and quite new in Malaysia. University Kebangsaan Malaysia (UKM Bangi) has taken initiative to perform such idea with a full scale implementation. Currently, UKM utilizes GIS in nine modules, where one of the main module called SEPADU, an internal use module system for asset and space information system. This paper describes the implementation of integrated GIS solution in information system. Spatial data acquisition, database development and system for FM will be discussed in this paper.

Multi-year observations of aerosol microphysical and optical properties, obtained through ground-based remote sensing at 50 China Aerosol Remote Sensing Network (CARSNET) sites, were used to characterize the aerosol climatology for representative remote, rural, and urban areas over China to assess effects on climate. The annual mean effective radii for total particles (ReffT) decreased from north to south and from rural to urban sites, and high total particle volumes were found at the urban sites. The aerosol optical depth at 440 nm (AOD440 nm) increased from remote and rural sites (0.12) to urban sites (0.79), and the extinction Ångström exponent (EAE440–870 nm) increased from 0.71 at the arid and semi-arid sites to 1.15 at the urban sites, presumably due to anthropogenic emissions. Single-scattering albedo (SSA440 nm) ranged from 0.88 to 0.92, indicating slightly to strongly absorbing aerosols. Absorption AOD440 nm values were 0.01 at the remote sites versus 0.07 at the urban sites. The average direct aerosol radiative effect (DARE) at the bottom of atmosphere increased from the sites in the remote areas (−24.40 W m−2) to the urban areas (−103.28 W m−2), indicating increased cooling at the latter. The DARE for the top of the atmosphere increased from −4.79 W m−2 at the remote sites to −30.05 W m−2 at the urban sites, indicating overall cooling effects for the Earth–atmosphere system. A classification method based on SSA440 nm, fine-mode fraction (FMF), and EAE440–870 nm showed that coarse-mode particles (mainly dust) were dominant at the rural sites near the northwestern deserts, while light-absorbing, fine-mode particles were important at most urban sites. This study will be important for understanding aerosol climate effects and regional environmental pollution, and the results will provide useful information for satellite validation and the improvement of climate modelling.

Aerosol optical depth (AOD) has become a crucial metric for assessing global climate change. Although global and regional AOD trends have been studied extensively, it remains unclear what factors are driving the inter-decadal variations in regional AOD and how to quantify the relative contribution of each dominant factor. This study used a long-term (1980–2016) aerosol dataset from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis, along with two satellite-based AOD datasets (MODIS/Terra and MISR) from 2001 to 2016, to investigate the long-term trends in global and regional aerosol loading. Statistical models based on emission factors and meteorological parameters were developed to identify the main factors driving the inter-decadal changes of regional AOD and to quantify their contribution. Evaluation of the MERRA-2 AOD with the ground-based measurements of AERONET indicated significant spatial agreement on the global scale (r= 0.85, root-mean-square error = 0.12, mean fractional error = 38.7 %, fractional gross error = 9.86 % and index of agreement = 0.94). However, when AOD observations from the China Aerosol Remote Sensing Network (CARSNET) were employed for independent verification, the results showed that MERRA-2 AODs generally underestimated CARSNET AODs in China (relative mean bias = 0.72 and fractional gross error =-34.3 %). In general, MERRA-2 was able to quantitatively reproduce the annual and seasonal AOD trends on both regional and global scales, as observed by MODIS/Terra, although some differences were found when compared to MISR. Over the 37-year period in this study, significant decreasing trends were observed over Europe and the eastern United States. In contrast, eastern China and southern Asia showed AOD increases, but the increasing trend of the former reversed sharply in the most recent decade. The statistical analyses suggested that the meteorological parameters explained a larger proportion of the AOD variability (20.4 %–72.8 %) over almost all regions of interest (ROIs) during 1980–2014 when compared with emission factors (0 %–56 %). Further analysis also showed that SO2 was the dominant emission factor, explaining 12.7 %–32.6 % of the variation in AOD over anthropogenic-aerosol-dominant regions, while black carbon or organic carbon was the leading factor over the biomass-burning-dominant (BBD) regions, contributing 24.0 %–27.7 % of the variation. Additionally, wind speed was found to be the leading meteorological parameter, explaining 11.8 %–30.3 % of the variance over the mineral-dust-dominant regions, while ambient humidity (including soil moisture and relative humidity) was the top meteorological parameter over the BBD regions, accounting for 11.7 %–35.5 % of the variation. The results of this study indicate that the variation in meteorological parameters is a key factor in determining the inter-decadal change in regional AOD.

Satellites provide information on the temporal and spatial distributions of aerosols on regional and global scales. With the same method applied to a single sensor all over the world, a consistent data set is to be expected. However, the application of different retrieval algorithms to the same sensor and the use of a series of different sensors may lead to substantial differences, and no single sensor or algorithm is better than any other everywhere and at all times. For the production of long-term climate data records, the use of multiple sensors cannot be avoided. The Along Track Scanning Radiometer (ATSR-2) and the Advanced ATSR (AATSR) aerosol optical depth (AOD) data sets have been used to provide a global AOD data record over land and ocean of 17 years (1995–2012), which is planned to be extended with AOD retrieved from a similar sensor. To investigate the possibility of extending the ATSR data record to earlier years, the use of an AOD data set from the Advanced Very High Resolution Radiometer (AVHRR) is investigated. AOD data sets used in this study were retrieved from the ATSR sensors using the ATSR Dual View algorithm ADV version 2.31, developed by Finnish Meteorological Institute (FMI), and from the AVHRR sensors using the aerosol optical depth over land (ADL) algorithm developed by RADI/CAS. Together, these data sets cover a multi-decadal period (1987–2012). The study area includes two contrasting areas, both in regards to aerosol content and composition and surface properties, i.e. a region over north-eastern China, encompassing a highly populated urban/industrialized area (Beijing–Tianjin–Hebei) and a sparsely populated mountainous area. Ground-based AOD observations available from ground-based sun photometer AOD data in AERONET and CARSNET are used as a reference, together with broadband extinction method (BEM) data at Beijing to cover the time before sun photometer observations became available in the early 2000s. In addition, MODIS-Terra C6.1 AOD data are used as a reference data set over the wide area where no ground-based data are available. All satellite data over the study area were validated against the reference data, showing the qualification of MODIS for comparison with ATSR and AVHRR. The comparison with MODIS shows that AVHRR performs better than ATSR in the north of the study area (40∘ N), whereas further south ATSR provides better results. The validation against sun photometer AOD shows that both AVHRR and ATSR underestimate the AOD, with ATSR failing to provide reliable results in the wintertime. This is likely due to the highly reflecting surface in the dry season, when AVHRR-retrieved AOD traces both MODIS and reference AOD data well. However, AVHRR does not provide AOD larger than about 0.6 and hence is not reliable when high AOD values have been observed over the last decade. In these cases, ATSR performs much better for AOD up to about 1.3. AVHRR-retrieved AOD compares favourably with BEM AOD, except for AOD higher than about 0.6. These comparisons lead to the conclusion that AVHRR and ATSR AOD data records each have their strengths and weaknesses that need to be accounted for when combining them in a single multi-decadal climate data record.

This paper presents a new statistical-based method of cutting tool wear progression in a milling process called Z-rotation method in association with tool wear progression. The method is a kurtosis-based that calculates the signal element variance from its mean as a measurement index. The measurement index can be implicated to determine the severity of wear. The study was conducted to strengthen the shortage in past studies notably considering signal feature extraction for the disintegration of non-deterministic signals. The Cutting force and vibration signals were measured as a tool of sensing element to study wear on the cutting tool edge at the discrete machining conditions. The monitored flank wear progression by the value of the RZ index, which then outlined in the model data pattern concerning wear and number of samples. Throughout the experimental studies, the index shows a significant degree of nonlinearity that appears in the measured impact. For that reason, the accretion of force components by Z-rotation method has successfully determined the abnormality existed in the signal data for both force and vibration. It corresponds to the number of cutting specifies a strong correlation over wear evolution with the highest correlation coefficient of R2 = 0.8702 and the average value of R2 = 0.8147. The index is more sensitive towards the end of the wear stage compared to the previous methods. Thus, it can be utilised to be the alternative experimental findings for monitoring tool wear progression by using threshold values on certain cutting condition.