Unveiling global land fine- and coarse-mode aerosol dynamics from 2005 to 2020 using enhanced satellite-based monthly inversion data

Accurate fine-mode and coarse-mode aerosol knowledge is crucial for understanding their impacts on the climate and Earth's ecosystems. However, current satellite-based Fine-Mode Aerosol Optical Depth (FAOD) and Coarse-Mode Aerosol Optical Depth (CAOD) methods have drawbacks including inaccuracies, low spatial coverage, and limited temporal duration. To overcome these issues, we developed new global-scale FAOD and CAOD from 2005 to 2020 using a novel deep learning model capable of the synergistic retrieval of two aerosol sizes. After validation with the aerosol robotic network (AERONET) and sky radiometer network (SKYNET), the new monthly FAOD and CAOD showed significant improvements in accuracy and spatial coverage. From 2005 to 2020, the new data showed that China had the greatest decrease in FAOD and CAOD. In contrast, India and South Latin America had a significant increase in FAOD versus North Africa in CAOD. FAOD in the regions of Argentina, Paraguay, and Uruguay in South America have shown an upward trend. The results reveal that FAOD and CAOD display distinct patterns of change in the same regions, particularly on the west coast of the United States where FAOD is increasing, while CAOD is decreasing. Aside from the year 2020 due to the global COVID-19 pandemic, the analysis showed that although China has seen at least an +85% increase in energy consumption and urban expansion in 2019 compared to 2005 due to the needs of development and construction, the implementation of China's air pollution control policies has led to a significant decrease in FAOD (-46%) and CAOD (-65%) after 2013. This research enriches our comprehension of global fine and coarse aerosol patterns, additional investigations are needed to determine the potential global implications of these changes.

Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor?

Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-temporal characteristics. However, long-time sequences and detailed AOD information can not be provided due to currently limited monitoring technology. In this paper, a daily AOD product, MODIS-based Multi-angle Implementation of Atmospheric Correction (MAIAC), is deployed to analyze the spatio-temporal characteristics in Xinjiang Uygur Autonomous Region from 2000 to 2019. In addition, the importance of influencing factors for AOD is calculated through Random Forest (RF) Model and the propagation trajectories of pollutants are simulated through Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Spatio distribution of AOD presents a tendency that AOD value in northern Xinjiang is low while the value in southern Xinjiang is high. Regions with high AOD values are mainly concentrated in Tarim Basin. AOD in southern Xinjiang is the highest, followed by that in eastern Xinjiang and AOD value in northern Xinjiang is the lowest. Seasonal variation of AOD is significant: Spring (0.309) > summer (0.200) > autumn (0.161) > winter (0.158). Average AOD value in Xinjiang is 0.196. AOD appears wavy from 2000 to 2014 with its low inflection point (0.157) appearing in 2005, and then increases, reaching its peak in 2014 (0.223). The obvious downward tendency after 2014 shows that the use of coal to natural gas (NG) conversion project improves the conditions of local environment. According to RF Model, NG contributes most to AOD. HYSPLIT Model reveals that aerosol in southern Xinjiang is related to the short-distant carriage of dust aerosol from the Taklimakan Desert. Aerosol there can affect Inner Mongolia through long-distant transport. Blocked by the Tianshan Mountains, fine dust particles can not cross the Tianshan Mountains to become a factor contributing to AOD in northern Xinjiang.

Analysis of Mineral Aerosol in the Surface Layer over the Caspian Lowland Desert by the Data of 12 Summer Field Campaigns in 2002–2020

In-situ knowledge on characteristics of mineral aerosols is important for weather and climate prediction models, particularly for modeling such processes as the entrainment, transport and deposition of aerosols. However, field measurements of the dust emission flux, dust size distribution and its chemical composition under realistic wind conditions remain rare. In this study, we present experimental data over annual expeditions in the arid and semi-arid zones of the Caspian Lowland Desert (Kalmykia, south of Russia); we evaluate characteristics of mineral aerosol concentration and fluxes, estimate its chemical composition and calculate its long-distance transport characteristics. The mass concentration in different years ranges from several tens to several hundred of μg m−3. The significant influence of wind velocity on the value of mass and counting concentration and on the proposed entrainment mechanisms is confirmed. An increased content of anthropogenic elements (S, Sn, Pb, Bi, Mo, Ag, Cd, Hg, etc.), which is characteristic for all observation points in the south of the European Russia, is found. The trajectory analysis show that long-range air particles transport from the Caspian Lowland Desert to the central regions of European Russia tends to increase in the recent decades.

Aerosol optical depth (AOD): spatial and temporal variations and association with meteorological covariates in Taklimakan desert, China

Aerosol optical depth (AOD) is a key parameter that reflects aerosol characteristics. However, research on the AOD of dust aerosols and various environmental variables is scarce. Therefore, we conducted in-depth studies on the distributions and variations of AOD in the Taklimakan Desert and its margins, China. We examined the correlation characteristics between AOD and meteorological factors combined with satellite remote sensing detection methods using MCD19A2-MODIS AOD products (from 2000, 2005, 2010, and 2015), MOD13Q1-MODIS normalized difference vegetation index products, and meteorological data. We analyzed the temporal and spatial distributions of AOD, periodic change trends, and important impacts of meteorological factors on AOD in the Taklimakan Desert and its margins. To explore the relationships between desert aerosols and meteorological factors, a random forest model was used along with environmental variables to predict AOD and rank factor contributions. Results indicated that the monthly average AOD exhibited a clear unimodal curve that reached its maximum in April. The AOD values followed the order spring (0.28) > summer (0.27) > autumn (0.18) > winter (0.17). This seasonality is clear and can be related to the frequent sandstorms occurring in spring and early summer. Interannual AOD showed a gradually increasing trend to 2010 then large changes to 2015. AOD tends to increase from south to north. Based on the general trend, the maximum value of AOD is more dispersed and its low-value area is always stable. The climatic index that has the most significant effect on AOD is relative humidity.

Optical and Physical Characteristics of Aerosol Vertical Layers over Northeastern China

The optical and physical characteristics of the aerosol vertical layers over Northeastern China (NEC) are investigated using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Level 2 layer products from 2007 to 2014. To better examine the spatial and temporal variations in the characteristics of aerosols over NEC, the region is divided into three parts (Heilongjiang province, Jilin province, and Liaoning province) to analyze the inter-annual and seasonal variations of nine selected aerosol parameters in each part during night and day times. The results reveal that the values of aerosol optical depth (AOD) increase year by year, over the whole NEC, being relatively high over the Liaoning (LN) province; this might be induced by higher levels of economic development and agricultural activity. The highest AOD values appear in summer, which is plausibly related to the temperate monsoon climate in NEC. Higher AOD values exist during the daytime than at night; this is intuitively the result of higher daytime anthropogenic activities. The base altitude of the lowest aerosol layer (BAL) and the top altitude of the highest aerosol layer (TAH) varied significantly due to the topography of NEC. The number of aerosol layers (N) is relatively large over LN, which might be caused by a relatively stronger atmospheric convection over this landscape. The thickness of the lowest aerosol layer (TLL) bore little relationship with the topography of NEC. The AOD proportion of the lowest aerosol layer (PAODL) is high (0.70 to 0.85 for the entire NEC), indicating that aerosols are mainly concentrated in the lowest layer of the atmosphere. The volume depolarization ratio of the lowest aerosol layer (VDRL) is large during spring and winter due to the presence of dust aerosols. The color ratio of the lowest aerosol layer (CRL) is large during the day due to relatively more human activities taking place than at night. Moreover, there is a significantly positive linear correlation between N and TAH, and a negative logarithm correlation between N and PAODL over NEC. The results of this study could provide researchers and the government departments with detailed and certain optical and physical information about aerosol layers over NEC, to help in the treatment of air pollution over NEC.

Insights into the phenomenon of an explosive growth and sharp decline in haze: A case study in Beijing

A severe haze episode occurred in winter in the North China Plain (NCP), and the phenomenon of an explosive growth and sharp decline in PM_2.5 (particulate matter with an aerodynamic diameter equal to or less than 2.5 μm) concentration was observed. To study the systematic causes for this phenomenon, comprehensive observations were conducted in Beijing from November 26 to December 2, 2015; during this period, meteorological parameters, LIDAR data, and the chemical compositions of aerosols were determined. The haze episode was characterized by rapidly varying PM_2.5 concentration, and the highest PM_2.5 concentration reached 667 μg/m³. During the haze episode, the NCP was dominated by a weak high-pressure system and continuously low PBL (planetary boundary layer) heights, which are unfavorable conditions for the diffusion of pollutants. The large increases in the concentrations of SNA (SO₄^2-, NO₃^- and NH₄⁺) during the haze implied that the formation of SNA was the largest contribution. Water vapor also played a vital role in the formation of haze by promoting the chemical transformation of secondary pollutants, which led to higher PM_2.5 concentrations. The spatial distributions of PM_2.5 in Beijing at different times and the backward trajectories of the air masses also indicated that pollutants from surrounding provinces in particular, contributed to the higher PM_2.5 concentration.

Exploring the impact of chemical composition on aerosol light extinction during winter in a heavily polluted urban area of China

An intensive measurement campaign was conducted in Xi'an, China from December 2012-January 2013 to investigate the chemical composition, formation, and optical properties of PM₁. The PM₁ mass concentration (average = 138.8 ± 83.2 μg m^-3) accounted for ∼50% of the PM_2.5 mass. Organic aerosols (OA) and secondary inorganic aerosols (SIA) were the most abundant PM₁ components, contributing 53.0% and 35.0% to the mass, respectively. Both primary emissions and aqueous-phase oxidation of secondary aerosols played roles in the pollution episodes. The average light scattering and absorption coefficients during the campaign were 805 ± 581 Mm^-1 and 123 ± 96 Mm^-1, respectively. Both the mass scattering and mass absorption efficiencies for PM₁ were higher than that for PM_2.5-1, indicating stronger ability of light extinction for the smaller particles at visible wavelengths compared with the larger ones. The contributions of aerosol species to light extinction coefficients under two visibility conditions were estimated based on multiple linear regression models, and the OA was found to be the largest contributor to light extinction in both cases. A larger contribution of SIA to light extinction for visibility <5 km demonstrated its greater impacts on visibility during heavy pollution conditions. These findings provide insights into the importance of submicron particles for pollution and visibility degradation in northwestern China.

Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments

The inaccurate quantification of personal exposure to air pollution introduces error and bias in health estimations, severely limiting causal inference in epidemiological research worldwide. Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to address this limitation by capturing the high variability of personal exposure during daily life in large-scale studies with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of novel sensing technologies for scientific and policy purposes. In this paper we characterise the performance of a portable personal air quality monitor (PAM) that integrates multiple miniaturised sensors for nitrogen oxides (NO x ), carbon monoxide (CO), ozone (O3) and particulate matter (PM) measurements along with temperature, relative humidity, acceleration, noise and GPS sensors. Overall, the air pollution sensors showed high reproducibility (meanR ¯ 2 = 0.93, min-max: 0.80-1.00) and excellent agreement with standard instrumentation (meanR ¯ 2 = 0.82, min-max: 0.54-0.99) in outdoor, indoor and commuting microenvironments across seasons and different geographical settings. An important outcome of this study is that the error of the PAM is significantly smaller than the error introduced when estimating personal exposure based on sparsely distributed outdoor fixed monitoring stations. Hence, novel sensing technologies such as the ones demonstrated here can revolutionise health studies by providing highly resolved reliable exposure metrics at a large scale to investigate the underlying mechanisms of the effects of air pollution on health.

Five-year observation of aerosol optical properties and its radiative effects to planetary boundary layer during air pollution episodes in North China: Intercomparison of a plain site and a mountainous site in Beijing

The aerosol microphysical, optical and radiative properties of the whole column and upper planetary boundary layer (PBL) were investigated during 2013 to 2018 based on long-term sun-photometer observations at a surface site (~106 m a.s.l.) and a mountainous site (~1225 m a.s.l.) in Beijing. Raman-Mie lidar data combined with radiosonde data were used to explore the aerosol radiative effects to PBL during dust and haze episodes. The results showed size distribution exhibited mostly bimodal pattern for the whole column and the upper PBL throughout the year, except in July for the upper PBL, when a trimodal distribution occurred due to the coagulation and hygroscopic growth of fine particles. The seasonal mean values of aerosol optical depth at 440 nm for the upper PBL were 0.31 ± 0.34, 0.30 ± 0.37, 0.17 ± 0.30 and 0.14 ± 0.09 in spring, summer, autumn and winter, respectively. The single-scattering albedo at 440 nm of the upper PBL varied oppositely to that of the whole column, with the monthly mean value between 0.91 and 0.96, indicating weakly to slightly strong absorptive ability at visible spectrum. The monthly mean direct aerosol radiative forcing at the Earth's surface and the top of the atmosphere varied from -40 ± 7 to -105 ± 25 and from -18 ± 4 to -49 ± 17 W m^-2, respectively, and the maximum atmospheric heating was found in summer (~66 ± 12 W m^-2). From a radiative point of view, during dust episode, the presence of mineral dust heated the lower atmosphere, thus promoting vertical turbulence, causing more air pollutants being transported to the upper air by the increasing PBLH. In contrast, during haze episode, a large quantity of absorbing aerosols (such as black carbon) had a cooling effect on the surface and a heating effect on the upper atmosphere, which favored the stabilization of PBL and occurrence of inversion layer, contributing to the depression of the PBLH.

Temporal Patterns in Fine Particulate Matter Time Series in Beijing: A Calendar View

Extremely high fine particulate matter (PM_2.5) concentration has become synonymous to Beijing, the capital of China, posing critical challenges to its sustainable development and leading to major public health concerns. In order to formulate mitigation measures and policies, knowledge on PM_2.5 variation patterns should be obtained. While previous studies are limited either because of availability of data, or because of problematic a priori assumptions that PM_2.5 concentration follows subjective seasonal, monthly, or weekly patterns, our study aims to reveal the data on a daily basis through visualization rather than imposing subjective periodic patterns upon the data. To achieve this, we conduct two time-series cluster analyses on full-year PM_2.5 data in Beijing in 2014, and provide an innovative calendar visualization of PM_2.5 measurements throughout the year. Insights from the analysis on temporal variation of PM_2.5 concentration show that there are three diurnal patterns and no weekly patterns; seasonal patterns exist but they do not follow a strict temporal division. These findings advance current understanding on temporal patterns in PM_2.5 data and offer a different perspective which can help with policy formulation on PM_2.5 mitigation.