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Dust is a major source of atmospheric aerosols. Its chemical composition is often assumed to be similar to the parent soil. However, this assumption has not been rigorously verified. Here, we generated dust aerosols from soils to determine if there is particle-size-dependent selectivity of heavy metals in the dust generation. Mn, Cd, Pb and other heavy metals were found to be highly enriched in fine-dust (PM 2.5) aerosols, which can be up to ∼ 6.5-fold. To calculate the contributions of dust to atmospheric heavy metals, regional air quality models usually use the dust chemical profiles from the U.S. Environmental Protection Agency's (EPA) SPECIATE database, which does not capture the correct size-dependent selectivity of heavy metals in dust aerosols. Our air quality modeling for China demonstrates that the calculated contribution of fine-dust aerosols to atmospheric heavy metals, as well as their cancer risks, could have significant errors without using proper dust profiles. [ABSTRACT FROM AUTHOR]

China is confronting severe ozone (O3) pollution although particulate matter reduced significantly, causing damages to public health and ecological systems. Here we utilized the comprehensive methods of ground‐level observations, satellite data, and source‐oriented chemical transport model to interpret O3 variations throughout China from 2016 to 2019. A remarkably worsened trend of O3 levels has been found both by observation and simulation in these years. Our results showed that the remarkable O3 elevation was found in the North China Plain (NCP) and Yangtze River Delta (YRD) (maximum daily 8 hr average O3 ∼60 ppb) with an annual increasing rate of 10%. In addition, O3 formation regimes also changed in the NCP, where 4.9% grids shifted from VOC‐limited to transition regimes and 9.6% grids shifted from transition to NOx‐limited regimes. The elevation of MDA8 O3 was mainly attributed to the enhanced atmospheric oxidation capacity (AOC) in above regions. Particularly, the increasing rates of OH and HO2 radicals (major oxidants) in NCP and YRD reached ∼15% and ∼5%, respectively. The comprehensive study of long‐term O3 changes, formation regimes, and AOC based on a multimethod approach should be considered when designing O3 control policies. Plain Language Summary: Tropospheric Ozone (O3) is a key secondary pollutant in the atmosphere, which is harmful to human health and the ecosystem. Although strict air pollution control policies have been implemented in China recently, the O3 pollution remains serious nevertheless the reduced precursor such as HCHO and NO2. While field measurements and model simulations have been used to investigate O3 variations, the roles of formation regimes, atmospheric oxidation capacity (AOC), and source apportionment of O3 are still unclear. To address this knowledge gap, we utilized a multi‐method approach, including satellite and ground‐level observations as well as improved source‐oriented simulations, to investigate the variations of O3 and its associated precursors. Our findings revealed that from 2016 to 2019, the annual increasing ratio of O3 was up to 10% in the North China Plain (NCP). The elevation of O3 levels was caused by shifts in O3 formation regimes and increases in AOC, which were associated with meteorological variations and anthropogenic emission reductions. Key Points: O3 formation regime shifted from VOC‐limited to transition or NOx‐limited regimes in North China Plain (NCP) and Yangtze River Delta (YRD)Enhanced atmospheric oxidant capacity mainly contributed to O3 elevation in NCP and YRD from 2016 to 2019O3 control policies should be considered from the comprehensive insights including O3 formation regime and atmospheric oxidant capacity [ABSTRACT FROM AUTHOR]

The greening impacts on China from 2000 to 2017 led to an increase in vegetated areas and thus enhanced biogenic volatile organic compound (BVOC) emissions. BVOCs are regarded as important precursors for ozone (O 3) and secondary organic aerosol (SOA). As a result, accurate estimation of BVOC emissions is critical to understand their impacts on air quality. In this study, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 was used to investigate the impact of different leaf area index (LAI) and land cover (LC) datasets on BVOC emissions in China in 2016, and the effects on O 3 and SOA were evaluated based on the Community Multiscale Air Quality (CMAQ) modeling system. Three LAI satellite datasets of the Global LAnd Surface Satellite (GLASS), the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A2H version 6 (MOD15), and the Copernicus Global Land Service (CGLS), as well as three LC satellite datasets of the MODIS MCD12Q1 LC products, the Copernicus Climate Change Service (C3S) LC products, and the CGLS LC products, were used in five parallel experiments (cases: C1–C5). Results show that changing LAI and LC datasets of the model input has an impact on BVOC estimations. BVOC emissions in China ranged from 25.42 to 37.39 Tg in 2016 and were mainly concentrated in central and southeastern China. Changing the LC inputs for the MEGAN model has a more significant difference in BVOC estimates than using different LAI datasets. The combination of C3S LC and GLASS LAI performs better in the CMAQ model, indicating that it is the better choice for BVOC estimations in China. The highest contribution of BVOCs to O 3 and SOA can reach 12 ppb and 9.8 µ g m -3 , respectively. Changing the MEGAN inputs further impacts the concentrations of O 3 and SOA, especially changing LC datasets. The relative difference between MCD12Q1 LC and C3S LC is over 52 % and 140 % in O 3 and biogenic SOA (BSOA) in central and eastern China. The BSOA difference is mainly attributed to the isoprene SOA (ISOA), a major contributor to BSOA. The relative differences in ISOA between different cases are up to 160 % in eastern China. Therefore, our results suggest that the uncertainties in MEGAN inputs should be fully considered in future O 3 and SOA simulations. [ABSTRACT FROM AUTHOR]

Economic activities and the associated emissions have significantly declined during the 2019 novel coronavirus (COVID‐19) pandemic, which has created a natural experiment to assess the impact of the emitted precursor control policy on ozone (O3) pollution. In this study, we utilized comprehensive satellite, ground‐level observations, and source‐oriented chemical transport modeling to investigate the O3 variations during the COVID‐19 pandemic in China. Here, we found that the significant elevated O3 in the North China Plain (40%) and Yangtze River Delta (35%) were mainly attributed to the enhanced atmospheric oxidation capacity (AOC) in these regions, associated with the meteorology and emission reduction during lockdown. Besides, O3 formation regimes shifted from VOC‐limited regimes to NOx‐limited and transition regimes with the decline of NOx during lockdown. We suggest that future O3 control policies should comprehensively consider the effects of AOC on the O3 elevation and coordinated regulations of the O3 precursor emissions. Plain Language Summary: Severe ozone (O3) pollution has been a public concern in China during the last decade. Due to the 2019 novel coronavirus (COVID‐19) pandemic, China has implemented the strict restrictions, leading to the significant decline of economic activities and the associated emissions. However, the O3 levels have been elevated in vast areas of China during the COVID‐19 lockdown period. In this study, we applied the comprehensive satellite, ground‐level observations, and source‐oriented chemical transport modeling to investigate the O3 elevation during the COVID‐19 lockdown periods. Importantly, our results showed that O3 has increased significantly in North China Plain (40%) and Yangtze River Delta (35%) during lockdown, which attributed to the enhanced atmospheric oxidation capacity (AOC) associated with the meteorology and emission reduction. Besides, we found the O3 formation regimes shifted from VOC‐limited to NOx‐limited due to the lower NOx during lockdown. In the future, we suggest that O3 control policies ought to ensure a balance between emitted NOx and VOCs to maintain stable O3 formation regimes and AOC levels and thereby control O3 emissions. Key Points: O3 formation regime shift from a VOC‐limited to a NOx‐limited regime has been found in most areas of ChinaEnhanced atmospheric oxidation capacity (AOC) contributed to O3 elevation during COVID‐19 lockdownO3 control policies should consider from the comprehensive sights of O3 formation regime and AOC in the future [ABSTRACT FROM AUTHOR]

• Impacts of Clean Air Action on PM 2.5 and O 3 are comprehensively evaluated from 2013 to 2020. • NCP experiences O 3 increase (4%) while other regions show O 3 decreases. • Emissions dominate the PM 2.5 reduction and contribute 54% to O 3 reduction. Since 2013, the Chinese Government implemented "Clean Air Action" Phase I (2013–2017) and Phase II (2018–2020) consecutively to improve air quality. However, it remains unclear how these policies have impacted air quality since most studies merely focus on Phase I. In this study, we applied the Community Multiscale Air Quality (CMAQ) model to investigate variations of air quality in China during "Clean Air Action" Phases I and Phase II (2013–2020). Results show that PM 2.5 is significantly reduced (-40%) across China except in summer. O 3 concentration also decreases, but a 3% increase is found in the Beijing-Tianjin-Hebei (BTH) region. Emission changes play a dominant role in the reduction of PM 2.5 (over 95%). The contributions from meteorology and emissions to O 3 reduction are 46% and 54%, respectively. Our results suggest that a more effective emission abatement strategy should be formulated, aiming to control O 3 and PM 2.5 synergistically. [Display omitted] [ABSTRACT FROM AUTHOR]

Evaluating ozone levels at high resolutions and accuracy is crucial for understanding the spatiotemporal characteristics of ozone distribution and assessing ozone exposure levels in epidemiological studies. The national models with high spatiotemporal resolutions to predict ground ozone concentrations are limited in China so far. In this study, we aimed to develop a random forest model by combining ground ozone measurements from fixed stations, ozone simulations from the Community Multiscale Air Quality (CMAQ) modeling system, meteorological parameters, population density, road length, and elevation to predict ground maximum daily 8-h average (MDA8) ozone concentrations at a daily level and 1 km × 1 km spatial resolution. The model cross-validation R 2 and root mean squared error (RMSE) were 0.80 and 20.93 μg/m3 at daily level in 2013–2019, respectively. CMAQ ozone simulations and near-surface temperature played vital roles in predicting ozone concentrations among all predictors. The population-weighted median concentrations of predicted MDA8 ozone were 89.34 μg/m3 in mainland China in 2013, and reached 100.96 μg/m3 in 2019. However, the long-term temporal variations among regions were heterogeneous. Central and Eastern China, as well as the Southeast Coastal Area, suffered higher ozone pollution and higher increased rates of ozone concentrations from 2013 to 2019. The seasonal pattern of ozone pollution varied spatially. The peak-season ozone pollution with the highest 6-month ozone concentrations occurred in different months among regions, with more than half domain in April–September. The predictions showed that not only the annual mean concentrations but also the percentages of grid-days with MDA8 ozone concentrations higher than 100/160 μg/m3 have been increasing in the past few years in China; meanwhile, majority areas in mainland China suffered peak-season ozone concentrations higher than the air quality guidelines launched by the World Health Organization in September 2021. The proposed model and ozone predictions with high spatiotemporal resolution and full coverage could provide health studies with flexible choices to evaluate ozone exposure levels at multiple spatiotemporal scales in the future. [Display omitted] • The CV R2 and RMSE were 0.80 and 20.93 μg/m3 at daily level, respectively. • Ozone predictions were produced at the daily and 1-km resolution nationwide. • The peak-season O 3 occurred in different months spatially, with 67% area in Apr.–Sep. • The grid-days with severe O 3 pollution increased from 0.88% to 2.38% in 2013–2019. • 94% domain of mainland China had peak-season O 3 over newly updated WHO AQG. [ABSTRACT FROM AUTHOR]

Complex air pollutant sources and distinct meteorological conditions resulted in unique wintertime haze pollution in the Harbin-Changchun (HC) metropolitan area, China's only national-level city cluster located in the severe cold climate region. In this study, field observation and air quality modeling were combined to investigate fine particulate matter (PM 2.5) pollution during a six-month long heating season in HC's central city (Harbin). The model significantly underpredicted PM 2.5 and organic carbon (by up to ∼230 μg/m3 and 110 μgC/m3, respectively, in terms of daily average) when levoglucosan concentrations were above 0.5 μg/m3. Based on a synthesis of levoglucosan concentrations and fire counts, the large gaps were attributed to underestimation of open burning emissions by the model. However, the model tended to overpredict elemental carbon (more significantly at higher NO 2), likely pointing to an overestimation of vehicle emissions. With increasing levoglucosan, the difference between observed and simulated nitrate (nitrate obs ‒ nitrate mod , i.e., Δnitrate) showed a transition from negative to positive values. The positive Δnitrate were attributed to underprediction of the open-burning related nitrate, whereas the negative Δnitrate were likely caused by overprediction of nitrate from other sources (presumably vehicle emissions). The dependence of Δnitrate on levoglucosan indicated that with stronger impact of open burning, the overprediction effect was gradually offset and finally overwhelmed. Influence of open burning on sulfate formation was evident as well, but less apparent compared to nitrate. This study illustrates how the uncertainties in open burning emissions will influence PM 2.5 simulation, on not only primary components but also secondary species. Image 1 • The model largely underpredicted PM 2.5 under circumstances of high levoglucosan. • Variation of levoglucosan was driven mainly by open burning of crop residues. • The PM 2.5 underprediction was primarily due to underestimation of organic carbon. • Open-burning independent overprediction of elemental carbon was observed. • Influence of open burning was more evident for nitrate formation than sulfate. [ABSTRACT FROM AUTHOR]

China implemented a stringent clean air initiative to improve air quality in 2013. By 2017, fine particulate matter (PM 2.5) levels in the Yangtze River Delta (YRD) region dropped significantly, but ozone (O 3) pollution surged, which aroused concerns about its adverse impact on crops, climate and human health. Due to the complex influences of atmospheric processes, the variation of O 3 is highly nonlinear, making the control of O 3 pollution highly challenging. It is urgent to deepen the understanding of the role of meteorological factors and atmospheric oxidation capacity (AOC) during O 3 episodes. To provide references for O 3 pollution control, the study used the Weather Research and Forecasting model (WRF) and the Community Multi-scale Air Quality model (CMAQ) simulations in the YRD from 2017 to 2020 to analyze the causes of severe O 3 pollution. Observations revealed a slight decline in heavily O 3 polluted days in the YRD region and the simulation results showed that O 3 pollution was more prevalent at temperatures above 25 °C and relative humidity below 80%. The increase in volatile organic compounds (VOCs), hydroxyl radical (OH) and nitrate radical (NO 3) was also more conducive to the formation of O 3 pollution. For areas that are primarily VOC-limited areas, such as Shanghai, a stricter policy on VOC control is needed to reduce O 3 pollution more effectively. • O 3 concentration and its heavily polluted episodes decreased in the YRD from 2017 to 2020. • Heavy O 3 pollution is typically accompanied by high temperatures (>25 °C), low humidity (<80%) and weak winds (-2 m·s−1). • Enhanced atmospheric oxidation (+200%) is a significant cause of O 3 pollution in the YRD region. [ABSTRACT FROM AUTHOR]

Since 2000, China has faced severe air pollution challenges，prompting the initiation of comprehensive emission control measures post-2013. The subsequent implementation of these measures has led to remarkable enhancements in air quality. This study aims to enhance our understanding of the long-term trends in fine particulate matter (PM 2.5 ) and gaseous pollutants of ozone (O 3 ) and nitrogen dioxide (NO 2 ) across China from 2000 to 2020. Utilizing the Community Multiscale Air Quality (CMAQ) model, we conducted a nationwide analysis of air quality, systematically quantifying model predictions against observations for pollutants. The CMAQ model effectively captured the trends of air pollutants, meeting recommended performance benchmarks. The findings reveal variations in pollutant concentrations, with initial increases in PM 2.5 followed by a decline after 2013. The proportion of the population living in high PM 2.5 concentrations (>75 μg/m 3 ) decreased to <5 % after 2015. However, during the period from 2017 to 2020, around 40 % of the population continued to live in regions that did not meet the criteria for Chinese air quality standards (35 μg/m 3 ). From 2000 to 2019, fewer than 20 % of the population met the WHO standard (100 μg/m 3 ) for MDA8 O 3 . In 2000, 77 % of the population met the NO 2 standard (<20 μg/m 3 ), a figure that declined to 60 % between 2005 and 2014, nearly reaching 70 % in 2020. This study offers a comprehensive analysis of the changes in pollutants and public exposure in 2000-2020. It serves as a foundational resource for future efforts in air pollution control and health research., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Particulate matter (PM) is a global health concern and causes millions of premature deaths worldwide annually. High-resolution and full-coverage PM datasets are essential to support the accurate assessment of PM exposure. Here, a three-stage model framework is developed based on the Community Multiscale Air Quality (CMAQ) simulations (12 km) and multisource data fusion to estimate 1 km daily PM concentrations across China in 2015, including PM 2.5 (<2.5 μm) and PM 10 (<10 μm). The three-stage model performs well with cross-validation coefficient of determination (R 2 ) of 0.91 and 0.87, and root mean square error (RMSE) of 17.3 μg/m 3 and 27.2 μg/m 3 for PM 2.5 and PM 10 , respectively. After data fusion from multiple sources, the concentrations of PM 2.5 and PM 10 are in better agreement with ground observations compared to the CMAQ simulation with RMSE reduced by 72 % and 67 %. High PM 2.5 events mainly occur in the North China Plain, Yangtze River Delta, and Sichuan Basin, and PM 10 show similar spatial patterns to PM 2.5 in eastern China. These full-coverage PM datasets enable in-depth analysis of PM pollution over small areas and support future epidemiological studies and health assessments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The Sichuan Basin (SCB) in southwestern China is largely affected by air pollution. Understanding the responses of air pollutant concentrations to emission changes is critical for designing and evaluating effective control strategies. Thus, this study used the Community Multi-scale Air Quality (CMAQ) model to simulate PM 2.5 (i.e., particulate matter with an aerodynamic diameter ≤ 2.5 μm) in winter (January 2015) and ozone (O 3 ) in summer (July 2015) under nine emission reduction scenarios. For each scenario, the anthropogenic emissions of each air pollutant in each SCB grid cell were reduced by the same percentage, ranging from 10% to 90%. We found that approximately 30-70% emission reductions are required to reduce the January mean PM 2.5 concentrations in all the SCB urban centers to a value that is less than the Chinese standard for daily mean PM 2.5 (24-h PM 2.5 : 75 μg m -3 ). However, the January mean PM 2.5 concentrations under 90% emission reduction still exceeded the World Health Organization (WHO) guideline (25 μg m -3 ) in 16 SCB urban centers. Moreover, reducing both SCB and non-SCB emissions were critical for achieving the PM 2.5 level recommended by WHO. An 80% emission reduction was required to prevent the occurrence of 8-h O 3 (i.e., daily maximum 8-h mean O 3 ) non-attainment days in all SCB urban centers. Under 90% emission reduction, July mean 8-h O 3 concentrations still exceeded the WHO guideline of 47 ppb in approximately 35% of the SCB areas. In conclusion, this study suggests that (1) compared with the governmental emission reduction targets for 2015-2020 (2-27%), more significant emission reductions are required to meet the Chinese and WHO pollution standards; and (2) both SCB and non-SCB emissions must significantly reduce to achieve the desired pollution targets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Aggressive air pollution control in China since 2013 has achieved sharp decreases in fine particulate matter (PM 2.5 ), along with increased ozone (O 3 ) concentrations. Due to the pandemic of coronavirus disease 2019 (COVID-19), China imposed nationwide restriction, leading to large reductions in economic activities and associated emissions. In particular, large decreases were found in nitrogen oxides (NO x ) emissions (>50%) from transportation. However, O 3 increased in the Yangtze River Delta (YRD), which cannot be fully explained by changes in NO x and volatile organic compound (VOCs) emissions. In this study, the Community Multi-scale Air Quality model was used to investigate O 3 increase in the YRD. Our results show a significant increase of atmospheric oxidation capacity (AOC) indicated by enhanced oxidants levels (up to +25%) especially in southern Jiangsu, Shanghai and northern Zhejiang, inducing the elevated O 3 during lockdown. Moreover, net P(HO x ) of 0.4 to 1.6 ppb h -1 during lockdown (Case 2) was larger than the case without lockdown (Case 1), mainly resulting in the enhanced AOC and higher O 3 production rate (+12%). This comprehensive analysis improves our understanding on AOC and associated O 3 formation, which helps to design effective strategies to control O 3 ., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2020. Published by Elsevier B.V.)

Severe fine particulate matter (PM 2.5 ) pollution and the associated health risks remain pressing issues in the Yangtze River Delta (YRD), although significant efforts have been made locally, such as the Clean Air Action since 2013. Regional transport is an important contributor to high PM 2.5 levels during haze episodes in the YRD, but its impact on human health is rarely analyzed. In this study, we evaluate the short-term PM 2.5 -related health risks and associated economic losses due to different source regions by estimating daily mortality based on model results in the YRD. The results show that regional transport induces significant health risks in the YRD during haze days, contributing over 60% of daily premature mortality in Shanghai and Nanjing (major cities in the YRD). Moreover, in Hangzhou and Jiaxing, regional transport's contribution can be as high as 70%. The total daily mean economic loss in the YRD is estimated as 526.8 million Chinese Yuan (approximately 81.4 million U.S. dollar) in winter of 2015 and 2016, accounting for 1.4% of the daily averaged gross domestic product (GDP) of the YRD. Emission control (in accordance with the 13th Five-year Energy Conservation and Emission Reduction Plan) is an effective way to reduce health risks in the YRD, reducing premature deaths during haze days by 12-33%. More stringent emission control measures are suggested for further reduce PM 2.5 -related health risks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

A revised Community Multi-scale Air Quality (CMAQ) model with updated secondary organic aerosol (SOA) yields and a more detailed description of SOA formation from isoprene (ISOP) oxidation was applied to study the spatial distribution of SOA, its components and precursors in Shaanxi in July of 2013. The emissions of biogenic volatile organic compounds (BVOCs) were generated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN), of which ISOP and monoterpene (MONO) were the top two, with 1.73 × 10 9  mol and 1.82 × 10 8  mol, respectively. The spatial distribution of BVOCs emission was significantly correlated with the vegetation coverage distribution. ISOP and its intermediate semi-volatile gases were up to ∼7.0 and ∼1.4 ppb respectively in the ambient. SOA was generally 2-6 μg/m 3 , of which biogenic SOA (BSOA) accounted for as high as 84% on average. There were three main BVOCs Precursors including ISOP (58%) and MONO (8%) emit in the studied domain, and ISOP (9%) transported. The Guanzhong Plain had the highest BSOA concentrations of 3-5 μg/m 3 , and the North Shaanxi had the lowest of 2-3 μg/m 3 . More than half of BSOA was due to reactive surface uptake of ISOP epoxide (0.2-0.7 μg/m 3 , ∼19%), glyoxal (GLY) (0.2-0.5 μg/m 3 , ∼11%) and methylglyoxal (MGLY) (0.4-1.4 μg/m 3 , ∼32%), while the remaining was due to the traditional equilibrium partitioning of semi-volatile components (0.1-1.2 μg/m 3 , ∼25%) and oligomerization (0.2-0.4 μg/m 3 , ∼12%). Overall, SOA formed from ISOP contributed 1-3 μg/m 3 (∼80%) to BSOA., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The Sinkiang Uygur Autonomous Region is located in western China and the centre of the Asian-European continent, which frequently suffers from sandstorm disasters and haze weathers. A 1-year measurement campaign in two selected points in Shihezi and Urumqi of Sinkiang was conducted to characterise the effects of particle matters and factors on particle extinction under different weather conditions. Results showed that the average concentration of PM 1-2.5 was 19.83, 9.230, 28.93 and 122.4 μg/m 3 in Shihezi and 67.25, 16.80, 59.19 and 324.0 μg/m 3 in Urumqi for spring, summer, autumn and winter, respectively. PM 5-10 concentrations can reach up to 500.0 and 160.0 μg/m 3 during polluted weather conditions in Shihezi and Urumqi, respectively. PM 5-10 also accounted for the largest fraction in Shihezi and Urumqi for all types of weather, reaching up to 40.0% under dusty weather conditions. PM 1-2.5 significantly increased during winter possibly due to the increased demand for heating compared with non-heating periods. PM 0.5-1 is possibly produced from motor vehicle exhaust. Particle size is concluded to be the dominant factor for particle extinction capability under fine weather based on calculations of aerosol optical properties. The refractive index for a particle with a diameter of 100 μm (3.10-3.11i) is substantially larger than that with a diameter of 0.5000 μm (1.600-0.07000i), but the extinction capability of the latter is 1.30 times that of the former. Comparatively, when the mass concentration of coarse particles is over 17.0 times that of the fine particles, and then mass concentration becomes the dominant factor. Therefore, visibility is negatively correlated to particle mass variations during dust storms and hazy days but not for fine days.