peer reviewed | It is now irrefutable that air pollution caused by large amounts of Total Suspended Particulates (TSP) and respiratory particulates or Particulate Matter less than 10 mu m in aerodynamic diameter (PM10) has numerous undesired consequences on human health. Air quality degradation far from the African continent, in the US and in Europe, caused by high concentrations of African dust, is seen as a major threat even though most of these countries are very distant from the Sahara. Surprisingly, no estimates of TSP or PM10 levels near the Saharan dust source are available. Based on horizontal visibility observations which are reduced by the presence of dust in the atmosphere, TSP and PM10 levels are estimated throughout the year 2000 at Nouakchott-Airport, Mauritania, using relations found in the literature. It appears that concentrations of particles are significant both in terms magnitude and frequency, as the 24-hour PM10 thresholds established by the US EPA National Ambient Air Quality Standards and the EU Limits Values for Air Quality were exceeded 86 and 137 times, respectively. The average annual concentration is far above air quality standards and estimated at 159 mu g m(-3) for TSP and 108 mu g m(-3) for PM10. These very high particulate levels are likely to represent an important public health hazard and should be considered as a major environmental risk.

Hourly PM₂.₅ speciation data have been widely used as an input of positive matrix factorization (PMF) model to apportion PM₂.₅ components to specific source-related factors. However, the influence of constant source profile presumption during the observation period is less investigated. In the current work, hourly concentrations of PM₂.₅ water-soluble inorganic ions, bulk organic and elemental carbon, and elements were obtained at an urban site in Nanjing, China from 2017 to 2020. PMF analysis based on observation data during specific pollution (firework combustion, sandstorm, and winter haze) and emission-reduction (COVID-19 pandemic) periods was compared with that using the whole 4-year data set (PMFwₕₒₗₑ). Due to the lack of data variability, event-based PMF solutions did not separate secondary sulfate and nitrate. But they showed better performance in simulating average concentrations and temporal variations of input species, particularly for primary source markers, than the PMFwₕₒₗₑ solution. After removing event data, PMF modeling was conducted for individual months (PMFₘₒₙₜₕ) and the 4-year period (PMF₄₋yₑₐᵣ), respectively. PMFₘₒₙₜₕ solutions reflected varied source profiles and contributions and reproduced monthly variations of input species better than the PMF₄₋yₑₐᵣ solution, but failed to capture seasonal patterns of secondary salts. Additionally, four winter pollution days were selected for hour-by-hour PMF simulations, and three sample sizes (500, 1000, and 2000) were tested using a moving window method. The results showed that using short-term observation data performed better in reflecting immediate changes in primary sources, which will benefit future air quality control when primary PM emissions begin to increase.

Although dust storms have been associated with adverse health outcomes, studies on the burden of dust storms on deaths are limited. As global warming has induced significant climate changes in recent decades, which have accelerated desertification worldwide, it is necessary to evaluate the burden of dust storm-induced premature mortality using a critical measure of disease burden, such as the years of life lost (YLL). The YLL attributable to dust storms have not been examined to date. This study investigated the association between Asian dust storms (ADS) and the YLL in Seoul, South Korea, during 2002–2013. We conducted a time-series study using a generalized additive model assuming a Gaussian distribution and applied a distributed lag model with a maximum lag of 5 days to investigate the delayed and cumulative effects of ADS on the YLL. We also conducted stratified analyses using the cause of death (respiratory and cardiovascular diseases) and sociodemographic status (sex, age, education level, occupation, and marital status). During the study period, 108 ADS events occurred, and the average daily YLL was 1511 years due to non-accidental causes. The cumulative ADS exposure over the 6-day lag period was associated with a significant increase of 104.7 (95% CI, 31.0–178.5 years) and 34.4 years (4.0–64.7 years) in the YLL due to non-accidental causes and cardiovascular mortality, respectively. Sociodemographic analyses revealed associations between ADS exposure and the YLL in males, both <65 and ≥ 65 years old, those with middle-level education, and the unemployed, unmarried, and widowed (26.5–83.8 years). This study provides new evidence suggesting that exposure to dust storms significantly increases the YLL. Our findings suggest that dust storms are a critical environmental risk affecting premature mortality. These results could contribute to the establishment of public health policies aimed at managing dust storm exposure and reducing premature deaths.

Northern China is a significant source of dust source in Central Asia. Thus, high-resolution analysis of dust storms and comparison of dust sources in different regions of northern China are important to clarify the formation mechanism of East Asian dust storms and predict or even prevent such storms. Here, we analyzed spatiotemporal trends in dust storms that occurred in three main dust source regions during 1960–2007: Taklimakan Desert (western region [WR]), Badain Jaran and Tengger Deserts (middle region [MR]), and Otindag Sandy Land (eastern region [ER]). We analyzed daily dust storm frequency (DSF) at the 10-day scale (first [FTDM], middle [MTDM], and last [LTDM] 10 days of a month), and investigated the association of dust storm occurrences with meteorological factors. The 10-day DSF was greatest in the FTDM (accounting for 77.14% of monthly occurrences) in the WR, MTDM (45.85%) in the MR, and LTDM (72.12%) in the ER, showing a clear trend of movement from the WR to the ER. Temporal analysis of DSF revealed trend changes over time at annual and 10-day scales, with mutation points at 1985 and 2000. We applied single-factor and multiple-factor analyses to explore the driving mechanisms of DSF at the 10-day scale. Among single factors, a low wind-speed threshold, high solar radiation, and high evaporation were correlated with a high DSF, effectively explaining the variations in DSF at the 10-day scale; however, temperature, relative humidity, and precipitation poorly explained variations in DSF. Similarly, multiple-factor analysis using a classification and regression tree revealed that maximum wind speed was a major influencing factor of dust storm occurrence at the 10-day scale, followed by relative humidity, evaporation, and solar radiation; temperature and precipitation had weak influences. These findings help clarify the mechanisms of dust storm occurrence in East Asia.

Elemental concentrations of ambient aerosols are commonly sampled over 12–24 h, and the low time resolution puts a great limit on current understanding about the temporal variations and source apportionment based on receptor models. In this work, hourly-resolved concentrations of eighteen elements in PM₂.₅ at an urban site in Nanjing, a megacity in Yangtze River Delta of east China, were obtained by using a Xact 625 ambient metals monitor from 12/12/2016 to 12/31/2017. The influence of traffic activities was clearly reflected by the spikes of crustal elements (e.g., Fe, Ca, and Si) in the morning rush hour, and the firework burning and sandstorm events during the sampling periods were tracked by sharp enrichment of Ba, K and Fe, Ca, Si, Ti in PM₂.₅, respectively. To evaluate the advantage of hourly-resolved elements data in identifying impacts from specific emission sources, positive matrix factorization (PMF) analysis was performed with the 1-h data set (PMF₁₋ₕ) and 23-h averaged data (PMF₂₃₋ₕ), respectively. The 4- and 6-factor PMF₂₃₋ₕ solutions had similar factor profiles and consistent factor contributions as the corresponding PMF₁₋ₕ solutions. However, due to the limit in inter-sample variability, PMF analysis with 23-h average data misclassified some major (e.g., K, Fe, Zn, Ca, and Si) and trace (e.g., Pb) elements in factor profiles, resulting in different absolute factor contributions between PMF₂₃₋ₕ and PMF₁₋ₕ solutions. These results suggested the use of high time-resolved data to obtain valid and robust source apportionment results.

This study investigated the effects of pollution emissions on the bioreactivity of PM2.5 during Asian dust periods. PM2.5 during the sampling period were 104.2 and 85.7 μg m−3 in Xi'an and Beijing, respectively, whereas PM2.5 which originated from the Tengger Desert was collected (dust background). Pollution conditions were classified as non-dust days, pollution episode (PE), dust storm (DS)-1, and DS-2 periods. We observed a significant decrease in cell viability and an increase in LDH that occurred in A549 cells after exposure to PM2.5 during a PE and DS-1 in Xi'an and Beijing compared to Tengger Desert PM2.5. Positive matrix factorization was used to identify pollution emission sources. PM2.5 from biomass and industrial sources contributed to alterations in cell viability and LDH in Xi'an, whereas vehicle emissions contributed to LDH in Beijing. OC, EC, Cl−, K+, Mg2+, Ca, Ti, Mn, Fe, Zn, and Pb were correlated with cell viability and LDH for industrial emissions in Xi'an during DS. OC, EC, SO42−, S, Ti, Mn, and Fe were correlated with LDH for vehicle emissions in Beijing during DS. In conclusion, the dust may carry pollutants on its surface to downwind areas, leading to increased risks of particle toxicity.

Continuous measurements of PM2.5, PM10 and CO were conducted at an urban site of Udaipur in India from April 2011 to March 2012. The annual mean concentrations of PM2.5, PM10 and CO were 42 ± 17 μg m−3, 114 ± 31 μg m−3 and 343 ± 136 ppbv, respectively. Concentrations of both particulate and CO showed high values during winter/pre-monsoon (dry) period and lowest in the monsoon season (wet). Local anthropogenic emission and long-range transport from open biomass burning sources along with favourable synoptic meteorology led to elevated levels of pollutants in the dry season. However, higher values of PM10/PM2.5 ratio during pre-monsoon season were caused by the episodes of dust storm. In the monsoon season, flow of cleaner air, rainfall and negligible emissions from biomass burning resulted in the lowest levels of pollutants. The concentrations of PM2.5, PM10 and CO showed highest values during morning and evening rush hours, while lowest in the afternoon hours. In winter season, reductions of PM2.5, CO and PM10 during weekends were highest of 15%, 13% and 9%, respectively. In each season, the highest PM2.5/PM10 ratio coincided with the highest concentrations of pollutants (CO and NOX) indicating predominant emissions from anthropogenic sources. Exceptionally high concentrations of PM10 during the episode of dust storm were due to transport from the Arabian Peninsula and Thar Desert. Up to ∼32% enhancements of PM10 were observed during strong dust storms. Relatively low levels of O3 and NOx during the storm periods indicate the role of heterogeneous removal.

To investigate the spatial and temporal behaviors of particulate matter in Lanzhou, Jinchang and Jiayuguan during 2014, the hourly concentrations of PM2.5 and PM10 were collected from the Ministry of Environmental Protection (MEP) in this study. The analysis indicated that the mean annual PM10 (PM2.5) concentrations during 2014 were 115 ± 52 μg/m3 (57 ± 28 μg/m3), 104 ± 75 μg/m3 (38 ± 22 μg/m3) and 114 ± 72 μg/m3 (32 ± 17 μg/m3) in Lanzhou, Jinchang and Jiayuguan, respectively, all of which exceeded the Chinese national ambient air quality II standards for PM. Higher values for both PM fractions were generally observed in spring and winter, and lower concentrations were found in summer and autumn. Besides, the trend of seasonal variation of particulate matter (PM) in each city monitoring site is consistent with the average of the corresponding cities. Anthropogenic activities along with the boundary layer height and wind scale contributed to diurnal variations in PM that varied bimodally (Lanzhou and Jinchang) or unimodally (Jiayuguan). With the arrival of dust events, the PM10 concentrations changed dramatically, and the PM10 concentrations during dust storm events were, respectively, 19, 43 and 17 times higher than the levels before dust events in Lanzhou, Jinchang and Jiayuguan. The ratios (PM2.5/PM10) were lowest, while the correlations were highest, indicating that dust events contributed more coarse than fine particles, and the sources of PM are similar during dust storms. The relationships between local meteorological parameters and PM concentrations suggest a clear association between the highest PM concentrations, with T ≤ 7 °C, and strong winds (3–4 scale). However, the effect of relative humidity is complicated, with more PM10 and PM2.5 exceedances being registered with a relative humidity of less than 40% and 40–60% in Lanzhou, while higher exceedances in Jinchang appeared at a relative humidity of 80–100%.

Reports on the effects of PM10 from dust storm on lung cells are limited. The main purpose of this study was to investigate the chemical composition and in vitro toxicological impacts of PM10 suspensions, its water-soluble fraction, and the solvent-extractable organics extracted from Middle Eastern Dust storms on the human lung epithelial cell (A549). Samples of dust storms and normal days (PM10 < 200 μg m⁻³) were collected from December 2012 until June 2013 in Ahvaz, the capital of Khuzestan Province in Iran. The chemical composition and cytotoxicity were analyzed by ICP- OES and Lactase Dehydrogenase (LDH) reduction assay, respectively. The results showed that PM10 suspensions, their water-soluble fraction and solvent-extractable organics from both dust storm and normal days caused a decrease in the cell viability and an increase in LDH in supernatant in a dose–response manner. Although samples of normal days showed higher cytotoxicity than those of dust storm at the highest treated dosage, T Test showed no significant difference in cytotoxicity between normal days and dust event days (Pvalue > 0.05). These results led to the conclusions that dust storm PM10 as well as normal day PM10 could lead to cytotoxicity, and the organic compounds (PAHs) and the insoluble particle-core might be the main contributors to cytotoxicity. Our results showed that cytotoxicity and the risk of PM10 to human lung may be more severe during dust storm than normal days due to inhalation of a higher mass concentration of airborne particles. Further research on PM dangerous fractions and the most responsible components to make cytotoxicity in exposed cells is recommended.

Size-segregated aerosol samples were collected in New Delhi, India from March 6 to April 6, 2012. Homologous series of n-alkanes (C19C33), n-fatty acids (C12C30) and n-alcohols (C16C32) were measured using gas chromatography/mass spectrometry. Results showed a high-variation in the concentrations and size distributions of these chemicals during non-haze, haze, and dust storm days. In general, n-alkanes, n-fatty acids and n-alcohols presented a bimodal distribution, peaking at 0.7–1.1 μm and 4.7–5.8 μm for fine modes and coarse modes, respectively. Overall, the particulate matter mainly existed in the coarse mode (≥2.1 μm), accounting for 64.8–68.5% of total aerosol mass. During the haze period, large-scale biomass burning emitted substantial fine hydrophilic smoke particles into the atmosphere, which leads to relatively larger GMDs (geometric mean diameter) of n-alkanes in the fine mode than those during the dust storms and non-haze periods. Additionally, the springtime dust storms transported a large quantity of coarse particles from surrounding or local areas into the atmosphere, enhancing organic aerosol concentration and inducing a remarkable size shift towards the coarse mode, which are consistent with the larger GMDs of most organic compounds especially in total and coarse modes. Our results suggest that fossil fuel combustion (e.g., vehicular and industrial exhaust), biomass burning, residential cooking, and microbial activities could be the major sources of lipid compounds in the urban atmosphere in New Delhi.