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.

Natural background levels (NBLs) and threshold values (TVs) are crucial parameters for identification and the quantification of groundwater pollution, and the evaluation of pollution control measures. The cumulative probability distribution technique was used for the evaluation of NBLs for 36 samples collected during two climate conditions in the part of the desert area from Rajasthan, India. The NBLs for Na⁺, Cl⁻, SO₄²⁻, HCO₃⁻, NO₃⁻ and F⁻ ions were assessed and compared with the natural and anthropogenic processes. The TVs were also calculated for Na⁺, Cl⁻, SO₄²⁻, HCO₃⁻, NO₃⁻ and F⁻ ions, and compared with the drinking limits of the Bureau of Indian Standards. Additionally, the pollution percentage (%) at the individual well was estimated and identified the polluted zones. Results indicate that most of the polluted areas were situated in the southern part, which was influenced by the natural and anthropogenic factors. The sodium concentrations above the TVs, in indicating the saline nature of water. Chloride threshold value above the drinking water limit was mainly observed in the dry season, related to intensive evaporation and industrial waste, which leads to groundwater quality degradation. The NO₃⁻ concentration (∼56% samples) above the TVs indicates extensive use of nitrate fertilizers and sewage effluent. The values of total dissolved solids (TDS) shows the suspicious scenario as about 84% of the samples in the dry period and about 89% in the wet season exceeding the drinking limit. Assessment of background concentrations and threshold values on regional and local scale assigns the basis for the identification of groundwater pollution, and helpful for better water quality guidelines to protecting of water resources.

This study employs the grain size distributions and the concentrations and isotopic compositions of Sr, Nd, and Pb in the precipitation samples collected from the Laohugou Glacier (LHG) in northeastern Tibetan Plateau (TP) during August 2014–2015 to investigate seasonal variability in the insoluble precipitation particle sources. Fine dust particle (0.57–27 μm) depositions dominated in autumn and winter, whereas both fine and coarse dust particle (27–100 μm) depositions were found in spring and summer. Furthermore, the concentrations of Sr, Nd, and Pb also varied seasonally—the highest and lowest Sr and Nd concentrations were recorded in spring and autumn, respectively, whereas the highest and lowest Pb concentrations were recorded in winter and summer, respectively. The Sr and Nd isotopes revealed that the dust in the winter precipitation originated predominately from the Taklimakan Desert and that in spring originated from the Badain Jaran and Qaidam deserts. The precipitation residues in summer were derived from a complex mixture of dust sources from the Gobi and other large deserts in northwest China. Autumn residues were predominately sourced from local soil near the LHG as well as from the Qaidam Basin and the northern TP surface soil. The Taklimakan, long suspected as a major source of long-range transported dust, was an insignificant contributor to the precipitation over LHG during spring, summer, and autumn. Further, the Pb isotopic ratios indicated a primary impact of anthropogenic pollutants for most part of the year (except spring). Meteorological data and the MODIS AOD model are in good agreement with the results from the analyses of the Sr, Nd, and Pb isotopes for the LHG particle source, and further clarify the source regions. Thus, this study thus provides new evidence on the seasonal variability of the sources of the residual particles in remote glaciers in Central Asia.

This work explores the use of Raman micro-spectroscopy to determine sources of airborne particulate matter collected on PM₂.₅ air filters in Imperial Valley, California. The goal is to examine if nearby soil is a potential source of particles sampled on air filters deployed in an urbanized desert area during events of unusually high PM₂.₅ excursions. Particle specific composition information can be an indicator of potential origin. This can provide insights into the source of unexpectedly high proportion of large particles sampled on PM₂.₅ filters in the vicinity of Imperial Valley. The measured spectral correspondence between the filter and soil particles, in the size range of 2.5–10 μm, is consistent with windblown dust being a likely source of the larger (>2.5 μm) particles collected on the PM₂.₅ filters. Additionally, these particles were identified as components of commonly occurring crustal minerals in the vicinity of the sampling site, such as iron oxides, hydroxides, sulfides, titanium dioxides and aluminosilicates. A substantial portion of the analyzed filter particles displayed a strong broadband fluorescence signal, which is consistent with the presence of organic matter and has been recognized as a marker for soil related origin of the filter particles. Elemental carbon (soot) was found to be prevalent among the particles as well, suggesting the existence of combustion related sources. Comparison between a heavily loaded filter sample and a filter with a more typical, lower loading did not show any obvious difference in chemical compositions. In both cases the particles appeared to be of crustal origin with the prevalence of elemental carbon. The primary difference between these two filter samples appear to be their particle size distribution - the heavily loaded filter sample contained greater proportion of large particles (>2.5 μm), and was more consistent with spectral signature of soils analyzed from the region.

The Ordos region of Inner Mongolia is rapidly developing and suffers from poor air quality and unhealthy levels of fine particulate matter. PM2.5 concentrations in the Ordos region were found to exceed 75 μg/m3 on average, annually, with peak pollution days in excess of 350 μg/m3, but local air pollution emissions from surrounding sources are not sufficient to drive pollution levels to these concentrations. The current study was designed to quantify sources of PM2.5 and assess the local source contributions and effects of regional transport on local pollution. The results show that the Ordos region is primarily impacted by regional long-range transport of pollutants from anthropogenic sources located outside of the Inner Mongolia in Shanxi province areas but is also largely affected by regional dust transported from the deserts located in western Inner Mongolia. The analysis proved that approximately 77% of PM2.5 mass is transported long-range from the sites exterior to the study area and contributes 59.32 μg/m3 on average, annually, while the local sources contribute 17.41 μg/m3 (23%) on annual average to the PM2.5 mass in the study area. High spatial correlation coefficients (R2 > 0.6) were observed for most of the factors pointing to the transport of external emissions into the area. Spatial correlation analysis, bivariate polar plots and hybrid trajectory models for industrial and secondary inorganic factors provide evidence for the impact of long-range transport from Shanxi province areas. In addition, the deserts in western Inner Mongolia were found to be the source regions for dust. Finally, our analysis shows that the source of oil combustion and mobile factors are impacted by local sources in the Ordos region; however, some regional impacts from other regions were also observed for mobile source in the area.

PM₂.₅ pollution is caused by multiple factors and determining how these factors affect PM₂.₅ pollution is important for haze control. In this study, we modified the geographically weighted regression (GWR) model and investigated the relationships between PM₂.₅ and its influencing factors. Experiments covering 368 cities and 9 urban agglomerations were conducted in China in 2015 and more than 20 factors were considered. The modified GWR coefficients (MGCs) were calculated for six variables, including two emission factors (SO₂ and NO₂ concentrations), two meteorological factors (relative humidity and lifted index), and two topographical factors (woodland percentage and elevation). Then the spatial distribution of MGCs was analyzed at city, cluster, and region scales. Results showed that the relationships between PM₂.₅ and the different factors varied with location. SO₂ emission positively affected PM₂.₅, and the impact was the strongest in the Beijing–Tianjin–Hebei (BTH) region. The impact of NO₂ was generally smaller than that of SO₂ and could be important in coastal areas. The impact of meteorological factors on PM₂.₅ was complicated in terms of spatial variations, with relative humidity and lifted index exerting a strong positive impact on PM₂.₅ in Pearl River Delta and Central China, respectively. Woodland percentage mainly influenced PM₂.₅ in regions of or near deserts, and elevation was important in BTH and Sichuan. The findings of this study can improve our understanding of haze formation and provide useful information for policy-making.

Natural sources, such as soil and wind-erosion dust (SWD), biomass open burning (BOB), sea salt spray (SSAS) and biogenic source (BIO), are major contributors to atmospheric emissions of trace elements (TEs) globally. In this study, we used a comprehensive approach to account for area-, production- and biofuel consumption-based emission factor calculation methods, and thus developed an integrated high-resolution emission inventory for 15 types of TEs (As, B, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Sb, Se, V and Zn) originated from natural sources in China for the year 2015. The results show that national emissions of TEs in 2015 range from 7.45 tons (Hg) to 1, 400 tons (Zn) except for the extremely high emissions of Mn (10, 677 tons). SWD and BIO are identified as the top two source contributors, accounting for approximately 67.7% and 26.1% of the total emissions, respectively. Absolute emissions of TEs from natural sources are high in the Xinjiang, Inner Mongolia and Tibet autonomous regions with large areas of bare soil and desert. However, emission intensity of TEs per unit area in the Southern provinces of China is higher than those in Northern China and Southwestern China, with the Yunnan and Sichuan provinces displaying the highest emission intensity. Our results suggest that controlling SWD can play a significant role in reducing fugitive particulate matter and the associated emissions of TEs from natural sources in China; and desertification control is particularly critical in the Northwest provinces where the majority of deserts are located.

A long-lasting high particulate matter (PM) concentration episode persisted over East Asia from May 24 to June 3, 2014. The Nested Air Quality Prediction Model System (NAQPMS) was used to investigate the mixing of dust and anthropogenic pollutants during this episode. Comparison of observations revealed that the NAQPMS successfully reproduced the time series PM₂.₅ and PM₁₀ concentrations, as well as the nitrate and sulfate concentrations in fine (aerodynamic diameter ≤ 2.5 μm) and coarse mode (2.5 μm < aerodynamic diameter ≤ 10 μm). This episode originated from two dust events that occurred in the inland desert areas of Mongolia and China, and then the long-range transported dust and anthropogenic pollutants were trapped over the downwind region of East Asia for more than one week due to the blocked north Pacific subtropical high-pressure system over the east of Japan. The model results showed that mineral dust accounted for 53–83% of PM₁₀, and 39–67% of PM₂.₅ over five cities in East Asia during this episode. Sensitivity analysis indicated that the Qingdao and Seoul regions experienced dust and pollution twice, by direct transport from the dust source region and from dust detoured over the Shanghai area. The results of the NAQPMS model confirmed the importance of dust heterogeneous reactions (HRs) over East Asia. Simulated dust NO₃⁻ concentrations accounted for 75% and 84% of total NO₃⁻ in fine and coarse mode, respectively, in Fukuoka, Japan. The horizontal distribution of model results revealed that the ratio of dust NO₃⁻/dust concentration increased from about 1% over the Chinese land mass to a maximum of 8% and 6% respectively in fine and coarse mode over the ocean to the southeast of Japan, indicating that dust NO₃⁻ was mainly formed over the Yellow Sea and the East China Sea before reaching Japan.

This study estimates the potential losses of vascular plant species richness due to terrestrial acidification for different world's biomes. We used empirical occurrence data of 2409 species from 140 studies and estimated the relative species richness – pH response curves using logistic regressions. The regressions were then used to quantify the fraction of species that are potentially lost due to soil pH changes. Although we found considerable variability within biomes, out results show that the pH at which species richness was maximized was found to be the lowest in (sub)tropical forests (pH = 4.1) and the highest in deserts (pH = 7.4). We also found that (sub)tropical moist forests are highly sensitive to decreases of in soil pH below 4.1. This study can be coupled with existing atmospheric deposition models to quantify the risk of species richness loss following soil acidification.

The Desert Southwest Coarse Particulate Matter Study was undertaken to further our understanding of ambient concentrations and the composition of fine and coarse particles in rural, arid environments. Sampling was conducted in Pinal County, Arizona between February 2009 and February 2010. The goals of this study were to: (1) chemically characterize the coarse and fine fraction of the ambient particulate matter in terms of mass, ions, elements, bulk organic and elemental carbon; (2) examine the temporal and spatial variability of particles within the area using a series of three sampling locations and use this information to determine the contribution of local vs. regional sources; (3) collect, re–suspend, and chemically characterize various crustal sources within the area to identify differences which may isolate them (crustal sources) as independent sources, and; (4) use a receptor based modeling approach to identify particle sources and the relative impact of each on ambient PM concentrations. This work reviews the study objectives, design, site descriptions, and measurement techniques relevant to this research effort and presents the general characteristics of PM during the study period. This unique dataset will support efforts to reduce PM10 and PM2.5 concentrations in the area to below the National Ambient Air Quality Standards (NAAQS) for these pollutants.Coarse particle concentrations are, on average, approximately 5 times fine particle mass concentrations within the region. Coarse particle concentrations in Pinal County are highest during spring and fall seasons, consistent with the tilling and harvesting seasons while fine particles concentrations are highest during fall. Crustal material is the dominant component of coarse particle composition, representing 50% of the mass on average followed closely by organic matter representing 15%. Fine particles still contain a significant crustal fraction (30%) but organic matter dominates at 37% of the particle mass.