Spatiotemporal variations and driving factors of dust storm events in northern China based on high-temporal-resolution analysis of meteorological data (1960-2007)

Dust and climate interactions in the Middle East: Spatio-temporal analysis of aerosol optical depth and climatic variables

The Middle East (ME) is grappling with an alarming increase in dust levels, measured as aerosol optical depth (AOD), which poses significant threats to air quality, human health, and ecological stability. This study aimed to investigate correlations between climate and non-climate driving factors and AOD in the ME over the last four-decade (1980-2020), based on analysis of three variables: actual evapotranspiration (AET), potential evapotranspiration (PET), and precipitation (P). A comprehensive analysis is conducted to discern patterns and trends, with a particular focus on regions such as Rub al-Khali, Ad-Dahna, An-Nafud Desert, and southern Iraq, where consistently high dust levels were observed. 77 % of the study area is classified as arid or semi-arid based on the aridity index. Our results indicate an upward trend in dust levels in Iraq, Iran, Yemen, and Saudi Arabia. We noted an increasing AET trend in regions such as the Euphrates and Tigris basin, northern-Iran, and the Nile region, along with rising PET levels in arid and semi-arid zones such as Iran, Iraq, and Syria. Conversely, P showed a notable decrease in northern-Iraq, Syria, southwestern Iran, and southern-Turkey. Comparison of long-term changes (10-year moving averages) of AOD and P showed a consistent increase in AOD with P levels decreasing in all climate regions. The Budyko space analysis indicates shifts in evaporation ratio across different climate classes from 1980 to 2020, with predominant movement patterns towards higher aridity indices in arid and semi-arid regions, while factors beyond long-term aridity changes influence shifts in evaporation ratio across various climatic zones. The Middle East experiences complex and intricate interactions between dust events and their drivers. To address this issue, a comprehensive and multi-system approach is necessary, which considers both climate and non-climate drivers. Moreover, an efficient dust control strategy should include soil and water conservation, advanced monitoring, and public awareness campaigns that involve regional and international collaboration.

Long-term variations of global dust emissions and climate control

Dust discharged from the surface into the air has an important impact on global climate change, the ecological environment, and human health. However, the spatiotemporal variations of global dust emissions and the climate control of dust emissions from different dust sources in recent decades are still unclear. This study explores the spatiotemporal variations of global dust emissions from 1980 to 2020 based on the MERRA-2 dust emissions dataset and provides a detailed investigation of the interannual variations of dust emissions from major dust sources in the world and their contribution to the global dust cycle. On this basis, the association between global dust emissions and average wind speed (AWS), surface air temperature (SAT), precipitation (Ppt), relative humidity (RH), soil evaporation (SE), soil moisture (SM), and solar radiation (SR) were explored. In particular, the comparative importance of these climatic factors and their combined structures on dust emissions from different dust sources. The results show that North Africa contributed the most to global dust emissions, contributing 58% of the total global emissions, while South Africa and North America contributed the least to global dust emissions, at less than 1%, respectively. Classification and Regression Tree (CART) analysis shows that SR was the major factor affecting the dust emissions of Australia, East Asia, South America, and Central Asia. AWS was the major factor influencing dust emissions in North Africa and South Asia. SAT, RH, and SM were the major factors affecting dust emissions in West Asia, North America, and South Africa, respectively. There were great differences in the climatic factors combinations on dust emissions intensity in different dust sources. These findings assist us in better understanding the control of climatic factors on dust emissions from global dust sources and have important scientific significance for accurately predicting dust events and reducing disaster risks.

Quantifying the contributions of natural and anthropogenic dust sources in Shanxi Province, northern China

Dust storms have direct or indirect impacts on climate change and human health. Identifying and quantifying natural/anthropogenic dust sources can facilitate effective prevention and control of dust events. Based on surface real-time PM10 monitoring data, satellite remote sensing and the HYSPLIT model, this study determined the specific timing, coverage and sources of dust events in Shanxi Province, Northern China. Thus, a composite fingerprinting technique was established to quantify potential dust sources and dust contributions of single dust events. The dust oxidation model was validated, indicating that the composite fingerprinting technique was well suited to the study region. The results show that natural dust sources (67%) contributed more to the study region than anthropogenic dust sources. They were mainly from the northwest and north of the study region. Particularly, the contributions of Taiyuan (TY) and Linfen (LF) accounted for the largest (82%) and smallest (55%) proportions, respectively, both exceeding 50%. Anthropogenic dust sources contributed 33%, mainly from the east and south of the study region. The contribution of anthropogenic dust sources increased in the study region from north to south. In terms of potential dust sources, the Tengger Desert and Badain Jaran Desert (TDBD) contributed the most (26%), followed by the Otindag Sandy Land (OL) (22%). The Taklimakan Desert (TD) contributed the least (2%). The Middle Farmland region of the Hexi Corridor (HMF) in the west (15%) had the largest proportion of anthropogenic dust sources. Differences in the regional contribution of potential dust sources mainly resulted from winter winds, surface drought severity and particle size. At an insignificant distance from the study region, the contribution of potential dust sources was larger in the west than in the east and increased from south to north overall. These methods and findings can contribute to improving the ecological environment in Northern China.

Spatiotemporal variations of internal dust events in urban environments of Iran, Southwest Asia

This article investigates the Dust Storm Index (DSI) and its trend using the Mann-Kendall test, across urban areas of Iran on the monthly, seasonally, and annually scales from 2000 to 2018. The results showed that cities located in the humid region, especially Khoram Abad and Avaj, had the lowest DSI values, and the cities located in arid regions, particularly Zabol, Sarakhs, and Zahedan, had the highest DSI values during the study period. On a monthly basis, the positive trends were observed in most cities of Iran in March, October, and August, while the negative trends were mainly observed in Feb, May, and June. Birjand, Torbat Heydariyeh, Saveh, Shiraz, and Kerman showed an increasing trend of DSI in most months of the study period. On a seasonal scale, the autumn and summer DSI changes showed significant positive trends in 18% of the urban environments in Iran. A similar trend was observed for 17% and 15% of study urban areas in the spring and winter, respectively. On an annual scale, the significant upward trends in DSI were observed in 13% while its negative changes were found in 10% of study cities. These results can be useful for decision-makers and managers to take appropriate measures to reduce and control dust events in urban areas that have suffered from the increasing trend of dust events in the past years.

Compound events and associated impacts in China

Owing to amplified impacts on human society and ecosystems, compound events (or extremes) have attracted ample attention in recent decades. China is particularly vulnerable to compound events due to the fast warming rate, dense populations, and fragile ecological environment. Recent studies have demonstrated tangible effects of climate change on compound events with mounting impacts on the economy, agriculture, public health, and infrastructure in China, posing unprecedented threats that are increasingly difficult to manage. Here, I synthesize recent progress in studies of compound events and associated impacts in China. Several lines of evidence indicate an increase in the frequency and intensity of multiple types of compound events across China. Future directions in studying compound events in China are suggested, including investigating extremes from a compound perspective, modeling compound events in the Anthropocene, quantitative evaluations of risks, and holistic adaptation measures of compound events.

Refined spatiotemporal analysis of drought characteristics under different characteristic variable matchings: a case study of the middle reaches of the Yellow River basin, China

The refined assessment of the spatiotemporal characteristics of droughts is of great significance for drought evaluation. Based on monthly precipitation and temperature grid data (1961-2019) in the middle reaches of the Yellow River basin (MYRB), the standardized precipitation evapotranspiration index (SPEI) was calculated at monthly, seasonal, and annual scales. The run theory was used to extract the drought features at the monthly scale, and the spatiotemporal characteristics of different drought levels were analyzed using Mann-Kendall mutation tests and spatial interpolation. The Moran' I was used to analyze the spatial heterogeneity of droughts. The results showed that the drought trend in the MYRB increased from 1961 to 2019, with the SPEI exhibiting an overall decreasing rate of - 0.1145/decade. Decreasing rates were observed in spring (- 0.1356/decade), summer (- 0.0362/decade), and autumn (- 0.0745/decade), whereas an increasing rate was observed in winter (0.0781/decade). Only extreme droughts were long term, with an intensity as low as - 22.29. The highest frequencies were observed for mild-moderate droughts, which mainly showed high-value clusters in the western and central regions. The frequencies of severe-extreme droughts mainly presented low-value clusters in the northern and southwestern areas. The frequencies of mild and severe droughts exhibited significant spatial cluster characteristics, while the drought intensity showed non-significant spatial clusters and a random distribution. The high and low values of drought intensity were mainly clustered in the middle-upper reaches. The research results provide reference for disaster prevention and mitigation, agricultural planning, and water resource allocation in the MYRB.

Air pollutant spatiotemporal evolution characteristics and effects on human health in North China

North China, the political, economic, and cultural center of China, has been greatly harmed by frequent air pollution incidents. Therefore, it is vital to study air pollution characteristics and clarify their impact on human health. In this study, we first analyzed the spatiotemporal variations of air pollutants (PM_2.5, PM₁₀, CO, SO₂, NO₂, and O₃) in North China from 2016 to 2019. Then, the air quality index (AQI), aggregate air quality index (AAQI), and health risk based air quality index (HAQI) were used to assess health risks. Based on these, the AirQ_2.2.3 model was used to quantify health effects. The results showed that the major pollutant in the cities surrounding Beijing was PM_2.5, while PM₁₀ dominated in distant cities. Annual concentrations decreased (except for O₃), which is related to governmental emission reduction policies. However, O₃ concentrations increased owing to the complex precursor emissions. The AQI underestimated air pollution, while the AAQI and HAQI were accurate; the latter indicated that 55% of the study region population was exposed to polluted air. The AirQ_2.2.3 model quantified the total mortality proportions attributable to PM_2.5, PM₁₀, SO₂, CO, NO₂, and O₃, which were 1.87%, 3.12%, 1.11%, 1.40%, 4.19%, and 2.52%, respectively. In high concentrations, PM₁₀ and PM_2.5 pose significant health risks. The health effects of SO₂, NO₂, CO, and O₃ at lower concentrations were more obvious, indicating that the expected mortality rate due to low concentrations of some pollutants was much higher than that due to high concentrations of other pollutants.

Dust storm index anomaly for sand-dust events monitoring in western Iran and its association with the NDVI and LST anomalies

Sand-dust events (SDE) are an increasing concern in many arid and semi-arid regions of the world, which have severely damaged air quality and human health in recent years. This study was conducted to monitor the SDE in western Iran using the dust storm index anomaly (DSIA) during 2000-2018. The spatio-temporal change detection and statistical analysis were used to understand the impacts of normalized difference vegetation cover anomaly (NDVIA) and land surface temperature anomaly (LSTA) on the SDE activities. The area has suffered from the highest dust pollution in 2004, 2009, and 2012 (DSIA>+40) while it experienced the lowest dust pollution in 2002 and 2017 (DSIA<-40). Approximately 48% of western Iran experienced decreasing changes and 52% of the total area experienced increasing changes in dust pollution during 2010-2018 compared to the previous years. Incremental changes in NDVIA and LSTA were observed in 73.2% and 7.5% of the study area while their decreasing changes were observed in 26.8% and 92.5% of the total area, respectively. Spatially, regions affected by the increase in dust pollution are mainly distributed in the eastern and southern regions of the study area. Significant effects of changes in anomalies of both terrestrial parameters on DSIA were observed throughout the study period ((R_LSTA-DSIA= +0.52; R_NDVIA-DSIA= -0.41); P<0.05). It was also found that spatial correlation between LSTA and DSIA, as well as NDVIA and DSIA in many parts of the study area, was significant at the 95% confidence level (|R| > 0.45). These findings can be useful for decision-makers to assess the risks of dust pollution and reduce its negative consequences in western Iran.

Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models

The characteristics of near-surface wind speed (NWS) are important to the study of dust storms, evapotranspiration, heavy rainfall, air pollution, and wind energy development. This study evaluated the performance of 30 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) through comparison with observational NWS data acquired in China during a historical period (1975–2014), and projected future changes in NWS under three scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) based on an optimal multi-model ensemble. Results showed that most models reproduced the spatial pattern of NWS for all seasons and the annual mean, although the models generally overestimated NWS magnitude. All models tended to underestimate the trends of decline of NWS for all seasons and the annual mean. On the basis of a comprehensive ranking index, the KIOST-ESM, CNRM-ESM2-1, HadGEM3-GC31-LL, CMCC-CM2-SR5, and KACE-1-0-G models were ranked as the five best-performing models. In the projections of future change, nationally averaged NWS for all months was weaker than in the historical period, and the trends decreased markedly under all the different scenarios except the winter time series under SSP2-4.5. Additionally, the projected NWS over most regions of China weakened in both the early period (2021–2060) and the later period (2061–2100).

Source Apportionment and Health Risk Assessment of Metal Elements in PM2.5 in Central Liaoning’s Urban Agglomeration

To better understand the source and health risk of metal elements in PM2.5, a field study was conducted from May to December 2018 in the central region of the Liaoning province, China, including the cities of Shenyang, Anshan, Fushun, Benxi, Yingkou, Liaoyang, and Tieling. 24 metal elements (Na, K, V, Cr, Mn, Co, Ni, Cu, Zn, As, Mo, Cd, Sn, Sb, Pb, Bi, Al, Sr, Mg, Ti, Ca, Fe, Ba, and Si) in PM2.5 were measured by ICP-MS and ICP-OES. They presented obvious seasonal variations, with the highest levels in winter and lowest in summer for all seven cities. The sum of 24 elements were ranged from to in these cities. The element mass concentration ratio was the highest in Yingkou in the spring (26.15%), and the lowest in Tieling in winter (3.63%). The highest values of elements in PM2.5 were mostly found in Anshan and Fushun among the studied cities. Positive matrix factorization (PMF) modelling revealed that coal combustion, industry, traffic emission, soil dust, biomass burning, and road dust were the main sources of measured elements in all cities except for Yingkou. In Yingkou, the primary sources were identified as coal combustion, metal smelting, traffic emission, soil dust, and sea salt. Health risk assessment suggested that Mn had non-carcinogenic risks for both adults and children. As for Cr, As, and Cd, there was carcinogenic risks for adults and children in most cities. This study provides a clearer understanding of the regional pollution status of industrial urban agglomeration.

Temporal variation characteristics and source apportionment of metal elements in PM2.5 in urban Beijing during 2018-2019

To explore high-resolution temporal variation characteristics of atmospheric metal elements concentration and more accurate pollution sources apportionment, online monitoring of metal elements in PM_2.5 with 1-h time resolution was conducted in Beijing from August 22, 2018 to August 21, 2019. Concentration of 18 elements varied between detection limit (ranging from 0.1 to 100 ng/m³) and nearly 25 μg/m³. Si, Fe, Ca, K and Al represented major elements and accounted for 93.47% of total concentration during the study period. Compared with previous studies, airborne metal pollution in Beijing has improved significantly which thanks to strict comprehensive control measures under the Clean Air Action Plan since 2013. Almost all elements present higher concentrations on weekdays than weekends, while concentrations of elements associated with dust sources during holidays are higher than those in working days after the morning peak, and there is almost no concentration difference in the evening peak period. Soil and dust, vehicle non-exhaust emissions, biomass, industrial processes and fuel combustion were apportioned as main sources of atmospheric metal pollution, accounting for 63.6%, 18.4%, 16.8%, 1.0% and 0.18%, respectively. Furthermore, main occurrence season of metal pollution is judged by characteristic radar chart of varied metal elements proposed for the first time in this study, for example, fuel combustion type pollution mainly occurs in winter and spring. Results of 72-h backward trajectory analysis of air masses showed that, except for local emissions, atmospheric metal pollution in Beijing is also affected by regional transport from Inner Mongolia, Hebei, the Bohai Sea and Heilongjiang.