Using composite fingerprints to quantify the potential dust source contributions in northwest China

Pollution sources and risk assessment of potentially toxic elements in soils of multiple land use types in the arid zone of Northwest China based on Monte Carlo simulation

The concentration of potentially toxic elements (PTEs) in soils of different land-use types varies depending on climatic conditions and human. Topsoil samples were collected in Northwest China to investigate PTE pollution and risk in different land uses, and thereby estimate the risk of various pollution sources. The results showed that human activity had an impact on PTE concentrations in the study area across all land use types, with farmland, grassland, woodland, and the gobi at moderate pollution levels and the desert at light pollution levels. Different PTE sources pose different risks depending on the land-use type. Apart from deserts, children are exposed to carcinogenic risk from a variety of sources. A mixed natural and agricultural source was the main source of public health risk in the study area, contributing 38.7% and 39.0% of the non-carcinogenic and 40.7% and 35.5% of the carcinogenic risks, respectively. Monte Carlo simulations showed children were at a higher health risk from PTEs than adult s under all land uses, which ranked in severity as farmland > woodland > grassland > gobi > desert. As and Ni has a higher probability of posing both a non-carcinogenic and a carcinogenic risk to children. Sensitivity analysis showed that the contribution of parameters to the assessment model of PTEs exhibited the following contribution pattern: concentration > average body weight > ingestion rate > other parameters. The PTEs affecting the risk assessment model were not common among different land use types, where the importance distribution pattern of each parameter was basically the same in woodland, grassland, and farmland, and Ni contributed the most to carcinogenic risk. However, Cr contributed the most to the carcinogenic risk in the desert and gobi.

Pollution indices of selected metals in tea (Camellia sinensis L.) growing soils of the Upper Assam region divulge a non-trifling menace of National Highway

The study investigated the influence of a National Highway (NH) traversing tea estates (TEs) on heavy metal (HM) contamination in the top soils of Upper Assam, India. The dispersion and accumulation of six HMs, viz. cadmium (Cd), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), and zinc (Zn), within tea-growing soils were assessed using diverse indices: contamination factor (CF), degree of contamination (DC), enrichment factor (EF), geo-accumulation index (Igeo), modified degree of contamination (MDC), Nemerow pollution index (PINemerow), pollution load index (PLI), potential ecological risk factor (Eri), and potential ecological risk index (RI). The order of HM prevalence was Fe > Mn > Zn > Ni > Cu > Cd. Elevated Cd levels near the NH prompted immediate attention, while Cd and Zn showed moderate pollution in CF, EF, and RI. The remaining metals posed minimal individual risk (Eri< 40), resulting in an overall contamination range of "nil to shallow," signifying slight contamination from the studied metals. From MDC values for investigated metals, it was found to be "zero to very low degree of contamination" at all locations except the vicinity of NH. Soil pollution, as determined by PLI, indicated unpolluted soils in both districts, yet PINemerow values indicated slight pollution. The statistical analysis revealed that there is a significant decrease in most of the indices of HM as the distance from NH increases. The application of multivariate statistical techniques namely Principal Component Analysis and Cluster Analysis showed the presence of three distinct homogenous groups of distances based on different indices. This investigation underscores NH-associated anthropogenic effects on TE soil quality due to HM deposition, warranting proactive mitigation measures.

Agricultural abandoned lands as emission sources of dust containing metals and pesticides in the Sonora-Arizona Desert

This investigation examines the transport of metal- and pesticide-polluted dust emitted by one of the most relevant agricultural areas of Northwestern Mexico. In the contaminated area, an excessive water extraction of the aquifer and seawater intrusion caused the abandonment of fields, which are pollutant-loaded dust emitters. We used air mass forward trajectories (HYSPLIT) model to obtain particle trajectories in the wind and the use of banned pesticides as geochemical tracers for dust transported by wind. Fifty dust samples from 10 agriculture fields and 26 roof dust of a city close to the agricultural area were analyzed for their contents of zirconium, lead, arsenic, zinc, copper, iron, manganese, vanadium, and titanium, by portable X-ray fluorescence. Nine pesticides were analyzed in the roof dust and agricultural soil samples by gas chromatography. Results show that the distribution of metals was significantly different between active and abandoned fields. Arsenic-lead-copper was mainly concentrated in abandoned fields, while zinc-iron-manganese-titanium was dominant in active fields. Two potential sources of metal contamination were found by principal component analysis (PCA): (I) a mixture of traffic and agricultural sources and (II) a group related to agricultural activities. The occurrence of banned pesticides in dust deposited on roofs collected at nearby cities confirms the atmospheric transport from the agricultural area. The HYSPLIT results indicated that the dust emitted from agricultural fields can reach up to the neighboring states of Sonora, Mexico, and the USA. The impacts that these emissions can have on human health should be studied in future research.

Variations of PM2.5-bound elements and their associated effects during long-distance transport of dust storms: Insights from multi-sites observations

Dust storms are a significant concern because of their adverse effects on ambient air quality and human health. To investigate the evolution of dust storms during long-distance transport and its impacts on air quality and human health risks in cities along the transport pathway, we monitored the major fraction of dust (i.e., particle-bound elements) online in four cities in northern China during March 2021. Three dust events originating from the Gobi Desert of North China and Mongolia and the Taklimakan Desert of Northwest China were captured. We investigated the source regions of dust storms using daily multi-sensor absorbing aerosol index products, backward trajectories, and specific element ratios, identified and quantified sources of particle-bound elements using Positive Matrix Factorization model, and calculated the carcinogenic and non-carcinogenic risks of elements using a health risk assessment model. Our results indicated that under the influence of dust storms, mass concentrations of crustal elements increased up to dozens of times in cities near the dust source and up to ten times in cities farther from the source. In contrast, anthropogenic elements increased less or even decreased, depending on the relative contributions of the increase caused by accumulation of dust itself and entrainment along the transport path and the decrease caused by dilution of high wind speeds. Si/Fe ratio was found to be a valuable indicator for characterizing the attenuation of the amount of dust along its transport pathways, especially for the case originated from northern source regions. This study highlights the significant role of source regions, intensity and attenuation rates of dust storms, and wind speeds in determining the increased levels of element concentrations during dust storms and its associated impacts on downwind areas. Furthermore, non-carcinogenic risks of particle-bound elements increased at all sites during dust events, emphasizing the importance of personal exposure protection during dust storms.

Short-term exposure to air pollution and outpatient visits for conjunctivitis: a time-series analysis in Urumqi, China

Conjunctivitis is an inflammatory disease of the conjunctival tissue caused by a variety of causes; despite the conjunctiva being directly exposed to the external atmospheric environment, the important role of air pollution is not fully evaluated, especially in areas with poor air quality undergoing rapid economic and industrial development. Information on 59,731 outpatient conjunctivitis visits from 1 January 2013 to 31 December 2020 was obtained from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China), and data on six air pollutants including particulate matter with a median aerometric diameter of less than 10 and 2.5 mm (PM₁₀ and PM_2.5, respectively), carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) from eleven standard urban background fixed air quality monitors were also recorded. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effect of exposure to air pollutants on the risk of conjunctivitis outpatient visits. Further subgroup analyses were conducted for gender, age, and season, as well as the type of conjunctivitis. Single and multi-pollutant models showed that exposure to PM_2.5, PM₁₀, NO₂, CO, and O₃ was associated with increased risk of outpatient conjunctivitis visits on the lag 0 day and various other lag days. Variations in the effect estimates on direction and magnitude were found in different subgroup analyses. We conducted the first time-series analysis with the longest duration as well as the largest sample size in Northwest China, which provides evidence that outpatient conjunctivitis visits is significantly associated with air pollution in Urumqi, China. Meanwhile, our results demonstrate the effectiveness of SO₂ reduction in reducing the risk of outpatient conjunctivitis visits in the Urumqi region and reaffirm the need to implement special air pollution control measures.

A Monte Carlo simulation-based health risk assessment of heavy metals in soils of an oasis agricultural region in northwest China

In recent years, heavy metal contamination of soils has been increasing, posing a major threat to food security, human health, and soil ecosystems. This study analyzed the spatial characteristics, contamination sources, risks of heavy metals by collecting topsoil samples from farmland in an oasis agricultural region in northwest China. The results found that soil heavy metals in farmland were at a moderate contamination level. The PMF model classifies soil heavy metals as fertilizer and pesticide sources dominated by As and Mn with 27.8 %, mixed sources of transport and agricultural sources dominated by Cu, Zn, Cd and Pb with 26.9 %, metal processing sources dominated by Cr and Ni with 22.6 %, and the combined pollution sources of Ti, V, Cr, Mn, Fe, As, Pb dominated by natural sources and fuel combustion. The noncarcinogenic and carcinogenic risks values from the ingestion route were higher for children than for adults. The non-carcinogenic risk of heavy metals to adults in the southwestern and central regions of the study area was >1 × 10^-4. The carcinogenic risk was >1 in all adults, but >1 in children in the central and southwestern study areas. Monte Carlo simulation takes into account the parameters and their distributions that affect the health risk assessment model by combining the uncertainty assessment with the health risk, which will reduce the uncertainty of the health risk assessment. The results showed that conventional deterministic risk assessment may overestimate health risk outcomes. In addition, As has a 1.85 % probability of non-carcinogenic risk to children, and an 85.3 % probability of total non-carcinogenic risk for children for all heavy metals. 69.5 % and 11.4 % probability of carcinogenic risk for children and adults respectively for Ni, and 96.4 % and 52.1 % probability of total carcinogenic risk, suggesting that Ni is a priority control heavy metal.

Spatiotemporal variations and relationships of absorbing aerosol-radiation-gross primary productivity over China

High-load carbonaceous and dust aerosols can significantly reduce direct radiation (DIRR), which would affect photosynthesis in terrestrial ecosystems, thereby further affecting the productivity of vegetation. Based on this, a variety of remote sensing data were used to study the spatiotemporal distributions and changing tendencies of the absorbing aerosols, CO, DIRR, and gross primary productivity (GPP) in China during 2005-2019; then, the relationships were analyzed between different types of absorbing aerosols and DIRR as well as GPP. The results showed that the annual mean absorbing aerosols index (AAI) in China during 2005-2019 was 0.39, with a slow growth rate of 0.02 year^-1, and the emission of CO showed a decreasing trend with each passing year, especially in North China Plain and Sichuan Basin. Carbonaceous and dust aerosols were predominantly bounded by Hu line. The east of Hu line was the dominant area of carbonaceous aerosols, and the west of Hu line was the topographical region of dust aerosols. Near the Hu line was the dominant area of carbonaceous-dust aerosols. However, the Karamay-Urumqi-Hami area and Northeast China Plain were exceptional. During the vegetation growing season, different types of absorbing aerosols significantly negatively affected GPP. From a perspective of regional scale variation pattern, the negative effect of absorbing aerosols on vegetation productivity was the most significant in Northeast China; from the perspective of the effects of different vegetation types, the negative effect of absorbing aerosols on grasslands was greater than that of woodlands; from the perspective of the composition characteristics of aerosols, the negative effect of dust aerosols on GPP was greater than that of carbonaceous aerosols.

A sandstorm extreme event from the Yellow River Basin in March 2021: Accurate identification and driving cause

Sandstorm is a natural meteorological disaster that can appear suddenly and is often extremely destructive. In areas with small number of meteorological observation stations, it is difficult to effectively monitor sandstorm. Moderate Resolution Imaging Spectroradiometer (MODIS) data have the characteristics of high resolution and wide coverage, making it possible to monitor dynamic weather changes in a large area over time, and such data are widely used in sandstorm monitoring. The purpose of our research was to achieve a more accurate identification of sandstorm according to the differences in reflectance and brightness temperature between sandstorm and other phenomena, and to better understand the formation, movement track and driving cause of sandstorm extreme event. Taking the intense sandstorm event that occurred in the Yellow River Basin from March 13th to 18th, 2021 as an example, sandstorm process was analyzed based on MODIS data and meteorological monitoring data. The threshold of Normalized Difference Dust Index (NDDI) and Normalized Brightness Temperature Dust Index (NBTDI) realized accurate sandstorm monitoring and quantification of the sandstorm coverage areas. Sandstorm covered 32.89 % and 37.23 % of the total areas of the Yellow River Basin on March 15th and 16th, 2021, respectively. In addition, observation data from 22 meteorological stations also provided an important reference for further understanding of sandstorm weather. The intense sandstorm event in China on March 15th, 2021 originated from the dust in Mongolia. This sandstorm event caused great damage to the ecological environment and caused serious losses to people's lives and properties. This study improved the monitoring of sandstorm by remote sensing technology, and the results had importance for the long-term monitoring and prevention of sandstorm.

Application of magnetic susceptibility and heavy metal bioaccessibility to assessments of urban sandstorm contamination and health risks: Case studies from Dunhuang and Lanzhou, Northwest China

Direct ingestion of sandstorm particles is an important pathway in human exposure to heavy metals. This study investigated the potential health risks of heavy metals transported in sandstorms from Dunhuang to Lanzhou in northwestern China using environmental magnetic parameters and metal bioaccessibilities in simulated gastric and intestinal tracts. The mean magnetic susceptibility of sandstorms in Lanzhou was 366.86 × 10^-8 m³/kg, which was more than 5-fold higher than that of sandstorms in Dunhuang, indicating that these sandstorms continuously receive heavy metals with high magnetic mineral content along their pathways. Heavy metal concentrations in sandstorms were higher than background values and those in urban topsoil. Enrichment factors and pollution load indices showed that these heavy metals were derived from both natural and anthropogenic sources, with Cu, Zn, Pb, and Cd being strongly influenced by anthropogenic sources. The bioaccessibilities of Cd, Cu, Zn, and Pb in the sandstorms of Lanzhou were very high, ranging from 22.69% (Cu) to 50.86% (Pb) for gastric phase, and 12.07% (Pb)-22.11% (Cd) for interstinal phase, with the significant reduction in χ_lf of the physiologically-based extraction testing (PBET) treated sandstorms. The magnetic minerals are significant correlation with the concentrations of heavy metals in sandstorm and effect the release of heavy metals during human digestion process. The overall ecological risk posed by heavy metals contained in sandstorms was relatively low; however, the risk was moderate to high at individual sites. Ingestion posed the highest carcinogenic and non-carcinogenic risks for both adults and children, with the risk for children being higher.

The Impact of COVID-19 Control Measures on Air Quality in Guangdong Province

COVID-19 control measures had a significant social and economic impact in Guangdong Province, and provided a unique opportunity to assess the impact of human activities on air quality. Based on the monitoring data of PM2.5, PM10, NO2, and O3 concentrations from 101 air quality monitoring stations in Guangdong Province from October 2019 to April 2020, the PSCF (potential source contribution factor) analysis and LSTM (long short-term memory) neural network were applied to explore the impact of epidemic control measures on air quality in Guangdong Province. Results showed that during the lockdown, the average concentration of PM2.5, PM10, NO2, and O3 decreased by 37.84%, 51.56%, 58.82%, and 24.00%, respectively. The ranges of potential sources of pollutants were reduced, indicating that air quality in Guangdong Province improved significantly. The Pearl River Delta, characterized by a high population density, recorded the highest NO2 concentration values throughout the whole study period. Due to the lockdown, the areas with the highest concentrations of O3, PM2.5, and PM10 changed from the Pearl River Delta to the eastern and western Guangdong. Moreover, LSTM simulation results showed that the average concentration of PM2.5, PM10, NO2, and O3 decreased by 46.34%, 54.56%, 70.63%, and 26.76%, respectively, which was caused by human-made impacts. These findings reveal the remarkable impact of human activities on air quality and provide effective theoretical support for the prevention and control of air pollution in Guangdong Province.

Spatio-Temporal Evolution of a Typical Sandstorm Event in an Arid Area of Northwest China in April 2018 Based on Remote Sensing Data

Northwest China is significantly affected by sandstorm disasters. To mitigate the negative impacts of sandstorm events, it is critical to understand the spatio-temporal variations in typical sand and dust storms and their influencing factors. In this work, using ground-based measurements of particulate matter and remote sensing data such as MODIS, OMI, and CALIPSO data, the sources of aerosol pollution and aerosol optical properties of a typical sandstorm event that occurred in Northwest China in 2018 was studied. In addition, the HYSPLIT model was used to explore the air mass trajectories in order to analyze the sand and dust migration process during the sandstorm event. Furthermore, the wind erosion sensitivity of Northwest China was analyzed via single factor analysis and multi-factor superposition of wind field intensity, soil drought index, vegetation coverage, and relief amplitude. Finally, the region of the study area having a high comprehensive wind erosion sensitivity was identified. The results showed that the PM10 concentrations exceeded 400 µg/m3 and the PM2.5/PM10 ratio did not exceeded 0.6 during the sandstorm event, indicating that natural particulate matter was dominant in the ambient air. At the epicenter of pollution, the aerosol optical depth (AOD) at 550 nm was 0.75–1. By combining AOD data with wind speed and direction data from field observation stations, it was found that the sandstorm event in 2018 mainly occurred between 1 April and 3 April, and affected all of Northwest China on 2 April and 3 April. The absorbed aerosol index (AAI) ranged between 2.5 and 4, indicating that the Taklimakan Desert was the main source of sandstorm events in Northwest China. The CALIPSO total attenuated backscatter coefficient at 532 nm indicated that the main component of tropospheric aerosol in this region was distributed in the range of 0–12.5 km. The simulated airflow track showed that it had the same dust source regions as AAI index studies. Moreover, investigation of wind erosion sensitivity in the study areas indicated that the Taklimakan Desert and other desert regions were the main ecologically sensitive areas. These conclusions can provide references and suggestions for the mitigation of damage caused by sandstorm events, in addition to the enhancement of ecological governance.

Seasonal Distribution of Atmospheric Coarse and Fine Particulate Matter in a Medium-Sized City of Northern China

Atmospheric particulate matter (PM) was measured continuously at an urban site in Baoji city in northern China in 2018 to investigate the seasonal distribution characteristics. Coarse PM (PM_2.5–10) was more prevalent in spring, substantially due to the regional transport of dust. High loadings of coarse PM were found at night compared to daytime, which could result from high production and unfavorable dispersion conditions. Fine PM (PM_2.5) constituted, on average, 54% of the total PM mass concentration, whereas it contributed more than 97% of the total PM number concentration. The number and mass concentrations of fine PM increased substantially in the winter, which was possibly due to the enhanced production of atmospheric secondary processes and coal combustion. Precursor gaseous pollutants and meteorology greatly influenced the PM distributions. Fine PM was associated more strongly with gas pollutants than coarse PM, which suggested that it largely originated from secondary production and combustion sources. High relative humidity appeared to promote the production of fine PM, whereas it facilitated the removal of coarse PM. This study highlights that different air-pollution control strategies should be used for coarse and fine PM according to the distribution characteristics and influencing factors in similar medium-sized urban areas.

Heavy metal pollution levels, source apportionment and risk assessment in dust storms in key cities in Northwest China

In this study, the potential hazards of heavy metals in dust storms were investigated by collecting dust storm samples, measuring their heavy metal concentrations, and using index evaluation, spatial analysis, positive matrix factorization (PMF) model and risk assessment model. Heavy metals in dust storms were contaminated by anthropogenic sources leading to their concentrations being higher than the background values. The enrichment factors and geoaccumulation indices showed that the heavy metals came from both natural and anthropogenic sources, Cu, Ni, Zn and Pb are strongly influenced by anthropogenic sources. Heavy metals in dust storms were divided into four sources: Cu and Ni were attributed to industrial sources mainly from local mining and metal processing; Cr was mainly contributed by industrial sources related to industrial production such as coal combustion; Pb and Zn were mainly contributed by transportation sources; and Ti, V, Mn, Fe, and As were from natural and agricultural sources. The level of comprehensive ecological risk of heavy metals in dust storms were low, but there were moderate and above risks at individual sites. Both adults and children had the highest carcinogenic and non-carcinogenic risks from the ingestion route, and the risk for children was higher than that for adults.

Persistent pollution episodes, transport pathways, and potential sources of air pollution during the heating season of 2016-2017 in Lanzhou, China

As one of the most important industrial cities in Northwest China, Lanzhou currently suffers from serious air pollution. This study analyzed the formation mechanism and potential source areas of persistent air pollution in Lanzhou during the heating period from November 1, 2016 to March 31, 2017 based on the air pollutant concentrations and relevant meteorological data. Our findings indicate that particulate pollution was extremely severe during the study period. The daily PM_2.5 and PM₁₀ concentrations had significantly negative correlations with daily temperature, wind speed, maximum daily boundary layer height, while the daily PM_2.5 and PM₁₀ concentrations showed significantly positive correlations with daily relative humidity. Five persistent pollution episodes were identified and classified as either stagnant accumulation or explosive growth types according to the mechanism of pollution formation and evolution. The PM_2.5 and PM₁₀ concentrations and PM_2.5/PM₁₀ ratio followed a growing "saw-tooth cycle" pattern during the stagnant accumulation type event. Dust storms caused abrupt peaks in PM₁₀ and a sharp decrease in the PM_2.5/PM₁₀ ratio in explosive growth type events. The potential sources of PM₁₀ were mainly distributed in the Kumtag Desert in Xinjiang Uygur Autonomous Region, the Qaidam Basin and Hehuang Valley in Qinghai Province, and the western and eastern Hexi Corridor in Gansu Province. The contributions to PM₁₀ were more than 120 μg/m³. The important potential sources of PM_2.5 were located in Hehuang Valley in Qinghai and Linxia Hui Autonomous Prefecture in Gansu; the concentrations of PM_2.5 were more than 60 μg/m³.

Modelling Spatial Heterogeneity in the Effects of Natural and Socioeconomic Factors, and Their Interactions, on Atmospheric PM2.5 Concentrations in China from 2000–2015

In recent years, atmospheric PM2.5 pollution in China has become increasingly severe and exploring the relationships among its influencing factors is important in the prevention and control of air pollution. Although previous studies have identified complexity in variations in PM2.5 concentrations and recognized the interaction of multiple factors, little quantitative information is available on the evolution of the relationships among these factors, their spatial heterogeneity, and the multiscale interactions between them. In this study, geographical detector and multiscale geographically weighted regression models have been used to explore the multiscale interactions among natural and socioeconomic factors and PM2.5 concentration in China over the period 2000–2015. The results indicate that the relationship between natural factors and PM2.5 concentration is stronger than that for socioeconomic factors. The type of interaction between each factor is dominated by bivariate and nonlinear enhancement, exhibiting strong interactions between natural factors and anthropogenic factors. Although the effect of each factor on PM2.5 is complex, the relative influence of both human activities and social factors is shown to have gradually increased over time and population, agriculture, urbanization, and socioeconomic activities in general make important contributions to PM2.5. In addition, the scale of effects related to natural factors is smaller and more stable compared to the influence of human activities during the period 2000-2015. There are significant differences in the way natural factors and socioeconomic factors affect PM2.5, and there is strong non-stationarity of spatial relationships. Factors associated with topography, vegetation (NDVI), climate (temperature), natural sources, and agricultural activity are shown to be important determinants of PM2.5 across China and warrant significant attention in terms of managing atmospheric pollution. The study demonstrates that spatial differences in the direction, intensity, and scale of each factor should be accounted for to improve prevention and control measures and alleviate regional PM2.5 pollution.